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Lundtoft C, Knight A, Meadows JRS, Karlsson Å, Rantapää-Dahlqvist S, Berglin E, Palm Ø, Haukeland H, Gunnarsson I, Bruchfeld A, Segelmark M, Ohlsson S, Mohammad AJ, Eriksson P, Söderkvist P, Ronnblom L, Omdal R, Jonsson R, Lindblad-Toh K, Dahlqvist J. The HLA region in ANCA-associated vasculitis: characterisation of genetic associations in a Scandinavian patient population. RMD Open 2024; 10:e004039. [PMID: 38580345 PMCID: PMC11002376 DOI: 10.1136/rmdopen-2023-004039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Accepted: 03/16/2024] [Indexed: 04/07/2024] Open
Abstract
OBJECTIVE The antineutrophil cytoplasmic antibody (ANCA)-associated vasculitides (AAV) are inflammatory disorders with ANCA autoantibodies recognising either proteinase 3 (PR3-AAV) or myeloperoxidase (MPO-AAV). PR3-AAV and MPO-AAV have been associated with distinct loci in the human leucocyte antigen (HLA) region. While the association between MPO-AAV and HLA has been well characterised in East Asian populations where MPO-AAV is more common, studies in populations of European descent are limited. The aim of this study was to thoroughly characterise associations to the HLA region in Scandinavian patients with PR3-AAV as well as MPO-AAV. METHODS Genotypes of single-nucleotide polymorphisms (SNPs) located in the HLA region were extracted from a targeted exome-sequencing dataset comprising Scandinavian AAV cases and controls. Classical HLA alleles were called using xHLA. After quality control, association analyses were performed of a joint SNP/classical HLA allele dataset for cases with PR3-AAV (n=411) and MPO-AAV (n=162) versus controls (n=1595). Disease-associated genetic variants were analysed for association with organ involvement, age at diagnosis and relapse, respectively. RESULTS PR3-AAV was significantly associated with both HLA-DPB1*04:01 and rs1042335 at the HLA-DPB1 locus, also after stepwise conditional analysis. MPO-AAV was significantly associated with HLA-DRB1*04:04. Neither carriage of HLA-DPB1*04:01 alleles in PR3-AAV nor of HLA-DRB1*04:04 alleles in MPO-AAV were associated with organ involvement, age at diagnosis or relapse. CONCLUSIONS The association to the HLA region was distinct in Scandinavian cases with MPO-AAV compared with cases of East Asian descent. In PR3-AAV, the two separate signals of association to the HLD-DPB1 region mediate potentially different functional effects.
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Affiliation(s)
| | - Ann Knight
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
- Uppsala University Hospital, Uppsala, Sweden
| | - Jennifer R S Meadows
- Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Åsa Karlsson
- Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | | | - Ewa Berglin
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Øyvind Palm
- Department of Rheumatology, Oslo University Hospital, Oslo, Norway
| | - Hilde Haukeland
- Department of Rheumatology, Martina Hansens Hospital, Sandvika, Norway
| | - Iva Gunnarsson
- Department of Medicine, Karolinska Institutet, Stockholm, Sweden
- Unit of Rheumatology, Karolinska University Hospital, Stockholm, Sweden
| | - Annette Bruchfeld
- Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
- Department of Renal Medicine, Karolinska University Hospital and CLINTEC Karolinska Institutet, Stockholm, Sweden
| | - Mårten Segelmark
- Department of Clinical Sciences, Lund University and Skåne University Hospital, Lund, Sweden
| | - Sophie Ohlsson
- Department of Clinical Sciences, Lund University and Skåne University Hospital, Lund, Sweden
| | - Aladdin J Mohammad
- Department of Clinical Sciences, Lund University and Skåne University Hospital, Lund, Sweden
- Department of Medicine, University of Cambridge, Cambridge, UK
| | - Per Eriksson
- Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
| | - Peter Söderkvist
- Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
| | - Lars Ronnblom
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Roald Omdal
- Research Department, Stavanger University Hospital, Stavanger, Norway
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Roland Jonsson
- Broegelmann Research Laboratory, Department of Clinical Science, University of Bergen, Bergen, Hordaland, Norway
| | - Kerstin Lindblad-Toh
- Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
- The Broad Institute of MIT and Harvard University, Cambridge, Massachusetts, USA
| | - Johanna Dahlqvist
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
- Uppsala University Hospital, Uppsala, Sweden
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Wirthlin ME, Schmid TA, Elie JE, Zhang X, Kowalczyk A, Redlich R, Shvareva VA, Rakuljic A, Ji MB, Bhat NS, Kaplow IM, Schäffer DE, Lawler AJ, Wang AZ, Phan BN, Annaldasula S, Brown AR, Lu T, Lim BK, Azim E, Clark NL, Meyer WK, Pond SLK, Chikina M, Yartsev MM, Pfenning AR, Andrews G, Armstrong JC, Bianchi M, Birren BW, Bredemeyer KR, Breit AM, Christmas MJ, Clawson H, Damas J, Di Palma F, Diekhans M, Dong MX, Eizirik E, Fan K, Fanter C, Foley NM, Forsberg-Nilsson K, Garcia CJ, Gatesy J, Gazal S, Genereux DP, Goodman L, Grimshaw J, Halsey MK, Harris AJ, Hickey G, Hiller M, Hindle AG, Hubley RM, Hughes GM, Johnson J, Juan D, Kaplow IM, Karlsson EK, Keough KC, Kirilenko B, Koepfli KP, Korstian JM, Kowalczyk A, Kozyrev SV, Lawler AJ, Lawless C, Lehmann T, Levesque DL, Lewin HA, Li X, Lind A, Lindblad-Toh K, Mackay-Smith A, Marinescu VD, Marques-Bonet T, Mason VC, Meadows JRS, Meyer WK, Moore JE, Moreira LR, Moreno-Santillan DD, Morrill KM, Muntané G, Murphy WJ, Navarro A, Nweeia M, Ortmann S, Osmanski A, Paten B, Paulat NS, Pfenning AR, Phan BN, Pollard KS, Pratt HE, Ray DA, Reilly SK, Rosen JR, Ruf I, Ryan L, Ryder OA, Sabeti PC, Schäffer DE, Serres A, Shapiro B, Smit AFA, Springer M, Srinivasan C, Steiner C, Storer JM, Sullivan KAM, Sullivan PF, Sundström E, Supple MA, Swofford R, Talbot JE, Teeling E, Turner-Maier J, Valenzuela A, Wagner F, Wallerman O, Wang C, Wang J, Weng Z, Wilder AP, Wirthlin ME, Xue JR, Zhang X. Vocal learning-associated convergent evolution in mammalian proteins and regulatory elements. Science 2024; 383:eabn3263. [PMID: 38422184 DOI: 10.1126/science.abn3263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 02/20/2024] [Indexed: 03/02/2024]
Abstract
Vocal production learning ("vocal learning") is a convergently evolved trait in vertebrates. To identify brain genomic elements associated with mammalian vocal learning, we integrated genomic, anatomical, and neurophysiological data from the Egyptian fruit bat (Rousettus aegyptiacus) with analyses of the genomes of 215 placental mammals. First, we identified a set of proteins evolving more slowly in vocal learners. Then, we discovered a vocal motor cortical region in the Egyptian fruit bat, an emergent vocal learner, and leveraged that knowledge to identify active cis-regulatory elements in the motor cortex of vocal learners. Machine learning methods applied to motor cortex open chromatin revealed 50 enhancers robustly associated with vocal learning whose activity tended to be lower in vocal learners. Our research implicates convergent losses of motor cortex regulatory elements in mammalian vocal learning evolution.
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Affiliation(s)
- Morgan E Wirthlin
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Tobias A Schmid
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94708, USA
| | - Julie E Elie
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94708, USA
- Department of Bioengineering, University of California, Berkeley, Berkeley, CA 94708, USA
| | - Xiaomeng Zhang
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Amanda Kowalczyk
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Ruby Redlich
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Varvara A Shvareva
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94708, USA
| | - Ashley Rakuljic
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94708, USA
| | - Maria B Ji
- Department of Psychology, University of California, Berkeley, Berkeley, CA 94708, USA
| | - Ninad S Bhat
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94708, USA
| | - Irene M Kaplow
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - Daniel E Schäffer
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Alyssa J Lawler
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Andrew Z Wang
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - BaDoi N Phan
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Siddharth Annaldasula
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Ashley R Brown
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Tianyu Lu
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Byung Kook Lim
- Neurobiology section, Division of Biological Science, University of California, San Diego, La Jolla, CA 92093, USA
| | - Eiman Azim
- Molecular Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Nathan L Clark
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Wynn K Meyer
- Department of Biological Sciences, Lehigh University, Bethlehem, PA 18015, USA
| | | | - Maria Chikina
- Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - Michael M Yartsev
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94708, USA
- Department of Bioengineering, University of California, Berkeley, Berkeley, CA 94708, USA
| | - Andreas R Pfenning
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
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Meadows JRS, Kidd JM, Wang GD, Parker HG, Schall PZ, Bianchi M, Christmas MJ, Bougiouri K, Buckley RM, Hitte C, Nguyen AK, Wang C, Jagannathan V, Niskanen JE, Frantz LAF, Arumilli M, Hundi S, Lindblad-Toh K, Ginja C, Agustina KK, André C, Boyko AR, Davis BW, Drögemüller M, Feng XY, Gkagkavouzis K, Iliopoulos G, Harris AC, Hytönen MK, Kalthof DC, Liu YH, Lymberakis P, Poulakakis N, Pires AE, Racimo F, Ramos-Almodovar F, Savolainen P, Venetsani S, Tammen I, Triantafyllidis A, vonHoldt B, Wayne RK, Larson G, Nicholas FW, Lohi H, Leeb T, Zhang YP, Ostrander EA. Author Correction: Genome sequencing of 2000 canids by the Dog10K consortium advances the understanding of demography, genome function and architecture. Genome Biol 2023; 24:255. [PMID: 37936157 PMCID: PMC10631033 DOI: 10.1186/s13059-023-03101-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2023] Open
Affiliation(s)
- Jennifer R S Meadows
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, 75132, Uppsala, Sweden.
| | - Jefrey M Kidd
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, 48107, USA.
| | - Guo-Dong Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Heidi G Parker
- National Human Genome Research Institute, National Institutes of Health, 50 South Drive, Building 50 Room 5351, Bethesda, MD, 20892, USA
| | - Peter Z Schall
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, 48107, USA
| | - Matteo Bianchi
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, 75132, Uppsala, Sweden
| | - Matthew J Christmas
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, 75132, Uppsala, Sweden
| | - Katia Bougiouri
- Section for Molecular Ecology and Evolution, Globe Institute, University of Copenhagen, Øster Voldgade 5-7, 1350, Copenhagen, Denmark
| | - Reuben M Buckley
- National Human Genome Research Institute, National Institutes of Health, 50 South Drive, Building 50 Room 5351, Bethesda, MD, 20892, USA
| | - Christophe Hitte
- University of Rennes, CNRS, Institute Genetics and Development Rennes - UMR6290, 35000, Rennes, France
| | - Anthony K Nguyen
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, 48107, USA
| | - Chao Wang
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, 75132, Uppsala, Sweden
| | - Vidhya Jagannathan
- Institute of Genetics, Vetsuisse Faculty, University of Bern, 3001, Bern, Switzerland
| | - Julia E Niskanen
- Department of Medical and Clinical Genetics, Department of Veterinary Biosciences, University of Helsinki and Folkhälsan Research Center, 02900, Helsinki, Finland
| | - Laurent A F Frantz
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, E14NS, UK and Palaeogenomics Group, Department of Veterinary Sciences, Ludwig Maximilian University, D-80539, Munich, Germany
| | - Meharji Arumilli
- Department of Medical and Clinical Genetics, Department of Veterinary Biosciences, University of Helsinki and Folkhälsan Research Center, 02900, Helsinki, Finland
| | - Sruthi Hundi
- Department of Medical and Clinical Genetics, Department of Veterinary Biosciences, University of Helsinki and Folkhälsan Research Center, 02900, Helsinki, Finland
| | - Kerstin Lindblad-Toh
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, 75132, Uppsala, Sweden
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Catarina Ginja
- BIOPOLIS-CIBIO-InBIO-Centro de Investigação Em Biodiversidade E Recursos Genéticos - ArchGen Group, Universidade Do Porto, 4485-661, Vairão, Portugal
| | | | - Catherine André
- University of Rennes, CNRS, Institute Genetics and Development Rennes - UMR6290, 35000, Rennes, France
| | - Adam R Boyko
- Department of Biomedical Sciences, Cornell University, 930 Campus Road, Ithaca, NY, 14853, USA
| | - Brian W Davis
- Department of Veterinary Integrative Biosciences, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, 77843, USA
| | - Michaela Drögemüller
- Institute of Genetics, Vetsuisse Faculty, University of Bern, 3001, Bern, Switzerland
| | - Xin-Yao Feng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Konstantinos Gkagkavouzis
- Department of Genetics, School of Biology, Aristotle University of Thessaloniki, Thessaloniki, Macedonia 54124, Greece and Genomics and Epigenomics Translational Research (GENeTres), Center for Interdisciplinary Research and Innovation (CIRI-AUTH, Balkan Center, Thessaloniki, Greece
| | - Giorgos Iliopoulos
- NGO "Callisto", Wildlife and Nature Conservation Society, 54621, Thessaloniki, Greece
| | - Alexander C Harris
- National Human Genome Research Institute, National Institutes of Health, 50 South Drive, Building 50 Room 5351, Bethesda, MD, 20892, USA
| | - Marjo K Hytönen
- Department of Medical and Clinical Genetics, Department of Veterinary Biosciences, University of Helsinki and Folkhälsan Research Center, 02900, Helsinki, Finland
| | - Daniela C Kalthof
- NGO "Callisto", Wildlife and Nature Conservation Society, 54621, Thessaloniki, Greece
| | - Yan-Hu Liu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Petros Lymberakis
- Natural History Museum of Crete & Department of Biology, University of Crete, 71202, Irakleio, Greece
- Biology Department, School of Sciences and Engineering, University of Crete, Heraklion, Greece
- Palaeogenomics and Evolutionary Genetics Lab, Institute of Molecular Biology and Biotechnology (IMBB), Foundation for Research and Technology - Hellas (FORTH), Heraklion, Greece
| | - Nikolaos Poulakakis
- Natural History Museum of Crete & Department of Biology, University of Crete, 71202, Irakleio, Greece
- Biology Department, School of Sciences and Engineering, University of Crete, Heraklion, Greece
- Palaeogenomics and Evolutionary Genetics Lab, Institute of Molecular Biology and Biotechnology (IMBB), Foundation for Research and Technology - Hellas (FORTH), Heraklion, Greece
| | - Ana Elisabete Pires
- BIOPOLIS-CIBIO-InBIO-Centro de Investigação Em Biodiversidade E Recursos Genéticos - ArchGen Group, Universidade Do Porto, 4485-661, Vairão, Portugal
| | - Fernando Racimo
- Section for Molecular Ecology and Evolution, Globe Institute, University of Copenhagen, Øster Voldgade 5-7, 1350, Copenhagen, Denmark
| | | | - Peter Savolainen
- Department of Gene Technology, Science for Life Laboratory, KTH - Royal Institute of Technology, 17121, Solna, Sweden
| | - Semina Venetsani
- Department of Genetics, School of Biology, Aristotle University of Thessaloniki, 54124, Thessaloniki, Macedonia, Greece
| | - Imke Tammen
- Sydney School of Veterinary Science, The University of Sydney, Sydney, NSW, 2570, Australia
| | - Alexandros Triantafyllidis
- Department of Genetics, School of Biology, Aristotle University of Thessaloniki, Thessaloniki, Macedonia 54124, Greece and Genomics and Epigenomics Translational Research (GENeTres), Center for Interdisciplinary Research and Innovation (CIRI-AUTH, Balkan Center, Thessaloniki, Greece
| | - Bridgett vonHoldt
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, 08544, USA
| | - Robert K Wayne
- Department of Ecology and Evolutionary Biology, Ecology and Evolutionary Biology, University of California, Los Angeles, CA, 90095-7246, USA
| | - Greger Larson
- Palaeogenomics and Bio-Archaeology Research Network, School of Archaeology, University of Oxford, Oxford, OX1 3TG, UK
| | - Frank W Nicholas
- Sydney School of Veterinary Science, The University of Sydney, Sydney, NSW, 2570, Australia
| | - Hannes Lohi
- Department of Medical and Clinical Genetics, Department of Veterinary Biosciences, University of Helsinki and Folkhälsan Research Center, 02900, Helsinki, Finland
| | - Tosso Leeb
- Institute of Genetics, Vetsuisse Faculty, University of Bern, 3001, Bern, Switzerland
| | - Ya-Ping Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Elaine A Ostrander
- National Human Genome Research Institute, National Institutes of Health, 50 South Drive, Building 50 Room 5351, Bethesda, MD, 20892, USA.
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4
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Meadows JRS, Kidd JM, Wang GD, Parker HG, Schall PZ, Bianchi M, Christmas MJ, Bougiouri K, Buckley RM, Hitte C, Nguyen AK, Wang C, Jagannathan V, Niskanen JE, Frantz LAF, Arumilli M, Hundi S, Lindblad-Toh K, Ginja C, Agustina KK, André C, Boyko AR, Davis BW, Drögemüller M, Feng XY, Gkagkavouzis K, Iliopoulos G, Harris AC, Hytönen MK, Kalthoff DC, Liu YH, Lymberakis P, Poulakakis N, Pires AE, Racimo F, Ramos-Almodovar F, Savolainen P, Venetsani S, Tammen I, Triantafyllidis A, vonHoldt B, Wayne RK, Larson G, Nicholas FW, Lohi H, Leeb T, Zhang YP, Ostrander EA. Genome sequencing of 2000 canids by the Dog10K consortium advances the understanding of demography, genome function and architecture. Genome Biol 2023; 24:187. [PMID: 37582787 PMCID: PMC10426128 DOI: 10.1186/s13059-023-03023-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 07/25/2023] [Indexed: 08/17/2023] Open
Abstract
BACKGROUND The international Dog10K project aims to sequence and analyze several thousand canine genomes. Incorporating 20 × data from 1987 individuals, including 1611 dogs (321 breeds), 309 village dogs, 63 wolves, and four coyotes, we identify genomic variation across the canid family, setting the stage for detailed studies of domestication, behavior, morphology, disease susceptibility, and genome architecture and function. RESULTS We report the analysis of > 48 M single-nucleotide, indel, and structural variants spanning the autosomes, X chromosome, and mitochondria. We discover more than 75% of variation for 239 sampled breeds. Allele sharing analysis indicates that 94.9% of breeds form monophyletic clusters and 25 major clades. German Shepherd Dogs and related breeds show the highest allele sharing with independent breeds from multiple clades. On average, each breed dog differs from the UU_Cfam_GSD_1.0 reference at 26,960 deletions and 14,034 insertions greater than 50 bp, with wolves having 14% more variants. Discovered variants include retrogene insertions from 926 parent genes. To aid functional prioritization, single-nucleotide variants were annotated with SnpEff and Zoonomia phyloP constraint scores. Constrained positions were negatively correlated with allele frequency. Finally, the utility of the Dog10K data as an imputation reference panel is assessed, generating high-confidence calls across varied genotyping platform densities including for breeds not included in the Dog10K collection. CONCLUSIONS We have developed a dense dataset of 1987 sequenced canids that reveals patterns of allele sharing, identifies likely functional variants, informs breed structure, and enables accurate imputation. Dog10K data are publicly available.
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Affiliation(s)
- Jennifer R S Meadows
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, 75132, Uppsala, Sweden.
| | - Jeffrey M Kidd
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, 48107, USA.
| | - Guo-Dong Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Heidi G Parker
- National Human Genome Research Institute, National Institutes of Health, 50 South Drive, Building 50 Room 5351, Bethesda, MD, 20892, USA
| | - Peter Z Schall
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, 48107, USA
| | - Matteo Bianchi
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, 75132, Uppsala, Sweden
| | - Matthew J Christmas
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, 75132, Uppsala, Sweden
| | - Katia Bougiouri
- Section for Molecular Ecology and Evolution, Globe Institute, University of Copenhagen, Øster Voldgade 5-7, 1350, Copenhagen, Denmark
| | - Reuben M Buckley
- National Human Genome Research Institute, National Institutes of Health, 50 South Drive, Building 50 Room 5351, Bethesda, MD, 20892, USA
| | - Christophe Hitte
- University of Rennes, CNRS, Institute Genetics and Development Rennes - UMR6290, 35000, Rennes, France
| | - Anthony K Nguyen
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, 48107, USA
| | - Chao Wang
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, 75132, Uppsala, Sweden
| | - Vidhya Jagannathan
- Institute of Genetics, Vetsuisse Faculty, University of Bern, 3001, Bern, Switzerland
| | - Julia E Niskanen
- Department of Medical and Clinical Genetics, Department of Veterinary Biosciences, University of Helsinki and Folkhälsan Research Center, 02900, Helsinki, Finland
| | - Laurent A F Frantz
- School of Biological and Behavioural Sciences, Queen Mary University of London, London E14NS, UK and Palaeogenomics Group, Department of Veterinary Sciences, Ludwig Maximilian University, D-80539, Munich, Germany
| | - Meharji Arumilli
- Department of Medical and Clinical Genetics, Department of Veterinary Biosciences, University of Helsinki and Folkhälsan Research Center, 02900, Helsinki, Finland
| | - Sruthi Hundi
- Department of Medical and Clinical Genetics, Department of Veterinary Biosciences, University of Helsinki and Folkhälsan Research Center, 02900, Helsinki, Finland
| | - Kerstin Lindblad-Toh
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, 75132, Uppsala, Sweden
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Catarina Ginja
- BIOPOLIS-CIBIO-InBIO-Centro de Investigação Em Biodiversidade E Recursos Genéticos - ArchGen Group, Universidade Do Porto, 4485-661, Vairão, Portugal
| | | | - Catherine André
- University of Rennes, CNRS, Institute Genetics and Development Rennes - UMR6290, 35000, Rennes, France
| | - Adam R Boyko
- Department of Biomedical Sciences, Cornell University, 930 Campus Road, Ithaca, NY, 14853, USA
| | - Brian W Davis
- Department of Veterinary Integrative Biosciences, School of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, 77843, USA
| | - Michaela Drögemüller
- Institute of Genetics, Vetsuisse Faculty, University of Bern, 3001, Bern, Switzerland
| | - Xin-Yao Feng
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Konstantinos Gkagkavouzis
- Department of Genetics, School of Biology, ), Aristotle University of Thessaloniki, Thessaloniki, Macedonia 54124, Greece and Genomics and Epigenomics Translational Research (GENeTres), Center for Interdisciplinary Research and Innovation (CIRI-AUTH, Balkan Center, Thessaloniki, Greece
| | - Giorgos Iliopoulos
- NGO "Callisto", Wildlife and Nature Conservation Society, 54621, Thessaloniki, Greece
| | - Alexander C Harris
- National Human Genome Research Institute, National Institutes of Health, 50 South Drive, Building 50 Room 5351, Bethesda, MD, 20892, USA
| | - Marjo K Hytönen
- Department of Medical and Clinical Genetics, Department of Veterinary Biosciences, University of Helsinki and Folkhälsan Research Center, 02900, Helsinki, Finland
| | - Daniela C Kalthoff
- NGO "Callisto", Wildlife and Nature Conservation Society, 54621, Thessaloniki, Greece
| | - Yan-Hu Liu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Petros Lymberakis
- Natural History Museum of Crete & Department of Biology, University of Crete, 71202, Irakleio, Greece
- Biology Department, School of Sciences and Engineering, University of Crete, Heraklion, Greece
- Palaeogenomics and Evolutionary Genetics Lab, Institute of Molecular Biology and Biotechnology (IMBB), Foundation for Research and Technology - Hellas (FORTH), Heraklion, Greece
| | - Nikolaos Poulakakis
- Natural History Museum of Crete & Department of Biology, University of Crete, 71202, Irakleio, Greece
- Biology Department, School of Sciences and Engineering, University of Crete, Heraklion, Greece
- Palaeogenomics and Evolutionary Genetics Lab, Institute of Molecular Biology and Biotechnology (IMBB), Foundation for Research and Technology - Hellas (FORTH), Heraklion, Greece
| | - Ana Elisabete Pires
- BIOPOLIS-CIBIO-InBIO-Centro de Investigação Em Biodiversidade E Recursos Genéticos - ArchGen Group, Universidade Do Porto, 4485-661, Vairão, Portugal
| | - Fernando Racimo
- Section for Molecular Ecology and Evolution, Globe Institute, University of Copenhagen, Øster Voldgade 5-7, 1350, Copenhagen, Denmark
| | | | - Peter Savolainen
- Department of Gene Technology, Science for Life Laboratory, KTH - Royal Institute of Technology, 17121, Solna, Sweden
| | - Semina Venetsani
- Department of Genetics, School of Biology, Aristotle University of Thessaloniki, 54124, Thessaloniki, Macedonia, Greece
| | - Imke Tammen
- Sydney School of Veterinary Science, The University of Sydney, Sydney, NSW, 2570, Australia
| | - Alexandros Triantafyllidis
- Department of Genetics, School of Biology, ), Aristotle University of Thessaloniki, Thessaloniki, Macedonia 54124, Greece and Genomics and Epigenomics Translational Research (GENeTres), Center for Interdisciplinary Research and Innovation (CIRI-AUTH, Balkan Center, Thessaloniki, Greece
| | - Bridgett vonHoldt
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, 08544, USA
| | - Robert K Wayne
- Department of Ecology and Evolutionary Biology, Ecology and Evolutionary Biology, University of California, Los Angeles, CA, 90095-7246, USA
| | - Greger Larson
- Palaeogenomics and Bio-Archaeology Research Network, School of Archaeology, University of Oxford, Oxford, OX1 3TG, UK
| | - Frank W Nicholas
- Sydney School of Veterinary Science, The University of Sydney, Sydney, NSW, 2570, Australia
| | - Hannes Lohi
- Department of Medical and Clinical Genetics, Department of Veterinary Biosciences, University of Helsinki and Folkhälsan Research Center, 02900, Helsinki, Finland
| | - Tosso Leeb
- Institute of Genetics, Vetsuisse Faculty, University of Bern, 3001, Bern, Switzerland
| | - Ya-Ping Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Elaine A Ostrander
- National Human Genome Research Institute, National Institutes of Health, 50 South Drive, Building 50 Room 5351, Bethesda, MD, 20892, USA.
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5
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Lundtoft C, Eriksson D, Bianchi M, Aranda-Guillén M, Landegren N, Rantapää-Dahlqvist S, Söderkvist P, Meadows JRS, Bensing S, Pielberg GR, Lindblad-Toh K, Rönnblom L, Kämpe O. Relation between HLA and copy number variation of steroid 21-hydroxylase in a Swedish cohort of patients with autoimmune Addison's disease. Eur J Endocrinol 2023; 189:235-241. [PMID: 37553728 DOI: 10.1093/ejendo/lvad102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 03/27/2023] [Accepted: 06/26/2023] [Indexed: 08/10/2023]
Abstract
OBJECTIVE Autoantibodies against the adrenal enzyme 21-hydroxylase is a hallmark manifestation in autoimmune Addison's disease (AAD). Steroid 21-hydroxylase is encoded by CYP21A2, which is located in the human leucocyte antigen (HLA) region together with the highly similar pseudogene CYP21A1P. A high level of copy number variation is seen for the 2 genes, and therefore, we asked whether genetic variation of the CYP21 genes is associated with AAD. DESIGN Case-control study on patients with AAD and healthy controls. METHODS Using next-generation DNA sequencing, we estimated the copy number of CYP21A2 and CYP21A1P, together with HLA alleles, in 479 Swedish patients with AAD and autoantibodies against 21-hydroxylase and in 1393 healthy controls. RESULTS With 95% of individuals carrying 2 functional 21-hydroxylase genes, no difference in CYP21A2 copy number was found when comparing patients and controls. In contrast, we discovered a lower copy number of the pseudogene CYP21A1P among AAD patients (P = 5 × 10-44), together with associations of additional nucleotide variants, in the CYP21 region. However, the strongest association was found for HLA-DQB1*02:01 (P = 9 × 10-63), which, in combination with the DRB1*04:04-DQB1*03:02 haplotype, imposed the greatest risk of AAD. CONCLUSIONS We identified strong associations between copy number variants in the CYP21 region and risk of AAD, although these associations most likely are due to linkage disequilibrium with disease-associated HLA class II alleles.
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Affiliation(s)
| | - Daniel Eriksson
- Department of Medicine (Solna), Center for Molecular Medicine, Karolinska Instituttet, Stockholm, Sweden
- Department of Clinical Genetics, Uppsala University Hospital, Uppsala, Sweden
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Matteo Bianchi
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Maribel Aranda-Guillén
- Department of Medicine (Solna), Center for Molecular Medicine, Karolinska Instituttet, Stockholm, Sweden
| | - Nils Landegren
- Department of Medicine (Solna), Center for Molecular Medicine, Karolinska Instituttet, Stockholm, Sweden
- Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | | | - Peter Söderkvist
- Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
| | - Jennifer R S Meadows
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Sophie Bensing
- Department of Endocrinology, Karolinska University Hospital, Stockholm, Sweden
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Gerli Rosengren Pielberg
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Kerstin Lindblad-Toh
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
- Broad Institute, MIT and Harvard, Cambridge, MA, United States
| | - Lars Rönnblom
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Olle Kämpe
- Department of Medicine (Solna), Center for Molecular Medicine, Karolinska Instituttet, Stockholm, Sweden
- Department of Endocrinology, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Science, University of Bergen, Bergen, Norway
- K.G. Jebsen Center for Autoimmune Diseases, University of Bergen, Bergen, Norway
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6
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Christmas MJ, Kaplow IM, Genereux DP, Dong MX, Hughes GM, Li X, Sullivan PF, Hindle AG, Andrews G, Armstrong JC, Bianchi M, Breit AM, Diekhans M, Fanter C, Foley NM, Goodman DB, Goodman L, Keough KC, Kirilenko B, Kowalczyk A, Lawless C, Lind AL, Meadows JRS, Moreira LR, Redlich RW, Ryan L, Swofford R, Valenzuela A, Wagner F, Wallerman O, Brown AR, Damas J, Fan K, Gatesy J, Grimshaw J, Johnson J, Kozyrev SV, Lawler AJ, Marinescu VD, Morrill KM, Osmanski A, Paulat NS, Phan BN, Reilly SK, Schäffer DE, Steiner C, Supple MA, Wilder AP, Wirthlin ME, Xue JR, Birren BW, Gazal S, Hubley RM, Koepfli KP, Marques-Bonet T, Meyer WK, Nweeia M, Sabeti PC, Shapiro B, Smit AFA, Springer MS, Teeling EC, Weng Z, Hiller M, Levesque DL, Lewin HA, Murphy WJ, Navarro A, Paten B, Pollard KS, Ray DA, Ruf I, Ryder OA, Pfenning AR, Lindblad-Toh K, Karlsson EK, Andrews G, Armstrong JC, Bianchi M, Birren BW, Bredemeyer KR, Breit AM, Christmas MJ, Clawson H, Damas J, Di Palma F, Diekhans M, Dong MX, Eizirik E, Fan K, Fanter C, Foley NM, Forsberg-Nilsson K, Garcia CJ, Gatesy J, Gazal S, Genereux DP, Goodman L, Grimshaw J, Halsey MK, Harris AJ, Hickey G, Hiller M, Hindle AG, Hubley RM, Hughes GM, Johnson J, Juan D, Kaplow IM, Karlsson EK, Keough KC, Kirilenko B, Koepfli KP, Korstian JM, Kowalczyk A, Kozyrev SV, Lawler AJ, Lawless C, Lehmann T, Levesque DL, Lewin HA, Li X, Lind A, Lindblad-Toh K, Mackay-Smith A, Marinescu VD, Marques-Bonet T, Mason VC, Meadows JRS, Meyer WK, Moore JE, Moreira LR, Moreno-Santillan DD, Morrill KM, Muntané G, Murphy WJ, Navarro A, Nweeia M, Ortmann S, Osmanski A, Paten B, Paulat NS, Pfenning AR, Phan BN, Pollard KS, Pratt HE, Ray DA, Reilly SK, Rosen JR, Ruf I, Ryan L, Ryder OA, Sabeti PC, Schäffer DE, Serres A, Shapiro B, Smit AFA, Springer M, Srinivasan C, Steiner C, Storer JM, Sullivan KAM, Sullivan PF, Sundström E, Supple MA, Swofford R, Talbot JE, Teeling E, Turner-Maier J, Valenzuela A, Wagner F, Wallerman O, Wang C, Wang J, Weng Z, Wilder AP, Wirthlin ME, Xue JR, Zhang X. Evolutionary constraint and innovation across hundreds of placental mammals. Science 2023. [PMID: 37104599 DOI: 0.1126/science.abn3943] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
Zoonomia is the largest comparative genomics resource for mammals produced to date. By aligning genomes for 240 species, we identify bases that, when mutated, are likely to affect fitness and alter disease risk. At least 332 million bases (~10.7%) in the human genome are unusually conserved across species (evolutionarily constrained) relative to neutrally evolving repeats, and 4552 ultraconserved elements are nearly perfectly conserved. Of 101 million significantly constrained single bases, 80% are outside protein-coding exons and half have no functional annotations in the Encyclopedia of DNA Elements (ENCODE) resource. Changes in genes and regulatory elements are associated with exceptional mammalian traits, such as hibernation, that could inform therapeutic development. Earth's vast and imperiled biodiversity offers distinctive power for identifying genetic variants that affect genome function and organismal phenotypes.
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Affiliation(s)
- Matthew J Christmas
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Irene M Kaplow
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | | | - Michael X Dong
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Graham M Hughes
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Xue Li
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Morningside Graduate School of Biomedical Sciences, UMass Chan Medical School, Worcester, MA 01605, USA
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Patrick F Sullivan
- Department of Genetics, University of North Carolina Medical School, Chapel Hill, NC 27599, USA
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Allyson G Hindle
- School of Life Sciences, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Gregory Andrews
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Joel C Armstrong
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Matteo Bianchi
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Ana M Breit
- School of Biology and Ecology, University of Maine, Orono, ME 04469, USA
| | - Mark Diekhans
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Cornelia Fanter
- School of Life Sciences, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Nicole M Foley
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX 77843, USA
| | - Daniel B Goodman
- Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA
| | | | - Kathleen C Keough
- Fauna Bio, Inc., Emeryville, CA 94608, USA
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94158, USA
- Gladstone Institutes, San Francisco, CA 94158, USA
| | - Bogdan Kirilenko
- Faculty of Biosciences, Goethe-University, 60438 Frankfurt, Germany
- LOEWE Centre for Translational Biodiversity Genomics, 60325 Frankfurt, Germany
- Senckenberg Research Institute, 60325 Frankfurt, Germany
| | - Amanda Kowalczyk
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Colleen Lawless
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Abigail L Lind
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94158, USA
- Gladstone Institutes, San Francisco, CA 94158, USA
| | - Jennifer R S Meadows
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Lucas R Moreira
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Ruby W Redlich
- Department of Biological Sciences, Mellon College of Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Louise Ryan
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Ross Swofford
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Alejandro Valenzuela
- Department of Experimental and Health Sciences, Institute of Evolutionary Biology (UPF-CSIC), Universitat Pompeu Fabra, 08003 Barcelona, Spain
| | - Franziska Wagner
- Museum of Zoology, Senckenberg Natural History Collections Dresden, 01109 Dresden, Germany
| | - Ola Wallerman
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Ashley R Brown
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Joana Damas
- The Genome Center, University of California Davis, Davis, CA 95616, USA
| | - Kaili Fan
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - John Gatesy
- Division of Vertebrate Zoology, American Museum of Natural History, New York, NY 10024, USA
| | - Jenna Grimshaw
- Department of Biological Sciences, Texas Tech University, Lubbock, TX 79409, USA
| | - Jeremy Johnson
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Sergey V Kozyrev
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Alyssa J Lawler
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Department of Biological Sciences, Mellon College of Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Voichita D Marinescu
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Kathleen M Morrill
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Morningside Graduate School of Biomedical Sciences, UMass Chan Medical School, Worcester, MA 01605, USA
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Austin Osmanski
- Medical Scientist Training Program, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Nicole S Paulat
- Department of Biological Sciences, Texas Tech University, Lubbock, TX 79409, USA
| | - BaDoi N Phan
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Medical Scientist Training Program, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Steven K Reilly
- Department of Genetics, Yale School of Medicine, New Haven, CT 06510, USA
| | - Daniel E Schäffer
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Cynthia Steiner
- Conservation Genetics, San Diego Zoo Wildlife Alliance, Escondido, CA 92027, USA
| | - Megan A Supple
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Aryn P Wilder
- Conservation Genetics, San Diego Zoo Wildlife Alliance, Escondido, CA 92027, USA
| | - Morgan E Wirthlin
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - James R Xue
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
| | - Bruce W Birren
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Steven Gazal
- Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | | | - Klaus-Peter Koepfli
- Center for Species Survival, Smithsonian's National Zoo and Conservation Biology Institute, Washington, DC 20008, USA
- Computer Technologies Laboratory, ITMO University, St. Petersburg 197101, Russia
- Smithsonian-Mason School of Conservation, George Mason University, Front Royal, VA 22630, USA
| | - Tomas Marques-Bonet
- Catalan Institution of Research and Advanced Studies (ICREA), 08010 Barcelona, Spain
- CNAG-CRG, Centre for Genomic Regulation, Barcelona Institute of Science and Technology (BIST), 08036 Barcelona, Spain
- Department of Medicine and Life Sciences, Institute of Evolutionary Biology (UPF-CSIC), Universitat Pompeu Fabra, 08003 Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Barcelona, Spain
| | - Wynn K Meyer
- Department of Biological Sciences, Lehigh University, Bethlehem, PA 18015, USA
| | - Martin Nweeia
- Department of Comprehensive Care, School of Dental Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
- Department of Vertebrate Zoology, Canadian Museum of Nature, Ottawa, Ontario K2P 2R1, Canada
- Department of Vertebrate Zoology, Smithsonian Institution, Washington, DC 20002, USA
- Narwhal Genome Initiative, Department of Restorative Dentistry and Biomaterials Sciences, Harvard School of Dental Medicine, Boston, MA 02115, USA
| | - Pardis C Sabeti
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA
| | - Beth Shapiro
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA 95064, USA
- Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | | | - Mark S Springer
- Department of Evolution, Ecology and Organismal Biology, University of California Riverside, Riverside, CA 92521, USA
| | - Emma C Teeling
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Michael Hiller
- Faculty of Biosciences, Goethe-University, 60438 Frankfurt, Germany
- LOEWE Centre for Translational Biodiversity Genomics, 60325 Frankfurt, Germany
- Senckenberg Research Institute, 60325 Frankfurt, Germany
| | | | - Harris A Lewin
- The Genome Center, University of California Davis, Davis, CA 95616, USA
- Department of Evolution and Ecology, University of California Davis, Davis, CA 95616, USA
- John Muir Institute for the Environment, University of California Davis, Davis, CA 95616, USA
| | - William J Murphy
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX 77843, USA
| | - Arcadi Navarro
- Catalan Institution of Research and Advanced Studies (ICREA), 08010 Barcelona, Spain
- Department of Medicine and Life Sciences, Institute of Evolutionary Biology (UPF-CSIC), Universitat Pompeu Fabra, 08003 Barcelona, Spain
- BarcelonaBeta Brain Research Center, Pasqual Maragall Foundation, 08005 Barcelona, Spain
- CRG, Centre for Genomic Regulation, Barcelona Institute of Science and Technology (BIST), 08003 Barcelona, Spain
| | - Benedict Paten
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Katherine S Pollard
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94158, USA
- Gladstone Institutes, San Francisco, CA 94158, USA
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
| | - David A Ray
- Department of Biological Sciences, Texas Tech University, Lubbock, TX 79409, USA
| | - Irina Ruf
- Division of Messel Research and Mammalogy, Senckenberg Research Institute and Natural History Museum Frankfurt, 60325 Frankfurt am Main, Germany
| | - Oliver A Ryder
- Conservation Genetics, San Diego Zoo Wildlife Alliance, Escondido, CA 92027, USA
- Department of Evolution, Behavior and Ecology, School of Biological Sciences, University of California San Diego, La Jolla, CA 92039, USA
| | - Andreas R Pfenning
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Kerstin Lindblad-Toh
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Elinor K Karlsson
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
- Program in Molecular Medicine, UMass Chan Medical School, Worcester, MA 01605, USA
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7
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Kaplow IM, Lawler AJ, Schäffer DE, Srinivasan C, Sestili HH, Wirthlin ME, Phan BN, Prasad K, Brown AR, Zhang X, Foley K, Genereux DP, Karlsson EK, Lindblad-Toh K, Meyer WK, Pfenning AR, Andrews G, Armstrong JC, Bianchi M, Birren BW, Bredemeyer KR, Breit AM, Christmas MJ, Clawson H, Damas J, Di Palma F, Diekhans M, Dong MX, Eizirik E, Fan K, Fanter C, Foley NM, Forsberg-Nilsson K, Garcia CJ, Gatesy J, Gazal S, Genereux DP, Goodman L, Grimshaw J, Halsey MK, Harris AJ, Hickey G, Hiller M, Hindle AG, Hubley RM, Hughes GM, Johnson J, Juan D, Kaplow IM, Karlsson EK, Keough KC, Kirilenko B, Koepfli KP, Korstian JM, Kowalczyk A, Kozyrev SV, Lawler AJ, Lawless C, Lehmann T, Levesque DL, Lewin HA, Li X, Lind A, Lindblad-Toh K, Mackay-Smith A, Marinescu VD, Marques-Bonet T, Mason VC, Meadows JRS, Meyer WK, Moore JE, Moreira LR, Moreno-Santillan DD, Morrill KM, Muntané G, Murphy WJ, Navarro A, Nweeia M, Ortmann S, Osmanski A, Paten B, Paulat NS, Pfenning AR, Phan BN, Pollard KS, Pratt HE, Ray DA, Reilly SK, Rosen JR, Ruf I, Ryan L, Ryder OA, Sabeti PC, Schäffer DE, Serres A, Shapiro B, Smit AFA, Springer M, Srinivasan C, Steiner C, Storer JM, Sullivan KAM, Sullivan PF, Sundström E, Supple MA, Swofford R, Talbot JE, Teeling E, Turner-Maier J, Valenzuela A, Wagner F, Wallerman O, Wang C, Wang J, Weng Z, Wilder AP, Wirthlin ME, Xue JR, Zhang X. Relating enhancer genetic variation across mammals to complex phenotypes using machine learning. Science 2023; 380:eabm7993. [PMID: 37104615 DOI: 10.1126/science.abm7993] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Abstract
Protein-coding differences between species often fail to explain phenotypic diversity, suggesting the involvement of genomic elements that regulate gene expression such as enhancers. Identifying associations between enhancers and phenotypes is challenging because enhancer activity can be tissue-dependent and functionally conserved despite low sequence conservation. We developed the Tissue-Aware Conservation Inference Toolkit (TACIT) to associate candidate enhancers with species' phenotypes using predictions from machine learning models trained on specific tissues. Applying TACIT to associate motor cortex and parvalbumin-positive interneuron enhancers with neurological phenotypes revealed dozens of enhancer-phenotype associations, including brain size-associated enhancers that interact with genes implicated in microcephaly or macrocephaly. TACIT provides a foundation for identifying enhancers associated with the evolution of any convergently evolved phenotype in any large group of species with aligned genomes.
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Affiliation(s)
- Irene M Kaplow
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Alyssa J Lawler
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
- Department of Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Daniel E Schäffer
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Chaitanya Srinivasan
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Heather H Sestili
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Morgan E Wirthlin
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
| | - BaDoi N Phan
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
- Medical Scientist Training Program, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Kavya Prasad
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Ashley R Brown
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Xiaomeng Zhang
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Kathleen Foley
- Department of Biological Sciences, Lehigh University, Bethlehem, PA, USA
| | - Diane P Genereux
- Broad Institute, Cambridge, MA, USA
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Elinor K Karlsson
- Broad Institute, Cambridge, MA, USA
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Kerstin Lindblad-Toh
- Broad Institute, Cambridge, MA, USA
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Wynn K Meyer
- Department of Biological Sciences, Lehigh University, Bethlehem, PA, USA
| | - Andreas R Pfenning
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
- Department of Biology, Carnegie Mellon University, Pittsburgh, PA, USA
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8
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Christmas MJ, Kaplow IM, Genereux DP, Dong MX, Hughes GM, Li X, Sullivan PF, Hindle AG, Andrews G, Armstrong JC, Bianchi M, Breit AM, Diekhans M, Fanter C, Foley NM, Goodman DB, Goodman L, Keough KC, Kirilenko B, Kowalczyk A, Lawless C, Lind AL, Meadows JRS, Moreira LR, Redlich RW, Ryan L, Swofford R, Valenzuela A, Wagner F, Wallerman O, Brown AR, Damas J, Fan K, Gatesy J, Grimshaw J, Johnson J, Kozyrev SV, Lawler AJ, Marinescu VD, Morrill KM, Osmanski A, Paulat NS, Phan BN, Reilly SK, Schäffer DE, Steiner C, Supple MA, Wilder AP, Wirthlin ME, Xue JR, Birren BW, Gazal S, Hubley RM, Koepfli KP, Marques-Bonet T, Meyer WK, Nweeia M, Sabeti PC, Shapiro B, Smit AFA, Springer MS, Teeling EC, Weng Z, Hiller M, Levesque DL, Lewin HA, Murphy WJ, Navarro A, Paten B, Pollard KS, Ray DA, Ruf I, Ryder OA, Pfenning AR, Lindblad-Toh K, Karlsson EK. Evolutionary constraint and innovation across hundreds of placental mammals. Science 2023; 380:eabn3943. [PMID: 37104599 PMCID: PMC10250106 DOI: 10.1126/science.abn3943] [Citation(s) in RCA: 34] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 12/16/2022] [Indexed: 04/29/2023]
Abstract
Zoonomia is the largest comparative genomics resource for mammals produced to date. By aligning genomes for 240 species, we identify bases that, when mutated, are likely to affect fitness and alter disease risk. At least 332 million bases (~10.7%) in the human genome are unusually conserved across species (evolutionarily constrained) relative to neutrally evolving repeats, and 4552 ultraconserved elements are nearly perfectly conserved. Of 101 million significantly constrained single bases, 80% are outside protein-coding exons and half have no functional annotations in the Encyclopedia of DNA Elements (ENCODE) resource. Changes in genes and regulatory elements are associated with exceptional mammalian traits, such as hibernation, that could inform therapeutic development. Earth's vast and imperiled biodiversity offers distinctive power for identifying genetic variants that affect genome function and organismal phenotypes.
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Affiliation(s)
- Matthew J. Christmas
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Irene M. Kaplow
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | | | - Michael X. Dong
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Graham M. Hughes
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Xue Li
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Morningside Graduate School of Biomedical Sciences, UMass Chan Medical School, Worcester, MA 01605, USA
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Patrick F. Sullivan
- Department of Genetics, University of North Carolina Medical School, Chapel Hill, NC 27599, USA
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Allyson G. Hindle
- School of Life Sciences, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Gregory Andrews
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Joel C. Armstrong
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Matteo Bianchi
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Ana M. Breit
- School of Biology and Ecology, University of Maine, Orono, ME 04469, USA
| | - Mark Diekhans
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Cornelia Fanter
- School of Life Sciences, University of Nevada Las Vegas, Las Vegas, NV 89154, USA
| | - Nicole M. Foley
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX 77843, USA
| | - Daniel B. Goodman
- Department of Microbiology and Immunology, University of California San Francisco, San Francisco, CA 94143, USA
| | | | - Kathleen C. Keough
- Fauna Bio, Inc., Emeryville, CA 94608, USA
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94158, USA
- Gladstone Institutes, San Francisco, CA 94158, USA
| | - Bogdan Kirilenko
- Faculty of Biosciences, Goethe-University, 60438 Frankfurt, Germany
- LOEWE Centre for Translational Biodiversity Genomics, 60325 Frankfurt, Germany
- Senckenberg Research Institute, 60325 Frankfurt, Germany
| | - Amanda Kowalczyk
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Colleen Lawless
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Abigail L. Lind
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94158, USA
- Gladstone Institutes, San Francisco, CA 94158, USA
| | - Jennifer R. S. Meadows
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Lucas R. Moreira
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Ruby W. Redlich
- Department of Biological Sciences, Mellon College of Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Louise Ryan
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Ross Swofford
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Alejandro Valenzuela
- Department of Experimental and Health Sciences, Institute of Evolutionary Biology (UPF-CSIC), Universitat Pompeu Fabra, 08003 Barcelona, Spain
| | - Franziska Wagner
- Museum of Zoology, Senckenberg Natural History Collections Dresden, 01109 Dresden, Germany
| | - Ola Wallerman
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Ashley R. Brown
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Joana Damas
- The Genome Center, University of California Davis, Davis, CA 95616, USA
| | - Kaili Fan
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - John Gatesy
- Division of Vertebrate Zoology, American Museum of Natural History, New York, NY 10024, USA
| | - Jenna Grimshaw
- Department of Biological Sciences, Texas Tech University, Lubbock, TX 79409, USA
| | - Jeremy Johnson
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Sergey V. Kozyrev
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Alyssa J. Lawler
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Department of Biological Sciences, Mellon College of Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Voichita D. Marinescu
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Kathleen M. Morrill
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Morningside Graduate School of Biomedical Sciences, UMass Chan Medical School, Worcester, MA 01605, USA
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Austin Osmanski
- Medical Scientist Training Program, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Nicole S. Paulat
- Department of Biological Sciences, Texas Tech University, Lubbock, TX 79409, USA
| | - BaDoi N. Phan
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Medical Scientist Training Program, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Steven K. Reilly
- Department of Genetics, Yale School of Medicine, New Haven, CT 06510, USA
| | - Daniel E. Schäffer
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Cynthia Steiner
- Conservation Genetics, San Diego Zoo Wildlife Alliance, Escondido, CA 92027, USA
| | - Megan A. Supple
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Aryn P. Wilder
- Conservation Genetics, San Diego Zoo Wildlife Alliance, Escondido, CA 92027, USA
| | - Morgan E. Wirthlin
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - James R. Xue
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
| | | | - Bruce W. Birren
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Steven Gazal
- Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | | | - Klaus-Peter Koepfli
- Center for Species Survival, Smithsonian’s National Zoo and Conservation Biology Institute, Washington, DC 20008, USA
- Computer Technologies Laboratory, ITMO University, St. Petersburg 197101, Russia
- Smithsonian-Mason School of Conservation, George Mason University, Front Royal, VA 22630, USA
| | - Tomas Marques-Bonet
- Catalan Institution of Research and Advanced Studies (ICREA), 08010 Barcelona, Spain
- CNAG-CRG, Centre for Genomic Regulation, Barcelona Institute of Science and Technology (BIST), 08036 Barcelona, Spain
- Department of Medicine and Life Sciences, Institute of Evolutionary Biology (UPF-CSIC), Universitat Pompeu Fabra, 08003 Barcelona, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Barcelona, Spain
| | - Wynn K. Meyer
- Department of Biological Sciences, Lehigh University, Bethlehem, PA 18015, USA
| | - Martin Nweeia
- Department of Comprehensive Care, School of Dental Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
- Department of Vertebrate Zoology, Canadian Museum of Nature, Ottawa, Ontario K2P 2R1, Canada
- Department of Vertebrate Zoology, Smithsonian Institution, Washington, DC 20002, USA
- Narwhal Genome Initiative, Department of Restorative Dentistry and Biomaterials Sciences, Harvard School of Dental Medicine, Boston, MA 02115, USA
| | - Pardis C. Sabeti
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
- Howard Hughes Medical Institute, Harvard University, Cambridge, MA 02138, USA
| | - Beth Shapiro
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA 95064, USA
- Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | | | - Mark S. Springer
- Department of Evolution, Ecology and Organismal Biology, University of California Riverside, Riverside, CA 92521, USA
| | - Emma C. Teeling
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Michael Hiller
- Faculty of Biosciences, Goethe-University, 60438 Frankfurt, Germany
- LOEWE Centre for Translational Biodiversity Genomics, 60325 Frankfurt, Germany
- Senckenberg Research Institute, 60325 Frankfurt, Germany
| | | | - Harris A. Lewin
- The Genome Center, University of California Davis, Davis, CA 95616, USA
- Department of Evolution and Ecology, University of California Davis, Davis, CA 95616, USA
- John Muir Institute for the Environment, University of California Davis, Davis, CA 95616, USA
| | - William J. Murphy
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX 77843, USA
| | - Arcadi Navarro
- Catalan Institution of Research and Advanced Studies (ICREA), 08010 Barcelona, Spain
- Department of Medicine and Life Sciences, Institute of Evolutionary Biology (UPF-CSIC), Universitat Pompeu Fabra, 08003 Barcelona, Spain
- BarcelonaBeta Brain Research Center, Pasqual Maragall Foundation, 08005 Barcelona, Spain
- CRG, Centre for Genomic Regulation, Barcelona Institute of Science and Technology (BIST), 08003 Barcelona, Spain
| | - Benedict Paten
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Katherine S. Pollard
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94158, USA
- Gladstone Institutes, San Francisco, CA 94158, USA
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
| | - David A. Ray
- Department of Biological Sciences, Texas Tech University, Lubbock, TX 79409, USA
| | - Irina Ruf
- Division of Messel Research and Mammalogy, Senckenberg Research Institute and Natural History Museum Frankfurt, 60325 Frankfurt am Main, Germany
| | - Oliver A. Ryder
- Conservation Genetics, San Diego Zoo Wildlife Alliance, Escondido, CA 92027, USA
- Department of Evolution, Behavior and Ecology, School of Biological Sciences, University of California San Diego, La Jolla, CA 92039, USA
| | - Andreas R. Pfenning
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Kerstin Lindblad-Toh
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Elinor K. Karlsson
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
- Program in Molecular Medicine, UMass Chan Medical School, Worcester, MA 01605, USA
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9
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Kirilenko BM, Munegowda C, Osipova E, Jebb D, Sharma V, Blumer M, Morales AE, Ahmed AW, Kontopoulos DG, Hilgers L, Lindblad-Toh K, Karlsson EK, Hiller M, Andrews G, Armstrong JC, Bianchi M, Birren BW, Bredemeyer KR, Breit AM, Christmas MJ, Clawson H, Damas J, Di Palma F, Diekhans M, Dong MX, Eizirik E, Fan K, Fanter C, Foley NM, Forsberg-Nilsson K, Garcia CJ, Gatesy J, Gazal S, Genereux DP, Goodman L, Grimshaw J, Halsey MK, Harris AJ, Hickey G, Hiller M, Hindle AG, Hubley RM, Hughes GM, Johnson J, Juan D, Kaplow IM, Karlsson EK, Keough KC, Kirilenko B, Koepfli KP, Korstian JM, Kowalczyk A, Kozyrev SV, Lawler AJ, Lawless C, Lehmann T, Levesque DL, Lewin HA, Li X, Lind A, Lindblad-Toh K, Mackay-Smith A, Marinescu VD, Marques-Bonet T, Mason VC, Meadows JRS, Meyer WK, Moore JE, Moreira LR, Moreno-Santillan DD, Morrill KM, Muntané G, Murphy WJ, Navarro A, Nweeia M, Ortmann S, Osmanski A, Paten B, Paulat NS, Pfenning AR, Phan BN, Pollard KS, Pratt HE, Ray DA, Reilly SK, Rosen JR, Ruf I, Ryan L, Ryder OA, Sabeti PC, Schäffer DE, Serres A, Shapiro B, Smit AFA, Springer M, Srinivasan C, Steiner C, Storer JM, Sullivan KAM, Sullivan PF, Sundström E, Supple MA, Swofford R, Talbot JE, Teeling E, Turner-Maier J, Valenzuela A, Wagner F, Wallerman O, Wang C, Wang J, Weng Z, Wilder AP, Wirthlin ME, Xue JR, Zhang X. Integrating gene annotation with orthology inference at scale. Science 2023; 380:eabn3107. [PMID: 37104600 DOI: 10.1126/science.abn3107] [Citation(s) in RCA: 24] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Abstract
Annotating coding genes and inferring orthologs are two classical challenges in genomics and evolutionary biology that have traditionally been approached separately, limiting scalability. We present TOGA (Tool to infer Orthologs from Genome Alignments), a method that integrates structural gene annotation and orthology inference. TOGA implements a different paradigm to infer orthologous loci, improves ortholog detection and annotation of conserved genes compared with state-of-the-art methods, and handles even highly fragmented assemblies. TOGA scales to hundreds of genomes, which we demonstrate by applying it to 488 placental mammal and 501 bird assemblies, creating the largest comparative gene resources so far. Additionally, TOGA detects gene losses, enables selection screens, and automatically provides a superior measure of mammalian genome quality. TOGA is a powerful and scalable method to annotate and compare genes in the genomic era.
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Affiliation(s)
- Bogdan M Kirilenko
- Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany
- Max Planck Institute for the Physics of Complex Systems, 01187 Dresden, Germany
- Center for Systems Biology Dresden, 01307 Dresden, Germany
- LOEWE Centre for Translational Biodiversity Genomics, 60325 Frankfurt, Germany
- Senckenberg Research Institute, 60325 Frankfurt, Germany
- Goethe University Frankfurt, Faculty of Biosciences, 60438 Frankfurt, Germany
| | - Chetan Munegowda
- Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany
- Max Planck Institute for the Physics of Complex Systems, 01187 Dresden, Germany
- Center for Systems Biology Dresden, 01307 Dresden, Germany
- LOEWE Centre for Translational Biodiversity Genomics, 60325 Frankfurt, Germany
- Senckenberg Research Institute, 60325 Frankfurt, Germany
- Goethe University Frankfurt, Faculty of Biosciences, 60438 Frankfurt, Germany
| | - Ekaterina Osipova
- Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany
- Max Planck Institute for the Physics of Complex Systems, 01187 Dresden, Germany
- Center for Systems Biology Dresden, 01307 Dresden, Germany
- LOEWE Centre for Translational Biodiversity Genomics, 60325 Frankfurt, Germany
- Senckenberg Research Institute, 60325 Frankfurt, Germany
- Goethe University Frankfurt, Faculty of Biosciences, 60438 Frankfurt, Germany
| | - David Jebb
- Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany
- Max Planck Institute for the Physics of Complex Systems, 01187 Dresden, Germany
- Center for Systems Biology Dresden, 01307 Dresden, Germany
| | - Virag Sharma
- Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany
- Max Planck Institute for the Physics of Complex Systems, 01187 Dresden, Germany
- Center for Systems Biology Dresden, 01307 Dresden, Germany
| | - Moritz Blumer
- Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany
- Max Planck Institute for the Physics of Complex Systems, 01187 Dresden, Germany
- Center for Systems Biology Dresden, 01307 Dresden, Germany
| | - Ariadna E Morales
- LOEWE Centre for Translational Biodiversity Genomics, 60325 Frankfurt, Germany
- Senckenberg Research Institute, 60325 Frankfurt, Germany
- Goethe University Frankfurt, Faculty of Biosciences, 60438 Frankfurt, Germany
| | - Alexis-Walid Ahmed
- LOEWE Centre for Translational Biodiversity Genomics, 60325 Frankfurt, Germany
- Senckenberg Research Institute, 60325 Frankfurt, Germany
- Goethe University Frankfurt, Faculty of Biosciences, 60438 Frankfurt, Germany
| | - Dimitrios-Georgios Kontopoulos
- LOEWE Centre for Translational Biodiversity Genomics, 60325 Frankfurt, Germany
- Senckenberg Research Institute, 60325 Frankfurt, Germany
- Goethe University Frankfurt, Faculty of Biosciences, 60438 Frankfurt, Germany
| | - Leon Hilgers
- LOEWE Centre for Translational Biodiversity Genomics, 60325 Frankfurt, Germany
- Senckenberg Research Institute, 60325 Frankfurt, Germany
- Goethe University Frankfurt, Faculty of Biosciences, 60438 Frankfurt, Germany
| | - Kerstin Lindblad-Toh
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, 751 32 Uppsala, Sweden
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Elinor K Karlsson
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
- Program in Molecular Medicine, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Michael Hiller
- Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany
- Max Planck Institute for the Physics of Complex Systems, 01187 Dresden, Germany
- Center for Systems Biology Dresden, 01307 Dresden, Germany
- LOEWE Centre for Translational Biodiversity Genomics, 60325 Frankfurt, Germany
- Senckenberg Research Institute, 60325 Frankfurt, Germany
- Goethe University Frankfurt, Faculty of Biosciences, 60438 Frankfurt, Germany
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10
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Sullivan PF, Meadows JRS, Gazal S, Phan BN, Li X, Genereux DP, Dong MX, Bianchi M, Andrews G, Sakthikumar S, Nordin J, Roy A, Christmas MJ, Marinescu VD, Wang C, Wallerman O, Xue J, Yao S, Sun Q, Szatkiewicz J, Wen J, Huckins LM, Lawler A, Keough KC, Zheng Z, Zeng J, Wray NR, Li Y, Johnson J, Chen J, Paten B, Reilly SK, Hughes GM, Weng Z, Pollard KS, Pfenning AR, Forsberg-Nilsson K, Karlsson EK, Lindblad-Toh K. Leveraging base-pair mammalian constraint to understand genetic variation and human disease. Science 2023; 380:eabn2937. [PMID: 37104612 PMCID: PMC10259825 DOI: 10.1126/science.abn2937] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 02/09/2023] [Indexed: 04/29/2023]
Abstract
Thousands of genomic regions have been associated with heritable human diseases, but attempts to elucidate biological mechanisms are impeded by an inability to discern which genomic positions are functionally important. Evolutionary constraint is a powerful predictor of function, agnostic to cell type or disease mechanism. Single-base phyloP scores from 240 mammals identified 3.3% of the human genome as significantly constrained and likely functional. We compared phyloP scores to genome annotation, association studies, copy-number variation, clinical genetics findings, and cancer data. Constrained positions are enriched for variants that explain common disease heritability more than other functional annotations. Our results improve variant annotation but also highlight that the regulatory landscape of the human genome still needs to be further explored and linked to disease.
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Affiliation(s)
- Patrick F. Sullivan
- Department of Genetics, University of North Carolina Medical School, Chapel Hill, NC 27599, USA
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, 17177 Stockholm, Sweden
| | - Jennifer R. S. Meadows
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 75132 Uppsala, Sweden
| | - Steven Gazal
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - BaDoi N. Phan
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Xue Li
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Diane P. Genereux
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Michael X. Dong
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 75132 Uppsala, Sweden
| | - Matteo Bianchi
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 75132 Uppsala, Sweden
| | - Gregory Andrews
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Sharadha Sakthikumar
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 75132 Uppsala, Sweden
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Jessika Nordin
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 75132 Uppsala, Sweden
| | - Ananya Roy
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, 75185 Uppsala, Sweden
| | - Matthew J. Christmas
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 75132 Uppsala, Sweden
| | - Voichita D. Marinescu
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 75132 Uppsala, Sweden
| | - Chao Wang
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 75132 Uppsala, Sweden
| | - Ola Wallerman
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 75132 Uppsala, Sweden
| | - James Xue
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Center for System Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
| | - Shuyang Yao
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, 17177 Stockholm, Sweden
| | - Quan Sun
- Department of Genetics, University of North Carolina Medical School, Chapel Hill, NC 27599, USA
| | - Jin Szatkiewicz
- Department of Genetics, University of North Carolina Medical School, Chapel Hill, NC 27599, USA
| | - Jia Wen
- Department of Genetics, University of North Carolina Medical School, Chapel Hill, NC 27599, USA
| | - Laura M. Huckins
- Department of Genetic and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Alyssa Lawler
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Kathleen C. Keough
- Gladstone Institutes, San Francisco, CA 94158, USA
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA 94158, USA
| | - Zhili Zheng
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD 4072, Australia
| | - Jian Zeng
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD 4072, Australia
| | - Naomi R. Wray
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD 4072, Australia
| | - Yun Li
- Department of Genetics, University of North Carolina Medical School, Chapel Hill, NC 27599, USA
| | - Jessica Johnson
- Department of Genetic and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jiawen Chen
- Department of Biostatistics, University of North Carolina Medical School, Chapel Hill, NC 27599, USA
| | | | - Benedict Paten
- UC Santa Cruz Genomics Institute, Santa Cruz, CA 95064, USA
| | - Steven K. Reilly
- Department of Genetics, Yale School of Medicine, New Haven, CT 06510, USA
| | - Graham M. Hughes
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Katherine S. Pollard
- Gladstone Institutes, San Francisco, CA 94158, USA
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA 94158, USA
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
| | - Andreas R. Pfenning
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Karin Forsberg-Nilsson
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, 75185 Uppsala, Sweden
- Biodiscovery Institute, University of Nottingham, Nottingham NG7 2RD, UK
| | - Elinor K. Karlsson
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Program in Molecular Medicine, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Kerstin Lindblad-Toh
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 75132 Uppsala, Sweden
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
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11
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Wilder AP, Supple MA, Subramanian A, Mudide A, Swofford R, Serres-Armero A, Steiner C, Koepfli KP, Genereux DP, Karlsson EK, Lindblad-Toh K, Marques-Bonet T, Munoz Fuentes V, Foley K, Meyer WK, Ryder OA, Shapiro B, Andrews G, Armstrong JC, Bianchi M, Birren BW, Bredemeyer KR, Breit AM, Christmas MJ, Clawson H, Damas J, Di Palma F, Diekhans M, Dong MX, Eizirik E, Fan K, Fanter C, Foley NM, Forsberg-Nilsson K, Garcia CJ, Gatesy J, Gazal S, Genereux DP, Goodman L, Grimshaw J, Halsey MK, Harris AJ, Hickey G, Hiller M, Hindle AG, Hubley RM, Hughes GM, Johnson J, Juan D, Kaplow IM, Karlsson EK, Keough KC, Kirilenko B, Koepfli KP, Korstian JM, Kowalczyk A, Kozyrev SV, Lawler AJ, Lawless C, Lehmann T, Levesque DL, Lewin HA, Li X, Lind A, Lindblad-Toh K, Mackay-Smith A, Marinescu VD, Marques-Bonet T, Mason VC, Meadows JRS, Meyer WK, Moore JE, Moreira LR, Moreno-Santillan DD, Morrill KM, Muntané G, Murphy WJ, Navarro A, Nweeia M, Ortmann S, Osmanski A, Paten B, Paulat NS, Pfenning AR, Phan BN, Pollard KS, Pratt HE, Ray DA, Reilly SK, Rosen JR, Ruf I, Ryan L, Ryder OA, Sabeti PC, Schäffer DE, Serres A, Shapiro B, Smit AFA, Springer M, Srinivasan C, Steiner C, Storer JM, Sullivan KAM, Sullivan PF, Sundström E, Supple MA, Swofford R, Talbot JE, Teeling E, Turner-Maier J, Valenzuela A, Wagner F, Wallerman O, Wang C, Wang J, Weng Z, Wilder AP, Wirthlin ME, Xue JR, Zhang X. The contribution of historical processes to contemporary extinction risk in placental mammals. Science 2023; 380:eabn5856. [PMID: 37104572 PMCID: PMC10184782 DOI: 10.1126/science.abn5856] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Abstract
Species persistence can be influenced by the amount, type, and distribution of diversity across the genome, suggesting a potential relationship between historical demography and resilience. In this study, we surveyed genetic variation across single genomes of 240 mammals that compose the Zoonomia alignment to evaluate how historical effective population size (Ne) affects heterozygosity and deleterious genetic load and how these factors may contribute to extinction risk. We find that species with smaller historical Ne carry a proportionally larger burden of deleterious alleles owing to long-term accumulation and fixation of genetic load and have a higher risk of extinction. This suggests that historical demography can inform contemporary resilience. Models that included genomic data were predictive of species' conservation status, suggesting that, in the absence of adequate census or ecological data, genomic information may provide an initial risk assessment.
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Affiliation(s)
- Aryn P Wilder
- Conservation Genetics, San Diego Zoo Wildlife Alliance, Escondido, CA 92027, USA
| | - Megan A Supple
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, CA 95064, USA
- Howard Hughes Medical Institute, University of California, Santa Cruz, CA 95064, USA
| | | | | | - Ross Swofford
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Aitor Serres-Armero
- Institute of Evolutionary Biology, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona 08003, Spain
| | - Cynthia Steiner
- Conservation Genetics, San Diego Zoo Wildlife Alliance, Escondido, CA 92027, USA
| | - Klaus-Peter Koepfli
- Smithsonian-Mason School of Conservation, George Mason University, Front Royal, VA 22630, USA
- Center for Species Survival, Smithsonian Conservation Biology Institute, National Zoological Park, Washington, DC 30008, USA
- Computer Technologies Laboratory, ITMO University, St. Petersburg 197101, Russia
| | | | - Elinor K Karlsson
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Kerstin Lindblad-Toh
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala 751 32, Sweden
| | - Tomas Marques-Bonet
- Institute of Evolutionary Biology, Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona 08003, Spain
- Catalan Institution of Research and Advanced Studies, Barcelona 08010, Spain
- Centre for Genomic Regulation, Barcelona Institute of Science and Technology, Barcelona 08028, Spain
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona, Barcelona 08193, Spain
| | - Violeta Munoz Fuentes
- European Molecular Biology Laboratory-European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Kathleen Foley
- College of Law, University of Iowa, Iowa City, IA 52242, USA
- Department of Biological Sciences, Lehigh University, Bethlehem, PA 18015, USA
| | - Wynn K Meyer
- Department of Biological Sciences, Lehigh University, Bethlehem, PA 18015, USA
| | - Oliver A Ryder
- Conservation Genetics, San Diego Zoo Wildlife Alliance, Escondido, CA 92027, USA
- Department of Evolution, Behavior and Ecology, Division of Biology, University of California, San Diego, La Jolla, CA 92039, USA
| | - Beth Shapiro
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, CA 95064, USA
- Howard Hughes Medical Institute, University of California, Santa Cruz, CA 95064, USA
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12
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Andrews G, Fan K, Pratt HE, Phalke N, Karlsson EK, Lindblad-Toh K, Gazal S, Moore JE, Weng Z, Andrews G, Armstrong JC, Bianchi M, Birren BW, Bredemeyer KR, Breit AM, Christmas MJ, Clawson H, Damas J, Di Palma F, Diekhans M, Dong MX, Eizirik E, Fan K, Fanter C, Foley NM, Forsberg-Nilsson K, Garcia CJ, Gatesy J, Gazal S, Genereux DP, Goodman L, Grimshaw J, Halsey MK, Harris AJ, Hickey G, Hiller M, Hindle AG, Hubley RM, Hughes GM, Johnson J, Juan D, Kaplow IM, Karlsson EK, Keough KC, Kirilenko B, Koepfli KP, Korstian JM, Kowalczyk A, Kozyrev SV, Lawler AJ, Lawless C, Lehmann T, Levesque DL, Lewin HA, Li X, Lind A, Lindblad-Toh K, Mackay-Smith A, Marinescu VD, Marques-Bonet T, Mason VC, Meadows JRS, Meyer WK, Moore JE, Moreira LR, Moreno-Santillan DD, Morrill KM, Muntané G, Murphy WJ, Navarro A, Nweeia M, Ortmann S, Osmanski A, Paten B, Paulat NS, Pfenning AR, Phan BN, Pollard KS, Pratt HE, Ray DA, Reilly SK, Rosen JR, Ruf I, Ryan L, Ryder OA, Sabeti PC, Schäffer DE, Serres A, Shapiro B, Smit AFA, Springer M, Srinivasan C, Steiner C, Storer JM, Sullivan KAM, Sullivan PF, Sundström E, Supple MA, Swofford R, Talbot JE, Teeling E, Turner-Maier J, Valenzuela A, Wagner F, Wallerman O, Wang C, Wang J, Weng Z, Wilder AP, Wirthlin ME, Xue JR, Zhang X. Mammalian evolution of human cis-regulatory elements and transcription factor binding sites. Science 2023; 380:eabn7930. [PMID: 37104580 DOI: 10.1126/science.abn7930] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Abstract
Understanding the regulatory landscape of the human genome is a long-standing objective of modern biology. Using the reference-free alignment across 241 mammalian genomes produced by the Zoonomia Consortium, we charted evolutionary trajectories for 0.92 million human candidate cis-regulatory elements (cCREs) and 15.6 million human transcription factor binding sites (TFBSs). We identified 439,461 cCREs and 2,024,062 TFBSs under evolutionary constraint. Genes near constrained elements perform fundamental cellular processes, whereas genes near primate-specific elements are involved in environmental interaction, including odor perception and immune response. About 20% of TFBSs are transposable element-derived and exhibit intricate patterns of gains and losses during primate evolution whereas sequence variants associated with complex traits are enriched in constrained TFBSs. Our annotations illuminate the regulatory functions of the human genome.
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Affiliation(s)
- Gregory Andrews
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Kaili Fan
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Henry E Pratt
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Nishigandha Phalke
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Elinor K Karlsson
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Program in Molecular Medicine, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Kerstin Lindblad-Toh
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, 75132 Uppsala, Sweden
| | - Steven Gazal
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Jill E Moore
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
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13
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Foley NM, Mason VC, Harris AJ, Bredemeyer KR, Damas J, Lewin HA, Eizirik E, Gatesy J, Karlsson EK, Lindblad-Toh K, Springer MS, Murphy WJ, Andrews G, Armstrong JC, Bianchi M, Birren BW, Bredemeyer KR, Breit AM, Christmas MJ, Clawson H, Damas J, Di Palma F, Diekhans M, Dong MX, Eizirik E, Fan K, Fanter C, Foley NM, Forsberg-Nilsson K, Garcia CJ, Gatesy J, Gazal S, Genereux DP, Goodman L, Grimshaw J, Halsey MK, Harris AJ, Hickey G, Hiller M, Hindle AG, Hubley RM, Hughes GM, Johnson J, Juan D, Kaplow IM, Karlsson EK, Keough KC, Kirilenko B, Koepfli KP, Korstian JM, Kowalczyk A, Kozyrev SV, Lawler AJ, Lawless C, Lehmann T, Levesque DL, Lewin HA, Li X, Lind A, Lindblad-Toh K, Mackay-Smith A, Marinescu VD, Marques-Bonet T, Mason VC, Meadows JRS, Meyer WK, Moore JE, Moreira LR, Moreno-Santillan DD, Morrill KM, Muntané G, Murphy WJ, Navarro A, Nweeia M, Ortmann S, Osmanski A, Paten B, Paulat NS, Pfenning AR, Phan BN, Pollard KS, Pratt HE, Ray DA, Reilly SK, Rosen JR, Ruf I, Ryan L, Ryder OA, Sabeti PC, Schäffer DE, Serres A, Shapiro B, Smit AFA, Springer M, Srinivasan C, Steiner C, Storer JM, Sullivan KAM, Sullivan PF, Sundström E, Supple MA, Swofford R, Talbot JE, Teeling E, Turner-Maier J, Valenzuela A, Wagner F, Wallerman O, Wang C, Wang J, Weng Z, Wilder AP, Wirthlin ME, Xue JR, Zhang X. A genomic timescale for placental mammal evolution. Science 2023; 380:eabl8189. [PMID: 37104581 DOI: 10.1126/science.abl8189] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Abstract
The precise pattern and timing of speciation events that gave rise to all living placental mammals remain controversial. We provide a comprehensive phylogenetic analysis of genetic variation across an alignment of 241 placental mammal genome assemblies, addressing prior concerns regarding limited genomic sampling across species. We compared neutral genome-wide phylogenomic signals using concatenation and coalescent-based approaches, interrogated phylogenetic variation across chromosomes, and analyzed extensive catalogs of structural variants. Interordinal relationships exhibit relatively low rates of phylogenomic conflict across diverse datasets and analytical methods. Conversely, X-chromosome versus autosome conflicts characterize multiple independent clades that radiated during the Cenozoic. Genomic time trees reveal an accumulation of cladogenic events before and immediately after the Cretaceous-Paleogene (K-Pg) boundary, implying important roles for Cretaceous continental vicariance and the K-Pg extinction in the placental radiation.
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Affiliation(s)
- Nicole M Foley
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, USA
| | - Victor C Mason
- Institute of Cell Biology, University of Bern, Bern, Switzerland
| | - Andrew J Harris
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, USA
- Interdisciplinary Program in Genetics and Genomics, Texas A&M University, College Station, TX, USA
| | - Kevin R Bredemeyer
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, USA
- Interdisciplinary Program in Genetics and Genomics, Texas A&M University, College Station, TX, USA
| | - Joana Damas
- The Genome Center, University of California, Davis, CA, USA
| | - Harris A Lewin
- The Genome Center, University of California, Davis, CA, USA
- Department of Evolution and Ecology, University of California, Davis, CA, USA
| | - Eduardo Eizirik
- School of Health and Life Sciences, Pontifical Catholic University of Rio Grande do Sul, Porto Alegre, Brazil
| | - John Gatesy
- Division of Vertebrate Zoology, American Museum of Natural History, New York, NY, USA
| | - Elinor K Karlsson
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA 01605, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Program in Molecular Medicine, University of Massachussetts Chan Medical School, Worcester, MA 01605, USA
| | - Kerstin Lindblad-Toh
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 751 32 Uppsala, Sweden
| | - Mark S Springer
- Department of Evolution, Ecology, and Organismal Biology, University of California, Riverside, CA, USA
| | - William J Murphy
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, USA
- Interdisciplinary Program in Genetics and Genomics, Texas A&M University, College Station, TX, USA
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14
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Xue JR, Mackay-Smith A, Mouri K, Garcia MF, Dong MX, Akers JF, Noble M, Li X, Lindblad-Toh K, Karlsson EK, Noonan JP, Capellini TD, Brennand KJ, Tewhey R, Sabeti PC, Reilly SK, Andrews G, Armstrong JC, Bianchi M, Birren BW, Bredemeyer KR, Breit AM, Christmas MJ, Clawson H, Damas J, Di Palma F, Diekhans M, Dong MX, Eizirik E, Fan K, Fanter C, Foley NM, Forsberg-Nilsson K, Garcia CJ, Gatesy J, Gazal S, Genereux DP, Goodman L, Grimshaw J, Halsey MK, Harris AJ, Hickey G, Hiller M, Hindle AG, Hubley RM, Hughes GM, Johnson J, Juan D, Kaplow IM, Karlsson EK, Keough KC, Kirilenko B, Koepfli KP, Korstian JM, Kowalczyk A, Kozyrev SV, Lawler AJ, Lawless C, Lehmann T, Levesque DL, Lewin HA, Li X, Lind A, Lindblad-Toh K, Mackay-Smith A, Marinescu VD, Marques-Bonet T, Mason VC, Meadows JRS, Meyer WK, Moore JE, Moreira LR, Moreno-Santillan DD, Morrill KM, Muntané G, Murphy WJ, Navarro A, Nweeia M, Ortmann S, Osmanski A, Paten B, Paulat NS, Pfenning AR, Phan BN, Pollard KS, Pratt HE, Ray DA, Reilly SK, Rosen JR, Ruf I, Ryan L, Ryder OA, Sabeti PC, Schäffer DE, Serres A, Shapiro B, Smit AFA, Springer M, Srinivasan C, Steiner C, Storer JM, Sullivan KAM, Sullivan PF, Sundström E, Supple MA, Swofford R, Talbot JE, Teeling E, Turner-Maier J, Valenzuela A, Wagner F, Wallerman O, Wang C, Wang J, Weng Z, Wilder AP, Wirthlin ME, Xue JR, Zhang X. The functional and evolutionary impacts of human-specific deletions in conserved elements. Science 2023; 380:eabn2253. [PMID: 37104592 DOI: 10.1126/science.abn2253] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Abstract
Conserved genomic sequences disrupted in humans may underlie uniquely human phenotypic traits. We identified and characterized 10,032 human-specific conserved deletions (hCONDELs). These short (average 2.56 base pairs) deletions are enriched for human brain functions across genetic, epigenomic, and transcriptomic datasets. Using massively parallel reporter assays in six cell types, we discovered 800 hCONDELs conferring significant differences in regulatory activity, half of which enhance rather than disrupt regulatory function. We highlight several hCONDELs with putative human-specific effects on brain development, including HDAC5, CPEB4, and PPP2CA. Reverting an hCONDEL to the ancestral sequence alters the expression of LOXL2 and developmental genes involved in myelination and synaptic function. Our data provide a rich resource to investigate the evolutionary mechanisms driving new traits in humans and other species.
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Affiliation(s)
- James R Xue
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for System Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | - Ava Mackay-Smith
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | | | | | - Michael X Dong
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Jared F Akers
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | - Mark Noble
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
| | - Xue Li
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA, USA
- Program in Molecular Medicine, UMass Chan Medical School, Worcester, MA, USA
| | - Kerstin Lindblad-Toh
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Elinor K Karlsson
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School, Worcester, MA, USA
- Program in Molecular Medicine, UMass Chan Medical School, Worcester, MA, USA
| | - James P Noonan
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
- Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA
| | - Terence D Capellini
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Human Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | - Kristen J Brennand
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Yale University, New Haven, CT, USA
| | - Ryan Tewhey
- The Jackson Laboratory, Bar Harbor, ME, USA
- Graduate School of Biomedical Sciences and Engineering, University of Maine, Orono, ME, USA
- Graduate School of Biomedical Sciences Tufts University School of Medicine, Boston, MA, USA
| | - Pardis C Sabeti
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for System Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
- Department of Immunology and Infectious Disease, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Steven K Reilly
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
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15
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Sullivan PF, Meadows JRS, Gazal S, Phan BN, Li X, Genereux DP, Dong MX, Bianchi M, Andrews G, Sakthikumar S, Nordin J, Roy A, Christmas MJ, Marinescu VD, Wallerman O, Xue JR, Li Y, Yao S, Sun Q, Szatkiewicz J, Wen J, Huckins LM, Lawler AJ, Keough KC, Zheng Z, Zeng J, Wray NR, Johnson J, Chen J, Paten B, Reilly SK, Hughes GM, Weng Z, Pollard KS, Pfenning AR, Forsberg-Nilsson K, Karlsson EK, Lindblad-Toh K. Leveraging Base Pair Mammalian Constraint to Understand Genetic Variation and Human Disease. bioRxiv 2023:2023.03.10.531987. [PMID: 36945512 PMCID: PMC10028973 DOI: 10.1101/2023.03.10.531987] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/13/2023]
Abstract
Although thousands of genomic regions have been associated with heritable human diseases, attempts to elucidate biological mechanisms are impeded by a general inability to discern which genomic positions are functionally important. Evolutionary constraint is a powerful predictor of function that is agnostic to cell type or disease mechanism. Here, single base phyloP scores from the whole genome alignment of 240 placental mammals identified 3.5% of the human genome as significantly constrained, and likely functional. We compared these scores to large-scale genome annotation, genome-wide association studies (GWAS), copy number variation, clinical genetics findings, and cancer data sets. Evolutionarily constrained positions are enriched for variants explaining common disease heritability (more than any other functional annotation). Our results improve variant annotation but also highlight that the regulatory landscape of the human genome still needs to be further explored and linked to disease.
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Affiliation(s)
- Patrick F. Sullivan
- Department of Genetics, University of North Carolina Medical School; Chapel Hill, NC 27599, USA
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet; Stockholm, Sweden
| | - Jennifer R. S. Meadows
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University; Uppsala, 751 32, Sweden
| | - Steven Gazal
- Keck School of Medicine, University of Southern California; Los Angeles, CA 90033, USA
| | - BaDoi N. Phan
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University; Pittsburgh, PA 15213, USA
- Medical Scientist Training Program, University of Pittsburgh School of Medicine; Pittsburgh, PA 15261, USA
- Neuroscience Institute, Carnegie Mellon University; Pittsburgh, PA 15213, USA
| | - Xue Li
- Broad Institute of MIT and Harvard; Cambridge, MA 02139, USA
- Morningside Graduate School of Biomedical Sciences, UMass Chan Medical School; Worcester, MA 01605, USA
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School; Worcester, MA 01605, USA
| | | | - Michael X. Dong
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University; Uppsala, 751 32, Sweden
| | - Matteo Bianchi
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University; Uppsala, 751 32, Sweden
| | - Gregory Andrews
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School; Worcester, MA 01605, USA
| | - Sharadha Sakthikumar
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University; Uppsala, 751 32, Sweden
- Broad Institute of MIT and Harvard; Cambridge, MA 02139, USA
| | - Jessika Nordin
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University; Uppsala, 751 85, Sweden
| | - Ananya Roy
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University; Uppsala, 751 85, Sweden
| | - Matthew J. Christmas
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University; Uppsala, 751 32, Sweden
| | - Voichita D. Marinescu
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University; Uppsala, 751 32, Sweden
| | - Ola Wallerman
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University; Uppsala, 751 32, Sweden
| | - James R. Xue
- Broad Institute of MIT and Harvard; Cambridge, MA 02139, USA
- Department of Organismic and Evolutionary Biology, Harvard University; Cambridge, MA 02138, USA
| | - Yun Li
- Department of Genetics, University of North Carolina Medical School; Chapel Hill, NC 27599, USA
| | - Shuyang Yao
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet; Stockholm, Sweden
| | - Quan Sun
- Department of Biostatistics, University of North Carolina at Chapel Hill; Chapel Hill, NC, USA
| | - Jin Szatkiewicz
- Department of Genetics, University of North Carolina Medical School; Chapel Hill, NC 27599, USA
| | - Jia Wen
- Department of Genetics, University of North Carolina Medical School; Chapel Hill, NC 27599, USA
| | - Laura M. Huckins
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai; New York, NY 10029, USA
| | - Alyssa J. Lawler
- Neuroscience Institute, Carnegie Mellon University; Pittsburgh, PA 15213, USA
- Broad Institute of MIT and Harvard; Cambridge, MA 02139, USA
- Department of Biological Sciences, Mellon College of Science, Carnegie Mellon University; Pittsburgh, PA 15213, USA
| | - Kathleen C. Keough
- Department of Epidemiology & Biostatistics, University of California San Francisco; San Francisco, CA 94158, USA
- Fauna Bio Incorporated; Emeryville, CA 94608, USA
- Gladstone Institutes; San Francisco, CA 94158, USA
| | - Zhili Zheng
- Institute for Molecular Bioscience, University of Queensland; Brisbane, Queensland, Australia
| | - Jian Zeng
- Institute for Molecular Bioscience, University of Queensland; Brisbane, Queensland, Australia
| | - Naomi R. Wray
- Institute for Molecular Bioscience, University of Queensland; Brisbane, Queensland, Australia
- Queensland Brain Institute, University of Queensland; Brisbane, Queensland, Australia
| | - Jessica Johnson
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai; New York, NY 10029, USA
| | - Jiawen Chen
- Department of Biostatistics, University of North Carolina at Chapel Hill; Chapel Hill, NC, USA
| | | | - Benedict Paten
- Genomics Institute, University of California Santa Cruz; Santa Cruz, CA 95064, USA
| | - Steven K. Reilly
- Department of Genetics, Yale School of Medicine; New Haven, CT 06510, USA
| | - Graham M. Hughes
- School of Biology and Environmental Science, University College Dublin; Belfield, Dublin 4, Ireland
| | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School; Worcester, MA 01605, USA
| | - Katherine S. Pollard
- Department of Epidemiology & Biostatistics, University of California San Francisco; San Francisco, CA 94158, USA
- Gladstone Institutes; San Francisco, CA 94158, USA
- Chan Zuckerberg Biohub; San Francisco, CA 94158, USA
| | - Andreas R. Pfenning
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University; Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University; Pittsburgh, PA 15213, USA
| | - Karin Forsberg-Nilsson
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University; Uppsala, 751 85, Sweden
- Biodiscovery Institute, University of Nottingham; Nottingham, UK
| | - Elinor K. Karlsson
- Broad Institute of MIT and Harvard; Cambridge, MA 02139, USA
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School; Worcester, MA 01605, USA
- Program in Molecular Medicine, UMass Chan Medical School; Worcester, MA 01605, USA
| | - Kerstin Lindblad-Toh
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University; Uppsala, 751 32, Sweden
- Broad Institute of MIT and Harvard; Cambridge, MA 02139, USA
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16
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Lingaas F, Tengvall K, Jansen JH, Pelander L, Hurst MH, Meuwissen T, Karlsson Å, Meadows JRS, Sundström E, Thoresen SI, Arnet EF, Guttersrud OA, Kierczak M, Hytönen MK, Lohi H, Hedhammar Å, Lindblad-Toh K, Wang C. Bayesian mixed model analysis uncovered 21 risk loci for chronic kidney disease in boxer dogs. PLoS Genet 2023; 19:e1010599. [PMID: 36693108 PMCID: PMC9897549 DOI: 10.1371/journal.pgen.1010599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Revised: 02/03/2023] [Accepted: 01/04/2023] [Indexed: 01/25/2023] Open
Abstract
Chronic kidney disease (CKD) affects 10% of the human population, with only a small fraction genetically defined. CKD is also common in dogs and has been diagnosed in nearly all breeds, but its genetic basis remains unclear. Here, we performed a Bayesian mixed model genome-wide association analysis for canine CKD in a boxer population of 117 canine cases and 137 controls, and identified 21 genetic regions associated with the disease. At the top markers from each CKD region, the cases carried an average of 20.2 risk alleles, significantly higher than controls (15.6 risk alleles). An ANOVA test showed that the 21 CKD regions together explained 57% of CKD phenotypic variation in the population. Based on whole genome sequencing data of 20 boxers, we identified 5,206 variants in LD with the top 50 BayesR markers. Following comparative analysis with human regulatory data, 17 putative regulatory variants were identified and tested with electrophoretic mobility shift assays. In total four variants, three intronic variants from the MAGI2 and GALNT18 genes, and one variant in an intergenic region on chr28, showed alternative binding ability for the risk and protective alleles in kidney cell lines. Many genes from the 21 CKD regions, RELN, MAGI2, FGFR2 and others, have been implicated in human kidney development or disease. The results from this study provide new information that may enlighten the etiology of CKD in both dogs and humans.
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Affiliation(s)
- Frode Lingaas
- Faculty of Veterinary Medicine, Department of Preclinical Sciences and Pathology, Norwegian University of Life Sciences, Ås, Norway
| | - Katarina Tengvall
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Johan Høgset Jansen
- Faculty of Veterinary Medicine, Department of Preclinical Sciences and Pathology, Norwegian University of Life Sciences, Ås, Norway
| | - Lena Pelander
- Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | | | - Theo Meuwissen
- Faculty of Biosciences, Norwegian University of Life Sciences, Ås, Norway
| | - Åsa Karlsson
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Jennifer R. S. Meadows
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Elisabeth Sundström
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Stein Istre Thoresen
- Faculty of Veterinary Medicine, Department of Preclinical Sciences and Pathology, Norwegian University of Life Sciences, Ås, Norway
| | - Ellen Frøysadal Arnet
- Faculty of Veterinary Medicine, Department of Preclinical Sciences and Pathology, Norwegian University of Life Sciences, Ås, Norway
| | - Ole Albert Guttersrud
- Faculty of Veterinary Medicine, Department of Preclinical Sciences and Pathology, Norwegian University of Life Sciences, Ås, Norway
| | - Marcin Kierczak
- Department of Cell and Molecular Biology, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Marjo K. Hytönen
- Department of Medical and Clinical Genetics, University of Helsinki, Helsinki, Finland
- Department of Veterinary Biosciences, University of Helsinki, Helsinki, Finland
- Folkhälsan Research Center, Helsinki, Finland
| | - Hannes Lohi
- Department of Medical and Clinical Genetics, University of Helsinki, Helsinki, Finland
- Department of Veterinary Biosciences, University of Helsinki, Helsinki, Finland
- Folkhälsan Research Center, Helsinki, Finland
| | - Åke Hedhammar
- Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Kerstin Lindblad-Toh
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- * E-mail: (KL-T); (CW)
| | - Chao Wang
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
- * E-mail: (KL-T); (CW)
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17
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Yones SA, Annett A, Stoll P, Diamanti K, Holmfeldt L, Barrenäs CF, Meadows JRS, Komorowski J. Interpretable machine learning identifies paediatric Systemic Lupus Erythematosus subtypes based on gene expression data. Sci Rep 2022; 12:7433. [PMID: 35523803 PMCID: PMC9076598 DOI: 10.1038/s41598-022-10853-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Accepted: 04/13/2022] [Indexed: 11/25/2022] Open
Abstract
Transcriptomic analyses are commonly used to identify differentially expressed genes between patients and controls, or within individuals across disease courses. These methods, whilst effective, cannot encompass the combinatorial effects of genes driving disease. We applied rule-based machine learning (RBML) models and rule networks (RN) to an existing paediatric Systemic Lupus Erythematosus (SLE) blood expression dataset, with the goal of developing gene networks to separate low and high disease activity (DA1 and DA3). The resultant model had an 81% accuracy to distinguish between DA1 and DA3, with unsupervised hierarchical clustering revealing additional subgroups indicative of the immune axis involved or state of disease flare. These subgroups correlated with clinical variables, suggesting that the gene sets identified may further the understanding of gene networks that act in concert to drive disease progression. This included roles for genes (i) induced by interferons (IFI35 and OTOF), (ii) key to SLE cell types (KLRB1 encoding CD161), or (iii) with roles in autophagy and NF-κB pathway responses (CKAP4). As demonstrated here, RBML approaches have the potential to reveal novel gene patterns from within a heterogeneous disease, facilitating patient clinical and therapeutic stratification.
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Affiliation(s)
- Sara A Yones
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden.
| | - Alva Annett
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
| | - Patricia Stoll
- Department of Biosystems Science and Engineering, ETH Zurich, Zurich, Switzerland
| | - Klev Diamanti
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Linda Holmfeldt
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Carl Fredrik Barrenäs
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
| | - Jennifer R S Meadows
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Jan Komorowski
- Science for Life Laboratory, Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden. .,Washington National Primate Research Center, Seattle, USA. .,Swedish Collegium for Advanced Study, Uppsala, Sweden. .,The Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland.
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18
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Bianchi M, Kozyrev SV, Notarnicola A, Hultin Rosenberg L, Karlsson Å, Pucholt P, Rothwell S, Alexsson A, Sandling JK, Andersson H, Cooper RG, Padyukov L, Tjärnlund A, Dastmalchi M, Meadows JRS, Pyndt Diederichsen L, Molberg Ø, Chinoy H, Lamb JA, Rönnblom L, Lindblad-Toh K, Lundberg IE. Contribution of Rare Genetic Variation to Disease Susceptibility in a Large Scandinavian Myositis Cohort. Arthritis Rheumatol 2022; 74:342-352. [PMID: 34279065 DOI: 10.1002/art.41929] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 07/02/2021] [Accepted: 07/13/2021] [Indexed: 11/09/2022]
Abstract
OBJECTIVE Idiopathic inflammatory myopathies (IIMs) are a heterogeneous group of complex autoimmune conditions characterized by inflammation in skeletal muscle and extramuscular compartments, and interferon (IFN) system activation. We undertook this study to examine the contribution of genetic variation to disease susceptibility and to identify novel avenues for research in IIMs. METHODS Targeted DNA sequencing was used to mine coding and potentially regulatory single nucleotide variants from ~1,900 immune-related genes in a Scandinavian case-control cohort of 454 IIM patients and 1,024 healthy controls. Gene-based aggregate testing, together with rare variant- and gene-level enrichment analyses, was implemented to explore genotype-phenotype relations. RESULTS Gene-based aggregate tests of all variants, including rare variants, identified IFI35 as a potential genetic risk locus for IIMs, suggesting a genetic signature of type I IFN pathway activation. Functional annotation of the IFI35 locus highlighted a regulatory network linked to the skeletal muscle-specific gene PTGES3L, as a potential candidate for IIM pathogenesis. Aggregate genetic associations with AGER and PSMB8 in the major histocompatibility complex locus were detected in the antisynthetase syndrome subgroup, which also showed a less marked genetic signature of the type I IFN pathway. Enrichment analyses indicated a burden of synonymous and noncoding rare variants in IIM patients, suggesting increased disease predisposition associated with these classes of rare variants. CONCLUSION Our study suggests the contribution of rare genetic variation to disease susceptibility in IIM and specific patient subgroups, and pinpoints genetic associations consistent with previous findings by gene expression profiling. These features highlight genetic profiles that are potentially relevant to disease pathogenesis.
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Affiliation(s)
- Matteo Bianchi
- Science for Life Laboratory and Uppsala University, Uppsala, Sweden
| | - Sergey V Kozyrev
- Science for Life Laboratory and Uppsala University, Uppsala, Sweden
| | | | | | - Åsa Karlsson
- Science for Life Laboratory and Uppsala University, Uppsala, Sweden
| | | | | | | | | | | | - Robert G Cooper
- Aintree University Hospital, MRC-Arthritis Research UK Centre for integrated Research into Musculoskeletal Ageing, and University of Liverpool, Liverpool, UK
| | - Leonid Padyukov
- Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
| | - Anna Tjärnlund
- Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
| | - Maryam Dastmalchi
- Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
| | | | | | | | | | - Øyvind Molberg
- Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Hector Chinoy
- National Institute for Health Research Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, University of Manchester, and Manchester Academic Health Science Centre, Manchester, UK, and Salford Royal NHS Foundation Trust, Salford, UK
| | | | | | - Kerstin Lindblad-Toh
- Science for Life Laboratory and Uppsala University, Uppsala, Sweden, and Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Ingrid E Lundberg
- Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
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19
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Dahlqvist J, Ekman D, Sennblad B, Kozyrev SV, Nordin J, Karlsson Å, Meadows JRS, Hellbacher E, Rantapää-Dahlqvist S, Berglin E, Stegmayr B, Baslund B, Palm Ø, Haukeland H, Gunnarsson I, Bruchfeld A, Segelmark M, Ohlsson S, Mohammad AJ, Svärd A, Pullerits R, Herlitz H, Söderbergh A, Rosengren Pielberg G, Hultin Rosenberg L, Bianchi M, Murén E, Omdal R, Jonsson R, Eloranta ML, Rönnblom L, Söderkvist P, Knight A, Eriksson P, Lindblad-Toh K. Identification and Functional Characterization of a Novel Susceptibility Locus for Small Vessel Vasculitis with MPO-ANCA. Rheumatology (Oxford) 2021; 61:3461-3470. [PMID: 34888651 PMCID: PMC9348767 DOI: 10.1093/rheumatology/keab912] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Revised: 12/01/2021] [Indexed: 11/14/2022] Open
Abstract
OBJECTIVE To identify and characterize genetic loci associated with the risk of developing anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitides (AAV). METHODS Genetic association analyses were performed after Illumina sequencing of 1,853 genes and subsequent replication with genotyping of selected SNPs in a total cohort of 1110 Scandinavian cases with granulomatosis with polyangiitis (GPA) or microscopic polyangiitis (MPA) and 1589 controls. A novel AAV-associated SNP was analysed for allele-specific effects on gene expression using luciferase reporter assay. RESULTS Proteinase 3 ANCA positive (PR3-ANCA+) AAV was significantly associated with two independent loci in the HLA-DPB1/A1 region (rs1042335, p= 6.3 x 1 0 -61, Odds ratio (OR)= 0.10; rs9277341, p= 1.5 x 1 0 -44, OR = 0.22) and with rs28929474 in the SERPINA1 gene (p= 2.7 x 1 0 -10, OR = 2.9). Myeloperoxidase (MPO)-ANCA+ AAV was significantly associated with the HLA-DQB1/HLA-DQA2 locus (rs9274619, p= 5.4 x 1 0 -25, OR = 3.7) and with a rare variant in the BACH2 gene (rs78275221, p= 7.9 x 1 0 -7, OR = 3.0), the latter a novel susceptibility locus for MPO-ANCA+ GPA/MPA. The rs78275221-A risk allele reduced luciferase gene expression in endothelial cells, specifically, as compared with the non-risk allele. CONCLUSION We identified a novel susceptibility locus for MPO-ANCA+ AAV and propose that the associated variant is of mechanistic importance, exerting a regulatory function on gene expression in specific cell types.
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Affiliation(s)
- Johanna Dahlqvist
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden.,Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.,Broad Institute of MIT and Harvard University, Cambridge, MA, USA
| | - Diana Ekman
- Department of Biochemistry and Biophysics, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Stockholm University, Sweden
| | - Bengt Sennblad
- Department of Cell and Molecular Biology, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Sergey V Kozyrev
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Jessika Nordin
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Åsa Karlsson
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Jennifer R S Meadows
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Erik Hellbacher
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | | | - Ewa Berglin
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Bernd Stegmayr
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Bo Baslund
- Copenhagen Lupus and Vasculitis Clinic, Center for Rheumatology and Spine Diseases, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Øyvind Palm
- Department of Rheumatology, Oslo University Hospital, Oslo, Norway
| | - Hilde Haukeland
- Department of Rheumatology, Martina Hansens Hospital, Oslo, Norway
| | - Iva Gunnarsson
- Department of Medicine, Division of Rheumatology, Karolinska Institutet, Stockholm, Sweden.,Unit of Rheumatology, Karolinska University Hospital, Stockholm, Sweden
| | - Annette Bruchfeld
- Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden.,Department of Renal Medicine, Karolinska University Hospital and CLINTEC Karolinska Institutet, Stockholm, Sweden
| | - Mårten Segelmark
- Department of Clinical Sciences, Division of Nephrology, Lund University and Skåne University Hospital, Lund, Sweden
| | - Sophie Ohlsson
- Department of Clinical Sciences, Division of Nephrology, Lund University and Skåne University Hospital, Lund, Sweden
| | - Aladdin J Mohammad
- Department of Clinical Sciences Lund, Section of Rheumatology, Skåne University Hospital, Lund University, Lund, Sweden.,Department of Medicine, University of Cambridge, Cambridge, UK
| | - Anna Svärd
- Center for Clinical Research Dalarna, Uppsala University, Uppsala, Sweden
| | - Rille Pullerits
- Department of Rheumatology and Inflammation Research, Institution of Medicine, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden.,Department of Clinical Immunology and Transfusion Medicine, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Hans Herlitz
- Department of Molecular and Clinical Medicine/Nephrology, Institute of Medicine, the Sahlgrenska Academy, University of Gothenburg, Sweden
| | - Annika Söderbergh
- Department of Rheumatology, Örebro University Hospital, Örebro, Sweden
| | - Gerli Rosengren Pielberg
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Lina Hultin Rosenberg
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Matteo Bianchi
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Eva Murén
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Roald Omdal
- Clinical Immunology Unit, Department of Internal Medicine, Stavanger University Hospital, Stavanger, Norway.,Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Roland Jonsson
- Broegelmann Research Laboratory, Department of Clinical Science, University of Bergen, Bergen, Norway
| | | | - Lars Rönnblom
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Peter Söderkvist
- Department of Biomedical and Clinical Sciences, Division of Cell Biology, Linköping University, Linköping, Sweden
| | - Ann Knight
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Per Eriksson
- Department of Biomedical and Clinical Sciences, Division of Inflammation and Infection, Linköping University, Linköping, Sweden
| | - Kerstin Lindblad-Toh
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.,Broad Institute of MIT and Harvard University, Cambridge, MA, USA
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20
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Arendt M, Ambrosen A, Fall T, Kierczak M, Tengvall K, Meadows JRS, Karlsson Å, Lagerstedt AS, Bergström T, Andersson G, Lindblad-Toh K, Hagman R. The ABCC4 gene is associated with pyometra in golden retriever dogs. Sci Rep 2021; 11:16647. [PMID: 34404837 PMCID: PMC8370986 DOI: 10.1038/s41598-021-95936-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2021] [Accepted: 07/29/2021] [Indexed: 11/24/2022] Open
Abstract
Pyometra is one of the most common diseases in female dogs, presenting as purulent inflammation and bacterial infection of the uterus. On average 20% of intact female dogs are affected before 10 years of age, a proportion that varies greatly between breeds (3–66%). The clear breed predisposition suggests that genetic risk factors are involved in disease development. To identify genetic risk factors associated with the disease, we performed a genome-wide association study (GWAS) in golden retrievers, a breed with increased risk of developing pyometra (risk ratio: 3.3). We applied a mixed model approach comparing 98 cases, and 96 healthy controls and identified an associated locus on chromosome 22 (p = 1.2 × 10–6, passing Bonferroni corrected significance). This locus contained five significantly associated SNPs positioned within introns of the ATP-binding cassette transporter 4 (ABCC4) gene. This gene encodes a transmembrane transporter that is important for prostaglandin transport. Next generation sequencing and genotyping of cases and controls subsequently identified four missense SNPs within the ABCC4 gene. One missense SNP at chr22:45,893,198 (p.Met787Val) showed complete linkage disequilibrium with the associated GWAS SNPs suggesting a potential role in disease development. Another locus on chromosome 18 overlapping the TESMIN gene, is also potentially implicated in the development of the disease.
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Affiliation(s)
- Maja Arendt
- Faculty of Health and Medical Sciences, Department of Veterinary Clinical Sciences, University of Copenhagen, Copenhagen, Denmark. .,Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.
| | - Aime Ambrosen
- Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Tove Fall
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Marcin Kierczak
- Department of Cell and Molecular Biology, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Katarina Tengvall
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Jennifer R S Meadows
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Åsa Karlsson
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Anne-Sofie Lagerstedt
- Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Tomas Bergström
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Göran Andersson
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Kerstin Lindblad-Toh
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.,Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Ragnvi Hagman
- Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden.
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21
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Nordin J, Pettersson M, Rosenberg LH, Mathioudaki A, Karlsson Å, Murén E, Tandre K, Rönnblom L, Kastbom A, Cedergren J, Eriksson P, Söderkvist P, Lindblad-Toh K, Meadows JRS. Association of Protective HLA-A With HLA-B∗27 Positive Ankylosing Spondylitis. Front Genet 2021; 12:659042. [PMID: 34335681 PMCID: PMC8320510 DOI: 10.3389/fgene.2021.659042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Accepted: 06/09/2021] [Indexed: 11/21/2022] Open
Abstract
Objectives To further elucidate the role of the MHC in ankylosing spondylitis by typing 17 genes, searching for HLA-B∗27 independent associations and assessing the impact of sex on this male biased disease. Methods High-confidence two-field resolution genotyping was performed on 310 cases and 2196 controls using an n-1 concordance method. Protein-coding variants were called from next-generation sequencing reads using up to four software programs and the consensus result recorded. Logistic regression tests were applied to the dataset as a whole, and also in stratified sets based on sex or HLA-B∗27 status. The amino acids driving association were also examined. Results Twenty-five HLA protein-coding variants were significantly associated to disease in the population. Three novel protective associations were found in a HLA-B∗27 positive population, HLA-A∗24:02 (OR = 0.4, CI = 0.2–0.7), and HLA-A amino acids Leu95 and Gln156. We identified a key set of seven loci that were common to both sexes, and robust to change in sample size. Stratifying by sex uncovered three novel risk variants restricted to the female population (HLA-DQA1∗04.01, -DQB1∗04:02, -DRB1∗08:01; OR = 2.4–3.1). We also uncovered a set of neutral variants in the female population, which in turn conferred strong effects in the male set, highlighting how population composition can lead to the masking of true associations. Conclusion Population stratification allowed for a nuanced investigation into the tightly linked MHC region, revealing novel HLA-B∗27 signals as well as replicating previous HLA-B∗27 dependent results. This dissection of signals may help to elucidate sex biased disease predisposition and clinical progression.
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Affiliation(s)
- Jessika Nordin
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.,Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Mats Pettersson
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Lina Hultin Rosenberg
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Argyri Mathioudaki
- Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Åsa Karlsson
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Eva Murén
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Karolina Tandre
- Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Lars Rönnblom
- Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Alf Kastbom
- Department of Rheumatology, University Hospital Linköping, Linköping, Sweden.,Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
| | - Jan Cedergren
- Department of Rheumatology, University Hospital Linköping, Linköping, Sweden.,Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
| | - Per Eriksson
- Department of Rheumatology, University Hospital Linköping, Linköping, Sweden.,Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
| | - Peter Söderkvist
- Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
| | - Kerstin Lindblad-Toh
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.,Broad Institute of MIT and Harvard, Cambridge, MA, United States
| | - Jennifer R S Meadows
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
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22
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Mathioudaki A, Ljungström V, Melin M, Arendt ML, Nordin J, Karlsson Å, Murén E, Saksena P, Meadows JRS, Marinescu VD, Sjöblom T, Lindblad-Toh K. Author Correction: Targeted sequencing reveals the somatic mutation landscape in a Swedish breast cancer cohort. Sci Rep 2021; 11:5310. [PMID: 33649492 PMCID: PMC7921395 DOI: 10.1038/s41598-021-84929-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Affiliation(s)
- Argyri Mathioudaki
- Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
| | - Viktor Ljungström
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala, Sweden
| | - Malin Melin
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala, Sweden
| | - Maja Louise Arendt
- Department of Veterinary Clinical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.,Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Jessika Nordin
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Åsa Karlsson
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Eva Murén
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Pushpa Saksena
- Department of Clinical Pathology and Genetics, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Jennifer R S Meadows
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Voichita D Marinescu
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Tobias Sjöblom
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Rudbeck Laboratory, Uppsala, Sweden
| | - Kerstin Lindblad-Toh
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden. .,Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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23
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Wang C, Wallerman O, Arendt ML, Sundström E, Karlsson Å, Nordin J, Mäkeläinen S, Pielberg GR, Hanson J, Ohlsson Å, Saellström S, Rönnberg H, Ljungvall I, Häggström J, Bergström TF, Hedhammar Å, Meadows JRS, Lindblad-Toh K. A novel canine reference genome resolves genomic architecture and uncovers transcript complexity. Commun Biol 2021; 4:185. [PMID: 33568770 PMCID: PMC7875987 DOI: 10.1038/s42003-021-01698-x] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Accepted: 12/17/2020] [Indexed: 12/13/2022] Open
Abstract
We present GSD_1.0, a high-quality domestic dog reference genome with chromosome length scaffolds and contiguity increased 55-fold over CanFam3.1. Annotation with generated and existing long and short read RNA-seq, miRNA-seq and ATAC-seq, revealed that 32.1% of lifted over CanFam3.1 gaps harboured previously hidden functional elements, including promoters, genes and miRNAs in GSD_1.0. A catalogue of canine "dark" regions was made to facilitate mapping rescue. Alignment in these regions is difficult, but we demonstrate that they harbour trait-associated variation. Key genomic regions were completed, including the Dog Leucocyte Antigen (DLA), T Cell Receptor (TCR) and 366 COSMIC cancer genes. 10x linked-read sequencing of 27 dogs (19 breeds) uncovered 22.1 million SNPs, indels and larger structural variants. Subsequent intersection with protein coding genes showed that 1.4% of these could directly influence gene products, and so provide a source of normal or aberrant phenotypic modifications.
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Affiliation(s)
- Chao Wang
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.
| | - Ola Wallerman
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Maja-Louise Arendt
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
- Department of Veterinary Clinical Sciences, University of Copenhagen, Frederiksberg D, Denmark
| | - Elisabeth Sundström
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Åsa Karlsson
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Jessika Nordin
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Suvi Mäkeläinen
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Gerli Rosengren Pielberg
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Jeanette Hanson
- Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Åsa Ohlsson
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Sara Saellström
- Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Henrik Rönnberg
- Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Ingrid Ljungvall
- Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Jens Häggström
- Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Tomas F Bergström
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Åke Hedhammar
- Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Jennifer R S Meadows
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Kerstin Lindblad-Toh
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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24
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Thorlacius GE, Hultin-Rosenberg L, Sandling JK, Bianchi M, Imgenberg-Kreuz J, Pucholt P, Theander E, Kvarnström M, Forsblad-d'Elia H, Bucher SM, Norheim KB, Johnsen SJA, Hammenfors D, Skarstein K, Jonsson MV, Baecklund E, Aqrawi LA, Jensen JL, Palm Ø, Morris AP, Meadows JRS, Rantapää-Dahlqvist S, Mandl T, Eriksson P, Lind L, Omdal R, Jonsson R, Lindblad-Toh K, Rönnblom L, Wahren-Herlenius M, Nordmark G. Genetic and clinical basis for two distinct subtypes of primary Sjögren's syndrome. Rheumatology (Oxford) 2021; 60:837-848. [PMID: 32889544 PMCID: PMC7850528 DOI: 10.1093/rheumatology/keaa367] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Revised: 04/21/2020] [Indexed: 11/21/2022] Open
Abstract
OBJECTIVES Clinical presentation of primary Sjögren's syndrome (pSS) varies considerably. A shortage of evidence-based objective markers hinders efficient drug development and most clinical trials have failed to reach primary endpoints. METHODS We performed a multicentre study to identify patient subgroups based on clinical, immunological and genetic features. Targeted DNA sequencing of 1853 autoimmune-related loci was performed. After quality control, 918 patients with pSS, 1264 controls and 107 045 single nucleotide variants remained for analysis. Replication was performed in 177 patients with pSS and 7672 controls. RESULTS We found strong signals of association with pSS in the HLA region. Principal component analysis of clinical data distinguished two patient subgroups defined by the presence of SSA/SSB antibodies. We observed an unprecedented high risk of pSS for an association in the HLA-DQA1 locus of odds ratio 6.10 (95% CI: 4.93, 7.54, P=2.2×10-62) in the SSA/SSB-positive subgroup, while absent in the antibody negative group. Three independent signals within the MHC were observed. The two most significant variants in MHC class I and II respectively, identified patients with a higher risk of hypergammaglobulinaemia, leukopenia, anaemia, purpura, major salivary gland swelling and lymphadenopathy. Replication confirmed the association with both MHC class I and II signals confined to SSA/SSB antibody positive pSS. CONCLUSION Two subgroups of patients with pSS with distinct clinical manifestations can be defined by the presence or absence of SSA/SSB antibodies and genetic markers in the HLA locus. These subgroups should be considered in clinical follow-up, drug development and trial outcomes, for the benefit of both subgroups.
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Affiliation(s)
| | - Lina Hultin-Rosenberg
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala, Sweden
| | - Johanna K Sandling
- Department of Medical Sciences, Rheumatology, and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Matteo Bianchi
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala, Sweden
- Department of Medical Sciences, Rheumatology, and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Juliana Imgenberg-Kreuz
- Department of Medical Sciences, Rheumatology, and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Pascal Pucholt
- Department of Medical Sciences, Rheumatology, and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Elke Theander
- Department of Rheumatology, Skåne University Hospital, Malmö, Sweden
| | | | - Helena Forsblad-d'Elia
- Department of Rheumatology and Inflammation Research, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Sara Magnusson Bucher
- Department of Rheumatology, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Katrine B Norheim
- Department of Internal Medicine, Stavanger University Hospital, Stavanger, Norway
| | | | - Daniel Hammenfors
- Department of Rheumatology, Haukeland University Hospital, Bergen, Norway
| | - Kathrine Skarstein
- Department of Clinical Science and Department of Clinical Dentistry, University of Bergen, Bergen, Norway
| | - Malin V Jonsson
- Department of Clinical Science and Department of Clinical Dentistry, University of Bergen, Bergen, Norway
| | - Eva Baecklund
- Department of Medical Sciences, Rheumatology, and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Lara A Aqrawi
- Department of Oral Surgery and Oral Medicine, Faculty of Dentistry, University of Oslo, Oslo, Norway
| | - Janicke Liaaen Jensen
- Department of Oral Surgery and Oral Medicine, Faculty of Dentistry, University of Oslo, Oslo, Norway
| | - Øyvind Palm
- Department of Rheumatology, Oslo University Hospital, Oslo, Norway
| | - Andrew P Morris
- Division of Musculoskeletal and Dermatological Sciences, The University of Manchester, Manchester, UK
| | - Jennifer R S Meadows
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala, Sweden
| | | | - Thomas Mandl
- Department of Rheumatology, Skåne University Hospital, Malmö, Sweden
| | - Per Eriksson
- Department of Clinical and Experimental Medicine, Rheumatology/Division of Neuro and Inflammation Sciences, Linköping University, Linköping, Sweden
| | - Lars Lind
- Department of Medical Sciences, Clinical Epidemiology, Uppsala University, Uppsala, Sweden
| | - Roald Omdal
- Department of Internal Medicine, Stavanger University Hospital, Stavanger, Norway
- Broegelmann Research Laboratory, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Roland Jonsson
- Department of Rheumatology, Haukeland University Hospital, Bergen, Norway
- Broegelmann Research Laboratory, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Kerstin Lindblad-Toh
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala, Sweden
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Lars Rönnblom
- Department of Medical Sciences, Rheumatology, and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | | | - Gunnel Nordmark
- Department of Medical Sciences, Rheumatology, and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
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25
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Nordin J, Ameur A, Lindblad-Toh K, Gyllensten U, Meadows JRS. SweHLA: the high confidence HLA typing bio-resource drawn from 1000 Swedish genomes. Eur J Hum Genet 2019; 28:627-635. [PMID: 31844174 PMCID: PMC7170882 DOI: 10.1038/s41431-019-0559-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2019] [Revised: 11/12/2019] [Accepted: 11/26/2019] [Indexed: 11/10/2022] Open
Abstract
There is a need to accurately call human leukocyte antigen (HLA) genes from existing short-read sequencing data, however there is no single solution that matches the gold standard of Sanger sequenced lab typing. Here we aimed to combine results from available software programs, minimizing the biases of applied algorithm and HLA reference. The result is a robust HLA population resource for the published 1000 Swedish genomes, and a framework for future HLA interrogation. HLA 2nd-field alleles were called using four imputation and inference methods for the classical eight genes (class I: HLA-A, HLA-B, HLA-C; class II: HLA-DPA1, HLA-DPB1, HLA-DQA1, HLA-DQB1, HLA-DRB1). A high confidence population set (SweHLA) was determined using an n−1 concordance rule for class I (four software) and class II (three software) alleles. Results were compared across populations and individual programs benchmarked to SweHLA. Per gene, 875 to 988 of the 1000 samples were genotyped in SweHLA; 920 samples had at least seven loci called. While a small fraction of reference alleles were common to all software (class I = 1.9% and class II = 4.1%), this did not affect the overall call rate. Gene-level concordance was high compared to European populations (>0.83%), with COX and PGF the dominant SweHLA haplotypes. We noted that 15/18 discordant alleles (delta allele frequency >2) were previously reported as disease-associated. These differences could in part explain across-study genetic replication failures, reinforcing the need to use multiple software solutions. SweHLA demonstrates a way to use existing NGS data to generate a population resource agnostic to individual HLA software biases.
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Affiliation(s)
- Jessika Nordin
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.
| | - Adam Ameur
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Kerstin Lindblad-Toh
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.,Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Ulf Gyllensten
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Jennifer R S Meadows
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
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26
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Eriksson D, Bianchi M, Landegren N, Dalin F, Skov J, Hultin-Rosenberg L, Mathioudaki A, Nordin J, Hallgren Å, Andersson G, Tandre K, Rantapää Dahlqvist S, Söderkvist P, Rönnblom L, Hulting AL, Wahlberg J, Dahlqvist P, Ekwall O, Meadows JRS, Lindblad-Toh K, Bensing S, Rosengren Pielberg G, Kämpe O. Common genetic variation in the autoimmune regulator (AIRE) locus is associated with autoimmune Addison's disease in Sweden. Sci Rep 2018; 8:8395. [PMID: 29849176 PMCID: PMC5976627 DOI: 10.1038/s41598-018-26842-2] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2018] [Accepted: 05/18/2018] [Indexed: 12/23/2022] Open
Abstract
Autoimmune Addison's disease (AAD) is the predominating cause of primary adrenal failure. Despite its high heritability, the rarity of disease has long made candidate-gene studies the only feasible methodology for genetic studies. Here we conducted a comprehensive reinvestigation of suggested AAD risk loci and more than 1800 candidate genes with associated regulatory elements in 479 patients with AAD and 2394 controls. Our analysis enabled us to replicate many risk variants, but several other previously suggested risk variants failed confirmation. By exploring the full set of 1800 candidate genes, we further identified common variation in the autoimmune regulator (AIRE) as a novel risk locus associated to sporadic AAD in our study. Our findings not only confirm that multiple loci are associated with disease risk, but also show to what extent the multiple risk loci jointly associate to AAD. In total, risk loci discovered to date only explain about 7% of variance in liability to AAD in our study population.
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Affiliation(s)
- Daniel Eriksson
- Department of Medicine (Solna), Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.
- Department of Endocrinology, Metabolism and Diabetes Karolinska University Hospital, Stockholm, Sweden.
| | - Matteo Bianchi
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Nils Landegren
- Department of Medicine (Solna), Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Frida Dalin
- Department of Medicine (Solna), Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Jakob Skov
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Lina Hultin-Rosenberg
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Argyri Mathioudaki
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Jessika Nordin
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Åsa Hallgren
- Department of Medicine (Solna), Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Göran Andersson
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Karolina Tandre
- Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | | | - Peter Söderkvist
- Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden
| | - Lars Rönnblom
- Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Anna-Lena Hulting
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Jeanette Wahlberg
- Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden
- Department of Endocrinology, Linköping University, Linköping, Sweden
- Department of Medical and Health Sciences, Linköping University, Linköping, Sweden
| | - Per Dahlqvist
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Olov Ekwall
- Department of Pediatrics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Rheumatology and Inflammation Research, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Jennifer R S Meadows
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Kerstin Lindblad-Toh
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Sophie Bensing
- Department of Endocrinology, Metabolism and Diabetes Karolinska University Hospital, Stockholm, Sweden
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Gerli Rosengren Pielberg
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Olle Kämpe
- Department of Medicine (Solna), Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Endocrinology, Metabolism and Diabetes Karolinska University Hospital, Stockholm, Sweden
- K.G. Jebsen Center for Autoimmune Diseases, Bergen, Norway
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27
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Sakthikumar S, Elvers I, Kim J, Arendt ML, Thomas R, Turner-Maier J, Swofford R, Johnson J, Schumacher SE, Alföldi J, Axelsson E, Couto CG, Kisseberth WC, Pettersson ME, Getz G, Meadows JRS, Modiano JF, Breen M, Kierczak M, Forsberg-Nilsson K, Marinescu VD, Lindblad-Toh K. SETD2 Is Recurrently Mutated in Whole-Exome Sequenced Canine Osteosarcoma. Cancer Res 2018; 78:3421-3431. [PMID: 29724721 DOI: 10.1158/0008-5472.can-17-3558] [Citation(s) in RCA: 56] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2017] [Revised: 03/15/2018] [Accepted: 04/30/2018] [Indexed: 11/16/2022]
Abstract
Osteosarcoma is a debilitating bone cancer that affects humans, especially children and adolescents. A homologous form of osteosarcoma spontaneously occurs in dogs, and its differential incidence observed across breeds allows for the investigation of tumor mutations in the context of multiple genetic backgrounds. Using whole-exome sequencing and dogs from three susceptible breeds (22 golden retrievers, 21 Rottweilers, and 23 greyhounds), we found that osteosarcoma tumors show a high frequency of somatic copy-number alterations (SCNA), affecting key oncogenes and tumor-suppressor genes. The across-breed results are similar to what has been observed for human osteosarcoma, but the disease frequency and somatic mutation counts vary in the three breeds. For all breeds, three mutational signatures (one of which has not been previously reported) and 11 significantly mutated genes were identified. TP53 was the most frequently altered gene (83% of dogs have either mutations or SCNA in TP53), recapitulating observations in human osteosarcoma. The second most frequently mutated gene, histone methyltransferase SETD2, has known roles in multiple cancers, but has not previously been strongly implicated in osteosarcoma. This study points to the likely importance of histone modifications in osteosarcoma and highlights the strong genetic similarities between human and dog osteosarcoma, suggesting that canine osteosarcoma may serve as an excellent model for developing treatment strategies in both species.Significance: Canine osteosarcoma genomics identify SETD2 as a possible oncogenic driver of osteosarcoma, and findings establish the canine model as a useful comparative model for the corresponding human disease. Cancer Res; 78(13); 3421-31. ©2018 AACR.
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Affiliation(s)
- Sharadha Sakthikumar
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.
- Broad Institute, Cambridge, Massachusetts
| | - Ingegerd Elvers
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
- Broad Institute, Cambridge, Massachusetts
| | - Jaegil Kim
- Broad Institute, Cambridge, Massachusetts
| | - Maja L Arendt
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
- Department of Veterinary Clinical Sciences, University of Copenhagen, Frederiksberg D, Denmark
| | - Rachael Thomas
- College of Veterinary Medicine, North Carolina State University, Raleigh, North Carolina
- Comparative Medicine Institute, North Carolina State University, Raleigh, North Carolina
| | | | | | | | | | | | - Erik Axelsson
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - C Guillermo Couto
- Department of Veterinary Clinical Sciences and Veterinary Medical Center, the Ohio State University, Columbus, Ohio
- Couto Veterinary Consultants, Hilliard, Ohio
| | - William C Kisseberth
- Department of Veterinary Clinical Sciences and Veterinary Medical Center, the Ohio State University, Columbus, Ohio
| | - Mats E Pettersson
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Gad Getz
- Broad Institute, Cambridge, Massachusetts
- Harvard Medical School, Boston, Massachusetts
- Massachusetts General Hospital, Boston, Massachusetts
| | - Jennifer R S Meadows
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Jaime F Modiano
- Animal Cancer Care and Research Program, College of Veterinary Medicine, St. Paul, Minnesota
- Department of Veterinary Clinical Sciences, College of Veterinary Medicine, St. Paul, Minnesota
- Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota
- Center for Immunology, University of Minnesota, Minneapolis, Minnesota
- Stem Cell Institute, University of Minnesota, Minneapolis, Minnesota
- Institute for Engineering and Medicine, University of Minnesota, Minneapolis, Minnesota
| | - Matthew Breen
- College of Veterinary Medicine, North Carolina State University, Raleigh, North Carolina
- Comparative Medicine Institute, North Carolina State University, Raleigh, North Carolina
| | - Marcin Kierczak
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Karin Forsberg-Nilsson
- Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Voichita D Marinescu
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Kerstin Lindblad-Toh
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.
- Broad Institute, Cambridge, Massachusetts
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Jäderkvist Fegraeus K, Velie BD, Axelsson J, Ang R, Hamilton NA, Andersson L, Meadows JRS, Lindgren G. A potential regulatory region near the EDN3 gene may control both harness racing performance and coat color variation in horses. Physiol Rep 2018; 6:e13700. [PMID: 29845762 PMCID: PMC5974718 DOI: 10.14814/phy2.13700] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Revised: 04/06/2018] [Accepted: 04/14/2018] [Indexed: 01/11/2023] Open
Abstract
The Swedish-Norwegian Coldblooded trotter and the heavier North-Swedish draught horse both descend from the North-Swedish horse, but the Coldblooded trotters have been selected for racing performance while the North-Swedish draught horse is mainly used for agricultural and forestry work. By comparing the genomes of Coldblooded trotters, North-Swedish draught horses and Standardbreds for a large number of single-nucleotide polymorphisms (SNPs), the aim of the study was to identify genetic regions that may be under selection for racing performance. We hypothesized that the selection for racing performance, in combination with unauthorized crossbreeding of Coldblooded trotters and Standardbreds, has created regions in the genome where the Coldblooded trotters and Standardbreds are similar, but differ from the North-Swedish draught horse. A fixation index (Fst) analysis was performed and sliding window Delta Fst values were calculated across the three breeds. Five windows, where the average Fst between Coldblooded trotters and Standardbreds was low and the average Fst between Coldblooded trotters and North-Swedish draught horses was high, were selected for further investigation. Associations between the most highly ranked SNPs and harness racing performance were analyzed in 400 raced Coldblooded trotters with race records. One SNP showed a significant association with racing performance, with the CC genotype appearing to be negatively associated. The SNP identified was genotyped in 1915 horses of 18 different breeds. The frequency of the TT genotype was high in breeds typically used for racing and show jumping while the frequency of the CC genotype was high in most pony breeds and draught horses. The closest gene in this region was the Endothelin3 gene (EDN3), a gene mainly involved in melanocyte and enteric neuron development. Both functional genetic and physiological studies are needed to fully understand the possible impacts of the gene on racing performance.
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Affiliation(s)
- Kim Jäderkvist Fegraeus
- Department of Animal Breeding & GeneticsSwedish University of Agricultural SciencesUppsalaSweden
| | - Brandon D. Velie
- Department of Animal Breeding & GeneticsSwedish University of Agricultural SciencesUppsalaSweden
| | - Jeanette Axelsson
- Department of Animal Breeding & GeneticsSwedish University of Agricultural SciencesUppsalaSweden
| | - Rachel Ang
- Faculty of ScienceUniversity of SydneySydneyAustralia
| | | | - Leif Andersson
- Department of Animal Breeding & GeneticsSwedish University of Agricultural SciencesUppsalaSweden
- Department of Medical Biochemistry and MicrobiologyScience for Life LaboratoryUppsala UniversityUppsalaSweden
- Department of Veterinary Integrative BiosciencesTexas A&M UniversityCollege StationTexas
| | - Jennifer R. S. Meadows
- Department of Medical Biochemistry and MicrobiologyScience for Life LaboratoryUppsala UniversityUppsalaSweden
| | - Gabriella Lindgren
- Department of Animal Breeding & GeneticsSwedish University of Agricultural SciencesUppsalaSweden
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29
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30
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Eriksson D, Bianchi M, Landegren N, Nordin J, Dalin F, Mathioudaki A, Eriksson GN, Hultin-Rosenberg L, Dahlqvist J, Zetterqvist H, Karlsson Å, Hallgren Å, Farias FHG, Murén E, Ahlgren KM, Lobell A, Andersson G, Tandre K, Dahlqvist SR, Söderkvist P, Rönnblom L, Hulting AL, Wahlberg J, Ekwall O, Dahlqvist P, Meadows JRS, Bensing S, Lindblad-Toh K, Kämpe O, Pielberg GR. Extended exome sequencing identifies BACH2 as a novel major risk locus for Addison's disease. J Intern Med 2016; 280:595-608. [PMID: 27807919 DOI: 10.1111/joim.12569] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
BACKGROUND Autoimmune disease is one of the leading causes of morbidity and mortality worldwide. In Addison's disease, the adrenal glands are targeted by destructive autoimmunity. Despite being the most common cause of primary adrenal failure, little is known about its aetiology. METHODS To understand the genetic background of Addison's disease, we utilized the extensively characterized patients of the Swedish Addison Registry. We developed an extended exome capture array comprising a selected set of 1853 genes and their potential regulatory elements, for the purpose of sequencing 479 patients with Addison's disease and 1394 controls. RESULTS We identified BACH2 (rs62408233-A, OR = 2.01 (1.71-2.37), P = 1.66 × 10-15 , MAF 0.46/0.29 in cases/controls) as a novel gene associated with Addison's disease development. We also confirmed the previously known associations with the HLA complex. CONCLUSION Whilst BACH2 has been previously reported to associate with organ-specific autoimmune diseases co-inherited with Addison's disease, we have identified BACH2 as a major risk locus in Addison's disease, independent of concomitant autoimmune diseases. Our results may enable future research towards preventive disease treatment.
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Affiliation(s)
- D Eriksson
- Department of Medicine (Solna), Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.,Department of Endocrinology, Metabolism and Diabetes Karolinska University Hospital, Stockholm, Sweden
| | - M Bianchi
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - N Landegren
- Department of Medicine (Solna), Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.,Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - J Nordin
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - F Dalin
- Department of Medicine (Solna), Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.,Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - A Mathioudaki
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - G N Eriksson
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - L Hultin-Rosenberg
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - J Dahlqvist
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - H Zetterqvist
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.,Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Å Karlsson
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Å Hallgren
- Department of Medicine (Solna), Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.,Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - F H G Farias
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - E Murén
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - K M Ahlgren
- Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - A Lobell
- Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - G Andersson
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - K Tandre
- Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - S R Dahlqvist
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - P Söderkvist
- Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden
| | - L Rönnblom
- Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - A-L Hulting
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - J Wahlberg
- Department of Endocrinology, Department of Medical and Health Sciences, Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden
| | - O Ekwall
- Department of Pediatrics, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Department of Rheumatology and Inflammation Research, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - P Dahlqvist
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - J R S Meadows
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - S Bensing
- Department of Endocrinology, Metabolism and Diabetes Karolinska University Hospital, Stockholm, Sweden.,Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - K Lindblad-Toh
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.,Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - O Kämpe
- Department of Medicine (Solna), Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden.,Department of Endocrinology, Metabolism and Diabetes Karolinska University Hospital, Stockholm, Sweden.,Science for Life Laboratory, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - G R Pielberg
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
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Olsson M, Kierczak M, Karlsson Å, Jabłońska J, Leegwater P, Koltookian M, Abadie J, De Citres CD, Thomas A, Hedhammar Å, Tintle L, Lindblad-Toh K, Meadows JRS. Absolute quantification reveals the stable transmission of a high copy number variant linked to autoinflammatory disease. BMC Genomics 2016; 17:299. [PMID: 27107962 PMCID: PMC4841964 DOI: 10.1186/s12864-016-2619-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2015] [Accepted: 04/13/2016] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Dissecting the role copy number variants (CNVs) play in disease pathogenesis is directly reliant on accurate methods for quantification. The Shar-Pei dog breed is predisposed to a complex autoinflammatory disease with numerous clinical manifestations. One such sign, recurrent fever, was previously shown to be significantly associated with a novel, but unstable CNV (CNV_16.1). Droplet digital PCR (ddPCR) offers a new mechanism for CNV detection via absolute quantification with the promise of added precision and reliability. The aim of this study was to evaluate ddPCR in relation to quantitative PCR (qPCR) and to assess the suitability of the favoured method as a genetic test for Shar-Pei Autoinflammatory Disease (SPAID). RESULTS One hundred and ninety-six individuals were assayed using both PCR methods at two CNV positions (CNV_14.3 and CNV_16.1). The digital method revealed a striking result. The CNVs did not follow a continuum of alleles as previously reported, rather the alleles were stable and pedigree analysis showed they adhered to Mendelian segregation. Subsequent analysis of ddPCR case/control data confirmed that both CNVs remained significantly associated with the subphenotype of fever, but also to the encompassing SPAID complex (p < 0.001). In addition, harbouring CNV_16.1 allele five (CNV_16.1|5) resulted in a four-fold increase in the odds for SPAID (p < 0.001). The inclusion of a genetic marker for CNV_16.1 in a genome-wide association test revealed that this variant explained 9.7 % of genetic variance and 25.8 % of the additive genetic heritability of this autoinflammatory disease. CONCLUSIONS This data shows the utility of the ddPCR method to resolve cryptic copy number inheritance patterns and so open avenues of genetic testing. In its current form, the ddPCR test presented here could be used in canine breeding to reduce the number of homozygote CNV_16.1|5 individuals and thereby to reduce the prevalence of disease in this breed.
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Affiliation(s)
- M Olsson
- Department of Medicine, Rheumatology Unit, Karolinska Institute, Stockholm, Sweden
| | - M Kierczak
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Å Karlsson
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - J Jabłońska
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - P Leegwater
- Department of Clinical Sciences of Companion Animals, Utrecht University, Utrecht, Netherlands
| | - M Koltookian
- Broad Institute of MIT and Harvard, Boston, MA, USA
| | - J Abadie
- LUNAM University, Oniris, AMaROC Unit, Nantes, F-44307, France
| | | | - A Thomas
- ANTAGENE Animal Genetics Laboratory, La Tour de Salvagny, Lyon, 69, France
| | - Å Hedhammar
- Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - L Tintle
- Wurtsboro Veterinary Clinic, Wurtsboro, New York, USA
| | - K Lindblad-Toh
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden.,Broad Institute of MIT and Harvard, Boston, MA, USA
| | - J R S Meadows
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
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Kierczak M, Jabłońska J, Forsberg SKG, Bianchi M, Tengvall K, Pettersson M, Scholz V, Meadows JRS, Jern P, Carlborg Ö, Lindblad-Toh K. cgmisc: enhanced genome-wide association analyses and visualization. Bioinformatics 2015; 31:3830-1. [PMID: 26249815 PMCID: PMC4653382 DOI: 10.1093/bioinformatics/btv426] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2015] [Accepted: 07/17/2015] [Indexed: 12/20/2022] Open
Abstract
UNLABELLED High-throughput genotyping and sequencing technologies facilitate studies of complex genetic traits and provide new research opportunities. The increasing popularity of genome-wide association studies (GWAS) leads to the discovery of new associated loci and a better understanding of the genetic architecture underlying not only diseases, but also other monogenic and complex phenotypes. Several softwares are available for performing GWAS analyses, R environment being one of them. RESULTS We present cgmisc, an R package that enables enhanced data analysis and visualization of results from GWAS. The package contains several utilities and modules that complement and enhance the functionality of the existing software. It also provides several tools for advanced visualization of genomic data and utilizes the power of the R language to aid in preparation of publication-quality figures. Some of the package functions are specific for the domestic dog (Canis familiaris) data. AVAILABILITY AND IMPLEMENTATION The package is operating system-independent and is available from: https://github.com/cgmisc-team/cgmisc CONTACT marcin.kierczak@imbim.uu.se. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Marcin Kierczak
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden, Computational Genetics Section, Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden and
| | - Jagoda Jabłońska
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Simon K G Forsberg
- Computational Genetics Section, Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden and
| | - Matteo Bianchi
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Katarina Tengvall
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Mats Pettersson
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden, Computational Genetics Section, Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden and
| | - Veronika Scholz
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Jennifer R S Meadows
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Patric Jern
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Örjan Carlborg
- Computational Genetics Section, Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden and
| | - Kerstin Lindblad-Toh
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden, Broad Institute of MIT and Harvard, Boston, MA, USA
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Zamani N, Sundström G, Meadows JRS, Höppner MP, Dainat J, Lantz H, Haas BJ, Grabherr MG. A universal genomic coordinate translator for comparative genomics. BMC Bioinformatics 2014; 15:227. [PMID: 24976580 PMCID: PMC4086997 DOI: 10.1186/1471-2105-15-227] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2014] [Accepted: 06/18/2014] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Genomic duplications constitute major events in the evolution of species, allowing paralogous copies of genes to take on fine-tuned biological roles. Unambiguously identifying the orthology relationship between copies across multiple genomes can be resolved by synteny, i.e. the conserved order of genomic sequences. However, a comprehensive analysis of duplication events and their contributions to evolution would require all-to-all genome alignments, which increases at N2 with the number of available genomes, N. RESULTS Here, we introduce Kraken, software that omits the all-to-all requirement by recursively traversing a graph of pairwise alignments and dynamically re-computing orthology. Kraken scales linearly with the number of targeted genomes, N, which allows for including large numbers of genomes in analyses. We first evaluated the method on the set of 12 Drosophila genomes, finding that orthologous correspondence computed indirectly through a graph of multiple synteny maps comes at minimal cost in terms of sensitivity, but reduces overall computational runtime by an order of magnitude. We then used the method on three well-annotated mammalian genomes, human, mouse, and rat, and show that up to 93% of protein coding transcripts have unambiguous pairwise orthologous relationships across the genomes. On a nucleotide level, 70 to 83% of exons match exactly at both splice junctions, and up to 97% on at least one junction. We last applied Kraken to an RNA-sequencing dataset from multiple vertebrates and diverse tissues, where we confirmed that brain-specific gene family members, i.e. one-to-many or many-to-many homologs, are more highly correlated across species than single-copy (i.e. one-to-one homologous) genes. Not limited to protein coding genes, Kraken also identifies thousands of newly identified transcribed loci, likely non-coding RNAs that are consistently transcribed in human, chimpanzee and gorilla, and maintain significant correlation of expression levels across species. CONCLUSIONS Kraken is a computational genome coordinate translator that facilitates cross-species comparisons, distinguishes orthologs from paralogs, and does not require costly all-to-all whole genome mappings. Kraken is freely available under LPGL from http://github.com/nedaz/kraken.
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Affiliation(s)
- Neda Zamani
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.
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Hoeppner MP, Lundquist A, Pirun M, Meadows JRS, Zamani N, Johnson J, Sundström G, Cook A, FitzGerald MG, Swofford R, Mauceli E, Moghadam BT, Greka A, Alföldi J, Abouelleil A, Aftuck L, Bessette D, Berlin A, Brown A, Gearin G, Lui A, Macdonald JP, Priest M, Shea T, Turner-Maier J, Zimmer A, Lander ES, di Palma F, Lindblad-Toh K, Grabherr MG. An improved canine genome and a comprehensive catalogue of coding genes and non-coding transcripts. PLoS One 2014; 9:e91172. [PMID: 24625832 PMCID: PMC3953330 DOI: 10.1371/journal.pone.0091172] [Citation(s) in RCA: 162] [Impact Index Per Article: 16.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2013] [Accepted: 02/08/2014] [Indexed: 12/22/2022] Open
Abstract
The domestic dog, Canis familiaris, is a well-established model system for mapping trait and disease loci. While the original draft sequence was of good quality, gaps were abundant particularly in promoter regions of the genome, negatively impacting the annotation and study of candidate genes. Here, we present an improved genome build, canFam3.1, which includes 85 MB of novel sequence and now covers 99.8% of the euchromatic portion of the genome. We also present multiple RNA-Sequencing data sets from 10 different canine tissues to catalog ∼175,000 expressed loci. While about 90% of the coding genes previously annotated by EnsEMBL have measurable expression in at least one sample, the number of transcript isoforms detected by our data expands the EnsEMBL annotations by a factor of four. Syntenic comparison with the human genome revealed an additional ∼3,000 loci that are characterized as protein coding in human and were also expressed in the dog, suggesting that those were previously not annotated in the EnsEMBL canine gene set. In addition to ∼20,700 high-confidence protein coding loci, we found ∼4,600 antisense transcripts overlapping exons of protein coding genes, ∼7,200 intergenic multi-exon transcripts without coding potential, likely candidates for long intergenic non-coding RNAs (lincRNAs) and ∼11,000 transcripts were reported by two different library construction methods but did not fit any of the above categories. Of the lincRNAs, about 6,000 have no annotated orthologs in human or mouse. Functional analysis of two novel transcripts with shRNA in a mouse kidney cell line altered cell morphology and motility. All in all, we provide a much-improved annotation of the canine genome and suggest regulatory functions for several of the novel non-coding transcripts.
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Affiliation(s)
- Marc P. Hoeppner
- Science for Life Laboratories, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Andrew Lundquist
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- Division of Nephrology, Massachusetts General Hospital and Harvard Medical School, Charlestown, Massachusetts, United States of America
| | - Mono Pirun
- Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America
| | - Jennifer R. S. Meadows
- Science for Life Laboratories, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Neda Zamani
- Science for Life Laboratories, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Jeremy Johnson
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Görel Sundström
- Science for Life Laboratories, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - April Cook
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Michael G. FitzGerald
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Ross Swofford
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Evan Mauceli
- Boston Children's Hospital, Boston, Massachusetts, United States of America
| | | | - Anna Greka
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Jessica Alföldi
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Amr Abouelleil
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Lynne Aftuck
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Daniel Bessette
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Aaron Berlin
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Adam Brown
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Gary Gearin
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Annie Lui
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | | | - Margaret Priest
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Terrance Shea
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Jason Turner-Maier
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Andrew Zimmer
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Eric S. Lander
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Federica di Palma
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- Vertebrate and Health Genomics, The Genome Analysis Centre, Norwich, United Kingdom
| | - Kerstin Lindblad-Toh
- Science for Life Laboratories, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- * E-mail: (KL-T); (MGG)
| | - Manfred G. Grabherr
- Science for Life Laboratories, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- * E-mail: (KL-T); (MGG)
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35
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Olsson M, Tintle L, Kierczak M, Perloski M, Tonomura N, Lundquist A, Murén E, Fels M, Tengvall K, Pielberg G, Dufaure de Citres C, Dorso L, Abadie J, Hanson J, Thomas A, Leegwater P, Hedhammar Å, Lindblad-Toh K, Meadows JRS. Thorough investigation of a canine autoinflammatory disease (AID) confirms one main risk locus and suggests a modifier locus for amyloidosis. PLoS One 2013; 8:e75242. [PMID: 24130694 PMCID: PMC3793984 DOI: 10.1371/journal.pone.0075242] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2013] [Accepted: 08/13/2013] [Indexed: 12/04/2022] Open
Abstract
Autoinflammatory disease (AID) manifests from the dysregulation of the innate immune system and is characterised by systemic and persistent inflammation. Clinical heterogeneity leads to patients presenting with one or a spectrum of phenotypic signs, leading to difficult diagnoses in the absence of a clear genetic cause. We used separate genome-wide SNP analyses to investigate five signs of AID (recurrent fever, arthritis, breed specific secondary dermatitis, otitis and systemic reactive amyloidosis) in a canine comparative model, the pure bred Chinese Shar-Pei. Analysis of 255 DNA samples revealed a shared locus on chromosome 13 spanning two peaks of association. A three-marker haplotype based on the most significant SNP (p<2.6×10−8) from each analysis showed that one haplotypic pair (H13-11) was present in the majority of AID individuals, implicating this as a shared risk factor for all phenotypes. We also noted that a genetic signature (FST) distinguishing the phenotypic extremes of the breed specific Chinese Shar-Pei thick and wrinkled skin, flanked the chromosome 13 AID locus; suggesting that breed development and differentiation has played a parallel role in the genetics of breed fitness. Intriguingly, a potential modifier locus for amyloidosis was revealed on chromosome 14, and an investigation of candidate genes from both this and the chromosome 13 regions revealed significant (p<0.05) renal differential expression in four genes previously implicated in kidney or immune health (AOAH, ELMO1, HAS2 and IL6). These results illustrate that phenotypic heterogeneity need not be a reflection of genetic heterogeneity, and that genetic modifiers of disease could be masked if syndromes were not first considered as individual clinical signs and then as a sum of their component parts.
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Affiliation(s)
- Mia Olsson
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
- * E-mail: (MO); (KL-T); (JRSM)
| | - Linda Tintle
- Wurtsboro Veterinary Clinic, Wurtsboro, New York, United States of America
| | - Marcin Kierczak
- Computational Genetics Section, Department of Clinical Sciences, Swedish University of Agricultural Sciences (SLU), Uppsala, Sweden
| | - Michele Perloski
- Broad Institute of Harvard and Massachusetts Institute of Technology (MIT), Cambridge, MA, United States of America
| | - Noriko Tonomura
- Broad Institute of Harvard and Massachusetts Institute of Technology (MIT), Cambridge, MA, United States of America
- Department of Clinical Sciences, Cummings School of Veterinary Medicine at Tufts University, North Grafton, Massachusetts, United States of America
| | - Andrew Lundquist
- Broad Institute of Harvard and Massachusetts Institute of Technology (MIT), Cambridge, MA, United States of America
| | - Eva Murén
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Max Fels
- Albert Einstein College of Medicine, Bronx, New York, United States of America
| | - Katarina Tengvall
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Gerli Pielberg
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | | | - Laetitia Dorso
- LUNAM University, Oniris, AMaROC Unit, Nantes, F-44307, France
| | - Jérôme Abadie
- LUNAM University, Oniris, AMaROC Unit, Nantes, F-44307, France
| | - Jeanette Hanson
- Department of Clinical Sciences, Swedish University of Agricultural Sciences (SLU), Uppsala, Sweden
| | - Anne Thomas
- ANTAGENE Animal Genetics Laboratory, La Tour de Salvagny (69 Lyon), France
| | - Peter Leegwater
- Department of Clinical Sciences of Companion Animals, Utrecht University, Utrecht, The Netherlands
| | - Åke Hedhammar
- Department of Clinical Sciences, Swedish University of Agricultural Sciences (SLU), Uppsala, Sweden
| | - Kerstin Lindblad-Toh
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
- Broad Institute of Harvard and Massachusetts Institute of Technology (MIT), Cambridge, MA, United States of America
- * E-mail: (MO); (KL-T); (JRSM)
| | - Jennifer R. S. Meadows
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
- * E-mail: (MO); (KL-T); (JRSM)
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Andersson LS, Swinburne JE, Meadows JRS, Broström H, Eriksson S, Fikse WF, Frey R, Sundquist M, Tseng CT, Mikko S, Lindgren G. Erratum to: The same ELA class II risk factors confer equine insect bite hypersensitivity in two distinct populations. Immunogenetics 2011. [PMCID: PMC3462919 DOI: 10.1007/s00251-011-0592-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Lisa S. Andersson
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 597, SE-751 24 Uppsala, Sweden
| | - June E. Swinburne
- Centre for Preventive Medicine, Animal Health Trust, Lanwades Park, Kentford, Newmarket, Suffolk, CB7 8UU UK
| | - Jennifer R. S. Meadows
- Department of Medical Biochemistry and Microbiology, Uppsala University, Box 582, SE-751 24 Uppsala, Sweden
| | - Hans Broström
- Department of Clinical Sciences, Swedish University of Agricultural Sciences, Box 7054, SE-750 07 Uppsala, Sweden
| | - Susanne Eriksson
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 7023, SE-750 07 Uppsala, Sweden
| | - W. Freddy Fikse
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 7023, SE-750 07 Uppsala, Sweden
| | - Rebecka Frey
- Norsholms Animal Hospital, Biskop Henriksv. 6, SE-602 37 Norrköping, Sweden
| | - Marie Sundquist
- Östra Greda Research Group, Vialmv. 5, SE-387 91 Borgholm, Sweden
| | - Chia T. Tseng
- Baker Institute for Animal Health, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853 USA
| | - Sofia Mikko
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 7023, SE-750 07 Uppsala, Sweden
| | - Gabriella Lindgren
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 597, SE-751 24 Uppsala, Sweden
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Andersson LS, Swinburne JE, Meadows JRS, Broström H, Eriksson S, Fikse WF, Frey R, Sundquist M, Tseng CT, Mikko S, Lindgren G. The same ELA class II risk factors confer equine insect bite hypersensitivity in two distinct populations. Immunogenetics 2011; 64:201-8. [PMID: 21947540 PMCID: PMC3276761 DOI: 10.1007/s00251-011-0573-1] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2011] [Accepted: 09/09/2011] [Indexed: 11/15/2022]
Abstract
Insect bite hypersensitivity (IBH) is a chronic allergic dermatitis common in horses. Affected horses mainly react against antigens present in the saliva from the biting midges, Culicoides ssp, and occasionally black flies, Simulium ssp. Because of this insect dependency, the disease is clearly seasonal and prevalence varies between geographical locations. For two distinct horse breeds, we genotyped four microsatellite markers positioned within the MHC class II region and sequenced the highly polymorphic exons two from DRA and DRB3, respectively. Initially, 94 IBH-affected and 93 unaffected Swedish born Icelandic horses were tested for genetic association. These horses had previously been genotyped on the Illumina Equine SNP50 BeadChip, which made it possible to ensure that our study did not suffer from the effects of stratification. The second population consisted of 106 unaffected and 80 IBH-affected Exmoor ponies. We show that variants in the MHC class II region are associated with disease susceptibility (praw = 2.34 × 10−5), with the same allele (COR112:274) associated in two separate populations. In addition, we combined microsatellite and sequencing data in order to investigate the pattern of homozygosity and show that homozygosity across the entire MHC class II region is associated with a higher risk of developing IBH (p = 0.0013). To our knowledge this is the first time in any atopic dermatitis suffering species, including man, where the same risk allele has been identified in two distinct populations.
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Affiliation(s)
- Lisa S Andersson
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 597, SE-751 24, Uppsala, Sweden
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Olsson M, Meadows JRS, Truvé K, Rosengren Pielberg G, Puppo F, Mauceli E, Quilez J, Tonomura N, Zanna G, Docampo MJ, Bassols A, Avery AC, Karlsson EK, Thomas A, Kastner DL, Bongcam-Rudloff E, Webster MT, Sanchez A, Hedhammar Å, Remmers EF, Andersson L, Ferrer L, Tintle L, Lindblad-Toh K. A novel unstable duplication upstream of HAS2 predisposes to a breed-defining skin phenotype and a periodic fever syndrome in Chinese Shar-Pei dogs. PLoS Genet 2011; 7:e1001332. [PMID: 21437276 PMCID: PMC3060080 DOI: 10.1371/journal.pgen.1001332] [Citation(s) in RCA: 100] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2010] [Accepted: 02/10/2011] [Indexed: 12/12/2022] Open
Abstract
Hereditary periodic fever syndromes are characterized by recurrent episodes of fever and inflammation with no known pathogenic or autoimmune cause. In humans, several genes have been implicated in this group of diseases, but the majority of cases remain unexplained. A similar periodic fever syndrome is relatively frequent in the Chinese Shar-Pei breed of dogs. In the western world, Shar-Pei have been strongly selected for a distinctive thick and heavily folded skin. In this study, a mutation affecting both these traits was identified. Using genome-wide SNP analysis of Shar-Pei and other breeds, the strongest signal of a breed-specific selective sweep was located on chromosome 13. The same region also harbored the strongest genome-wide association (GWA) signal for susceptibility to the periodic fever syndrome (praw = 2.3×10−6, pgenome = 0.01). Dense targeted resequencing revealed two partially overlapping duplications, 14.3 Kb and 16.1 Kb in size, unique to Shar-Pei and upstream of the Hyaluronic Acid Synthase 2 (HAS2) gene. HAS2 encodes the rate-limiting enzyme synthesizing hyaluronan (HA), a major component of the skin. HA is up-regulated and accumulates in the thickened skin of Shar-Pei. A high copy number of the 16.1 Kb duplication was associated with an increased expression of HAS2 as well as the periodic fever syndrome (p<0.0001). When fragmented, HA can act as a trigger of the innate immune system and stimulate sterile fever and inflammation. The strong selection for the skin phenotype therefore appears to enrich for a pleiotropic mutation predisposing these dogs to a periodic fever syndrome. The identification of HA as a major risk factor for this canine disease raises the potential of this glycosaminoglycan as a risk factor for human periodic fevers and as an important driver of chronic inflammation. Shar-Pei dogs have two unique features: a breed defining “wrinkled” skin phenotype and a genetic disorder called Familial Shar-Pei Fever (FSF). The wrinkled phenotype is strongly selected for and is the result of excessive hyaluronan (HA) deposited in the skin. HA is a molecule that may behave in a pro-inflammatory manner and create a “danger signal” by being analogous to molecules on the surface of pathogens. FSF is characterized by unprovoked episodes of fever and/or inflammation and resembles several human autoinflammatory syndromes. Here we show that the two features are connected and have the same genetic origin, a regulatory mutation located close to a HA synthesizing gene (HAS2). The mutation is a 16.1 Kb duplication, the copy number of which correlates with HAS2 expression and disease. We suggest that the large amount of HA responsible for the skin condition predisposes to sterile fever and inflammation. HAS2 was previously not known to associate with autoinflammatory disease, and this finding is of wide interest since approximately 60% of human patients with periodic fever syndrome remain genetically unexplained. This investigation also demonstrates how strong artificial selection may affect not only desired and selected phenotypes, but also the health of domestic animals.
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Affiliation(s)
- Mia Olsson
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
- * E-mail: (MO); (LT); (KL-T)
| | - Jennifer R. S. Meadows
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Katarina Truvé
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Gerli Rosengren Pielberg
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Francesca Puppo
- National Human Genome Research Institute, Bethesda, Maryland, United States of America
| | - Evan Mauceli
- Broad Institute of Harvard and Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts, United States of America
| | - Javier Quilez
- Department of Animal and Food Science, Veterinary Molecular Genetics Service, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Noriko Tonomura
- Broad Institute of Harvard and Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts, United States of America
| | - Giordana Zanna
- Department of Animal Medicine and Surgery, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Maria José Docampo
- Department of Biochemistry and Molecular Biology, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Anna Bassols
- Department of Biochemistry and Molecular Biology, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Anne C. Avery
- Department of Microbiology, Immunology, and Pathology, Colorado State University, Fort Collins, Colorado, United States of America
| | - Elinor K. Karlsson
- Broad Institute of Harvard and Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts, United States of America
- FAS Center for Systems Biology, Harvard University, Cambridge, Massachusetts, United States of America
| | | | - Daniel L. Kastner
- National Human Genome Research Institute, Bethesda, Maryland, United States of America
| | | | - Matthew T. Webster
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Armand Sanchez
- Department of Animal and Food Science, Veterinary Molecular Genetics Service, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Åke Hedhammar
- Department of Clinical Sciences, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Elaine F. Remmers
- National Human Genome Research Institute, Bethesda, Maryland, United States of America
| | - Leif Andersson
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Lluis Ferrer
- Department of Animal Medicine and Surgery, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Linda Tintle
- Wurtsboro Veterinary Clinic, Wurtsboro, New York, United States of America
- * E-mail: (MO); (LT); (KL-T)
| | - Kerstin Lindblad-Toh
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
- Broad Institute of Harvard and Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts, United States of America
- * E-mail: (MO); (LT); (KL-T)
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Meadows JRS, Hiendleder S, Kijas JW. Haplogroup relationships between domestic and wild sheep resolved using a mitogenome panel. Heredity (Edinb) 2010; 106:700-6. [PMID: 20940734 DOI: 10.1038/hdy.2010.122] [Citation(s) in RCA: 73] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
Five haplogroups have been identified in domestic sheep through global surveys of mitochondrial (mt) sequence variation, however these group classifications are often based on small fragments of the complete mtDNA sequence; partial control region or the cytochrome B gene. This study presents the complete mitogenome from representatives of each haplogroup identified in domestic sheep, plus a sample of their wild relatives. Comparison of the sequence successfully resolved the relationships between each haplogroup and provided insight into the relationship with wild sheep. The five haplogroups were characterised as branching independently, a radiation that shared a common ancestor 920,000 ± 190,000 years ago based on protein coding sequence. The utility of various mtDNA components to inform the true relationship between sheep was also examined with Bayesian, maximum likelihood and partitioned Bremmer support analyses. The control region was found to be the mtDNA component, which contributed the highest amount of support to the tree generated using the complete data set. This study provides the nucleus of a mtDNA mitogenome panel, which can be used to assess additional mitogenomes and serve as a reference set to evaluate small fragments of the mtDNA.
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Affiliation(s)
- J R S Meadows
- CSIRO Livestock Industries, St Lucia, Queensland, Australia
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Wright D, Boije H, Meadows JRS, Bed'hom B, Gourichon D, Vieaud A, Tixier-Boichard M, Rubin CJ, Imsland F, Hallböök F, Andersson L. Copy number variation in intron 1 of SOX5 causes the Pea-comb phenotype in chickens. PLoS Genet 2009; 5:e1000512. [PMID: 19521496 PMCID: PMC2685452 DOI: 10.1371/journal.pgen.1000512] [Citation(s) in RCA: 175] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2009] [Accepted: 05/12/2009] [Indexed: 01/09/2023] Open
Abstract
Pea-comb is a dominant mutation in chickens that drastically reduces the size of the comb and wattles. It is an adaptive trait in cold climates as it reduces heat loss and makes the chicken less susceptible to frost lesions. Here we report that Pea-comb is caused by a massive amplification of a duplicated sequence located near evolutionary conserved non-coding sequences in intron 1 of the gene encoding the SOX5 transcription factor. This must be the causative mutation since all other polymorphisms associated with the Pea-comb allele were excluded by genetic analysis. SOX5 controls cell fate and differentiation and is essential for skeletal development, chondrocyte differentiation, and extracellular matrix production. Immunostaining in early embryos demonstrated that Pea-comb is associated with ectopic expression of SOX5 in mesenchymal cells located just beneath the surface ectoderm where the comb and wattles will subsequently develop. The results imply that the duplication expansion interferes with the regulation of SOX5 expression during the differentiation of cells crucial for the development of comb and wattles. The study provides novel insight into the nature of mutations that contribute to phenotypic evolution and is the first description of a spontaneous and fully viable mutation in this developmentally important gene. The featherless comb and wattles are defining features of the chicken. Whilst the Pea-comb allele was known to show a dominant inheritance and drastically reduce the size of both comb and wattles, the genetics underlying the mutation remained elusive. Chicken comb is primarily composed of collagen and hyaluronan, which are produced by chondrocytes. These cells are formed through the condensation and differentiation of mesenchyme cells during the chondrogenesis pathway, the early stages of which are regulated by SOX transcription factors. Here we pinpoint a massive amplification of a duplicated sequence in the first intron of SOX5 as causing the Pea-comb phenotype. By studying early embryos, we show that SOX5 is ectopically expressed during a restricted stage of development in the cells which underlie the comb and wattles of Pea-comb animals. We hypothesise that the sequence duplication alters the regulation of SOX5 expression when the differentiation of cells essential for comb and wattle development is taking place. Pea-comb adds to the growing list of phenotypic variation which is explained by regulatory mutations and so demonstrates the evolutionary significance of such events.
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Affiliation(s)
- Dominic Wright
- Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Henrik Boije
- Department of Neuroscience, Uppsala University, Uppsala, Sweden
| | - Jennifer R. S. Meadows
- Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Bertrand Bed'hom
- INRA, AgroParisTech, UMR1313 Animal Genetics and Integrative Biology, Jouy-en-Josas, France
| | | | - Agathe Vieaud
- INRA, AgroParisTech, UMR1313 Animal Genetics and Integrative Biology, Jouy-en-Josas, France
| | | | - Carl-Johan Rubin
- Department of Medical Sciences, Uppsala University Hospital, Uppsala, Sweden
| | - Freyja Imsland
- Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Finn Hallböök
- Department of Neuroscience, Uppsala University, Uppsala, Sweden
| | - Leif Andersson
- Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
- * E-mail:
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Meadows JRS, Chan EKF, Kijas JW. Linkage disequilibrium compared between five populations of domestic sheep. BMC Genet 2008; 9:61. [PMID: 18826649 PMCID: PMC2572059 DOI: 10.1186/1471-2156-9-61] [Citation(s) in RCA: 57] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2008] [Accepted: 09/30/2008] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The success of genome-wide scans depends on the strength and magnitude of linkage disequilibrium (LD) present within the populations under investigation. High density SNP arrays are currently in development for the sheep genome, however little is known about the behaviour of LD in this livestock species. This study examined the behaviour of LD within five sheep populations using two LD metrics, D' and x2'. Four economically important Australian sheep flocks, three pure breeds (White Faced Suffolk, Poll Dorset, Merino) and a crossbred population (Merino x Border Leicester), along with an inbred Australian Merino museum flock were analysed. RESULTS Short range LD (0 - 5 cM) was observed in all five populations, however the persistence with increasing distance and magnitude of LD varied considerably between populations. Average LD (x2') for markers spaced up to 20 cM exceeded the non-syntenic average within the White Faced Suffolk, Poll Dorset and Macarthur Merino. LD decayed faster within the Merino and Merino x Border Leicester, with LD below or consistent with observed background levels. Using marker-marker LD as a guide to the behaviour of marker-QTL LD, estimates of minimum marker spacing were made. For a 95% probability of detecting QTL, a microsatellite marker would be required every 0.1 - 2.5 centimorgans, depending on the population used. CONCLUSION Sheep populations were selected which were inbred (Macarthur Merino), highly heterogeneous (Merino) or intermediate between these two extremes. This facilitated analysis and comparison of LD (x2') between populations. The strength and magnitude of LD was found to differ markedly between breeds and aligned closely with both observed levels of genetic diversity and expectations based on breed history. This confirmed that breed specific information is likely to be important for genome wide selection and during the design of successful genome scans where tens of thousands of markers will be required.
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Affiliation(s)
- Jennifer R S Meadows
- CSIRO Livestock Industries, Level 5 Queensland Bioscience Precinct, 306 Carmody Road, St Lucia 4067, Australia.
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Abstract
This survey represents the first characterization of mitochondrial DNA diversity within three breeds of Indian sheep (two strains of the Deccani breed, as well as the Bannur and Garole breeds) from different geographic regions and with divergent phenotypic characteristics. A 1061-bp fragment of the mitochondrial genome spanning the control region, a portion of the 12S rRNA gene and the complete phenyl tRNA gene, was sequenced from 73 animals and compared with the corresponding published sequence from European and Asian breeds and the European Mouflon (Ovis musimon). Analysis of all 156 sequences revealed 73 haplotypes, 52 of which belonged to the Indian breeds. The three Indian breeds had no haplotypes in common, but one Indian haplotype was shared with European and other Asian breeds. The highest nucleotide and haplotype diversity was observed in the Bannur breed (0.00355 and 0.981 respectively), while the minimum was in the Sangamneri strain of the Deccani breed (0.00167 and 0.882 respectively). All 52 Indian haplotypes belonged to mitochondrial lineage A. Therefore, these Indian sheep are distinct from other Asian and European breeds studied so far. The relationships among the haplotypes showed strong breed structure and almost no introgression among these Indian breeds, consistent with Indian sheep husbandry, which discourages genetic exchange between breeds. These results have implications for the conservation of India's ovine biodiversity and suggest a common origin for the breeds investigated.
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Affiliation(s)
- V C Pardeshi
- Plant Molecular Biology Group, Biochemical Sciences Division, National Chemical Laboratory, Pune 411008, India
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Abstract
Archaeozoological evidence indicates that sheep were first domesticated in the Fertile Crescent. To search for DNA sequence diversity arising from previously undetected domestication events, this survey examined nine breeds of sheep from modern-day Turkey and Israel. A total of 2027 bp of mitochondrial DNA (mtDNA) sequence from 197 sheep revealed a total of 85 haplotypes and a high level of genetic diversity. Six individuals carried three haplotypes, which clustered separately from the known ovine mtDNA lineages A, B, and C. Analysis of genetic distance, mismatch distribution, and comparisons with wild sheep confirmed that these represent two additional mtDNA lineages denoted D and E. The two haplogroup E sequences were found to link the previously identified groups A and C. The single haplogroup D sequence branched with the eastern mouflon (Ovis orientalis), urial (O. vignei), and argali (O. ammon) sheep. High sequence diversity (K = 1.86%, haplogroup D and O. orientalis) indicates that the wild progenitor of this domestic lineage remains unresolved. The identification in this study of evidence for additional domestication events adds to the emerging view that sheep were recruited from wild populations multiple times in the same way as for other livestock species such as goat, cattle, and pig.
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Meadows JRS, Hanotte O, Drögemüller C, Calvo J, Godfrey R, Coltman D, Maddox JF, Marzanov N, Kantanen J, Kijas JW. Globally dispersed Y chromosomal haplotypes in wild and domestic sheep. Anim Genet 2006; 37:444-53. [PMID: 16978172 DOI: 10.1111/j.1365-2052.2006.01496.x] [Citation(s) in RCA: 64] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
To date, investigations of genetic diversity and the origins of domestication in sheep have utilised autosomal microsatellites and variation in the mitochondrial genome. We present the first analysis of both domestic and wild sheep using genetic markers residing on the ovine Y chromosome. Analysis of a single nucleotide polymorphism (oY1) in the SRY promoter region revealed that allele A-oY1 was present in all wild bighorn sheep (Ovis canadensis), two subspecies of thinhorn sheep (Ovis dalli), European Mouflon (Ovis musimon) and the Barbary (Ammontragis lervia). A-oY1 also had the highest frequency (71.4%) within 458 domestic sheep drawn from 65 breeds sampled from Africa, Asia, Australia, the Caribbean, Europe, the Middle East and Central Asia. Sequence analysis of a second locus, microsatellite SRYM18, revealed a compound repeat array displaying fixed differences, which identified bighorn and thinhorn sheep as distinct from the European Mouflon and domestic animals. Combined genotypic data identified 11 male-specific haplotypes that represented at least two separate lineages. Investigation of the geographical distribution of each haplotype revealed that one (H6) was both very common and widespread in the global sample of domestic breeds. The remaining haplotypes each displayed more restricted and informative distributions. For example, H5 was likely founded following the domestication of European breeds and was used to trace the recent transportation of animals to both the Caribbean and Australia. A high rate of Y chromosomal dispersal appears to have taken place during the development of domestic sheep as only 12.9% of the total observed variation was partitioned between major geographical regions.
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Affiliation(s)
- J R S Meadows
- CSIRO Livestock Industries, Queensland Bioscience Precinct, 306 Carmody Road, St Lucia 4067, Australia
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Hawken RJ, Cavanagh JAL, Meadows JRS, Khatkar MS, Husaini Y, Zenger KR, McClintock S, McClintock AE, Raadsma HW. Technical note: Whole-genome amplification of DNA extracted from cattle semen samples. J Dairy Sci 2006; 89:2217-21. [PMID: 16702288 DOI: 10.3168/jds.s0022-0302(06)72292-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
The bovine genome sequence project and the discovery of many thousands of bovine single nucleotide polymorphisms has opened the door for large-scale genotyping studies to identify genes that contribute to economically important traits with relevance to the beef and dairy industries. Large amounts of DNA will be required for these research projects. This study reports the use of the whole-genome amplification (WGA) method to create an unlimited supply of DNA for use in genotyping studies and long-term storage for future gene discovery projects. Two commercial WGA kits (GenomiPhi, Amersham Biosciences, Sydney, Australia, and REPLI-g, Qiagen, Doncaster, Australia) were used to amplify DNA from straws of bull semen, resulting in an average of 7.2 and 67 microg of DNA per reaction, respectively. The comparison of 3.5 kb of sequences from the amplified and unamplified DNA indicated no detectable DNA differences. Similarly, gene marker analysis conducted on genomic DNA and DNA after WGA indicated no difference in marker amplification or clarity and accuracy of scoring for approximately 10,000 single nucleotide polymorphism markers when compared with WGA samples genotyped in duplicate. These results illustrate that WGA is a suitable method for the amplification and recovery of DNA from bull semen samples for routine genomic investigations.
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Affiliation(s)
- R J Hawken
- CSIRO Livestock Industries, Queensland Biosciences Precinct, St Lucia, 4067, Queensland, Australia.
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Meadows JRS, Li K, Kantanen J, Tapio M, Sipos W, Pardeshi V, Gupta V, Calvo JH, Whan V, Norris B, Kijas JW. Mitochondrial Sequence Reveals High Levels of Gene Flow Between Breeds of Domestic Sheep from Asia and Europe. J Hered 2005; 96:494-501. [PMID: 16135704 DOI: 10.1093/jhered/esi100] [Citation(s) in RCA: 69] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Sequence variation present within the mitochondrial genome was used to investigate genetic diversity within sheep breeds from Asia and Europe. Comparison of 2027 bp of sequence from 121 animals revealed 44 phylogenetically informative nucleotide positions and a single insertion/deletion. A total of 57 haplotypes were observed which formed two distinct clades. Type A haplotypes were found in breeds from Asia (India, Indonesia, Mongolia, and Tibet), while type B haplotypes were observed at the highest frequency in breeds sourced from Europe (nine breeds from Austria, Aland, Finland, Spain, and northwestern Russia). The distribution of haplotypes indicates sheep appear to have the weakest population structure and the highest rate of intercontinental dispersal of any domestic animal reported to date. Only 2.7% of the sequence variation observed was partitioned between continents, which is lower than both goat (approximately 10%) and cattle (approximately 50%). Diagnostic restriction fragment length polymorphism polymerase chain reaction (RFLP-PCR) tests which distinguish type A and B haplotypes were used to test an additional 223 animals from 17 breeds of European and Asian origin. A mixture of the two lineages was found in every breed except Suffolk and the Indian Garole, indicating introgression has played a major part during breed development and subsequent selection.
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Affiliation(s)
- J R S Meadows
- CSIRO Livestock Industries, Level 5 Queensland Bioscience Precinct, 306 Carmody Rd., St. Lucia 4067, Australia
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Abstract
To investigate the impact of male-mediated introgression during the evolution of sheep breeds, a sequencing approach was used to identify single nucleotide polymorphisms (SNPs) from the male-specific region of the ovine Y chromosome (MSY). A total of 4380 bp, which comprised nine fragments from five MSY genes was sequenced within a panel of 14 males from seven breeds. Sequence alignment identified a single segregating site, an A/G SNP located approximately 1685 bp upstream of the ovine SRY gene. The resulting estimation of nucleotide diversity (piY = 0.90 +/- 0.50 x 10(-4)) falls towards the lower end of estimates from other species. This was compared with the nucleotide diversity estimated from the autosomal component of the genome. Sequence analysis of 2933 bp amplified from eight autosomal genes revealed a nucleotide diversity (piA = 2.15 +/- 0.27 x 10(-3)) higher than previously reported for sheep. Following adjustment for the contrasting influence of effective population size and a male biased mutation rate, comparison revealed that approximately 10% of the expected nucleotide diversity is present on the ovine Y chromosome.
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Affiliation(s)
- J R S Meadows
- CSIRO Livestock Industries, Level 5 Queensland Bioscience Precinct, 306 Carmody Road, St Lucia 4067, Australia
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