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Pan J, Liu X, Baca M, Calvière-Tonasso L, Schiavinato S, Chauvey L, Tressières G, Perdereau A, Aury JM, Oliveira PH, Wincker P, Abdykanova A, Arsuaga JL, Bayarsaikhan J, Belinskiy AB, Carbonell E, Davoudi H, Lira Garrido J, Gilbert AS, Hermes T, Warinner C, Kalmykov AA, Lordkipanidze D, Mackiewicz P, Mohaseb AF, Richter K, Sayfullaev N, Shapiro B, Shnaider S, Southon J, Stefaniak K, Summers GD, van Asperen EN, Vanishvili N, Hill EA, Kuznetsov P, Reinhold S, Hansen S, Mashkour M, Berthon R, Taylor WTT, Houle JL, Hekkala E, Popović D, Orlando L. Genome-wide population affinities and signatures of adaptation in hydruntines, sussemiones and Asian wild asses. Mol Ecol 2024; 33:e17527. [PMID: 39279684 DOI: 10.1111/mec.17527] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 06/08/2024] [Accepted: 09/03/2024] [Indexed: 09/18/2024]
Abstract
The extremely rich palaeontological record of the horse family, also known as equids, has provided many examples of macroevolutionary change over the last ~55 Mya. This family is also one of the most documented at the palaeogenomic level, with hundreds of ancient genomes sequenced. While these data have advanced understanding of the domestication history of horses and donkeys, the palaeogenomic record of other equids remains limited. In this study, we have generated genome-wide data for 25 ancient equid specimens spanning over 44 Ky and spread across Anatolia, the Caucasus, Central Asia and Mongolia. Our dataset includes the genomes from two extinct species, the European wild ass, Equus hydruntinus, and the sussemione Equus ovodovi. We document, for the first time, the presence of sussemiones in Mongolia and their survival around ~3.9 Kya, a finding that should be considered when discussing the timing of the first arrival of the domestic horse in the region. We also identify strong spatial differentiation within the historical ecological range of Asian wild asses, Equus hemionus, and incomplete reproductive isolation in several groups yet considered as different species. Finally, we find common selection signatures at ANTXR2 gene in European, Asian and African wild asses. This locus, which encodes a receptor for bacterial toxins, shows no selection signal in E. ovodovi, but a 5.4-kb deletion within intron 7. Whether such genetic modifications played any role in the sussemione extinction remains unknown.
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Affiliation(s)
- Jianfei Pan
- Centre d'Anthropobiologie et de Génomique de Toulouse, CNRS UMR5288, Université Paul Sabatier, Toulouse, France
- State Key Laboratory of Animal Biotech Breeding, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xuexue Liu
- Centre d'Anthropobiologie et de Génomique de Toulouse, CNRS UMR5288, Université Paul Sabatier, Toulouse, France
| | - Mateusz Baca
- Centre of New Technologies, University of Warsaw, Warsaw, Poland
| | - Laure Calvière-Tonasso
- Centre d'Anthropobiologie et de Génomique de Toulouse, CNRS UMR5288, Université Paul Sabatier, Toulouse, France
| | - Stéphanie Schiavinato
- Centre d'Anthropobiologie et de Génomique de Toulouse, CNRS UMR5288, Université Paul Sabatier, Toulouse, France
| | - Loreleï Chauvey
- Centre d'Anthropobiologie et de Génomique de Toulouse, CNRS UMR5288, Université Paul Sabatier, Toulouse, France
| | - Gaétan Tressières
- Centre d'Anthropobiologie et de Génomique de Toulouse, CNRS UMR5288, Université Paul Sabatier, Toulouse, France
| | - Aude Perdereau
- Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, Evry, France
| | - Jean-Marc Aury
- Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, Evry, France
| | - Pedro H Oliveira
- Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, Evry, France
| | - Patrick Wincker
- Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, Evry, France
| | - Aida Abdykanova
- Anthropology Department, American University of Central Asia, Bishkek, Kyrgyzstan
| | - Juan Luis Arsuaga
- Centro Mixto UCM-ISCIII de Evolución y Comportamiento Humanos, Madrid, Spain
- Departamento de Geodinámica, Estratigrafía y Paleontología. Facultad de Ciencias Geológicas, Universidad Complutense de Madrid, Madrid, Spain
| | - Jamsranjav Bayarsaikhan
- Department of Archaeology, Max Planck Institute for the Science of Human History, Jena, Germany
- National Museum of Mongolia, Ulaanbaatar, Mongolia
| | | | - Eudald Carbonell
- Departament d'Història i Història de l'Art, Universitat Rovira i Virgili, Tarragona, Spain
- Institut Català de Paleoecologia Humana I Evolució Social (IPHES-CERCA), Tarragona, Spain
| | - Hossein Davoudi
- Bioarchaeology Laboratory, Central Laboratory, University of Tehran, Tehran, Iran
| | - Jaime Lira Garrido
- Centre d'Anthropobiologie et de Génomique de Toulouse, CNRS UMR5288, Université Paul Sabatier, Toulouse, France
| | - Allan S Gilbert
- Department of Sociology and Anthropology, Fordham University, New York, New York, USA
| | - Taylor Hermes
- Department of Anthropology, University of Arkansas, Fayetteville, Arkansas, USA
- Department of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Christina Warinner
- Department of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
- Department of Anthropology, Harvard University, Cambridge, Massachusetts, USA
| | | | - David Lordkipanidze
- Georgian National Museum, Tbilisi, Tbilisi, Georgia
- Tbilisi State University Tbilisi I. Chavchavadze Avenue 1, Tbilisi, Georgia
| | - Paweł Mackiewicz
- Department of Bioinformatics and Genomics, Faculty of Biotechnology, University of Wrocław, Wrocław, Poland
| | - Azadeh F Mohaseb
- UMR 7209 'Archéozoologie, Archéobotanique: sociétés, Pratiques et Environnements', CNRS, Muséum National d'Histoire Naturelle, Paris, France
| | - Kristine Richter
- Department of Anthropology, Harvard University, Cambridge, Massachusetts, USA
| | - Nuritdin Sayfullaev
- Donish Institute of History, Archaeology and Ethnography, Dushanbe, Tajikistan
| | - Beth Shapiro
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, California, USA
| | - Svetlana Shnaider
- International Laboratory "Archaeozoology in Siberia and Central Asia" ZooSCAn, IRL 2013, National Center for Scientific Research - Institute of Archeology and Ethnography SB RAS, Novosibirsk, Russia
| | - John Southon
- Earth System Science Department, University of California, Irvine, California, USA
| | | | - Geoffrey D Summers
- Ecole Nationale Supérieure d'Architecture de Nantes-Mauritius, Pierrefonds, Mauritius
- The Oriental Institute, Chicago University, Chicago, Illinois, USA
| | | | - Nikoloz Vanishvili
- Department of Vertebrate Paleontology, L. Davitashvili Institute of Paleobiology, Georgian National Museum, Tbilisi, Georgia
| | - Eden A Hill
- Department of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Pavel Kuznetsov
- The Museum of Archeology of the Volga Region Samara State University of Social Sciences and Education, Samara, Russia
| | - Sabine Reinhold
- Eurasia Department, German Archaeological Institute, Berlin, Germany
| | - Svend Hansen
- Eurasia Department, German Archaeological Institute, Berlin, Germany
| | - Marjan Mashkour
- UMR 7209 'Archéozoologie, Archéobotanique: sociétés, Pratiques et Environnements', CNRS, Muséum National d'Histoire Naturelle, Paris, France
| | - Rémi Berthon
- UMR 7209 'Archéozoologie, Archéobotanique: sociétés, Pratiques et Environnements', CNRS, Muséum National d'Histoire Naturelle, Paris, France
| | - William Timothy Treal Taylor
- Museum of Natural History, University of Colorado Boulder, Boulder, Colorado, USA
- Department of Anthropology, University of Colorado Boulder, Boulder, Colorado, USA
| | - Jean-Luc Houle
- Department of Folk Studies and Anthropology, Western Kentucky University, Bowling Green, Kentucky, USA
| | - Evon Hekkala
- Department Biological Sciences, Fordham University, New York, New York, USA
| | - Danijela Popović
- Centre of New Technologies, University of Warsaw, Warsaw, Poland
| | - Ludovic Orlando
- Centre d'Anthropobiologie et de Génomique de Toulouse, CNRS UMR5288, Université Paul Sabatier, Toulouse, France
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Schoville SD, Burke RL, Dong DY, Ginsberg HS, Maestas L, Paskewitz SM, Tsao JI. Genome resequencing reveals population divergence and local adaptation of blacklegged ticks in the United States. Mol Ecol 2024; 33:e17460. [PMID: 38963031 DOI: 10.1111/mec.17460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Revised: 03/12/2024] [Accepted: 04/15/2024] [Indexed: 07/05/2024]
Abstract
Tick vectors and tick-borne disease are increasingly impacting human populations globally. An important challenge is to understand tick movement patterns, as this information can be used to improve management and predictive modelling of tick population dynamics. Evolutionary analysis of genetic divergence, gene flow and local adaptation provides insight on movement patterns at large spatiotemporal scales. We develop low coverage, whole genome resequencing data for 92 blacklegged ticks, Ixodes scapularis, representing range-wide variation across the United States. Through analysis of population genomic data, we find that tick populations are structured geographically, with gradual isolation by distance separating three population clusters in the northern United States, southeastern United States and a unique cluster represented by a sample from Tennessee. Populations in the northern United States underwent population contractions during the last glacial period and diverged from southern populations at least 50 thousand years ago. Genome scans of selection provide strong evidence of local adaptation at genes responding to host defences, blood-feeding and environmental variation. In addition, we explore the potential of low coverage genome sequencing of whole-tick samples for documenting the diversity of microbial pathogens and recover important tick-borne pathogens such as Borrelia burgdorferi. The combination of isolation by distance and local adaptation in blacklegged ticks demonstrates that gene flow, including recent expansion, is limited to geographical scales of a few hundred kilometres.
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Affiliation(s)
- Sean D Schoville
- Department of Entomology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Russell L Burke
- Department of Biology, Hofstra University, Hempstead, New York, USA
| | - Dahn-Young Dong
- Department of Integrative Biology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Howard S Ginsberg
- United States Geological Survey, Eastern Ecological Science Center, Woodward Hall - PSE, Field Station at the University of Rhode Island, Kingston, Rhode Island, USA
| | - Lauren Maestas
- Cattle Fever Tick Research Laboratory, USDA, Agricultural Research Service, Edinburg, Texas, USA
| | - Susan M Paskewitz
- Department of Entomology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Jean I Tsao
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, Michigan, USA
- Department of Large Animal Clinical Sciences, Michigan State University, East Lansing, Michigan, USA
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Giel AS, Bigge J, Schumacher J, Maj C, Dasmeh P. Analysis of Evolutionary Conservation, Expression Level, and Genetic Association at a Genome-wide Scale Reveals Heterogeneity Across Polygenic Phenotypes. Mol Biol Evol 2024; 41:msae115. [PMID: 38865495 PMCID: PMC11247350 DOI: 10.1093/molbev/msae115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 03/22/2024] [Accepted: 05/03/2024] [Indexed: 06/14/2024] Open
Abstract
Understanding the expression level and evolutionary rate of associated genes with human polygenic diseases provides crucial insights into their disease-contributing roles. In this work, we leveraged genome-wide association studies (GWASs) to investigate the relationship between the genetic association and both the evolutionary rate (dN/dS) and expression level of human genes associated with the two polygenic diseases of schizophrenia and coronary artery disease. Our findings highlight a distinct variation in these relationships between the two diseases. Genes associated with both diseases exhibit a significantly greater variance in evolutionary rate compared to those implicated in monogenic diseases. Expanding our analyses to 4,756 complex traits in the GWAS atlas database, we unraveled distinct trait categories with a unique interplay among the evolutionary rate, expression level, and genetic association of human genes. In most polygenic traits, highly expressed genes were more associated with the polygenic phenotypes compared to lowly expressed genes. About 69% of polygenic traits displayed a negative correlation between genetic association and evolutionary rate, while approximately 30% of these traits showed a positive correlation between genetic association and evolutionary rate. Our results demonstrate the presence of a spectrum among complex traits, shaped by natural selection. Notably, at opposite ends of this spectrum, we find metabolic traits being more likely influenced by purifying selection, and immunological traits that are more likely shaped by positive selection. We further established the polygenic evolution portal (evopolygen.de) as a resource for investigating relationships and generating hypotheses in the field of human polygenic trait evolution.
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Affiliation(s)
- Ann-Sophie Giel
- Centre for Human Genetics, Marburg University, Marburg, Germany
| | - Jessica Bigge
- Centre for Human Genetics, Marburg University, Marburg, Germany
| | | | - Carlo Maj
- Centre for Human Genetics, Marburg University, Marburg, Germany
| | - Pouria Dasmeh
- Centre for Human Genetics, Marburg University, Marburg, Germany
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Institute for Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland
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Cole SA, Lyke MM, Christensen C, Newman D, Bagwell A, Galindo S, Glenn J, Layne-Colon DG, Sayers K, Tardif S, Cox LA, Ross C, Cheeseman IH. Genetic characterization of a captive marmoset (Callithrix jacchus) colony using genotype-by-sequencing. Am J Primatol 2024; 86:e23630. [PMID: 38655843 PMCID: PMC11182716 DOI: 10.1002/ajp.23630] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 03/27/2024] [Accepted: 04/14/2024] [Indexed: 04/26/2024]
Abstract
The marmoset is a fundamental nonhuman primate model for the study of aging, neurobiology, and many other topics. Genetic management of captive marmoset colonies is complicated by frequent chimerism in the blood and other tissues, a lack of tools to enable cost-effective, genome-wide interrogation of variation, and historic mergers and migrations of animals between colonies. We implemented genotype-by-sequencing (GBS) of hair follicle derived DNA (a minimally chimeric DNA source) of 82 marmosets housed at the Southwest National Primate Research Center (SNPRC). Our primary goals were the genetic characterization of our marmoset population for pedigree verification and colony management and to inform the scientific community of the functional genetic makeup of this valuable resource. We used the GBS data to reconstruct the genetic legacy of recent mergers between colonies, to identify genetically related animals whose relationships were previously unknown due to incomplete pedigree information, and to show that animals in the SNPRC colony appear to exhibit low levels of inbreeding. Of the >99,000 single-nucleotide variants (SNVs) that we characterized, >9800 are located within gene regions known to harbor pathogenic variants of clinical significance in humans. Overall, we show the combination of low-resolution (sparse) genotyping using hair follicle DNA is a powerful strategy for the genetic management of captive marmoset colonies and for identifying potential SNVs for the development of biomedical research models.
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Affiliation(s)
- Shelley A Cole
- Southwest National Primate Research Center, San Antonio, Texas, USA
- Texas Biomedical Research Institute, San Antonio, Texas, USA
| | - Martha M Lyke
- Southwest National Primate Research Center, San Antonio, Texas, USA
- Texas Biomedical Research Institute, San Antonio, Texas, USA
| | - Clinton Christensen
- Southwest National Primate Research Center, San Antonio, Texas, USA
- Texas Biomedical Research Institute, San Antonio, Texas, USA
| | - Deborah Newman
- Southwest National Primate Research Center, San Antonio, Texas, USA
- Texas Biomedical Research Institute, San Antonio, Texas, USA
| | - Alec Bagwell
- Southwest National Primate Research Center, San Antonio, Texas, USA
- Texas Biomedical Research Institute, San Antonio, Texas, USA
| | - Samuel Galindo
- Southwest National Primate Research Center, San Antonio, Texas, USA
- Texas Biomedical Research Institute, San Antonio, Texas, USA
| | - Jeremy Glenn
- Texas Biomedical Research Institute, San Antonio, Texas, USA
| | - Donna G Layne-Colon
- Southwest National Primate Research Center, San Antonio, Texas, USA
- Texas Biomedical Research Institute, San Antonio, Texas, USA
| | - Ken Sayers
- Southwest National Primate Research Center, San Antonio, Texas, USA
- Texas Biomedical Research Institute, San Antonio, Texas, USA
| | - Suzette Tardif
- Southwest National Primate Research Center, San Antonio, Texas, USA
| | - Laura A Cox
- Center for Precision Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
| | - Corinna Ross
- Southwest National Primate Research Center, San Antonio, Texas, USA
- Texas Biomedical Research Institute, San Antonio, Texas, USA
| | - Ian H Cheeseman
- Southwest National Primate Research Center, San Antonio, Texas, USA
- Texas Biomedical Research Institute, San Antonio, Texas, USA
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Shpak M, Lawrence KN, Pool JE. The Precision and Power of Population Branch Statistics in Identifying the Genomic Signatures of Local Adaptation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.14.594139. [PMID: 38798330 PMCID: PMC11118325 DOI: 10.1101/2024.05.14.594139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Population branch statistics, which estimate the branch lengths of focal populations with respect to two outgroups, have been used as an alternative to FST-based genome-wide scans for identifying loci associated with local selective sweeps. In addition to the original population branch statistic (PBS), there are subsequently proposed branch rescalings: normalized population branch statistic (PBSn1), which adjusts focal branch length with respect to outgroup branch lengths at the same locus, and population branch excess (PBE), which also incorporates median branch lengths at other loci. PBSn1 and PBE have been proposed to be less sensitive to allele frequency divergence generated by background selection or geographically ubiquitous positive selection rather than local selective sweeps. However, the accuracy and statistical power of branch statistics have not been systematically assessed. To do so, we simulate genomes in representative large and small populations with varying proportions of sites evolving under genetic drift or background selection (approximated using variable Ne), local selective sweeps, and geographically parallel selective sweeps. We then assess the probability that local selective sweep loci are correctly identified as outliers by FST and by each of the branch statistics. We find that branch statistics consistently outperform FST at identifying local sweeps. When background selection and/or parallel sweeps are introduced, PBSn1 and especially PBE correctly identify local sweeps among their top outliers at a higher frequency than PBS. These results validate the greater specificity of rescaled branch statistics such as PBE to detect population-specific positive selection, supporting their use in genomic studies focused on local adaptation.
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Affiliation(s)
- Max Shpak
- Laboratory of Genetics, University of Wisconsin–Madison, Madison, WI, USA
| | - Kadee N. Lawrence
- Laboratory of Genetics, University of Wisconsin–Madison, Madison, WI, USA
| | - John E. Pool
- Laboratory of Genetics, University of Wisconsin–Madison, Madison, WI, USA
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Chen J, Liu C, Li W, Zhang W, Wang Y, Clark AG, Lu J. From sub-Saharan Africa to China: Evolutionary history and adaptation of Drosophila melanogaster revealed by population genomics. SCIENCE ADVANCES 2024; 10:eadh3425. [PMID: 38630810 PMCID: PMC11023512 DOI: 10.1126/sciadv.adh3425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Accepted: 03/13/2024] [Indexed: 04/19/2024]
Abstract
Drosophila melanogaster is a widely used model organism for studying environmental adaptation. However, the genetic diversity of populations in Asia is poorly understood, leaving a notable gap in our knowledge of the global evolution and adaptation of this species. We sequenced genomes of 292 D. melanogaster strains from various ecological settings in China and analyzed them along with previously published genome sequences. We have identified six global genetic ancestry groups, despite the presence of widespread genetic admixture. The strains from China represent a unique ancestry group, although detectable differentiation exists among populations within China. We deciphered the global migration and demography of D. melanogaster, and identified widespread signals of adaptation, including genetic changes in response to insecticides. We validated the effects of insecticide resistance variants using population cage trials and deep sequencing. This work highlights the importance of population genomics in understanding the genetic underpinnings of adaptation, an effort that is particularly relevant given the deterioration of ecosystems.
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Affiliation(s)
- Junhao Chen
- State Key Laboratory of Protein and Plant Gene Research, Center for Bioinformatics, School of Life Sciences, Peking University, Beijing 100871, China
| | - Chenlu Liu
- State Key Laboratory of Protein and Plant Gene Research, Center for Bioinformatics, School of Life Sciences, Peking University, Beijing 100871, China
| | - Weixuan Li
- State Key Laboratory of Protein and Plant Gene Research, Center for Bioinformatics, School of Life Sciences, Peking University, Beijing 100871, China
| | - Wenxia Zhang
- State Key Laboratory of Protein and Plant Gene Research, Center for Bioinformatics, School of Life Sciences, Peking University, Beijing 100871, China
| | - Yirong Wang
- College of Biology, Hunan University, Changsha 410082, China
| | - Andrew G. Clark
- Department of Molecular Biology and Genetics, Cornell University, Ithaca, NY 14853, USA
| | - Jian Lu
- State Key Laboratory of Protein and Plant Gene Research, Center for Bioinformatics, School of Life Sciences, Peking University, Beijing 100871, China
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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: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [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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8
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Arunkumar R, Zhou SO, Day JP, Bakare S, Pitton S, Zhang Y, Hsing CY, O’Boyle S, Pascual-Gil J, Clark B, Chandler RJ, Leitão AB, Jiggins FM. Natural selection has driven the recurrent loss of an immunity gene that protects Drosophila against a major natural parasite. Proc Natl Acad Sci U S A 2023; 120:e2211019120. [PMID: 37552757 PMCID: PMC10438844 DOI: 10.1073/pnas.2211019120] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2022] [Accepted: 06/26/2023] [Indexed: 08/10/2023] Open
Abstract
Polymorphisms in immunity genes can have large effects on susceptibility to infection. To understand the origins of this variation, we have investigated the genetic basis of resistance to the parasitoid wasp Leptopilina boulardi in Drosophila melanogaster. We found that increased expression of the gene lectin-24A after infection by parasitic wasps was associated with a faster cellular immune response and greatly increased rates of killing the parasite. lectin-24A encodes a protein that is strongly up-regulated in the fat body after infection and localizes to the surface of the parasite egg. In certain susceptible lines, a deletion upstream of the lectin-24A has largely abolished expression. Other mutations predicted to abolish the function of this gene have arisen recurrently in this gene, with multiple loss-of-expression alleles and premature stop codons segregating in natural populations. The frequency of these alleles varies greatly geographically, and in some southern African populations, natural selection has driven them near to fixation. We conclude that natural selection has favored the repeated loss of an important component of the immune system, suggesting that in some populations, a pleiotropic cost to lectin-24A expression outweighs the benefits of resistance.
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Affiliation(s)
- Ramesh Arunkumar
- Department of Genetics, School of Biological Sciences, University of Cambridge, Downing Street, CambridgeCB2 3EH, United Kingdom
| | - Shuyu Olivia Zhou
- Department of Genetics, School of Biological Sciences, University of Cambridge, Downing Street, CambridgeCB2 3EH, United Kingdom
| | - Jonathan P. Day
- Department of Genetics, School of Biological Sciences, University of Cambridge, Downing Street, CambridgeCB2 3EH, United Kingdom
| | - Sherifat Bakare
- Department of Genetics, School of Biological Sciences, University of Cambridge, Downing Street, CambridgeCB2 3EH, United Kingdom
- Department of Biochemical Sciences, School of Biosciences, University of Surrey, 388 Stag Hill, Guildford,GU2 7XH, United Kingdom
| | - Simone Pitton
- Department of Genetics, School of Biological Sciences, University of Cambridge, Downing Street, CambridgeCB2 3EH, United Kingdom
- Biosciences Department, Università degli Studi di Milano, Via Celoria 26, Milano, MI20133, Italy
| | - Yexin Zhang
- Department of Genetics, School of Biological Sciences, University of Cambridge, Downing Street, CambridgeCB2 3EH, United Kingdom
| | - Chi-Yun Hsing
- Department of Genetics, School of Biological Sciences, University of Cambridge, Downing Street, CambridgeCB2 3EH, United Kingdom
| | - Sinead O’Boyle
- Department of Genetics, School of Biological Sciences, University of Cambridge, Downing Street, CambridgeCB2 3EH, United Kingdom
- School of Biomolecular and Biomedical Science, University College Dublin, DublinD04 V1W8, Ireland
| | - Juan Pascual-Gil
- Department of Genetics, School of Biological Sciences, University of Cambridge, Downing Street, CambridgeCB2 3EH, United Kingdom
- Facultad de Ciencias, Universidad Autónoma de Madrid, C. Francisco Tomás y Valiente 7, 28049Madrid, Spain
| | - Belinda Clark
- Department of Genetics, School of Biological Sciences, University of Cambridge, Downing Street, CambridgeCB2 3EH, United Kingdom
| | - Rachael J. Chandler
- Department of Genetics, School of Biological Sciences, University of Cambridge, Downing Street, CambridgeCB2 3EH, United Kingdom
- Department of Biochemical Sciences, School of Biosciences, University of Surrey, 388 Stag Hill, Guildford,GU2 7XH, United Kingdom
| | - Alexandre B. Leitão
- Department of Genetics, School of Biological Sciences, University of Cambridge, Downing Street, CambridgeCB2 3EH, United Kingdom
| | - Francis M. Jiggins
- Department of Genetics, School of Biological Sciences, University of Cambridge, Downing Street, CambridgeCB2 3EH, United Kingdom
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9
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L Rocha J, Silva P, Santos N, Nakamura M, Afonso S, Qninba A, Boratynski Z, Sudmant PH, Brito JC, Nielsen R, Godinho R. North African fox genomes show signatures of repeated introgression and adaptation to life in deserts. Nat Ecol Evol 2023; 7:1267-1286. [PMID: 37308700 PMCID: PMC10527534 DOI: 10.1038/s41559-023-02094-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 04/26/2023] [Indexed: 06/14/2023]
Abstract
Elucidating the evolutionary process of animal adaptation to deserts is key to understanding adaptive responses to climate change. Here we generated 82 individual whole genomes of four fox species (genus Vulpes) inhabiting the Sahara Desert at different evolutionary times. We show that adaptation of new colonizing species to a hot arid environment has probably been facilitated by introgression and trans-species polymorphisms shared with older desert resident species, including a putatively adaptive 25 Mb genomic region. Scans for signatures of selection implicated genes affecting temperature perception, non-renal water loss and heat production in the recent adaptation of North African red foxes (Vulpes vulpes), after divergence from Eurasian populations approximately 78 thousand years ago. In the extreme desert specialists, Rueppell's fox (V. rueppellii) and fennec (V. zerda), we identified repeated signatures of selection in genes affecting renal water homeostasis supported by gene expression and physiological differences. Our study provides insights into the mechanisms and genetic underpinnings of a natural experiment of repeated adaptation to extreme conditions.
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Affiliation(s)
- Joana L Rocha
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, Universidade do Porto, Vairão, Portugal.
- Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, Porto, Portugal.
- BIOPOLIS Program in Genomics, Biodiversity and Land Planning, CIBIO, Campus de Vairão, Vairão, Portugal.
- Department of Integrative Biology and Department of Statistics, University of California Berkeley, Berkeley, CA, USA.
| | - Pedro Silva
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, Universidade do Porto, Vairão, Portugal
- Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, Porto, Portugal
- BIOPOLIS Program in Genomics, Biodiversity and Land Planning, CIBIO, Campus de Vairão, Vairão, Portugal
| | - Nuno Santos
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, Universidade do Porto, Vairão, Portugal
- BIOPOLIS Program in Genomics, Biodiversity and Land Planning, CIBIO, Campus de Vairão, Vairão, Portugal
| | - Mónia Nakamura
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, Universidade do Porto, Vairão, Portugal
- Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, Porto, Portugal
- BIOPOLIS Program in Genomics, Biodiversity and Land Planning, CIBIO, Campus de Vairão, Vairão, Portugal
| | - Sandra Afonso
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, Universidade do Porto, Vairão, Portugal
- BIOPOLIS Program in Genomics, Biodiversity and Land Planning, CIBIO, Campus de Vairão, Vairão, Portugal
| | - Abdeljebbar Qninba
- Laboratory of Geophysics and Natural Hazards, Geophysics, Natural Patrimony and Green Chemistry Research Center (GEOPAC), Institut Scientifique, Mohammed V University of Rabat, Rabat, Morocco
| | - Zbyszek Boratynski
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, Universidade do Porto, Vairão, Portugal
- BIOPOLIS Program in Genomics, Biodiversity and Land Planning, CIBIO, Campus de Vairão, Vairão, Portugal
| | - Peter H Sudmant
- Department of Integrative Biology and Department of Statistics, University of California Berkeley, Berkeley, CA, USA
- Center for Computational Biology, University of California, Berkeley, CA, USA
| | - José C Brito
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, Universidade do Porto, Vairão, Portugal
- Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, Porto, Portugal
- BIOPOLIS Program in Genomics, Biodiversity and Land Planning, CIBIO, Campus de Vairão, Vairão, Portugal
| | - Rasmus Nielsen
- Department of Integrative Biology and Department of Statistics, University of California Berkeley, Berkeley, CA, USA.
- Center for Computational Biology, University of California, Berkeley, CA, USA.
- Globe Institute, University of Copenhagen, Copenhagen, Denmark.
| | - Raquel Godinho
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, Universidade do Porto, Vairão, Portugal.
- Departamento de Biologia, Faculdade de Ciências, Universidade do Porto, Porto, Portugal.
- BIOPOLIS Program in Genomics, Biodiversity and Land Planning, CIBIO, Campus de Vairão, Vairão, Portugal.
- Department of Zoology, University of Johannesburg, Auckland Park, South Africa.
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10
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Caro-Consuegra R, Lucas-Sánchez M, Comas D, Bosch E. Identifying signatures of positive selection in human populations from North Africa. Sci Rep 2023; 13:8166. [PMID: 37210386 DOI: 10.1038/s41598-023-35312-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 05/16/2023] [Indexed: 05/22/2023] Open
Abstract
Because of its location, North Africa (NA) has witnessed continuous demographic movements with an impact on the genomes of present-day human populations. Genomic data describe a complex scenario with varying proportions of at least four main ancestry components: Maghrebi, Middle Eastern-, European-, and West-and-East-African-like. However, the footprint of positive selection in NA has not been studied. Here, we compile genome-wide genotyping data from 190 North Africans and individuals from surrounding populations, investigate for signatures of positive selection using allele frequencies and linkage disequilibrium-based methods and infer ancestry proportions to discern adaptive admixture from post-admixture selection events. Our results show private candidate genes for selection in NA involved in insulin processing (KIF5A), immune function (KIF5A, IL1RN, TLR3), and haemoglobin phenotypes (BCL11A). We also detect signatures of positive selection related to skin pigmentation (SLC24A5, KITLG), and immunity function (IL1R1, CD44, JAK1) shared with European populations and candidate genes associated with haemoglobin phenotypes (HPSE2, HBE1, HBG2), other immune-related (DOCK2) traits, and insulin processing (GLIS3) traits shared with West and East African populations. Finally, the SLC8A1 gene, which codifies for a sodium-calcium exchanger, was the only candidate identified under post-admixture selection in Western NA.
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Affiliation(s)
- Rocio Caro-Consuegra
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, 08003, Barcelona, Spain
| | - Marcel Lucas-Sánchez
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, 08003, Barcelona, Spain
| | - David Comas
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, 08003, Barcelona, Spain
| | - Elena Bosch
- Institut de Biologia Evolutiva (UPF-CSIC), Departament de Medicina i Ciències de la Vida, Universitat Pompeu Fabra, Parc de Recerca Biomèdica de Barcelona, 08003, Barcelona, Spain.
- Centro de Investigación Biomédica en Red de Salud Mental, Instituto de Salud Carlos III, 28029, Madrid, Spain.
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11
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Skovbjerg CK, Angra D, Robertson-Shersby-Harvie T, Kreplak J, Keeble-Gagnère G, Kaur S, Ecke W, Windhorst A, Nielsen LK, Schiemann A, Knudsen J, Gutierrez N, Tagkouli V, Fechete LI, Janss L, Stougaard J, Warsame A, Alves S, Khazaei H, Link W, Torres AM, O'Sullivan DM, Andersen SU. Genetic analysis of global faba bean diversity, agronomic traits and selection signatures. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2023; 136:114. [PMID: 37074596 PMCID: PMC10115707 DOI: 10.1007/s00122-023-04360-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 03/31/2023] [Indexed: 05/03/2023]
Abstract
KEY MESSAGE We identified marker-trait associations for key faba bean agronomic traits and genomic signatures of selection within a global germplasm collection. Faba bean (Vicia faba L.) is a high-protein grain legume crop with great potential for sustainable protein production. However, little is known about the genetics underlying trait diversity. In this study, we used 21,345 high-quality SNP markers to genetically characterize 2678 faba bean genotypes. We performed genome-wide association studies of key agronomic traits using a seven-parent-MAGIC population and detected 238 significant marker-trait associations linked to 12 traits of agronomic importance. Sixty-five of these were stable across multiple environments. Using a non-redundant diversity panel of 685 accessions from 52 countries, we identified three subpopulations differentiated by geographical origin and 33 genomic regions subjected to strong diversifying selection between subpopulations. We found that SNP markers associated with the differentiation of northern and southern accessions explained a significant proportion of agronomic trait variance in the seven-parent-MAGIC population, suggesting that some of these traits were targets of selection during breeding. Our findings point to genomic regions associated with important agronomic traits and selection, facilitating faba bean genomics-based breeding.
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Affiliation(s)
- Cathrine Kiel Skovbjerg
- Department of Molecular Biology and Genetics, Aarhus University, 8000, Aarhus, Denmark.
- Center for Quantitative Genetics and Genomics, Aarhus University, 8000, Aarhus, Denmark.
| | - Deepti Angra
- School of Agriculture, Policy and Development, University of Reading, Reading, UK
| | | | - Jonathan Kreplak
- Agroécologie, AgroSup Dijon, INRAE, Univ. Bourgogne, Univ. Bourgogne Franche-Comté, Dijon, France
| | | | - Sukhjiwan Kaur
- Agriculture Victoria, AgriBio, Centre for AgriBioscience, Bundoora, VIC, Australia
| | - Wolfgang Ecke
- Department of Crop Sciences, Georg-August-University, Göttingen, Germany
| | - Alex Windhorst
- Georg-August-Universität Göttingen, DNPW, Carl-Sprengel 1, Germany
| | | | | | | | - Natalia Gutierrez
- Área de Mejora Vegetal y Biotecnología, IFAPA Centro "Alameda del Obispo", Apdo 3092, 14080, Córdoba, Spain
| | - Vasiliki Tagkouli
- School of Agriculture, Policy and Development, University of Reading, Reading, UK
| | - Lavinia Ioana Fechete
- Department of Molecular Biology and Genetics, Aarhus University, 8000, Aarhus, Denmark
| | - Luc Janss
- Center for Quantitative Genetics and Genomics, Aarhus University, 8000, Aarhus, Denmark
| | - Jens Stougaard
- Department of Molecular Biology and Genetics, Aarhus University, 8000, Aarhus, Denmark
| | - Ahmed Warsame
- School of Agriculture, Policy and Development, University of Reading, Reading, UK
| | - Sheila Alves
- Crops Research, Teagasc, Oak Park, Carlow, Ireland
| | - Hamid Khazaei
- Production Systems, Natural Resources Institute Finland (Luke), Latokartanonkaari 9, 00790, Helsinki, Finland
| | - Wolfgang Link
- Georg-August-Universität Göttingen, DNPW, Carl-Sprengel 1, Germany
| | - Ana Maria Torres
- Área de Mejora Vegetal y Biotecnología, IFAPA Centro "Alameda del Obispo", Apdo 3092, 14080, Córdoba, Spain
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12
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Garcia OA, Arslanian K, Whorf D, Thariath S, Shriver M, Li JZ, Bigham AW. The Legacy of Infectious Disease Exposure on the Genomic Diversity of Indigenous Southern Mexicans. Genome Biol Evol 2023; 15:7023365. [PMID: 36726304 PMCID: PMC10016042 DOI: 10.1093/gbe/evad015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 12/19/2022] [Accepted: 01/25/2023] [Indexed: 02/03/2023] Open
Abstract
To characterize host risk factors for infectious disease in Mesoamerican populations, we interrogated 857,481 SNPs assayed using the Affymetrix 6.0 genotyping array for signatures of natural selection in immune response genes. We applied three statistical tests to identify signatures of natural selection: locus-specific branch length (LSBL), the cross-population extended haplotype homozygosity (XP-EHH), and the integrated haplotype score (iHS). Each of the haplotype tests (XP-EHH and iHS) were paired with LSBL and significance was determined at the 1% level. For the paired analyses, we identified 95 statistically significant windows for XP-EHH/LSBL and 63 statistically significant windows for iHS/LSBL. Among our top immune response loci, we found evidence of recent directional selection associated with the major histocompatibility complex (MHC) and the peroxisome proliferator-activated receptor gamma (PPAR-γ) signaling pathway. These findings illustrate that Mesoamerican populations' immunity has been shaped by exposure to infectious disease. As targets of selection, these variants are likely to encode phenotypes that manifest themselves physiologically and therefore may contribute to population-level variation in immune response. Our results shed light on past selective events influencing the host response to modern diseases, both pathogenic infection as well as autoimmune disorders.
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Affiliation(s)
- Obed A Garcia
- Department of Anthropology, University of Michigan, Ann Arbor, Michigan.,Department of Biomedical Data Science, Stanford University, Stanford, California
| | | | - Daniel Whorf
- College of Medicine, University of Illinois, Peoria, Illinois
| | - Serena Thariath
- Department of Anthropology, University of Tennessee, Knoxville, Tennessee
| | - Mark Shriver
- Department of Anthropology, Penn State University, State College, Pennsylvania
| | - Jun Z Li
- Department of Human Genetics, University of Michigan, Ann Arbor, Michigan
| | - Abigail W Bigham
- Department of Anthropology, University of California, Los Angeles, California
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13
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Li R, Gong M, Zhang X, Wang F, Liu Z, Zhang L, Yang Q, Xu Y, Xu M, Zhang H, Zhang Y, Dai X, Gao Y, Zhang Z, Fang W, Yang Y, Fu W, Cao C, Yang P, Ghanatsaman ZA, Negari NJ, Nanaei HA, Yue X, Song Y, Lan X, Deng W, Wang X, Pan C, Xiang R, Ibeagha-Awemu EM, Heslop-Harrison PJS, Rosen BD, Lenstra JA, Gan S, Jiang Y. A sheep pangenome reveals the spectrum of structural variations and their effects on tail phenotypes. Genome Res 2023; 33:463-477. [PMID: 37310928 PMCID: PMC10078295 DOI: 10.1101/gr.277372.122] [Citation(s) in RCA: 25] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Accepted: 02/21/2023] [Indexed: 03/29/2023]
Abstract
Structural variations (SVs) are a major contributor to genetic diversity and phenotypic variations, but their prevalence and functions in domestic animals are largely unexplored. Here we generated high-quality genome assemblies for 15 individuals from genetically diverse sheep breeds using Pacific Biosciences (PacBio) high-fidelity sequencing, discovering 130.3 Mb nonreference sequences, from which 588 genes were annotated. A total of 149,158 biallelic insertions/deletions, 6531 divergent alleles, and 14,707 multiallelic variations with precise breakpoints were discovered. The SV spectrum is characterized by an excess of derived insertions compared to deletions (94,422 vs. 33,571), suggesting recent active LINE expansions in sheep. Nearly half of the SVs display low to moderate linkage disequilibrium with surrounding single-nucleotide polymorphisms (SNPs) and most SVs cannot be tagged by SNP probes from the widely used ovine 50K SNP chip. We identified 865 population-stratified SVs including 122 SVs possibly derived in the domestication process among 690 individuals from sheep breeds worldwide. A novel 168-bp insertion in the 5' untranslated region (5' UTR) of HOXB13 is found at high frequency in long-tailed sheep. Further genome-wide association study and gene expression analyses suggest that this mutation is causative for the long-tail trait. In summary, we have developed a panel of high-quality de novo assemblies and present a catalog of structural variations in sheep. Our data capture abundant candidate functional variations that were previously unexplored and provide a fundamental resource for understanding trait biology in sheep.
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Affiliation(s)
- Ran Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Mian Gong
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Xinmiao Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Fei Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Zhenyu Liu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Lei Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Qimeng Yang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Yuan Xu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Mengsi Xu
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, Xinjiang 832000, China
| | - Huanhuan Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Yunfeng Zhang
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, Xinjiang 832000, China
| | - Xuelei Dai
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Yuanpeng Gao
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Zhuangbiao Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Wenwen Fang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Yuta Yang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Weiwei Fu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Chunna Cao
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Peng Yang
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, Xinjiang 832000, China
| | - Zeinab Amiri Ghanatsaman
- Department of Animal Science, Fars Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education & Extension Organization (AREEO), Shiraz 7155863511, Iran
| | | | | | - Xiangpeng Yue
- State Key Laboratory of Grassland Agro-ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730020, China
| | - Yuxuan Song
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Xianyong Lan
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Weidong Deng
- Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
| | - Xihong Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Chuanying Pan
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Ruidong Xiang
- Faculty of Veterinary & Agricultural Science, The University of Melbourne, Parkville, 3052 Victoria, Australia
| | - Eveline M Ibeagha-Awemu
- Sherbrooke Research and Development Centre, Agriculture and Agri-Food Canada, Sherbrooke, Quebec J1M 0C8, Canada
| | - Pat J S Heslop-Harrison
- Department of Genetics and Genome Biology, University of Leicester, Leicester LE1 7RH, United Kingdom
| | - Benjamin D Rosen
- Animal Genomics and Improvement Laboratory, USDA-ARS, Beltsville, Maryland 20705, USA
| | - Johannes A Lenstra
- Faculty of Veterinary Medicine, Utrecht University, Utrecht 3508 TD, The Netherlands
| | - Shangquan Gan
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, Xinjiang 832000, China;
- College of Coastal Agricultural Sciences, Guangdong Ocean University, Zhanjiang 524088, China
| | - Yu Jiang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China;
- Key Laboratory of Livestock Biology, Northwest A&F University, Yangling, Shaanxi 712100, China
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14
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Nielsen SV, Vaughn AH, Leppälä K, Landis MJ, Mailund T, Nielsen R. Bayesian inference of admixture graphs on Native American and Arctic populations. PLoS Genet 2023; 19:e1010410. [PMID: 36780565 PMCID: PMC9956672 DOI: 10.1371/journal.pgen.1010410] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 02/24/2023] [Accepted: 01/23/2023] [Indexed: 02/15/2023] Open
Abstract
Admixture graphs are mathematical structures that describe the ancestry of populations in terms of divergence and merging (admixing) of ancestral populations as a graph. An admixture graph consists of a graph topology, branch lengths, and admixture proportions. The branch lengths and admixture proportions can be estimated using numerous numerical optimization methods, but inferring the topology involves a combinatorial search for which no polynomial algorithm is known. In this paper, we present a reversible jump MCMC algorithm for sampling high-probability admixture graphs and show that this approach works well both as a heuristic search for a single best-fitting graph and for summarizing shared features extracted from posterior samples of graphs. We apply the method to 11 Native American and Siberian populations and exploit the shared structure of high-probability graphs to characterize the relationship between Saqqaq, Inuit, Koryaks, and Athabascans. Our analyses show that the Saqqaq is not a good proxy for the previously identified gene flow from Arctic people into the Na-Dene speaking Athabascans.
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Affiliation(s)
- Svend V. Nielsen
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
| | - Andrew H. Vaughn
- Center for Computational Biology, University of California Berkeley, Berkeley, California, United States of America
| | - Kalle Leppälä
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
- Research Unit of Mathematical Sciences, University of Oulu, Oulu, Finland
| | - Michael J. Landis
- Department of Biology, Washington University in St. Louis, St. Louis, Missouri, United States of America
| | - Thomas Mailund
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
| | - Rasmus Nielsen
- Departments of Integrative Biology and Statistics, University of California Berkeley, Berkeley, California, United States of America
- Center for GeoGenetics, University of Copenhagen, Copenhagen, Denmark
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15
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Bernal MA, Yule DL, Stott W, Evrard L, Dowling TE, Krabbenhoft TJ. Concordant patterns of morphological, stable isotope, and genetic variation in a recent ecological radiation (Salmonidae: Coregonus spp.). Mol Ecol 2022; 31:4495-4509. [PMID: 35785504 DOI: 10.1111/mec.16596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Revised: 04/11/2022] [Accepted: 05/04/2022] [Indexed: 11/28/2022]
Abstract
Groups of sympatric taxa with low inter-specific genetic differentiation, but considerable ecological differences, offer great opportunities to study the dynamics of divergence and speciation. This is the case of ciscoes (Coregonus spp.) in the Laurentian Great Lakes, which are characterized by a complex evolutionary history and are commonly described as having undergone an adaptive radiation. In this study, morphometrics, stable isotopes and transcriptome sequencing were used to study the relationships within the Coregonus artedi complex in western Lake Superior. We observed general concordance for morphological, ecological and genomic variation, but the latter was more taxonomically informative as it showed less overlap among species in multivariate space. Low levels of genetic differentiation were observed between individuals morphologically identified as C. hoyi and C. zenithicus, which could be evidence of incomplete lineage sorting or recent hybridization between the two groups. Transcriptome-based single nucleotide polymorphisms exhibited significant divergence for genes associated with vision, development, metabolism and immunity among species that occupy different habitats. This study highlights the importance of using an integrative approach when studying groups of taxa with a complex evolutionary history, as individual-level analyses of multiple independent datasets can provide a clearer picture of the patterns and processes associated with the origins of biodiversity.
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Affiliation(s)
- Moisés A Bernal
- Department of Biological Sciences, College of Science and Mathematics, Auburn University, Auburn, Alabama 36849, United States of America.,Department of Biological Sciences and RENEW Institute, University at Buffalo, Buffalo, NY 14260, United States of America
| | - Daniel L Yule
- U.S. Geological Survey, Great Lakes Science Center - Lake Superior Biological Station, 2800 Lake Shore Drive E., Ashland, WI 54806, United States of America
| | - Wendylee Stott
- Michigan State University CESU working for U.S. Geological Survey, Great Lakes Science Center, 1451 Green Road, Ann Arbor, MI 48105-2807, United States of America
| | - Lori Evrard
- U.S. Geological Survey, Great Lakes Science Center - Lake Superior Biological Station, 2800 Lake Shore Drive E., Ashland, WI 54806, United States of America
| | - Thomas E Dowling
- Wayne State University, Department of Biological Sciences, Detroit, Michigan, 48202, United States of America
| | - Trevor J Krabbenhoft
- Department of Biological Sciences and RENEW Institute, University at Buffalo, Buffalo, NY 14260, United States of America
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16
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Gopalan S, Smith SP, Korunes K, Hamid I, Ramachandran S, Goldberg A. Human genetic admixture through the lens of population genomics. Philos Trans R Soc Lond B Biol Sci 2022; 377:20200410. [PMID: 35430881 PMCID: PMC9014191 DOI: 10.1098/rstb.2020.0410] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Accepted: 03/24/2022] [Indexed: 12/13/2022] Open
Abstract
Over the past 50 years, geneticists have made great strides in understanding how our species' evolutionary history gave rise to current patterns of human genetic diversity classically summarized by Lewontin in his 1972 paper, 'The Apportionment of Human Diversity'. One evolutionary process that requires special attention in both population genetics and statistical genetics is admixture: gene flow between two or more previously separated source populations to form a new admixed population. The admixture process introduces ancestry-based structure into patterns of genetic variation within and between populations, which in turn influences the inference of demographic histories, identification of genetic targets of selection and prediction of complex traits. In this review, we outline some challenges for admixture population genetics, including limitations of applying methods designed for populations without recent admixture to the study of admixed populations. We highlight recent studies and methodological advances that aim to overcome such challenges, leveraging genomic signatures of admixture that occurred in the past tens of generations to gain insights into human history, natural selection and complex trait architecture. This article is part of the theme issue 'Celebrating 50 years since Lewontin's apportionment of human diversity'.
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Affiliation(s)
- Shyamalika Gopalan
- Department of Evolutionary Anthropology, Duke University, Durham, NC 27708, USA
| | - Samuel Pattillo Smith
- Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA
- Department of Ecology, Evolution and Organismal Biology, Brown University, Providence, RI 02912, USA
| | - Katharine Korunes
- Department of Evolutionary Anthropology, Duke University, Durham, NC 27708, USA
| | - Iman Hamid
- Department of Evolutionary Anthropology, Duke University, Durham, NC 27708, USA
| | - Sohini Ramachandran
- Center for Computational Molecular Biology, Brown University, Providence, RI 02912, USA
- Department of Ecology, Evolution and Organismal Biology, Brown University, Providence, RI 02912, USA
- Data Science Initiative, Brown University, Providence, RI 02912, USA
| | - Amy Goldberg
- Department of Evolutionary Anthropology, Duke University, Durham, NC 27708, USA
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17
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Childebayeva A, Rohrlach AB, Barquera R, Rivollat M, Aron F, Szolek A, Kohlbacher O, Nicklisch N, Alt KW, Gronenborn D, Meller H, Friederich S, Prüfer K, Deguilloux MF, Krause J, Haak W. Population Genetics and Signatures of Selection in Early Neolithic European Farmers. Mol Biol Evol 2022; 39:6586604. [PMID: 35578825 PMCID: PMC9171004 DOI: 10.1093/molbev/msac108] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Abstract
Human expansion in the course of the Neolithic transition in western Eurasia has been one of the major topics in ancient DNA research in the last 10 years. Multiple studies have shown that the spread of agriculture and animal husbandry from the Near East across Europe was accompanied by large-scale human expansions. Moreover, changes in subsistence and migration associated with the Neolithic transition have been hypothesized to involve genetic adaptation. Here, we present high quality genome-wide data from the Linear Pottery Culture site Derenburg-Meerenstieg II (DER) (N = 32 individuals) in Central Germany. Population genetic analyses show that the DER individuals carried predominantly Anatolian Neolithic-like ancestry and a very limited degree of local hunter-gatherer admixture, similar to other early European farmers. Increasing the Linear Pottery culture cohort size to ∼100 individuals allowed us to perform various frequency- and haplotype-based analyses to investigate signatures of selection associated with changes following the adoption of the Neolithic lifestyle. In addition, we developed a new method called Admixture-informed Maximum-likelihood Estimation for Selection Scans that allowed us test for selection signatures in an admixture-aware fashion. Focusing on the intersection of results from these selection scans, we identified various loci associated with immune function (JAK1, HLA-DQB1) and metabolism (LMF1, LEPR, SORBS1), as well as skin color (SLC24A5, CD82) and folate synthesis (MTHFR, NBPF3). Our findings shed light on the evolutionary pressures, such as infectious disease and changing diet, that were faced by the early farmers of Western Eurasia.
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Affiliation(s)
- Ainash Childebayeva
- Archaeogenetics Department, Max Planck Institute for the Science of Human History, Kahlaische Straße 10, D-07745 Jena, Germany.,Archaeogenetics Department, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany
| | - Adam Benjamin Rohrlach
- Archaeogenetics Department, Max Planck Institute for the Science of Human History, Kahlaische Straße 10, D-07745 Jena, Germany.,Archaeogenetics Department, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany.,ARC Centre of Excellence for Mathematical and Statistical Frontiers, School of Mathematical Sciences, The University of Adelaide, Adelaide, Australia
| | - Rodrigo Barquera
- Archaeogenetics Department, Max Planck Institute for the Science of Human History, Kahlaische Straße 10, D-07745 Jena, Germany.,Archaeogenetics Department, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany
| | - Maïté Rivollat
- Archaeogenetics Department, Max Planck Institute for the Science of Human History, Kahlaische Straße 10, D-07745 Jena, Germany.,Université de Bordeaux, CNRS, PACEA-UMR 5199, 33615 Pessac, France
| | - Franziska Aron
- Archaeogenetics Department, Max Planck Institute for the Science of Human History, Kahlaische Straße 10, D-07745 Jena, Germany
| | - András Szolek
- Applied Bioinformatics, Dept. of Computer Science, University of Tübingen, Tübingen, Germany.,Department of Immunology, Interfaculty Institute for Cell Biology, University of Tübingen, Tübingen, Germany
| | - Oliver Kohlbacher
- Applied Bioinformatics, Dept. of Computer Science, University of Tübingen, Tübingen, Germany.,Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany.,Translational Bioinformatics, University Hospital Tübingen, Tübingen, Germany.,Biomolecular Interactions, Max Planck Institute for Developmental Biology, Tübingen, Germany
| | - Nicole Nicklisch
- Center of Natural and Cultural Human History, Danube Private University, Krems-Stein, Austria.,State Office for Heritage Management and Archaeology Saxony-Anhalt - State Museum of Prehistory, Halle (Saale), Germany
| | - Kurt W Alt
- Center of Natural and Cultural Human History, Danube Private University, Krems-Stein, Austria.,State Office for Heritage Management and Archaeology Saxony-Anhalt - State Museum of Prehistory, Halle (Saale), Germany
| | - Detlef Gronenborn
- Römisch-Germanisches Zentralmuseum, Leibniz Research Institute for Archaeology, Ernst-Ludwig-Platz 2, 55116 Mainz, Germany
| | - Harald Meller
- State Office for Heritage Management and Archaeology Saxony-Anhalt - State Museum of Prehistory, Halle (Saale), Germany
| | - Susanne Friederich
- State Office for Heritage Management and Archaeology Saxony-Anhalt - State Museum of Prehistory, Halle (Saale), Germany
| | - Kay Prüfer
- Archaeogenetics Department, Max Planck Institute for the Science of Human History, Kahlaische Straße 10, D-07745 Jena, Germany.,Archaeogenetics Department, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany
| | | | - Johannes Krause
- Archaeogenetics Department, Max Planck Institute for the Science of Human History, Kahlaische Straße 10, D-07745 Jena, Germany.,Archaeogenetics Department, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany
| | - Wolfgang Haak
- Archaeogenetics Department, Max Planck Institute for the Science of Human History, Kahlaische Straße 10, D-07745 Jena, Germany.,Archaeogenetics Department, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany
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18
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Aganezov S, Yan SM, Soto DC, Kirsche M, Zarate S, Avdeyev P, Taylor DJ, Shafin K, Shumate A, Xiao C, Wagner J, McDaniel J, Olson ND, Sauria MEG, Vollger MR, Rhie A, Meredith M, Martin S, Lee J, Koren S, Rosenfeld JA, Paten B, Layer R, Chin CS, Sedlazeck FJ, Hansen NF, Miller DE, Phillippy AM, Miga KH, McCoy RC, Dennis MY, Zook JM, Schatz MC. A complete reference genome improves analysis of human genetic variation. Science 2022; 376:eabl3533. [PMID: 35357935 PMCID: PMC9336181 DOI: 10.1126/science.abl3533] [Citation(s) in RCA: 149] [Impact Index Per Article: 74.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Compared to its predecessors, the Telomere-to-Telomere CHM13 genome adds nearly 200 million base pairs of sequence, corrects thousands of structural errors, and unlocks the most complex regions of the human genome for clinical and functional study. We show how this reference universally improves read mapping and variant calling for 3202 and 17 globally diverse samples sequenced with short and long reads, respectively. We identify hundreds of thousands of variants per sample in previously unresolved regions, showcasing the promise of the T2T-CHM13 reference for evolutionary and biomedical discovery. Simultaneously, this reference eliminates tens of thousands of spurious variants per sample, including reduction of false positives in 269 medically relevant genes by up to a factor of 12. Because of these improvements in variant discovery coupled with population and functional genomic resources, T2T-CHM13 is positioned to replace GRCh38 as the prevailing reference for human genetics.
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Affiliation(s)
- Sergey Aganezov
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Stephanie M. Yan
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Daniela C. Soto
- Department of Biochemistry and Molecular Medicine, Genome Center, MIND Institute, University of California, Davis, CA, USA
| | - Melanie Kirsche
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Samantha Zarate
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - Pavel Avdeyev
- Genome Informatics Section, National Human Genome Research Institute, Bethesda, MD, USA
| | - Dylan J. Taylor
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Kishwar Shafin
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Alaina Shumate
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Chunlin Xiao
- National Center for Biotechnology Information, National Library of Medicine, Bethesda, MD, USA
| | - Justin Wagner
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Jennifer McDaniel
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Nathan D. Olson
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | | | | | - Arang Rhie
- Genome Informatics Section, National Human Genome Research Institute, Bethesda, MD, USA
| | - Melissa Meredith
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Skylar Martin
- Department of Computer Science and Biofrontiers Institute, University of Colorado, Boulder, CO, USA
| | - Joyce Lee
- Bionano Genomics, San Diego, CA, USA
| | - Sergey Koren
- Genome Informatics Section, National Human Genome Research Institute, Bethesda, MD, USA
| | | | - Benedict Paten
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Ryan Layer
- Department of Computer Science and Biofrontiers Institute, University of Colorado, Boulder, CO, USA
| | | | - Fritz J. Sedlazeck
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Nancy F. Hansen
- Comparative Genomics Analysis Unit, National Human Genome Research Institute, Rockville, MD, USA
| | - Danny E. Miller
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Department of Pediatrics, Division of Genetic Medicine, University of Washington and Seattle Children’s Hospital, Seattle, WA, USA
| | - Adam M. Phillippy
- Genome Informatics Section, National Human Genome Research Institute, Bethesda, MD, USA
| | - Karen H. Miga
- UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA
| | - Rajiv C. McCoy
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Megan Y. Dennis
- Department of Biochemistry and Molecular Medicine, Genome Center, MIND Institute, University of California, Davis, CA, USA
| | - Justin M. Zook
- National Institute of Standards and Technology, Gaithersburg, MD, USA
| | - Michael C. Schatz
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
- Department of Biology, Johns Hopkins University, Baltimore, MD, USA
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
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19
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Chen ZH, Xu YX, Xie XL, Wang DF, Aguilar-Gómez D, Liu GJ, Li X, Esmailizadeh A, Rezaei V, Kantanen J, Ammosov I, Nosrati M, Periasamy K, Coltman DW, Lenstra JA, Nielsen R, Li MH. Whole-genome sequence analysis unveils different origins of European and Asiatic mouflon and domestication-related genes in sheep. Commun Biol 2021; 4:1307. [PMID: 34795381 PMCID: PMC8602413 DOI: 10.1038/s42003-021-02817-4] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Accepted: 10/27/2021] [Indexed: 02/06/2023] Open
Abstract
The domestication and subsequent development of sheep are crucial events in the history of human civilization and the agricultural revolution. However, the impact of interspecific introgression on the genomic regions under domestication and subsequent selection remains unclear. Here, we analyze the whole genomes of domestic sheep and their wild relative species. We found introgression from wild sheep such as the snow sheep and its American relatives (bighorn and thinhorn sheep) into urial, Asiatic and European mouflons. We observed independent events of adaptive introgression from wild sheep into the Asiatic and European mouflons, as well as shared introgressed regions from both snow sheep and argali into Asiatic mouflon before or during the domestication process. We revealed European mouflons might arise through hybridization events between a now extinct sheep in Europe and feral domesticated sheep around 6000-5000 years BP. We also unveiled later introgressions from wild sheep to their sympatric domestic sheep after domestication. Several of the introgression events contain loci with candidate domestication genes (e.g., PAPPA2, NR6A1, SH3GL3, RFX3 and CAMK4), associated with morphological, immune, reproduction or production traits (wool/meat/milk). We also detected introgression events that introduced genes related to nervous response (NEURL1), neurogenesis (PRUNE2), hearing ability (USH2A), and placental viability (PAG11 and PAG3) into domestic sheep and their ancestral wild species from other wild species.
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Affiliation(s)
- Ze-Hui Chen
- grid.9227.e0000000119573309CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, China ,grid.410726.60000 0004 1797 8419University of Chinese Academy of Sciences (UCAS), Beijing, China ,grid.22935.3f0000 0004 0530 8290College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Ya-Xi Xu
- grid.22935.3f0000 0004 0530 8290College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Xing-Long Xie
- grid.9227.e0000000119573309CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, China ,grid.410726.60000 0004 1797 8419University of Chinese Academy of Sciences (UCAS), Beijing, China
| | - Dong-Feng Wang
- grid.9227.e0000000119573309CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, China ,grid.410726.60000 0004 1797 8419University of Chinese Academy of Sciences (UCAS), Beijing, China
| | - Diana Aguilar-Gómez
- grid.47840.3f0000 0001 2181 7878Center for Computational Biology, University of California at Berkeley, Berkeley, CA 94720 USA
| | | | - Xin Li
- grid.9227.e0000000119573309CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, China ,grid.410726.60000 0004 1797 8419University of Chinese Academy of Sciences (UCAS), Beijing, China
| | - Ali Esmailizadeh
- grid.412503.10000 0000 9826 9569Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran
| | - Vahideh Rezaei
- grid.412503.10000 0000 9826 9569Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran
| | - Juha Kantanen
- grid.22642.300000 0004 4668 6757Natural Resources Institute Finland (Luke), Jokioinen, Finland
| | - Innokentyi Ammosov
- grid.495192.2Laboratory of Reindeer Husbandry and Traditional Industries, Yakut Scientific Research Institute of Agriculture, The Sakha Republic (Yakutia), Yakutsk, Russia
| | - Maryam Nosrati
- grid.412462.70000 0000 8810 3346Department of Agriculture, Payame Noor University, Tehran, Iran
| | - Kathiravan Periasamy
- grid.420221.70000 0004 0403 8399Animal Production and Health Laboratory, Joint FAO/IAEA Division of Nuclear Techniques in Food and Agriculture, International Atomic Energy Agency, Vienna, Austria
| | - David W. Coltman
- grid.17089.37Department of Biological Sciences, University of Alberta, Edmonton, AB T6G2E9 Canada
| | - Johannes A. Lenstra
- grid.5477.10000000120346234Faculty of Veterinary Medicine, Utrecht University, Utrecht, the Netherlands
| | - Rasmus Nielsen
- Department of Integrative Biology, University of California at Berkeley, Berkeley, CA, 94720, USA. .,Department of Statistics, UC Berkeley, Berkeley, CA, 94707, USA. .,Globe Institute, University of Copenhagen, 1350, København K, Denmark.
| | - Meng-Hua Li
- College of Animal Science and Technology, China Agricultural University, Beijing, China.
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