1
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Skuladottir AT, Tragante V, Sveinbjornsson G, Helgason H, Sturluson A, Bjornsdottir A, Jonsson P, Palmadottir V, Sveinsson OA, Jensson BO, Gudjonsson SA, Ivarsdottir EV, Gisladottir RS, Gunnarsson AF, Walters GB, Jonsdottir GA, Thorgeirsson TE, Bjornsdottir G, Holm H, Gudbjartsson DF, Sulem P, Stefansson H, Stefansson K. Loss-of-function variants in ITSN1 confer high risk of Parkinson's disease. NPJ Parkinsons Dis 2024; 10:140. [PMID: 39147844 PMCID: PMC11327306 DOI: 10.1038/s41531-024-00752-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Accepted: 07/12/2024] [Indexed: 08/17/2024] Open
Abstract
Parkinson's disease (PD) is a debilitating neurodegenerative disorder and its rising global incidence highlights the need for the identification of modifiable risk factors. In a gene-based burden test of rare variants (8647 PD cases and 777,693 controls) we discovered a novel association between loss-of-function variants in ITSN1 and PD. This association was further supported with burden data from the Neurodegenerative Disease Knowledge Portal and the Accelerating Medicines Partnership Parkinson's Disease Knowledge Platform. Our findings show that Rho GTPases and disruptions in synaptic vesicle transport may be involved in the pathogenesis of PD, pointing to the possibility of novel therapeutic approaches.
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Affiliation(s)
- Astros Th Skuladottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland.
| | | | | | | | | | | | - Palmi Jonsson
- Department of Geriatric Medicine, Landspitali University Hospital, Reykjavik, Iceland
| | - Vala Palmadottir
- Department of Internal Medicine, Landspitali University Hospital, Reykjavik, Iceland
| | | | | | | | | | - Rosa S Gisladottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Icelandic and Comparative Cultural Studies, University of Iceland, Reykjavik, Iceland
| | | | | | | | | | | | - Hilma Holm
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
| | - Daniel F Gudbjartsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | - Kari Stefansson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland.
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2
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Stefansson OA, Sigurpalsdottir BD, Rognvaldsson S, Halldorsson GH, Juliusson K, Sveinbjornsson G, Gunnarsson B, Beyter D, Jonsson H, Gudjonsson SA, Olafsdottir TA, Saevarsdottir S, Magnusson MK, Lund SH, Tragante V, Oddsson A, Hardarson MT, Eggertsson HP, Gudmundsson RL, Sverrisson S, Frigge ML, Zink F, Holm H, Stefansson H, Rafnar T, Jonsdottir I, Sulem P, Helgason A, Gudbjartsson DF, Halldorsson BV, Thorsteinsdottir U, Stefansson K. The correlation between CpG methylation and gene expression is driven by sequence variants. Nat Genet 2024; 56:1624-1631. [PMID: 39048797 PMCID: PMC11319203 DOI: 10.1038/s41588-024-01851-2] [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: 04/13/2022] [Accepted: 06/27/2024] [Indexed: 07/27/2024]
Abstract
Gene promoter and enhancer sequences are bound by transcription factors and are depleted of methylated CpG sites (cytosines preceding guanines in DNA). The absence of methylated CpGs in these sequences typically correlates with increased gene expression, indicating a regulatory role for methylation. We used nanopore sequencing to determine haplotype-specific methylation rates of 15.3 million CpG units in 7,179 whole-blood genomes. We identified 189,178 methylation depleted sequences where three or more proximal CpGs were unmethylated on at least one haplotype. A total of 77,789 methylation depleted sequences (~41%) associated with 80,503 cis-acting sequence variants, which we termed allele-specific methylation quantitative trait loci (ASM-QTLs). RNA sequencing of 896 samples from the same blood draws used to perform nanopore sequencing showed that the ASM-QTL, that is, DNA sequence variability, drives most of the correlation found between gene expression and CpG methylation. ASM-QTLs were enriched 40.2-fold (95% confidence interval 32.2, 49.9) among sequence variants associating with hematological traits, demonstrating that ASM-QTLs are important functional units in the noncoding genome.
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Affiliation(s)
| | - Brynja Dogg Sigurpalsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Technology, Reykjavik University, Reykjavik, Iceland
| | | | - Gisli Hreinn Halldorsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | | | | | | | - Thorunn Asta Olafsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Saedis Saevarsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Magnus Karl Magnusson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Sigrun Helga Lund
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | - Marteinn Thor Hardarson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Technology, Reykjavik University, Reykjavik, Iceland
| | | | | | | | | | | | - Hilma Holm
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
| | | | | | - Ingileif Jonsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | | | - Agnar Helgason
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Department of Anthropology, University of Iceland, Reykjavik, Iceland
| | - Daniel F Gudbjartsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Bjarni V Halldorsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Technology, Reykjavik University, Reykjavik, Iceland
| | - Unnur Thorsteinsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Kari Stefansson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland.
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3
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Styrkarsdottir U, Tragante V, Stefansdottir L, Thorleifsson G, Oddsson A, Sørensen E, Erikstrup C, Schwarz P, Jørgensen HL, Lauritzen JB, Brunak S, Knowlton KU, Nadauld LD, Ullum H, Pedersen OBV, Ostrowski SR, Holm H, Gudbjartsson DF, Sulem P, Stefansson K. Obesity Variants in the GIPR Gene Are not Associated With Risk of Fracture or Bone Mineral Density. J Clin Endocrinol Metab 2024; 109:e1608-e1615. [PMID: 38118020 PMCID: PMC11244190 DOI: 10.1210/clinem/dgad734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 12/07/2023] [Accepted: 12/12/2023] [Indexed: 12/22/2023]
Abstract
CONTEXT It is not clear if antagonizing the GIP (glucose-dependent insulinotropic polypeptide) receptor (GIPR) for treatment of obesity is likely to increase the risk of fractures, or to lower bone mineral density (BMD) beyond what is expected with rapid weight loss. OBJECTIVE The objective of this study was to investigate the risk of fracture and BMD of sequence variants in GIPR that reduce the activity of the GIP receptor and have been associated with reduced body mass index (BMI). METHODS We analyzed the association of 3 missense variants in GIPR, a common variant, rs1800437 (p.Glu354Gln), and 2 rare variants, rs139215588 (p.Arg190Gln) and rs143430880 (p.Glu288Gly), as well as a burden of predicted loss-of-function (LoF) variants with risk of fracture and with BMD in a large meta-analysis of up to 1.2 million participants. We analyzed associations with fractures at different skeletal sites in the general population: any fractures, hip fractures, vertebral fractures and forearm fractures, and specifically nonvertebral and osteoporotic fractures in postmenopausal women. We also evaluated associations with BMD at the lumbar spine, femoral neck, and total body measured with dual-energy x-ray absorptiometry (DXA), and with BMD estimated from heel ultrasound (eBMD). RESULTS None of the 3 missense variants in GIPR was significantly associated with increased risk of fractures or with lower BMD. Burden of LoF variants in GIPR was not associated with fractures or with BMD measured with clinically validated DXA, but was associated with eBMD. CONCLUSION Missense variants in GIPR, or burden of LoF variants in the gene, are not associated with risk of fractures or with lower BMD.
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Affiliation(s)
| | - Vinicius Tragante
- Population Genomics, deCODE genetics/Amgen Inc, Reykjavik 102, Iceland
| | | | | | - Asmundur Oddsson
- Population Genomics, deCODE genetics/Amgen Inc, Reykjavik 102, Iceland
| | - Erik Sørensen
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen 2100, Denmark
| | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus 8200, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus 8200, Denmark
| | - Peter Schwarz
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
- Department of Endocrinology, Copenhagen University Hospital, Rigshospitalet, Copenhagen 2100, Denmark
| | - Henrik Løvendahl Jørgensen
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
- Department of Clinical Biochemistry, Amager Hvidovre Hospital, Copenhagen 2650, Denmark
| | - Jes Bruun Lauritzen
- Department of Orthopedic Surgery, Bispebjerg Hospital, University of Copenhagen, Copenhagen 2400, Denmark
| | - Søren Brunak
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen 2200, Denmark
| | - Kirk U Knowlton
- Intermountain Health, Heart Institute, Salt Lake City, UT 84143, USA
| | | | - Henrik Ullum
- Statens Serum Institut, Copenhagen 2300, Denmark
| | - Ole Birger Vesterager Pedersen
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
- Department of Clinical Immunology, Zealand University Hospital, Køge 4600, Denmark
| | - Sisse Rye Ostrowski
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen 2100, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Hilma Holm
- Population Genomics, deCODE genetics/Amgen Inc, Reykjavik 102, Iceland
| | - Daniel F Gudbjartsson
- Population Genomics, deCODE genetics/Amgen Inc, Reykjavik 102, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik 102, Iceland
| | - Patrick Sulem
- Population Genomics, deCODE genetics/Amgen Inc, Reykjavik 102, Iceland
| | - Kari Stefansson
- Population Genomics, deCODE genetics/Amgen Inc, Reykjavik 102, Iceland
- Faculty of Medicine, School of Health Science, University of Iceland, Reykjavik 102, Iceland
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4
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Saevarsdottir S, Bjarnadottir K, Markusson T, Berglund J, Olafsdottir TA, Halldorsson GH, Rutsdottir G, Gunnarsdottir K, Arnthorsson AO, Lund SH, Stefansdottir L, Gudmundsson J, Johannesson AJ, Sturluson A, Oddsson A, Halldorsson B, Ludviksson BR, Ferkingstad E, Ivarsdottir EV, Sveinbjornsson G, Grondal G, Masson G, Eldjarn GH, Thorisson GA, Kristjansdottir K, Knowlton KU, Moore KHS, Gudjonsson SA, Rognvaldsson S, Knight S, Nadauld LD, Holm H, Magnusson OT, Sulem P, Gudbjartsson DF, Rafnar T, Thorleifsson G, Melsted P, Norddahl GL, Jonsdottir I, Stefansson K. Start codon variant in LAG3 is associated with decreased LAG-3 expression and increased risk of autoimmune thyroid disease. Nat Commun 2024; 15:5748. [PMID: 38982041 PMCID: PMC11233504 DOI: 10.1038/s41467-024-50007-7] [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: 09/15/2023] [Accepted: 06/27/2024] [Indexed: 07/11/2024] Open
Abstract
Autoimmune thyroid disease (AITD) is a common autoimmune disease. In a GWAS meta-analysis of 110,945 cases and 1,084,290 controls, 290 sequence variants at 225 loci are associated with AITD. Of these variants, 115 are previously unreported. Multiomics analysis yields 235 candidate genes outside the MHC-region and the findings highlight the importance of genes involved in T-cell regulation. A rare 5'-UTR variant (rs781745126-T, MAF = 0.13% in Iceland) in LAG3 has the largest effect (OR = 3.42, P = 2.2 × 10-16) and generates a novel start codon for an open reading frame upstream of the canonical protein translation initiation site. rs781745126-T reduces mRNA and surface expression of the inhibitory immune checkpoint LAG-3 co-receptor on activated lymphocyte subsets and halves LAG-3 levels in plasma among heterozygotes. All three homozygous carriers of rs781745126-T have AITD, of whom one also has two other T-cell mediated diseases, that is vitiligo and type 1 diabetes. rs781745126-T associates nominally with vitiligo (OR = 5.1, P = 6.5 × 10-3) but not with type 1 diabetes. Thus, the effect of rs781745126-T is akin to drugs that inhibit LAG-3, which unleash immune responses and can have thyroid dysfunction and vitiligo as adverse events. This illustrates how a multiomics approach can reveal potential drug targets and safety concerns.
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Affiliation(s)
- Saedis Saevarsdottir
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland.
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland.
- Department of Medicine, Landspitali, the National University Hospital of Iceland, Reykjavik, Iceland.
| | | | - Thorsteinn Markusson
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | | | - Thorunn A Olafsdottir
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Gisli H Halldorsson
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Gudrun Rutsdottir
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | | | | | - Ari J Johannesson
- Department of Medicine, Landspitali, the National University Hospital of Iceland, Reykjavik, Iceland
| | | | | | | | - Björn R Ludviksson
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
- Department of Immunology, Landspitali, the National University Hospital of Iceland, Reykjavik, Iceland
| | | | - Erna V Ivarsdottir
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | - Gerdur Grondal
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
- Department of Medicine, Landspitali, the National University Hospital of Iceland, Reykjavik, Iceland
| | | | | | | | | | - Kirk U Knowlton
- Intermountain Medical Center, Intermountain Heart Institute, Salt Lake City, UT, USA
- School of Medicine, University of Utah, Salt Lake City, UT, USA
| | | | | | | | - Stacey Knight
- Intermountain Medical Center, Intermountain Heart Institute, Salt Lake City, UT, USA
| | | | - Hilma Holm
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland
| | | | | | - Daniel F Gudbjartsson
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | - Pall Melsted
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | - Ingileif Jonsdottir
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
- Department of Immunology, Landspitali, the National University Hospital of Iceland, Reykjavik, Iceland
| | - Kari Stefansson
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland.
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland.
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5
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Tavakoli N, Gibney D, Aluru S. GraphSlimmer: Preserving Read Mappability with the Minimum Number of Variants. J Comput Biol 2024; 31:616-637. [PMID: 38990757 DOI: 10.1089/cmb.2024.0601] [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] [Indexed: 07/13/2024] Open
Abstract
Modern genomic datasets, like those generated under the 1000 Genome Project, contain millions of variants belonging to known haplotypes. Although these datasets are more representative than a single reference sequence and can alleviate issues like reference bias, they are significantly more computationally burdensome to work with, often involving large-indexed genome graph data structures for tasks such as read mapping. The construction, preprocessing, and mapping algorithms can require substantial computational resources depending on the size of these variant sets. Moreover, the accuracy of mapping algorithms has been shown to decrease when working with complete variant sets. Therefore, a drastically reduced set of variants that preserves important properties of the original set is desirable. This work provides a technique for finding a minimal subset of variants S such that for given parameters α and δ, all substrings up to length α in the haplotypes are guaranteed to be still alignable to the appropriate locations with either Hamming or edit distance at most δ, using only S . Our contributions include showing the NP-hardness and inapproximability of these optimization problems and providing Integer Linear Programming (ILP) formulations. Our edit distance ILP formulation carefully decomposes the problem according to variant locations, which allows it to scale to support all of chromosome 22's variants from the 1000 Genome Project. Our experiments also demonstrate a significant reduction in the number of variants. For example, for moderately long reads, e.g., α = 1000, over 75% of the variants can be removed while preserving read mappability with edit distance at most one.
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Affiliation(s)
- Neda Tavakoli
- School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Gxeorgia, USA
| | - Daniel Gibney
- Department of Computer Science, University of Texas at Dallas, Richardson, Texas, USA
| | - Srinivas Aluru
- School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Gxeorgia, USA
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6
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Wertenbroek R, Hofmeister RJ, Xenarios I, Thoma Y, Delaneau O. Improving population scale statistical phasing with whole-genome sequencing data. PLoS Genet 2024; 20:e1011092. [PMID: 38959269 PMCID: PMC11251608 DOI: 10.1371/journal.pgen.1011092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 07/16/2024] [Accepted: 06/11/2024] [Indexed: 07/05/2024] Open
Abstract
Haplotype estimation, or phasing, has gained significant traction in large-scale projects due to its valuable contributions to population genetics, variant analysis, and the creation of reference panels for imputation and phasing of new samples. To scale with the growing number of samples, haplotype estimation methods designed for population scale rely on highly optimized statistical models to phase genotype data, and usually ignore read-level information. Statistical methods excel in resolving common variants, however, they still struggle at rare variants due to the lack of statistical information. In this study we introduce SAPPHIRE, a new method that leverages whole-genome sequencing data to enhance the precision of haplotype calls produced by statistical phasing. SAPPHIRE achieves this by refining haplotype estimates through the realignment of sequencing reads, particularly targeting low-confidence phase calls. Our findings demonstrate that SAPPHIRE significantly enhances the accuracy of haplotypes obtained from state of the art methods and also provides the subset of phase calls that are validated by sequencing reads. Finally, we show that our method scales to large data sets by its successful application to the extensive 3.6 Petabytes of sequencing data of the last UK Biobank 200,031 sample release.
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Affiliation(s)
- Rick Wertenbroek
- University of Lausanne, Lausanne, Vaud, Switzerland
- School of Engineering and Management Vaud (HEIG-VD), HES-SO University of Applied Sciences and Arts Western Switzerland, Yverdon-les-Bains, Vaud, Switzerland
| | | | | | - Yann Thoma
- School of Engineering and Management Vaud (HEIG-VD), HES-SO University of Applied Sciences and Arts Western Switzerland, Yverdon-les-Bains, Vaud, Switzerland
| | - Olivier Delaneau
- Regeneron Genetics Center, Tarrytown, New York, United States of America
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7
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Erven JAM, Scheu A, Verdugo MP, Cassidy L, Chen N, Gehlen B, Street M, Madsen O, Mullin VE. A High-Coverage Mesolithic Aurochs Genome and Effective Leveraging of Ancient Cattle Genomes Using Whole Genome Imputation. Mol Biol Evol 2024; 41:msae076. [PMID: 38662789 PMCID: PMC11090068 DOI: 10.1093/molbev/msae076] [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: 01/24/2024] [Revised: 04/05/2024] [Accepted: 04/09/2024] [Indexed: 05/14/2024] Open
Abstract
Ancient genomic analyses are often restricted to utilizing pseudohaploid data due to low genome coverage. Leveraging low-coverage data by imputation to calculate phased diploid genotypes that enables haplotype-based interrogation and single nucleotide polymorphism (SNP) calling at unsequenced positions is highly desirable. This has not been investigated for ancient cattle genomes despite these being compelling subjects for archeological, evolutionary, and economic reasons. Here, we test this approach by sequencing a Mesolithic European aurochs (18.49×; 9,852 to 9,376 calBCE) and an Early Medieval European cow (18.69×; 427 to 580 calCE) and combine these with published individuals: two ancient and three modern. We downsample these genomes (0.25×, 0.5×, 1.0×, and 2.0×) and impute diploid genotypes, utilizing a reference panel of 171 published modern cattle genomes that we curated for 21.7 million (Mn) phased SNPs. We recover high densities of correct calls with an accuracy of >99.1% at variant sites for the lowest downsample depth of 0.25×, increasing to >99.5% for 2.0× (transversions only, minor allele frequency [MAF] ≥ 2.5%). The recovery of SNPs correlates with coverage; on average, 58% of sites are recovered for 0.25× increasing to 87% for 2.0×, utilizing an average of 3.5 million (Mn) transversions (MAF ≥2.5%), even in the aurochs, despite the highest temporal distance from the modern reference panel. Our imputed genomes behave similarly to directly called data in allele frequency-based analyses, for example consistently identifying runs of homozygosity >2 Mb, including a long homozygous region in the Mesolithic European aurochs.
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Affiliation(s)
- Jolijn A M Erven
- Groningen Institute of Archaeology, University of Groningen, Groningen, The Netherlands
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin D02 PN40, Ireland
| | - Amelie Scheu
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin D02 PN40, Ireland
- Palaeogenetics Group, Institute of Organismic and Molecular Evolution (iOME), Johannes Gutenberg-University Mainz, 55099 Mainz, Germany
| | | | - Lara Cassidy
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin D02 PN40, Ireland
| | - Ningbo Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Birgit Gehlen
- Institute for Prehistory and Protohistory, University of Cologne, 50931 Cologne, Germany
| | - Martin Street
- LEIZA, Archaeological Research Centre and Museum for Human Behavioural Evolution, Schloss Monrepos, D - 56567 Neuwied, Germany
| | - Ole Madsen
- Animal Breeding and Genomics, Wageningen University and Research, Wageningen, The Netherlands
| | - Victoria E Mullin
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin D02 PN40, Ireland
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8
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Choi S, Kang JG, Tran YTH, Jeong SH, Park KY, Shin H, Kim YH, Park M, Nahmgoong H, Seol T, Jeon H, Kim Y, Park S, Kim HJ, Kim MS, Li X, Bou Sleiman M, Lee E, Choi J, Eisenbarth D, Lee SH, Cho S, Moore DD, Auwerx J, Kim IY, Kim JB, Park JE, Lim DS, Suh JM. Hippo-YAP/TAZ signalling coordinates adipose plasticity and energy balance by uncoupling leptin expression from fat mass. Nat Metab 2024; 6:847-860. [PMID: 38811804 PMCID: PMC11136666 DOI: 10.1038/s42255-024-01045-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Accepted: 04/10/2024] [Indexed: 05/31/2024]
Abstract
Adipose tissues serve as an energy reservoir and endocrine organ, yet the mechanisms that coordinate these functions remain elusive. Here, we show that the transcriptional coregulators, YAP and TAZ, uncouple fat mass from leptin levels and regulate adipocyte plasticity to maintain metabolic homeostasis. Activating YAP/TAZ signalling in adipocytes by deletion of the upstream regulators Lats1 and Lats2 results in a profound reduction in fat mass by converting mature adipocytes into delipidated progenitor-like cells, but does not cause lipodystrophy-related metabolic dysfunction, due to a paradoxical increase in circulating leptin levels. Mechanistically, we demonstrate that YAP/TAZ-TEAD signalling upregulates leptin expression by directly binding to an upstream enhancer site of the leptin gene. We further show that YAP/TAZ activity is associated with, and functionally required for, leptin regulation during fasting and refeeding. These results suggest that adipocyte Hippo-YAP/TAZ signalling constitutes a nexus for coordinating adipose tissue lipid storage capacity and systemic energy balance through the regulation of adipocyte plasticity and leptin gene transcription.
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Affiliation(s)
- Sungwoo Choi
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
- National Creative Research Center for Cell Plasticity, KAIST Stem Cell Center, Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
| | - Ju-Gyeong Kang
- National Creative Research Center for Cell Plasticity, KAIST Stem Cell Center, Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
| | - Yen T H Tran
- National Creative Research Center for Cell Plasticity, KAIST Stem Cell Center, Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
| | - Sun-Hye Jeong
- National Creative Research Center for Cell Plasticity, KAIST Stem Cell Center, Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
| | - Kun-Young Park
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
| | - Hyemi Shin
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
| | - Young Hoon Kim
- National Creative Research Center for Cell Plasticity, KAIST Stem Cell Center, Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
| | - Myungsun Park
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
| | - Hahn Nahmgoong
- National Creative Research Initiatives Center for Adipocyte Structure and Function, Institute of Molecular Biology and Genetics, School of Biological Sciences, Seoul National University, Seoul, Republic of Korea
| | - Taejun Seol
- National Creative Research Center for Cell Plasticity, KAIST Stem Cell Center, Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
| | - Haeyon Jeon
- National Creative Research Center for Cell Plasticity, KAIST Stem Cell Center, Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
| | - Yeongmin Kim
- Department of Health Sciences and Technology, Gachon Advanced Institute for Health Sciences & Technology, Gachon University, Incheon, Republic of Korea
| | - Sanghee Park
- Department of Molecular Medicine, Lee Gil Ya Cancer and Diabetes Institute, College of Medicine, Gachon University, Incheon, Republic of Korea
| | - Hee-Joo Kim
- Department of Health Sciences and Technology, Gachon Advanced Institute for Health Sciences & Technology, Gachon University, Incheon, Republic of Korea
| | - Min-Seob Kim
- Department of Fundamental Environment Research, Environmental Measurement and Analysis Center, National Institute of Environmental Research, Incheon, Republic of Korea
| | - Xiaoxu Li
- Laboratory of Integrative Systems Physiology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Maroun Bou Sleiman
- Laboratory of Integrative Systems Physiology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Eries Lee
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
| | - Jinhyuk Choi
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
| | - David Eisenbarth
- National Creative Research Center for Cell Plasticity, KAIST Stem Cell Center, Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
| | - Sang Heon Lee
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
| | - Suhyeon Cho
- National Creative Research Center for Cell Plasticity, KAIST Stem Cell Center, Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
| | - David D Moore
- Department of Nutritional Sciences and Toxicology, University of California, Berkeley, Berkeley, CA, USA
| | - Johan Auwerx
- Laboratory of Integrative Systems Physiology, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Il-Young Kim
- Department of Molecular Medicine, Lee Gil Ya Cancer and Diabetes Institute, College of Medicine, Gachon University, Incheon, Republic of Korea
| | - Jae Bum Kim
- National Creative Research Initiatives Center for Adipocyte Structure and Function, Institute of Molecular Biology and Genetics, School of Biological Sciences, Seoul National University, Seoul, Republic of Korea
| | - Jong-Eun Park
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
| | - Dae-Sik Lim
- National Creative Research Center for Cell Plasticity, KAIST Stem Cell Center, Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea.
| | - Jae Myoung Suh
- Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea.
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9
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Henkel C, Erikstrup C, Ostrowski SR, Pedersen OB, Troelsen A. Genetics may affect the risk of undergoing surgery for rhizarthrosis. J Orthop Res 2024; 42:1001-1008. [PMID: 38263870 DOI: 10.1002/jor.25753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 10/25/2023] [Accepted: 11/28/2023] [Indexed: 01/25/2024]
Abstract
Osteoarthritis is a prevalent and severe disease. Involvement of the trapeziometacarpal joint is common and can lead to both pain and disability. Genetics are known to affect the risk of osteoarthritis, but it remains unclear how genetics affect disease trajectories. In this study, we investigated whether the genetic associations of trapeziometacarpal osteoarthritis (rhizarthrosis) vary with the need for surgical treatment. The study was conducted as a case-control genome-wide association study using individuals from the Copenhagen Hospital Biobank pain and degenerative musculoskeletal disease study and the Danish Blood Donor Study (N = 208,342). We identified patients diagnosed with rhizarthrosis and grouped them by treatment status, resulting in two case groups: surgical (N = 1083) and nonsurgical (N = 1888). The case groups were tested against osteoarthritis-free controls in two genome-wide association studies. We then compared variants suggestive of association (p < 10-6) in either of these analyses directly between the treatment groups (surgical vs. nonsurgical rhizarthrosis). We identified 10 variants suggestive of association with either surgical (seven variants) or nonsurgical (three variants) rhizarthrosis. None of the variants reached nominal significance in the opposite treatment group (p ≥ 0.14), and all 10 variants were significantly different between the treatment groups at a false discovery rate of 5%. These results suggest possible differences in the genetic associations of rhizarthrosis depending on surgical treatment. Clinical significance: Uncovering genetic differences between clinically distinct patient groups can reveal biological determinants of disease trajectories.
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Affiliation(s)
- Cecilie Henkel
- Clinical Orthopaedic Research Hvidovre (CORH), Department of Orthopaedic Surgery, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
| | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Health, Aarhus University, Aarhus, Denmark
| | - Sisse R Ostrowski
- Department of Clinical Immunology, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
- Clinical Academic Group: Research OsteoArthritis Denmark (CAG ROAD), Greater Copenhagen Health Science Partners, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ole B Pedersen
- Clinical Academic Group: Research OsteoArthritis Denmark (CAG ROAD), Greater Copenhagen Health Science Partners, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Immunology, Zealand University Hospital Køge, Køge, Denmark
| | - Anders Troelsen
- Clinical Orthopaedic Research Hvidovre (CORH), Department of Orthopaedic Surgery, Copenhagen University Hospital Hvidovre, Hvidovre, Denmark
- Clinical Academic Group: Research OsteoArthritis Denmark (CAG ROAD), Greater Copenhagen Health Science Partners, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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10
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DeHaas D, Pan Z, Wei X. Genotype Representation Graphs: Enabling Efficient Analysis of Biobank-Scale Data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.23.590800. [PMID: 38712040 PMCID: PMC11071416 DOI: 10.1101/2024.04.23.590800] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Computational analysis of a large number of genomes requires a data structure that can represent the dataset compactly while also enabling efficient operations on variants and samples. Current practice is to store large-scale genetic polymorphism data using tabular data structures and file formats, where rows and columns represent samples and genetic variants. However, encoding genetic data in such formats has become unsustainable. For example, the UK Biobank polymorphism data of 200,000 phased whole genomes has exceeded 350 terabytes (TB) in Variant Call Format (VCF), too large to fit into hard drives in uncompressed form. To mitigate the computational burden, we introduce the Genotype Representation Graph (GRG), an extremely compact data structure to losslessly present phased whole-genome polymorphisms. A GRG is a fully connected hierarchical graph that exploits variant-sharing across samples, leveraging on ideas inspired by Ancestral Recombination Graphs. Capturing variant-sharing in a graph format compresses biobank-scale data to the point where it can fit in a typical server's RAM (5-26GB per chromosome), and enables graph-traversal algorithms to trivially reuse computed values, both of which can significantly reduce computation time. We have developed a command-line tool and a library usable via both C++ and Python for constructing and processing GRG files which scales to a million whole genomes. It takes 160GB disk space to encode the information in 200,000 UK Biobank phased whole genomes as a GRG, more than 2000 times smaller than the size of VCF. Moreover, the size of GRG increases sublinearly with the number of samples stored, making it a sustainable solution to the increasing number of samples in large datasets. We show that summaries of genetic variants can be computed on GRG via graph traversal that runs 230 times faster than on VCF. We anticipate that GRG-based algorithms will improve the scalability of various types of computation and generally lower the cost of analyzing large genomic datasets.
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Affiliation(s)
- Drew DeHaas
- Department of Computational Biology, Cornell University, Ithaca, NY
| | - Ziqing Pan
- Department of Computational Biology, Cornell University, Ithaca, NY
| | - Xinzhu Wei
- Department of Computational Biology, Cornell University, Ithaca, NY
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11
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Skuladottir AT, Stefansdottir L, Halldorsson GH, Stefansson OA, Bjornsdottir A, Jonsson P, Palmadottir V, Thorgeirsson TE, Walters GB, Gisladottir RS, Bjornsdottir G, Jonsdottir GA, Sulem P, Gudbjartsson DF, Knowlton KU, Jones DA, Ottas A, Pedersen OB, Didriksen M, Brunak S, Banasik K, Hansen TF, Erikstrup C, Haavik J, Andreassen OA, Rye D, Igland J, Ostrowski SR, Milani LA, Nadauld LD, Stefansson H, Stefansson K. GWAS meta-analysis reveals key risk loci in essential tremor pathogenesis. Commun Biol 2024; 7:504. [PMID: 38671141 PMCID: PMC11053069 DOI: 10.1038/s42003-024-06207-4] [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: 12/04/2023] [Accepted: 04/17/2024] [Indexed: 04/28/2024] Open
Abstract
Essential tremor (ET) is a prevalent neurological disorder with a largely unknown underlying biology. In this genome-wide association study meta-analysis, comprising 16,480 ET cases and 1,936,173 controls from seven datasets, we identify 12 sequence variants at 11 loci. Evaluating mRNA expression, splicing, plasma protein levels, and coding effects, we highlight seven putative causal genes at these loci, including CA3 and CPLX1. CA3 encodes Carbonic Anhydrase III and carbonic anhydrase inhibitors have been shown to decrease tremors. CPLX1, encoding Complexin-1, regulates neurotransmitter release. Through gene-set enrichment analysis, we identify a significant association with specific cell types, including dopaminergic and GABAergic neurons, as well as biological processes like Rho GTPase signaling. Genetic correlation analyses reveals a positive association between ET and Parkinson's disease, depression, and anxiety-related phenotypes. This research uncovers risk loci, enhancing our knowledge of the complex genetics of this common but poorly understood disorder, and highlights CA3 and CPLX1 as potential therapeutic targets.
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Affiliation(s)
- Astros Th Skuladottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland.
| | | | | | | | | | - Palmi Jonsson
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Department of Geriatric Medicine, Landspitali University Hospital, Reykjavik, Iceland
| | - Vala Palmadottir
- Department of Internal Medicine, Landspitali University Hospital, Reykjavik, Iceland
| | | | | | - Rosa S Gisladottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Icelandic and Comparative Cultural Studies, University of Iceland, Reykjavik, Iceland
| | | | | | | | - Daniel F Gudbjartsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Kirk U Knowlton
- Intermountain Medical Center, Intermountain Heart Institute, Salt Lake City, USA
| | - David A Jones
- Precision Genomics, Intermountain Healthcare, Saint George, Utah, UK
| | - Aigar Ottas
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Ole B Pedersen
- Department of Clinical Immunology, Zealand University Hospital, Køge, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Maria Didriksen
- Department of Clinical Immunology, Copenhagen University Hospital, Righospitale, Copenhagen, Denmark
| | - Søren Brunak
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Karina Banasik
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Thomas Folkmann Hansen
- Danish Headache Center, Department of Neurology, Copenhagen University Hospital, Righospitalet-Glostrup, Copenhagen, Denmark
| | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Righospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, Aarhus University, Aarhus, Denmark
| | - Jan Haavik
- Department of Biomedicine, University of Bergen, Bergen, Norway
- Bergen Center of Brain Plasticity, Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
| | - Ole A Andreassen
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - David Rye
- Emory Department of Neurology, Wesley Woods Health Center, Atlanta, GA, USA
| | - Jannicke Igland
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
- Department of Health and Caring sciences, Western Norway University of Applied Sciences, Bergen, Norway
| | - Sisse Rye Ostrowski
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Immunology, Copenhagen University Hospital, Righospitale, Copenhagen, Denmark
| | - Lili A Milani
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Lincoln D Nadauld
- Precision Genomics, Intermountain Healthcare, Saint George, Utah, UK
- Stanford University, School of Medicine, Stanford, CA, USA
| | | | - Kari Stefansson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland.
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12
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Du ZZ, He JB, Jiao WB. A comprehensive benchmark of graph-based genetic variant genotyping algorithms on plant genomes for creating an accurate ensemble pipeline. Genome Biol 2024; 25:91. [PMID: 38589937 PMCID: PMC11003132 DOI: 10.1186/s13059-024-03239-1] [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: 07/19/2023] [Accepted: 04/04/2024] [Indexed: 04/10/2024] Open
Abstract
BACKGROUND Although sequencing technologies have boosted the measurement of the genomic diversity of plant crops, it remains challenging to accurately genotype millions of genetic variants, especially structural variations, with only short reads. In recent years, many graph-based variation genotyping methods have been developed to address this issue and tested for human genomes. However, their performance in plant genomes remains largely elusive. Furthermore, pipelines integrating the advantages of current genotyping methods might be required, considering the different complexity of plant genomes. RESULTS Here we comprehensively evaluate eight such genotypers in different scenarios in terms of variant type and size, sequencing parameters, genomic context, and complexity, as well as graph size, using both simulated and real data sets from representative plant genomes. Our evaluation reveals that there are still great challenges to applying existing methods to plants, such as excessive repeats and variants or high resource consumption. Therefore, we propose a pipeline called Ensemble Variant Genotyper (EVG) that can achieve better genotyping performance in almost all experimental scenarios and comparably higher genotyping recall and precision even using 5× reads. Furthermore, we demonstrate that EVG is more robust with an increasing number of graphed genomes, especially for insertions and deletions. CONCLUSIONS Our study will provide new insights into the development and application of graph-based genotyping algorithms. We conclude that EVG provides an accurate, unbiased, and cost-effective way for genotyping both small and large variations and will be potentially used in population-scale genotyping for large, repetitive, and heterozygous plant genomes.
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Affiliation(s)
- Ze-Zhen Du
- National Key Laboratory for Germplasm Innovation & Utilization of Horticultural Crops, Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Jia-Bao He
- National Key Laboratory for Germplasm Innovation & Utilization of Horticultural Crops, Huazhong Agricultural University, Wuhan, China
- Hubei Hongshan Laboratory, Wuhan, China
| | - Wen-Biao Jiao
- National Key Laboratory for Germplasm Innovation & Utilization of Horticultural Crops, Huazhong Agricultural University, Wuhan, China.
- Hubei Hongshan Laboratory, Wuhan, China.
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13
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Brown SRB, Bland R, McIntyre L, Shyng S, Weisberg AJ, Riutta ER, Chang JH, Kovacevic J. Genomic characterization of Listeria monocytogenes recovered from dairy facilities in British Columbia, Canada from 2007 to 2017. Front Microbiol 2024; 15:1304734. [PMID: 38585707 PMCID: PMC10995413 DOI: 10.3389/fmicb.2024.1304734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 03/11/2024] [Indexed: 04/09/2024] Open
Abstract
Listeria monocytogenes is a foodborne pathogen of concern in dairy processing facilities, with the potential to cause human illness and trigger regulatory actions if found in the product. Monitoring for Listeria spp. through environmental sampling is recommended to prevent establishment of these microorganisms in dairy processing environments, thereby reducing the risk of product contamination. To inform on L. monocytogenes diversity and transmission, we analyzed genome sequences of L. monocytogenes strains (n = 88) obtained through the British Columbia Dairy Inspection Program. Strains were recovered from five different dairy processing facilities over a 10 year period (2007-2017). Analysis of whole genome sequences (WGS) grouped the isolates into nine sequence types and 11 cgMLST types (CT). The majority of isolates (93%) belonged to lineage II. Within each CT, single nucleotide polymorphism (SNP) differences ranged from 0 to 237 between isolates. A highly similar (0-16 SNPs) cluster of over 60 isolates, collected over 9 years within one facility (#71), was identified suggesting a possible persistent population. Analyses of genome content revealed a low frequency of genes associated with stress tolerance, with the exception of widely disseminated cadmium resistance genes cadA1 and cadA2. The distribution of virulence genes and mutations within internalin genes varied across the isolates and facilities. Further studies are needed to elucidate their phenotypic effect on pathogenicity and stress response. These findings demonstrate the diversity of L. monocytogenes isolates across dairy facilities in the same region. Findings also showed the utility of using WGS to discern potential persistence events within a single facility over time.
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Affiliation(s)
| | - Rebecca Bland
- Food Innovation Center, Oregon State University, Portland, OR, United States
| | | | - Sion Shyng
- British Columbia Centre for Disease Control, Vancouver, BC, Canada
| | - Alexandra J. Weisberg
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, United States
| | - Elizabeth R. Riutta
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, United States
| | - Jeff H. Chang
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR, United States
| | - Jovana Kovacevic
- Food Innovation Center, Oregon State University, Portland, OR, United States
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14
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Kwon D, Park N, Wy S, Lee D, Park W, Chai HH, Cho IC, Lee J, Kwon K, Kim H, Moon Y, Kim J, Kim J. Identification and characterization of structural variants related to meat quality in pigs using chromosome-level genome assemblies. BMC Genomics 2024; 25:299. [PMID: 38515031 PMCID: PMC10956321 DOI: 10.1186/s12864-024-10225-1] [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: 01/19/2024] [Accepted: 03/14/2024] [Indexed: 03/23/2024] Open
Abstract
BACKGROUND Many studies have been performed to identify various genomic loci and genes associated with the meat quality in pigs. However, the full genetic architecture of the trait still remains unclear in part because of the lack of accurate identification of related structural variations (SVs) which resulted from the shortage of target breeds, the limitations of sequencing data, and the incompleteness of genome assemblies. The recent generation of a new pig breed with superior meat quality, called Nanchukmacdon, and its chromosome-level genome assembly (the NCMD assembly) has provided new opportunities. RESULTS By applying assembly-based SV calling approaches to various genome assemblies of pigs including Nanchukmacdon, the impact of SVs on meat quality was investigated. Especially, by checking the commonality of SVs with other pig breeds, a total of 13,819 Nanchukmacdon-specific SVs (NSVs) were identified, which have a potential effect on the unique meat quality of Nanchukmacdon. The regulatory potentials of NSVs for the expression of nearby genes were further examined using transcriptome- and epigenome-based analyses in different tissues. CONCLUSIONS Whole-genome comparisons based on chromosome-level genome assemblies have led to the discovery of SVs affecting meat quality in pigs, and their regulatory potentials were analyzed. The identified NSVs will provide new insights regarding genetic architectures underlying the meat quality in pigs. Finally, this study confirms the utility of chromosome-level genome assemblies and multi-omics analysis to enhance the understanding of unique phenotypes.
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Affiliation(s)
- Daehong Kwon
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea
| | - Nayoung Park
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea
| | - Suyeon Wy
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea
| | - Daehwan Lee
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea
| | - Woncheoul Park
- Animal Genomics and Bioinformatics Division, National Institute of Animal Science, RDA, Wanju, 55365, Republic of Korea
| | - Han-Ha Chai
- Animal Genomics and Bioinformatics Division, National Institute of Animal Science, RDA, Wanju, 55365, Republic of Korea
| | - In-Cheol Cho
- Subtropical Livestock Research Institute, National Institute of Animal Science, RDA, Jeju, 63242, Republic of Korea
| | - Jongin Lee
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea
| | - Kisang Kwon
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea
| | - Heesun Kim
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea
| | - Youngbeen Moon
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea
| | - Juyeon Kim
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea
| | - Jaebum Kim
- Department of Biomedical Science and Engineering, Konkuk University, Seoul, 05029, Republic of Korea.
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15
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Martiniano R, Haber M, Almarri MA, Mattiangeli V, Kuijpers MCM, Chamel B, Breslin EM, Littleton J, Almahari S, Aloraifi F, Bradley DG, Lombard P, Durbin R. Ancient genomes illuminate Eastern Arabian population history and adaptation against malaria. CELL GENOMICS 2024; 4:100507. [PMID: 38417441 PMCID: PMC10943591 DOI: 10.1016/j.xgen.2024.100507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 11/01/2023] [Accepted: 01/31/2024] [Indexed: 03/01/2024]
Abstract
The harsh climate of Arabia has posed challenges in generating ancient DNA from the region, hindering the direct examination of ancient genomes for understanding the demographic processes that shaped Arabian populations. In this study, we report whole-genome sequence data obtained from four Tylos-period individuals from Bahrain. Their genetic ancestry can be modeled as a mixture of sources from ancient Anatolia, Levant, and Iran/Caucasus, with variation between individuals suggesting population heterogeneity in Bahrain before the onset of Islam. We identify the G6PD Mediterranean mutation associated with malaria resistance in three out of four ancient Bahraini samples and estimate that it rose in frequency in Eastern Arabia from 5 to 6 kya onward, around the time agriculture appeared in the region. Our study characterizes the genetic composition of ancient Arabians, shedding light on the population history of Bahrain and demonstrating the feasibility of studies of ancient DNA in the region.
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Affiliation(s)
- Rui Martiniano
- School of Biological and Environmental Sciences, Liverpool John Moores University, L3 3AF Liverpool, UK.
| | - Marc Haber
- Institute of Cancer and Genomic Sciences, University of Birmingham Dubai, Dubai, United Arab Emirates
| | - Mohamed A Almarri
- Department of Forensic Science and Criminology, Dubai Police GHQ, Dubai, United Arab Emirates; College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates
| | | | - Mirte C M Kuijpers
- Department of Ecology, Behavior and Evolution, School of Biological Sciences, University of California, San Diego, La Jolla, CA, USA
| | - Berenice Chamel
- Institut Français du Proche-Orient (MEAE/CNRS), Beirut, Lebanon
| | - Emily M Breslin
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin 2, Ireland
| | - Judith Littleton
- School of Social Sciences, University of Auckland, Auckland, New Zealand
| | - Salman Almahari
- Bahrain Authority for Culture and Antiquities, Manama, Kingdom of Bahrain
| | - Fatima Aloraifi
- Mersey and West Lancashire Teaching Hospitals NHS Trust, Whiston Hospital, Warrington Road, Prescot, L35 5DR Liverpool, UK
| | - Daniel G Bradley
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin 2, Ireland
| | - Pierre Lombard
- Bahrain Authority for Culture and Antiquities, Manama, Kingdom of Bahrain; Archéorient UMR 5133, CNRS, Université Lyon 2, Maison de l'Orient et de la Méditerranée - Jean Pouilloux, Lyon, France
| | - Richard Durbin
- Department of Genetics, University of Cambridge, CB2 3EH Cambridge, UK.
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16
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Rajput J, Chandra G, Jain C. Co-linear chaining on pangenome graphs. Algorithms Mol Biol 2024; 19:4. [PMID: 38279113 PMCID: PMC11288099 DOI: 10.1186/s13015-024-00250-w] [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: 11/21/2023] [Accepted: 01/02/2024] [Indexed: 01/28/2024] Open
Abstract
Pangenome reference graphs are useful in genomics because they compactly represent the genetic diversity within a species, a capability that linear references lack. However, efficiently aligning sequences to these graphs with complex topology and cycles can be challenging. The seed-chain-extend based alignment algorithms use co-linear chaining as a standard technique to identify a good cluster of exact seed matches that can be combined to form an alignment. Recent works show how the co-linear chaining problem can be efficiently solved for acyclic pangenome graphs by exploiting their small width and how incorporating gap cost in the scoring function improves alignment accuracy. However, it remains open on how to effectively generalize these techniques for general pangenome graphs which contain cycles. Here we present the first practical formulation and an exact algorithm for co-linear chaining on cyclic pangenome graphs. We rigorously prove the correctness and computational complexity of the proposed algorithm. We evaluate the empirical performance of our algorithm by aligning simulated long reads from the human genome to a cyclic pangenome graph constructed from 95 publicly available haplotype-resolved human genome assemblies. While the existing heuristic-based algorithms are faster, the proposed algorithm provides a significant advantage in terms of accuracy. Implementation ( https://github.com/at-cg/PanAligner ).
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Affiliation(s)
- Jyotshna Rajput
- Department of Computational and Data Sciences, Indian Institute of Science, Bangalore, 560012, Karnataka, India
| | - Ghanshyam Chandra
- Department of Computational and Data Sciences, Indian Institute of Science, Bangalore, 560012, Karnataka, India
| | - Chirag Jain
- Department of Computational and Data Sciences, Indian Institute of Science, Bangalore, 560012, Karnataka, India.
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17
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Stacey SN, Zink F, Halldorsson GH, Stefansdottir L, Gudjonsson SA, Einarsson G, Hjörleifsson G, Eiriksdottir T, Helgadottir A, Björnsdottir G, Thorgeirsson TE, Olafsdottir TA, Jonsdottir I, Gretarsdottir S, Tragante V, Magnusson MK, Jonsson H, Gudmundsson J, Olafsson S, Holm H, Gudbjartsson DF, Sulem P, Helgason A, Thorsteinsdottir U, Tryggvadottir L, Rafnar T, Melsted P, Ulfarsson MÖ, Vidarsson B, Thorleifsson G, Stefansson K. Genetics and epidemiology of mutational barcode-defined clonal hematopoiesis. Nat Genet 2023; 55:2149-2159. [PMID: 37932435 PMCID: PMC10703693 DOI: 10.1038/s41588-023-01555-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 09/28/2023] [Indexed: 11/08/2023]
Abstract
Clonal hematopoiesis (CH) arises when a substantial proportion of mature blood cells is derived from a single hematopoietic stem cell lineage. Using whole-genome sequencing of 45,510 Icelandic and 130,709 UK Biobank participants combined with a mutational barcode method, we identified 16,306 people with CH. Prevalence approaches 50% in elderly participants. Smoking demonstrates a dosage-dependent impact on risk of CH. CH associates with several smoking-related diseases. Contrary to published claims, we find no evidence that CH is associated with cardiovascular disease. We provide evidence that CH is driven by genes that are commonly mutated in myeloid neoplasia and implicate several new driver genes. The presence and nature of a driver mutation alters the risk profile for hematological disorders. Nevertheless, most CH cases have no known driver mutations. A CH genome-wide association study identified 25 loci, including 19 not implicated previously in CH. Splicing, protein and expression quantitative trait loci were identified for CD164 and TCL1A.
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Affiliation(s)
| | | | - Gisli H Halldorsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | | | | | | | | | | | - Thorunn A Olafsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Ingileif Jonsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
- Department of Immunology, Landspitali University Hospital, Reykjavik, Iceland
| | | | | | - Magnus K Magnusson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | - Hilma Holm
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
| | - Daniel F Gudbjartsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | - Agnar Helgason
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Department of Anthropology, University of Iceland, Reykjavik, Iceland
| | - Unnur Thorsteinsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | - Pall Melsted
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Magnus Ö Ulfarsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Brynjar Vidarsson
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
- Department of Hematology, Landspitali University Hospital, Reykjavik, Iceland
| | | | - Kari Stefansson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland.
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18
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Chandra G, Jain C. Gap-Sensitive Colinear Chaining Algorithms for Acyclic Pangenome Graphs. J Comput Biol 2023; 30:1182-1197. [PMID: 37902967 DOI: 10.1089/cmb.2023.0186] [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] [Indexed: 11/01/2023] Open
Abstract
A pangenome graph can serve as a better reference for genomic studies because it allows a compact representation of multiple genomes within a species. Aligning sequences to a graph is critical for pangenome-based resequencing. The seed-chain-extend heuristic works by finding short exact matches between a sequence and a graph. In this heuristic, colinear chaining helps identify a good cluster of exact matches that can be combined to form an alignment. Colinear chaining algorithms have been extensively studied for aligning two sequences with various gap costs, including linear, concave, and convex cost functions. However, extending these algorithms for sequence-to-graph alignment presents significant challenges. Recently, Makinen et al. introduced a sparse dynamic programming framework that exploits the small path cover property of acyclic pangenome graphs, enabling efficient chaining. However, this framework does not consider gap costs, limiting its practical effectiveness. We address this limitation by developing novel problem formulations and provably good chaining algorithms that support a variety of gap cost functions. These functions are carefully designed to enable fast chaining algorithms whose time requirements are parameterized in terms of the size of the minimum path cover. Through an empirical evaluation, we demonstrate the superior performance of our algorithm compared with existing aligners. When mapping simulated long reads to a pangenome graph comprising 95 human haplotypes, we achieved 98.7% precision while leaving <2% of reads unmapped.
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Affiliation(s)
- Ghanshyam Chandra
- Department of Computational and Data Sciences, Indian Institute of Science Bengaluru, India
| | - Chirag Jain
- Department of Computational and Data Sciences, Indian Institute of Science Bengaluru, India
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19
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Weisberg AJ, Pearce E, Kramer CG, Chang JH, Clarke CR. Diverse mobile genetic elements shaped the evolution of Streptomyces virulence. Microb Genom 2023; 9. [PMID: 37930748 DOI: 10.1099/mgen.0.001127] [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] [Indexed: 11/07/2023] Open
Abstract
Mobile genetic elements can innovate bacteria with new traits. In plant pathogenic Streptomyces, frequent and recent acquisition of integrative and conjugative or mobilizable genetic elements is predicted to lead to the emergence of new lineages that gained the capacity to synthesize Thaxtomin, a phytotoxin neccesary for induction of common scab disease on tuber and root crops. Here, we identified components of the Streptomyces-potato pathosystem implicated in virulence and investigated them as a nested and interacting system to reevaluate evolutionary models. We sequenced and analysed genomes of 166 strains isolated from over six decades of sampling primarily from field-grown potatoes. Virulence genes were associated to multiple subtypes of genetic elements differing in mechanisms of transmission and evolutionary histories. Evidence is consistent with few ancient acquisition events followed by recurrent loss or swaps of elements carrying Thaxtomin A-associated genes. Subtypes of another genetic element implicated in virulence are more distributed across Streptomyces. However, neither the subtype classification of genetic elements containing virulence genes nor taxonomic identity was predictive of pathogenicity on potato. Last, findings suggested that phytopathogenic strains are generally endemic to potato fields and some lineages were established by historical spread and further dispersed by few recent transmission events. Results from a hierarchical and system-wide characterization refine our understanding by revealing multiple mechanisms that gene and bacterial dispersion have had on shaping the evolution of a Gram-positive pathogen in agricultural settings.
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Affiliation(s)
- Alexandra J Weisberg
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Emma Pearce
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Charles G Kramer
- USDA Agricultural Research Service, USDA Agricultural Research Service, Genetic Improvement for Fruits and Vegetables Lab, Beltsville, MD, USA
| | - Jeff H Chang
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA
| | - Christopher R Clarke
- USDA Agricultural Research Service, USDA Agricultural Research Service, Genetic Improvement for Fruits and Vegetables Lab, Beltsville, MD, USA
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20
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Booyse RP, Twesigomwe D, Hazelhurst S. Characterization of CYP2C19 pharmacogenetic variation in African populations and comparison with other global populations. Pharmacogenomics 2023; 24:845-857. [PMID: 37929326 PMCID: PMC10694788 DOI: 10.2217/pgs-2023-0166] [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: 08/24/2023] [Accepted: 10/12/2023] [Indexed: 11/07/2023] Open
Abstract
Background: CYP2C19 is important in the metabolism of clopidogrel and several antidepressants. This study aimed to characterize the distribution of CYP2C19 star alleles (haplotypes) across diverse African populations compared with global populations. Methods: CYP2C19 star alleles and diplotypes were called from high coverage genomes using the StellarPGx pipeline. Results: CYP2C19*1 (51%), *2 (17%) and *17 (22%) were the most common star alleles across African populations in this study. It was observed that 3% of African participants had potentially novel CYP2C19 haplotypes. Conclusion: This study supports the necessity for CYP2C19 pharmacogenetic testing in African and global clinical settings, as well as the importance of comprehensive star allele characterization in the African context.
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Affiliation(s)
- Ross P Booyse
- Division of Human Genetics, National Health Laboratory Service, and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - David Twesigomwe
- Division of Human Genetics, National Health Laboratory Service, and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Scott Hazelhurst
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- School of Electrical & Information Engineering, University of the Witwatersrand, Johannesburg, South Africa
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21
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Bjornsdottir G, Chalmer MA, Stefansdottir L, Skuladottir AT, Einarsson G, Andresdottir M, Beyter D, Ferkingstad E, Gretarsdottir S, Halldorsson BV, Halldorsson GH, Helgadottir A, Helgason H, Hjorleifsson Eldjarn G, Jonasdottir A, Jonasdottir A, Jonsdottir I, Knowlton KU, Nadauld LD, Lund SH, Magnusson OT, Melsted P, Moore KHS, Oddsson A, Olason PI, Sigurdsson A, Stefansson OA, Saemundsdottir J, Sveinbjornsson G, Tragante V, Unnsteinsdottir U, Walters GB, Zink F, Rødevand L, Andreassen OA, Igland J, Lie RT, Haavik J, Banasik K, Brunak S, Didriksen M, T Bruun M, Erikstrup C, Kogelman LJA, Nielsen KR, Sørensen E, Pedersen OB, Ullum H, Masson G, Thorsteinsdottir U, Olesen J, Ludvigsson P, Thorarensen O, Bjornsdottir A, Sigurdardottir GR, Sveinsson OA, Ostrowski SR, Holm H, Gudbjartsson DF, Thorleifsson G, Sulem P, Stefansson H, Thorgeirsson TE, Hansen TF, Stefansson K. Rare variants with large effects provide functional insights into the pathology of migraine subtypes, with and without aura. Nat Genet 2023; 55:1843-1853. [PMID: 37884687 PMCID: PMC10632135 DOI: 10.1038/s41588-023-01538-0] [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: 12/02/2022] [Accepted: 09/18/2023] [Indexed: 10/28/2023]
Abstract
Migraine is a complex neurovascular disease with a range of severity and symptoms, yet mostly studied as one phenotype in genome-wide association studies (GWAS). Here we combine large GWAS datasets from six European populations to study the main migraine subtypes, migraine with aura (MA) and migraine without aura (MO). We identified four new MA-associated variants (in PRRT2, PALMD, ABO and LRRK2) and classified 13 MO-associated variants. Rare variants with large effects highlight three genes. A rare frameshift variant in brain-expressed PRRT2 confers large risk of MA and epilepsy, but not MO. A burden test of rare loss-of-function variants in SCN11A, encoding a neuron-expressed sodium channel with a key role in pain sensation, shows strong protection against migraine. Finally, a rare variant with cis-regulatory effects on KCNK5 confers large protection against migraine and brain aneurysms. Our findings offer new insights with therapeutic potential into the complex biology of migraine and its subtypes.
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Affiliation(s)
| | - Mona A Chalmer
- Danish Headache Center, Department of Neurology, Copenhagen University Hospital, Rigshospitalet-Glostrup, Copenhagen, Denmark
| | | | | | | | | | | | | | | | - Bjarni V Halldorsson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- Reykjavik University, School of Technology, Reykjavik, Iceland
| | - Gisli H Halldorsson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | - Hannes Helgason
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | - Ingileif Jonsdottir
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | - Sigrun H Lund
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- Faculty of Physical Sciences, School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | - Pall Melsted
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | | | | | | | | | | | | | | | | | - Linn Rødevand
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Ole A Andreassen
- NORMENT, Centre for Mental Disorders Research, Division of Mental Health and Addiction, Oslo University Hospital, and Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Jannicke Igland
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
- Department of Health and Social Science, Centre for Evidence-Based Practice, Western Norway University of Applied Science, Bergen, Norway
| | - Rolv T Lie
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Jan Haavik
- Department of Biomedicine, University of Bergen, Bergen, Norway
- Division of Psychiatry, Haukeland University Hospital, Bergen, Norway
| | - Karina Banasik
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Søren Brunak
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Maria Didriksen
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Mie T Bruun
- Department of Clinical Immunology, Odense University Hospital, Odense, Denmark
| | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine Health, Aarhus University, Aarhus, Denmark
| | - Lisette J A Kogelman
- Danish Headache Center, Department of Neurology, Copenhagen University Hospital, Rigshospitalet-Glostrup, Copenhagen, Denmark
| | - Kaspar R Nielsen
- Department of Clinical Immunology, Aalborg University Hospital, Aalborg, Denmark
- Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
| | - Erik Sørensen
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Ole B Pedersen
- Department of Clinical Immunology, Zealand University Hospital, Køge, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | | | - Unnur Thorsteinsdottir
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Jes Olesen
- Danish Headache Center, Department of Neurology, Copenhagen University Hospital, Rigshospitalet-Glostrup, Copenhagen, Denmark
| | - Petur Ludvigsson
- Department of Pediatrics, Landspitali University Hostpital, Reykjavik, Iceland
| | - Olafur Thorarensen
- Department of Pediatrics, Landspitali University Hostpital, Reykjavik, Iceland
| | | | | | - Olafur A Sveinsson
- Laeknasetrid Clinic, Reykjavik, Iceland
- Department of Neurology, Landspitali University Hospital, Reykjavik, Iceland
| | - Sisse R Ostrowski
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Hilma Holm
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
| | - Daniel F Gudbjartsson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | | | - Thomas F Hansen
- Danish Headache Center, Department of Neurology, Copenhagen University Hospital, Rigshospitalet-Glostrup, Copenhagen, Denmark
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Kari Stefansson
- deCODE Genetics/Amgen, Inc., Reykjavik, Iceland.
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland.
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22
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Eldjarn GH, Ferkingstad E, Lund SH, Helgason H, Magnusson OT, Gunnarsdottir K, Olafsdottir TA, Halldorsson BV, Olason PI, Zink F, Gudjonsson SA, Sveinbjornsson G, Magnusson MI, Helgason A, Oddsson A, Halldorsson GH, Magnusson MK, Saevarsdottir S, Eiriksdottir T, Masson G, Stefansson H, Jonsdottir I, Holm H, Rafnar T, Melsted P, Saemundsdottir J, Norddahl GL, Thorleifsson G, Ulfarsson MO, Gudbjartsson DF, Thorsteinsdottir U, Sulem P, Stefansson K. Large-scale plasma proteomics comparisons through genetics and disease associations. Nature 2023; 622:348-358. [PMID: 37794188 PMCID: PMC10567571 DOI: 10.1038/s41586-023-06563-x] [Citation(s) in RCA: 34] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 08/22/2023] [Indexed: 10/06/2023]
Abstract
High-throughput proteomics platforms measuring thousands of proteins in plasma combined with genomic and phenotypic information have the power to bridge the gap between the genome and diseases. Here we performed association studies of Olink Explore 3072 data generated by the UK Biobank Pharma Proteomics Project1 on plasma samples from more than 50,000 UK Biobank participants with phenotypic and genotypic data, stratifying on British or Irish, African and South Asian ancestries. We compared the results with those of a SomaScan v4 study on plasma from 36,000 Icelandic people2, for 1,514 of whom Olink data were also available. We found modest correlation between the two platforms. Although cis protein quantitative trait loci were detected for a similar absolute number of assays on the two platforms (2,101 on Olink versus 2,120 on SomaScan), the proportion of assays with such supporting evidence for assay performance was higher on the Olink platform (72% versus 43%). A considerable number of proteins had genomic associations that differed between the platforms. We provide examples where differences between platforms may influence conclusions drawn from the integration of protein levels with the study of diseases. We demonstrate how leveraging the diverse ancestries of participants in the UK Biobank helps to detect novel associations and refine genomic location. Our results show the value of the information provided by the two most commonly used high-throughput proteomics platforms and demonstrate the differences between them that at times provides useful complementarity.
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Affiliation(s)
| | | | - Sigrun H Lund
- deCODE Genetics/Amgen, Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Hannes Helgason
- deCODE Genetics/Amgen, Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | - Bjarni V Halldorsson
- deCODE Genetics/Amgen, Reykjavik, Iceland
- School of Technology, Reykjavik University, Reykjavik, Iceland
| | | | | | | | | | | | - Agnar Helgason
- deCODE Genetics/Amgen, Reykjavik, Iceland
- Department of Anthropology, University of Iceland, Reykjavik, Iceland
| | | | | | - Magnus K Magnusson
- deCODE Genetics/Amgen, Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Saedis Saevarsdottir
- deCODE Genetics/Amgen, Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | - Ingileif Jonsdottir
- deCODE Genetics/Amgen, Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Hilma Holm
- deCODE Genetics/Amgen, Reykjavik, Iceland
| | | | - Pall Melsted
- deCODE Genetics/Amgen, Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | - Magnus O Ulfarsson
- deCODE Genetics/Amgen, Reykjavik, Iceland
- Faculty of Electrical and Computer Engineering, University of Iceland, Reykjavik, Iceland
| | - Daniel F Gudbjartsson
- deCODE Genetics/Amgen, Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Unnur Thorsteinsdottir
- deCODE Genetics/Amgen, Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | | | - Kari Stefansson
- deCODE Genetics/Amgen, Reykjavik, Iceland.
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland.
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23
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Naithani S, Deng CH, Sahu SK, Jaiswal P. Exploring Pan-Genomes: An Overview of Resources and Tools for Unraveling Structure, Function, and Evolution of Crop Genes and Genomes. Biomolecules 2023; 13:1403. [PMID: 37759803 PMCID: PMC10527062 DOI: 10.3390/biom13091403] [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: 07/31/2023] [Revised: 08/29/2023] [Accepted: 09/12/2023] [Indexed: 09/29/2023] Open
Abstract
The availability of multiple sequenced genomes from a single species made it possible to explore intra- and inter-specific genomic comparisons at higher resolution and build clade-specific pan-genomes of several crops. The pan-genomes of crops constructed from various cultivars, accessions, landraces, and wild ancestral species represent a compendium of genes and structural variations and allow researchers to search for the novel genes and alleles that were inadvertently lost in domesticated crops during the historical process of crop domestication or in the process of extensive plant breeding. Fortunately, many valuable genes and alleles associated with desirable traits like disease resistance, abiotic stress tolerance, plant architecture, and nutrition qualities exist in landraces, ancestral species, and crop wild relatives. The novel genes from the wild ancestors and landraces can be introduced back to high-yielding varieties of modern crops by implementing classical plant breeding, genomic selection, and transgenic/gene editing approaches. Thus, pan-genomic represents a great leap in plant research and offers new avenues for targeted breeding to mitigate the impact of global climate change. Here, we summarize the tools used for pan-genome assembly and annotations, web-portals hosting plant pan-genomes, etc. Furthermore, we highlight a few discoveries made in crops using the pan-genomic approach and future potential of this emerging field of study.
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Affiliation(s)
- Sushma Naithani
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA;
| | - Cecilia H. Deng
- Molecular & Digital Breeing Group, New Cultivar Innovation, The New Zealand Institute for Plant and Food Research Limited, Private Bag 92169, Auckland 1142, New Zealand;
| | - Sunil Kumar Sahu
- State Key Laboratory of Agricultural Genomics, Key Laboratory of Genomics, Ministry of Agriculture, BGI Research, Shenzhen 518083, China;
| | - Pankaj Jaiswal
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA;
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24
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Snaebjarnarson AS, Helgadottir A, Arnadottir GA, Ivarsdottir EV, Thorleifsson G, Ferkingstad E, Einarsson G, Sveinbjornsson G, Thorgeirsson TE, Ulfarsson MO, Halldorsson BV, Olafsson I, Erikstrup C, Pedersen OB, Nyegaard M, Bruun MT, Ullum H, Brunak S, Iversen KK, Christensen AH, Olesen MS, Ghouse J, Banasik K, Knowlton KU, Arnar DO, Thorgeirsson G, Nadauld L, Ostrowski SR, Bundgaard H, Holm H, Sulem P, Stefansson K, Gudbjartsson DF. Complex effects of sequence variants on lipid levels and coronary artery disease. Cell 2023; 186:4085-4099.e15. [PMID: 37714134 DOI: 10.1016/j.cell.2023.08.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 05/06/2023] [Accepted: 08/10/2023] [Indexed: 09/17/2023]
Abstract
Many sequence variants have additive effects on blood lipid levels and, through that, on the risk of coronary artery disease (CAD). We show that variants also have non-additive effects and interact to affect lipid levels as well as affecting variance and correlations. Variance and correlation effects are often signatures of epistasis or gene-environmental interactions. These complex effects can translate into CAD risk. For example, Trp154Ter in FUT2 protects against CAD among subjects with the A1 blood group, whereas it associates with greater risk of CAD in others. His48Arg in ADH1B interacts with alcohol consumption to affect lipid levels and CAD. The effect of variants in TM6SF2 on blood lipids is greatest among those who never eat oily fish but absent from those who often do. This work demonstrates that variants that affect variance of quantitative traits can allow for the discovery of epistasis and interactions of variants with the environment.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Magnus O Ulfarsson
- deCODE genetics/Amgen, Inc., Reykjavik 102, Iceland; Faculty of Electrical and Computer Engineering, University of Iceland, Reykjavik 102, Iceland
| | | | - Isleifur Olafsson
- Department of Clinical Biochemistry, Landspitali - National University Hospital of Iceland, Hringbraut, Reykjavik 101, Iceland
| | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus 8200, Denmark; Department of Clinical Medicine, Health, Aarhus University, Aarhus 8200, Denmark
| | - Ole B Pedersen
- Department of Clinical Immunology, Zealand University Hospital, Køge 4600, Denmark; Department of Clinical Medicine, University of Copenhagen, Copenhagen 1165, Denmark
| | - Mette Nyegaard
- Department of Health Science and Technology, Faculty of Medicine, Aalborg University, Aalborg 9220, Denmark
| | - Mie T Bruun
- Department of Clinical Immunology, Odense University Hospital, Odense 5000, Denmark
| | - Henrik Ullum
- Statens Serum Institut, Copenhagen 2300, Denmark
| | - Søren Brunak
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Kasper Karmark Iversen
- Department of Clinical Medicine, University of Copenhagen, Copenhagen 1165, Denmark; Department of Emergency Medicine, Copenhagen University Hospital Herlev and Gentofte, Herlev 2900, Denmark; Department of Cardiology, Copenhagen University Hospital, Herlev-Gentofte Hospital, Herlev 2900, Denmark
| | - Alex Hoerby Christensen
- Department of Clinical Medicine, University of Copenhagen, Copenhagen 1165, Denmark; Department of Cardiology, Copenhagen University Hospital, Herlev-Gentofte Hospital, Herlev 2900, Denmark
| | - Morten S Olesen
- Laboratory for Molecular Cardiology, Department of Cardiology, Rigshospitalet, Copenhagen University Hospital, Copenhagen 2100, Denmark; Laboratory for Molecular Cardiology, Department of Biomedical Sciences, University of Copenhagen, Copenhagen 1165, Denmark
| | - Jonas Ghouse
- Laboratory for Molecular Cardiology, Department of Cardiology, Rigshospitalet, Copenhagen University Hospital, Copenhagen 2100, Denmark; Laboratory for Molecular Cardiology, Department of Biomedical Sciences, University of Copenhagen, Copenhagen 1165, Denmark
| | - Karina Banasik
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Kirk U Knowlton
- Intermountain Medical Center, Intermountain Heart Institute, Salt Lake City, UT 84143, USA
| | - David O Arnar
- deCODE genetics/Amgen, Inc., Reykjavik 102, Iceland; Faculty of Medicine, University of Iceland, Vatnsmyrarvegur, Reykjavik 101, Iceland; Division of Cardiology, Department of Internal Medicine, Landspitali - National University Hospital of Iceland, Hringbraut, Reykjavik 101, Iceland
| | - Gudmundur Thorgeirsson
- deCODE genetics/Amgen, Inc., Reykjavik 102, Iceland; Faculty of Medicine, University of Iceland, Vatnsmyrarvegur, Reykjavik 101, Iceland; Division of Cardiology, Department of Internal Medicine, Landspitali - National University Hospital of Iceland, Hringbraut, Reykjavik 101, Iceland
| | - Lincoln Nadauld
- Precision Genomics, Intermountain Healthcare, Saint George, UT 84790, USA
| | - Sisse Rye Ostrowski
- Department of Clinical Medicine, University of Copenhagen, Copenhagen 1165, Denmark; Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen 2100, Denmark
| | - Henning Bundgaard
- Department of Clinical Medicine, University of Copenhagen, Copenhagen 1165, Denmark; Department of Cardiology, Rigshospitalet, Copenhagen University Hospital, Copenhagen 2100, Denmark
| | - Hilma Holm
- deCODE genetics/Amgen, Inc., Reykjavik 102, Iceland
| | | | - Kari Stefansson
- deCODE genetics/Amgen, Inc., Reykjavik 102, Iceland; Faculty of Medicine, University of Iceland, Vatnsmyrarvegur, Reykjavik 101, Iceland.
| | - Daniel F Gudbjartsson
- deCODE genetics/Amgen, Inc., Reykjavik 102, Iceland; School of Engineering and Natural Sciences, University of Iceland, Reykjavik 102, Iceland.
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25
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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: 9] [Impact Index Per Article: 9.0] [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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26
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Song B, Ning W, Wei D, Jiang M, Zhu K, Wang X, Edwards D, Odeny DA, Cheng S. Plant genome resequencing and population genomics: Current status and future prospects. MOLECULAR PLANT 2023; 16:1252-1268. [PMID: 37501370 DOI: 10.1016/j.molp.2023.07.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 05/30/2023] [Accepted: 07/25/2023] [Indexed: 07/29/2023]
Abstract
Advances in DNA sequencing technology have sparked a genomics revolution, driving breakthroughs in plant genetics and crop breeding. Recently, the focus has shifted from cataloging genetic diversity in plants to exploring their functional significance and delivering beneficial alleles for crop improvement. This transformation has been facilitated by the increasing adoption of whole-genome resequencing. In this review, we summarize the current progress of population-based genome resequencing studies and how these studies affect crop breeding. A total of 187 land plants from 163 countries have been resequenced, comprising 54 413 accessions. As part of resequencing efforts 367 traits have been surveyed and 86 genome-wide association studies have been conducted. Economically important crops, particularly cereals, vegetables, and legumes, have dominated the resequencing efforts, leaving a gap in 49 orders, including Lycopodiales, Liliales, Acorales, Austrobaileyales, and Commelinales. The resequenced germplasm is distributed across diverse geographic locations, providing a global perspective on plant genomics. We highlight genes that have been selected during domestication, or associated with agronomic traits, and form a repository of candidate genes for future research and application. Despite the opportunities for cross-species comparative genomics, many population genomic datasets are not accessible, impeding secondary analyses. We call for a more open and collaborative approach to population genomics that promotes data sharing and encourages contribution-based credit policy. The number of plant genome resequencing studies will continue to rise with the decreasing DNA sequencing costs, coupled with advances in analysis and computational technologies. This expansion, in terms of both scale and quality, holds promise for deeper insights into plant trait genetics and breeding design.
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Affiliation(s)
- Bo Song
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China
| | - Weidong Ning
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; Huazhong Agricultural University, College of Informatics, Hubei Key Laboratory of Agricultural Bioinformatics, Wuhan, Hubei, China
| | - Di Wei
- Biotechnology Research Institute, Guangxi Academy of Agricultural Sciences, Nanning 53007, China
| | - Mengyun Jiang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng 475004, China; Shenzhen Research Institute of Henan University, Shenzhen 518000, China
| | - Kun Zhu
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng 475004, China; Shenzhen Research Institute of Henan University, Shenzhen 518000, China
| | - Xingwei Wang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; State Key Laboratory of Crop Stress Adaptation and Improvement, School of Life Sciences, Henan University, Kaifeng 475004, China; Shenzhen Research Institute of Henan University, Shenzhen 518000, China
| | - David Edwards
- School of Biological Sciences and Institute of Agriculture, University of Western Australia, Perth, WA, Australia
| | - Damaris A Odeny
- International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) - Eastern and Southern Africa, Nairobi, Kenya
| | - Shifeng Cheng
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China.
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27
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Todd ET, Fromentier A, Sutcliffe R, Running Horse Collin Y, Perdereau A, Aury JM, Èche C, Bouchez O, Donnadieu C, Wincker P, Kalbfleisch T, Petersen JL, Orlando L. Imputed genomes of historical horses provide insights into modern breeding. iScience 2023; 26:107104. [PMID: 37416458 PMCID: PMC10319840 DOI: 10.1016/j.isci.2023.107104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 04/25/2023] [Accepted: 06/08/2023] [Indexed: 07/08/2023] Open
Abstract
Historical genomes can provide important insights into recent genomic changes in horses, especially the development of modern breeds. In this study, we characterized 8.7 million genomic variants from a panel of 430 horses from 73 breeds, including newly sequenced genomes from 20 Clydesdales and 10 Shire horses. We used this modern genomic variation to impute the genomes of four historically important horses, consisting of publicly available genomes from 2 Przewalski's horses, 1 Thoroughbred, and a newly sequenced Clydesdale. Using these historical genomes, we identified modern horses with higher genetic similarity to those in the past and unveiled increased inbreeding in recent times. We genotyped variants associated with appearance and behavior to uncover previously unknown characteristics of these important historical horses. Overall, we provide insights into the history of Thoroughbred and Clydesdale breeds and highlight genomic changes in the endangered Przewalski's horse following a century of captive breeding.
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Affiliation(s)
- Evelyn T. Todd
- Centre d’Anthropobiologie et de Génomique de Toulouse (CAGT), CNRS UMR 5288, Université Paul Sabatier, 37 Allées Jules Guesde, Bâtiment A, 31000 Toulouse, France
| | - Aurore Fromentier
- Centre d’Anthropobiologie et de Génomique de Toulouse (CAGT), CNRS UMR 5288, Université Paul Sabatier, 37 Allées Jules Guesde, Bâtiment A, 31000 Toulouse, France
| | - Richard Sutcliffe
- Glasgow Museums Resource Centre, 200 Woodhead Road, Nitshill, G53 7NN Glasgow, UK
| | - Yvette Running Horse Collin
- Centre d’Anthropobiologie et de Génomique de Toulouse (CAGT), CNRS UMR 5288, Université Paul Sabatier, 37 Allées Jules Guesde, Bâtiment A, 31000 Toulouse, France
| | - Aude Perdereau
- Genoscope, Institut de biologie François Jacob, CEA, Université d’Evry, Université Paris-Saclay, 91042 Evry, France
| | - Jean-Marc Aury
- Genoscope, Institut de biologie François Jacob, CEA, Université d’Evry, Université Paris-Saclay, 91042 Evry, France
| | - Camille Èche
- GeT-PlaGe - Génome et Transcriptome - Plateforme Génomique, GET - Plateforme Génome & Transcriptome, Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, 31326 Castanet-Tolosan Cedex, France
| | - Olivier Bouchez
- GeT-PlaGe - Génome et Transcriptome - Plateforme Génomique, GET - Plateforme Génome & Transcriptome, Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, 31326 Castanet-Tolosan Cedex, France
| | - Cécile Donnadieu
- GeT-PlaGe - Génome et Transcriptome - Plateforme Génomique, GET - Plateforme Génome & Transcriptome, Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, 31326 Castanet-Tolosan Cedex, France
| | - Patrick Wincker
- Genoscope, Institut de biologie François Jacob, CEA, Université d’Evry, Université Paris-Saclay, 91042 Evry, France
| | - Ted Kalbfleisch
- MH Gluck Equine Research Center, University of Kentucky, Lexington, KY 40546-0091, USA
| | - Jessica L. Petersen
- Department of Animal Science, University of Nebraska-Lincoln, 3940 Fair St, Lincoln, NE 68583-0908, USA
| | - Ludovic Orlando
- Centre d’Anthropobiologie et de Génomique de Toulouse (CAGT), CNRS UMR 5288, Université Paul Sabatier, 37 Allées Jules Guesde, Bâtiment A, 31000 Toulouse, France
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28
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Kristjansson RP, Oskarsson GR, Skuladottir A, Oddsson A, Rognvaldsson S, Sveinbjornsson G, Lund SH, Jensson BO, Styrmisdottir EL, Halldorsson GH, Ferkingstad E, Eldjarn GH, Beyter D, Kristmundsdottir S, Juliusson K, Fridriksdottir R, Arnadottir GA, Katrinardottir H, Snorradottir MH, Tragante V, Stefansdottir L, Ivarsdottir EV, Bjornsdottir G, Halldorsson BV, Thorleifsson G, Ludviksson BR, Onundarson PT, Saevarsdottir S, Melsted P, Norddahl GL, Bjornsdottir US, Olafsdottir T, Gudbjartsson DF, Thorsteinsdottir U, Jonsdottir I, Sulem P, Stefansson K. Sequence variant affects GCSAML splicing, mast cell specific proteins, and risk of urticaria. Commun Biol 2023; 6:703. [PMID: 37430141 DOI: 10.1038/s42003-023-05079-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Accepted: 06/28/2023] [Indexed: 07/12/2023] Open
Abstract
Urticaria is a skin disorder characterized by outbreaks of raised pruritic wheals. In order to identify sequence variants associated with urticaria, we performed a meta-analysis of genome-wide association studies for urticaria with a total of 40,694 cases and 1,230,001 controls from Iceland, the UK, Finland, and Japan. We also performed transcriptome- and proteome-wide analyses in Iceland and the UK. We found nine sequence variants at nine loci associating with urticaria. The variants are at genes participating in type 2 immune responses and/or mast cell biology (CBLB, FCER1A, GCSAML, STAT6, TPSD1, ZFPM1), the innate immunity (C4), and NF-κB signaling. The most significant association was observed for the splice-donor variant rs56043070[A] (hg38: chr1:247556467) in GCSAML (MAF = 6.6%, OR = 1.24 (95%CI: 1.20-1.28), P-value = 3.6 × 10-44). We assessed the effects of the variants on transcripts, and levels of proteins relevant to urticaria pathophysiology. Our results emphasize the role of type 2 immune response and mast cell activation in the pathogenesis of urticaria. Our findings may point to an IgE-independent urticaria pathway that could help address unmet clinical need.
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Affiliation(s)
| | - Gudjon R Oskarsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | | | | | | | | | | | | | | | | | - Snædis Kristmundsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Science and Engineering, Reykjavik University, Reykjavik, Iceland
| | | | | | | | | | | | | | | | - Erna V Ivarsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | - Bjarni V Halldorsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Science and Engineering, Reykjavik University, Reykjavik, Iceland
| | | | - Bjorn R Ludviksson
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
- Department of Immunology, Landspitali, the National University Hospital of Iceland, Reykjavik, Iceland
| | - Pall T Onundarson
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
- Department of Laboratory Hematology, Landspitali, the National University Hospital of Iceland, Reykjavik, Iceland
| | - Saedis Saevarsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
- Rheumatology Unit, Department of Medicine, Karolinska Institutet, Solna, Stockholm, Sweden
- Department of Medicine, Landspitali, the National University Hospital of Iceland, Reykjavik, Iceland
| | - Pall Melsted
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | - Unnur S Bjornsdottir
- Department of Medicine, Landspitali, the National University Hospital of Iceland, Reykjavik, Iceland
- The Medical Center Mjodd, Reykjavik, Iceland
| | - Thorunn Olafsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Daniel F Gudbjartsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Unnur Thorsteinsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Ingileif Jonsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | | | - Kari Stefansson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland.
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29
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Houwaart T, Scholz S, Pollock NR, Palmer WH, Kichula KM, Strelow D, Le DB, Belick D, Hülse L, Lautwein T, Wachtmeister T, Wollenweber TE, Henrich B, Köhrer K, Parham P, Guethlein LA, Norman PJ, Dilthey AT. Complete sequences of six major histocompatibility complex haplotypes, including all the major MHC class II structures. HLA 2023; 102:28-43. [PMID: 36932816 PMCID: PMC10986641 DOI: 10.1111/tan.15020] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 02/10/2023] [Accepted: 02/24/2023] [Indexed: 03/19/2023]
Abstract
Accurate and comprehensive immunogenetic reference panels are key to the successful implementation of population-scale immunogenomics. The 5Mbp Major Histocompatibility Complex (MHC) is the most polymorphic region of the human genome and associated with multiple immune-mediated diseases, transplant matching and therapy responses. Analysis of MHC genetic variation is severely complicated by complex patterns of sequence variation, linkage disequilibrium and a lack of fully resolved MHC reference haplotypes, increasing the risk of spurious findings on analyzing this medically important region. Integrating Illumina, ultra-long Nanopore, and PacBio HiFi sequencing as well as bespoke bioinformatics, we completed five of the alternative MHC reference haplotypes of the current (GRCh38/hg38) build of the human reference genome and added one other. The six assembled MHC haplotypes encompass the DR1 and DR4 haplotype structures in addition to the previously completed DR2 and DR3, as well as six distinct classes of the structurally variable C4 region. Analysis of the assembled haplotypes showed that MHC class II sequence structures, including repeat element positions, are generally conserved within the DR haplotype supergroups, and that sequence diversity peaks in three regions around HLA-A, HLA-B+C, and the HLA class II genes. Demonstrating the potential for improved short-read analysis, the number of proper read pairs recruited to the MHC was found to be increased by 0.06%-0.49% in a 1000 Genomes Project read remapping experiment with seven diverse samples. Furthermore, the assembled haplotypes can serve as references for the community and provide the basis of a structurally accurate genotyping graph of the complete MHC region.
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Affiliation(s)
- Torsten Houwaart
- Institute of Medical Microbiology and Hospital HygieneHeinrich Heine University DüsseldorfDüsseldorfGermany
| | - Stephan Scholz
- Institute of Medical Microbiology and Hospital HygieneHeinrich Heine University DüsseldorfDüsseldorfGermany
| | - Nicholas R. Pollock
- Department of Biomedical InformaticsAnschutz Medical Campus, University of ColoradoAuroraColoradoUSA
- Department of Immunology and MicrobiologyAnschutz Medical Campus, University of ColoradoAuroraColoradoUSA
| | - William H. Palmer
- Department of Biomedical InformaticsAnschutz Medical Campus, University of ColoradoAuroraColoradoUSA
- Department of Immunology and MicrobiologyAnschutz Medical Campus, University of ColoradoAuroraColoradoUSA
| | - Katherine M. Kichula
- Department of Biomedical InformaticsAnschutz Medical Campus, University of ColoradoAuroraColoradoUSA
- Department of Immunology and MicrobiologyAnschutz Medical Campus, University of ColoradoAuroraColoradoUSA
| | - Daniel Strelow
- Institute of Medical Microbiology and Hospital HygieneHeinrich Heine University DüsseldorfDüsseldorfGermany
| | - Duyen B. Le
- Institute of Medical Microbiology and Hospital HygieneHeinrich Heine University DüsseldorfDüsseldorfGermany
| | - Dana Belick
- Institute of Medical Microbiology and Hospital HygieneHeinrich Heine University DüsseldorfDüsseldorfGermany
| | - Lisanna Hülse
- Institute of Medical Microbiology and Hospital HygieneHeinrich Heine University DüsseldorfDüsseldorfGermany
| | - Tobias Lautwein
- Biologisch‐Medizinisches‐Forschungszentrum (BMFZ)Genomics & Transcriptomics Laboratory, Heinrich Heine University DüsseldorfDüsseldorfGermany
| | - Thorsten Wachtmeister
- Biologisch‐Medizinisches‐Forschungszentrum (BMFZ)Genomics & Transcriptomics Laboratory, Heinrich Heine University DüsseldorfDüsseldorfGermany
| | - Tassilo E. Wollenweber
- Biologisch‐Medizinisches‐Forschungszentrum (BMFZ)Genomics & Transcriptomics Laboratory, Heinrich Heine University DüsseldorfDüsseldorfGermany
| | - Birgit Henrich
- Institute of Medical Microbiology and Hospital HygieneHeinrich Heine University DüsseldorfDüsseldorfGermany
| | - Karl Köhrer
- Biologisch‐Medizinisches‐Forschungszentrum (BMFZ)Genomics & Transcriptomics Laboratory, Heinrich Heine University DüsseldorfDüsseldorfGermany
| | - Peter Parham
- Department of Structural Biology, and Department of Microbiology and ImmunologyStanford UniversityStanfordCaliforniaUSA
| | - Lisbeth A. Guethlein
- Department of Structural Biology, and Department of Microbiology and ImmunologyStanford UniversityStanfordCaliforniaUSA
| | - Paul J. Norman
- Department of Biomedical InformaticsAnschutz Medical Campus, University of ColoradoAuroraColoradoUSA
- Department of Immunology and MicrobiologyAnschutz Medical Campus, University of ColoradoAuroraColoradoUSA
| | - Alexander T. Dilthey
- Institute of Medical Microbiology and Hospital HygieneHeinrich Heine University DüsseldorfDüsseldorfGermany
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30
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Romain S, Lemaitre C. SVJedi-graph: improving the genotyping of close and overlapping structural variants with long reads using a variation graph. Bioinformatics 2023; 39:i270-i278. [PMID: 37387169 DOI: 10.1093/bioinformatics/btad237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/01/2023] Open
Abstract
MOTIVATION Structural variation (SV) is a class of genetic diversity whose importance is increasingly revealed by genome resequencing, especially with long-read technologies. One crucial problem when analyzing and comparing SVs in several individuals is their accurate genotyping, that is determining whether a described SV is present or absent in one sequenced individual, and if present, in how many copies. There are only a few methods dedicated to SV genotyping with long-read data, and all either suffer of a bias toward the reference allele by not representing equally all alleles, or have difficulties genotyping close or overlapping SVs due to a linear representation of the alleles. RESULTS We present SVJedi-graph, a novel method for SV genotyping that relies on a variation graph to represent in a single data structure all alleles of a set of SVs. The long reads are mapped on the variation graph and the resulting alignments that cover allele-specific edges in the graph are used to estimate the most likely genotype for each SV. Running SVJedi-graph on simulated sets of close and overlapping deletions showed that this graph model prevents the bias toward the reference alleles and allows maintaining high genotyping accuracy whatever the SV proximity, contrary to other state of the art genotypers. On the human gold standard HG002 dataset, SVJedi-graph obtained the best performances, genotyping 99.5% of the high confidence SV callset with an accuracy of 95% in less than 30 min. AVAILABILITY AND IMPLEMENTATION SVJedi-graph is distributed under an AGPL license and available on GitHub at https://github.com/SandraLouise/SVJedi-graph and as a BioConda package.
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Affiliation(s)
- Sandra Romain
- Univ Rennes, Inria, CNRS, IRISA, Rennes F-35000, France
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31
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Kosugi S, Kamatani Y, Harada K, Tomizuka K, Momozawa Y, Morisaki T, Terao C. Detection of trait-associated structural variations using short-read sequencing. CELL GENOMICS 2023; 3:100328. [PMID: 37388916 PMCID: PMC10300613 DOI: 10.1016/j.xgen.2023.100328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 02/17/2023] [Accepted: 04/25/2023] [Indexed: 07/01/2023]
Abstract
Genomic structural variation (SV) affects genetic and phenotypic characteristics in diverse organisms, but the lack of reliable methods to detect SV has hindered genetic analysis. We developed a computational algorithm (MOPline) that includes missing call recovery combined with high-confidence SV call selection and genotyping using short-read whole-genome sequencing (WGS) data. Using 3,672 high-coverage WGS datasets, MOPline stably detected ∼16,000 SVs per individual, which is over ∼1.7-3.3-fold higher than previous large-scale projects while exhibiting a comparable level of statistical quality metrics. We imputed SVs from 181,622 Japanese individuals for 42 diseases and 60 quantitative traits. A genome-wide association study with the imputed SVs revealed 41 top-ranked or nearly top-ranked genome-wide significant SVs, including 8 exonic SVs with 5 novel associations and enriched mobile element insertions. This study demonstrates that short-read WGS data can be used to identify rare and common SVs associated with a variety of traits.
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Affiliation(s)
- Shunichi Kosugi
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
| | - Yoichiro Kamatani
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5, Kashiwanoha, Kashiwa-shi, Chiba 277-8562, Japan
| | - Katsutoshi Harada
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
| | - Kohei Tomizuka
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama City, Kanagawa 230-0045, Japan
| | - Takayuki Morisaki
- Division of Molecular Pathology, Institute of Medical Science, The University of Tokyo, 4-6-1, Shirokane-dai, Minato-ku, Tokyo 108-8639, Japan
| | | | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- The Department of Applied Genetics, The School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
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32
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Gisladottir RS, Helgason A, Halldorsson BV, Helgason H, Borsky M, Chien YR, Gudnason J, Gudjonsson SA, Moisik S, Dediu D, Thorleifsson G, Tragante V, Bustamante M, Jonsdottir GA, Stefansdottir L, Rutsdottir G, Magnusson SH, Hardarson M, Ferkingstad E, Halldorsson GH, Rognvaldsson S, Skuladottir A, Ivarsdottir EV, Norddahl G, Thorgeirsson G, Jonsdottir I, Ulfarsson MO, Holm H, Stefansson H, Thorsteinsdottir U, Gudbjartsson DF, Sulem P, Stefansson K. Sequence variants affecting voice pitch in humans. SCIENCE ADVANCES 2023; 9:eabq2969. [PMID: 37294764 PMCID: PMC10256171 DOI: 10.1126/sciadv.abq2969] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 05/04/2023] [Indexed: 06/11/2023]
Abstract
The genetic basis of the human vocal system is largely unknown, as are the sequence variants that give rise to individual differences in voice and speech. Here, we couple data on diversity in the sequence of the genome with voice and vowel acoustics in speech recordings from 12,901 Icelanders. We show how voice pitch and vowel acoustics vary across the life span and correlate with anthropometric, physiological, and cognitive traits. We found that voice pitch and vowel acoustics have a heritable component and discovered correlated common variants in ABCC9 that associate with voice pitch. The ABCC9 variants also associate with adrenal gene expression and cardiovascular traits. By showing that voice and vowel acoustics are influenced by genetics, we have taken important steps toward understanding the genetics and evolution of the human vocal system.
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Affiliation(s)
- Rosa S. Gisladottir
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland
- Department of Icelandic and Comparative Cultural Studies, University of Iceland, Saemundargata 2, 102 Reykjavik, Iceland
| | - Agnar Helgason
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland
- Department of Anthropology, University of Iceland, Saemundargata 10, 102 Reykjavik, Iceland
| | - Bjarni V. Halldorsson
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland
- Department of Engineering, Reykjavik University, Menntavegur 1, 101 Reykjavik, Iceland
| | - Hannes Helgason
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland
| | - Michal Borsky
- Department of Engineering, Reykjavik University, Menntavegur 1, 101 Reykjavik, Iceland
| | - Yu-Ren Chien
- Department of Engineering, Reykjavik University, Menntavegur 1, 101 Reykjavik, Iceland
| | - Jon Gudnason
- Department of Engineering, Reykjavik University, Menntavegur 1, 101 Reykjavik, Iceland
| | | | - Scott Moisik
- Division of Linguistics and Multilingual Studies, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore
| | - Dan Dediu
- Department of Catalan Philology and General Linguistics, University of Barcelona, Gran Via 585, Barcelona 08007, Spain
- University of Barcelona Institute for Complex Systems (UBICS), Martí Franquès 1, Barcelona 08028, Spain
- Catalan Institute for Research and Advanced Studies (ICREA), Passeig Lluís Companys 23, Barcelona 08010, Spain
| | | | | | | | | | | | | | | | | | - Egil Ferkingstad
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland
| | - Gisli H. Halldorsson
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Dunhagi 5, 107 Reykjavik, Iceland
| | | | | | | | | | - Gudmundur Thorgeirsson
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Vatnsmyrarvegur 16, 101 Reykjavik, Iceland
| | - Ingileif Jonsdottir
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Vatnsmyrarvegur 16, 101 Reykjavik, Iceland
| | - Magnus O. Ulfarsson
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Dunhagi 5, 107 Reykjavik, Iceland
| | - Hilma Holm
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland
| | | | - Unnur Thorsteinsdottir
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Vatnsmyrarvegur 16, 101 Reykjavik, Iceland
| | - Daniel F. Gudbjartsson
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Dunhagi 5, 107 Reykjavik, Iceland
| | - Patrick Sulem
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland
| | - Kari Stefansson
- deCODE Genetics/Amgen Inc., Sturlugata 8, 101 Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Vatnsmyrarvegur 16, 101 Reykjavik, Iceland
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Iruegas-Bocardo F, Weisberg AJ, Riutta ER, Kilday K, Bonkowski JC, Creswell T, Daughtrey ML, Rane K, Grünwald NJ, Chang JH, Putnam ML. Whole Genome Sequencing-Based Tracing of a 2022 Introduction and Outbreak of Xanthomonas hortorum pv. pelargonii. PHYTOPATHOLOGY 2023; 113:975-984. [PMID: 36515656 DOI: 10.1094/phyto-09-22-0321-r] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Globalization has made agricultural commodities more accessible, available, and affordable. However, their global movement increases the potential for invasion by pathogens and necessitates development and implementation of sensitive, rapid, and scalable surveillance methods. Here, we used 35 strains, isolated by multiple diagnostic laboratories, as a case study for using whole genome sequence data in a plant disease diagnostic setting. Twenty-seven of the strains were isolated in 2022 and identified as Xanthomonas hortorum pv. pelargonii. Eighteen of these strains originated from material sold by a plant breeding company that had notified clients following a release of infected geranium cuttings. Analyses of whole genome sequences revealed epidemiological links among the 27 strains from different growers that confirmed a common source of the outbreak and uncovered likely secondary spread events within facilities that housed plants originating from different plant breeding companies. Whole genome sequencing data were also analyzed to reveal how preparatory and analytical methods can impact conclusions on outbreaks of clonal pathogenic strains. The results demonstrate the potential power of using whole genome sequencing among a network of diagnostic labs and highlight how sharing such data can help shorten response times to mitigate outbreaks more expediently and precisely than standard methods.
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Affiliation(s)
| | - Alexandra J Weisberg
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331
| | - Elizabeth R Riutta
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331
| | - Kameron Kilday
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331
| | - John C Bonkowski
- Botany and Plant Pathology, Purdue University, West Lafayette, IN 47907
| | - Tom Creswell
- Botany and Plant Pathology, Purdue University, West Lafayette, IN 47907
| | - Margery L Daughtrey
- Long Island Horticultural Research and Extension Center, Cornell University, Riverhead, NY 11901
| | - Karen Rane
- Department of Entomology, University of Maryland, College Park, MD 20742
| | - Niklaus J Grünwald
- Horticultural Crops Research Laboratory, U.S. Department of Agriculture-Agricultural Research Service, Corvallis, OR 97331
| | - Jeff H Chang
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331
| | - Melodie L Putnam
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331
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Nudel R, Christensen RV, Kalnak N, Schwinn M, Banasik K, Dinh KM, Erikstrup C, Pedersen OB, Burgdorf KS, Ullum H, Ostrowski SR, Hansen TF, Werge T. Developmental language disorder - a comprehensive study of more than 46,000 individuals. Psychiatry Res 2023; 323:115171. [PMID: 36963307 DOI: 10.1016/j.psychres.2023.115171] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 02/16/2023] [Accepted: 03/14/2023] [Indexed: 03/26/2023]
Abstract
Developmental language disorder (DLD) is characterized by enduring low language abilities with a significant functional impact, in the absence of biomedical conditions in which language impairment is part of a complex of impairments. There is a lack of awareness of DLD even among healthcare professionals. Here we estimated the prevalence of DLD and its links to reading and learning difficulties and physical and mental health in the Danish Blood Donor Study (N = 46,547), where DLD-related information is based on questionnaires (self-report). We compared the questionnaire-derived DLD status with the relevant language-related diagnoses from hospital registers. We also investigated the genetic architecture of DLD in a subset of the cohort (N = 18,380). DLD was significantly associated with reading and learning difficulties and poorer mental and physical health. DLD prevalence was 3.36%-3.70% based on questionnaires, compared with 0.04% in hospital registers. Our genetic analyses identified one genome-wide significant locus, but not a significant heritability estimate. Our study shows that DLD has health-related implications that may last into adulthood, and that DLD may be undiagnosed in general healthcare. Furthermore, DLD is likely more genetically heterogeneous than narrower developmental language phenotypes. Our results emphasize the need to raise awareness of DLD and consider criteria for molecular studies of DLD to reduce case heterogeneity.
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Affiliation(s)
- Ron Nudel
- CORE - Copenhagen Research Centre for Mental Health, Mental Health Centre Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark; iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Denmark.
| | - Rikke Vang Christensen
- Department of Nordic Studies and Linguistics, University of Copenhagen, Emil Holms Kanal 2, Copenhagen 2300, Denmark.
| | - Nelli Kalnak
- Department of Women's and Children's Health, Karolinska Institute, Stockholm, Sweden; Department of Speech-Language Pathology, Helsingborg Hospital, Helsingborg, Sweden.
| | - Michael Schwinn
- Department of Clinical Immunology, Copenhagen University Hospital, Copenhagen, Denmark
| | - Karina Banasik
- Novo Nordisk foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Khoa Manh Dinh
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark
| | | | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark; Department of Clinical Medicine, Aarhus University Hospital, Aarhus, Denmark
| | - Ole Birger Pedersen
- Department of Immunology, Næstved Hospital, Næstved, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Kristoffer Sølvsten Burgdorf
- Department of Immunology, Rigshospitalet, Copenhagen, Denmark; Translational Disease Systems Biology, Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Sisse Rye Ostrowski
- Department of Clinical Immunology, Copenhagen University Hospital, Copenhagen, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Thomas Folkmann Hansen
- Novo Nordisk foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; Danish Headache Center, Rigshospitalet Glostrup, Glostrup, Denmark
| | - Thomas Werge
- iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Denmark; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; Mental Health Centre Sct. Hans, Mental Health Services Copenhagen, Institute of Biological Psychiatry, Roskilde, Denmark
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35
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Shipilina D, Pal A, Stankowski S, Chan YF, Barton NH. On the origin and structure of haplotype blocks. Mol Ecol 2023; 32:1441-1457. [PMID: 36433653 PMCID: PMC10946714 DOI: 10.1111/mec.16793] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Revised: 11/16/2022] [Accepted: 11/18/2022] [Indexed: 11/27/2022]
Abstract
The term "haplotype block" is commonly used in the developing field of haplotype-based inference methods. We argue that the term should be defined based on the structure of the Ancestral Recombination Graph (ARG), which contains complete information on the ancestry of a sample. We use simulated examples to demonstrate key features of the relationship between haplotype blocks and ancestral structure, emphasizing the stochasticity of the processes that generate them. Even the simplest cases of neutrality or of a "hard" selective sweep produce a rich structure, often missed by commonly used statistics. We highlight a number of novel methods for inferring haplotype structure, based on the full ARG, or on a sequence of trees, and illustrate how they can be used to define haplotype blocks using an empirical data set. While the advent of new, computationally efficient methods makes it possible to apply these concepts broadly, they (and additional new methods) could benefit from adding features to explore haplotype blocks, as we define them. Understanding and applying the concept of the haplotype block will be essential to fully exploit long and linked-read sequencing technologies.
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Affiliation(s)
- Daria Shipilina
- Evolutionary Biology Program, Department of Ecology and Genetics (IEG), Uppsala University, Uppsala, Sweden
- Institute of Science and Technology Austria, Klosterneuburg, Austria
- Swedish Collegium for Advanced Study, Uppsala, Sweden
| | - Arka Pal
- Institute of Science and Technology Austria, Klosterneuburg, Austria
| | - Sean Stankowski
- Institute of Science and Technology Austria, Klosterneuburg, Austria
| | | | - Nicholas H Barton
- Institute of Science and Technology Austria, Klosterneuburg, Austria
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36
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Sirén J, Paten B. GBZ file format for pangenome graphs. Bioinformatics 2022; 38:5012-5018. [PMID: 36179091 PMCID: PMC9665857 DOI: 10.1093/bioinformatics/btac656] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 09/06/2022] [Accepted: 09/30/2022] [Indexed: 12/24/2022] Open
Abstract
MOTIVATION Pangenome graphs representing aligned genome assemblies are being shared in the text-based Graphical Fragment Assembly format. As the number of assemblies grows, there is a need for a file format that can store the highly repetitive data space efficiently. RESULTS We propose the GBZ file format based on data structures used in the Giraffe short-read aligner. The format provides good compression, and the files can be efficiently loaded into in-memory data structures. We provide compression and decompression tools and libraries for using GBZ graphs, and we show that they can be efficiently used on a variety of systems. AVAILABILITY AND IMPLEMENTATION C++ and Rust implementations are available at https://github.com/jltsiren/gbwtgraph and https://github.com/jltsiren/gbwt-rs, respectively. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Jouni Sirén
- Genomics Institute, University of California, Santa Cruz, CA 95064, USA
| | - Benedict Paten
- Genomics Institute, University of California, Santa Cruz, CA 95064, USA
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37
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Singh V, Pandey S, Bhardwaj A. From the reference human genome to human pangenome: Premise, promise and challenge. Front Genet 2022; 13:1042550. [PMID: 36437921 PMCID: PMC9684177 DOI: 10.3389/fgene.2022.1042550] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 10/21/2022] [Indexed: 11/11/2022] Open
Abstract
The Reference Human Genome remains the single most important resource for mapping genetic variations and assessing their impact. However, it is monophasic, incomplete and not representative of the variation that exists in the population. Given the extent of ethno-geographic diversity and the consequent diversity in clinical manifestations of these variations, population specific references were developed overtime. The dramatically plummeting cost of sequencing whole genomes and the advent of third generation long range sequencers allowing accurate, error free, telomere-to-telomere assemblies of human genomes present us with a unique and unprecedented opportunity to develop a more composite standard reference consisting of a collection of multiple genomes that capture the maximal variation existing in the population, with the deepest annotation possible, enabling a realistic, reliable and actionable estimation of clinical significance of specific variations. The Human Pangenome Project thus is a logical next step promising a more accurate and global representation of genomic variations. The pangenome effort must be reciprocally complemented with precise variant discovery tools and exhaustive annotation to ensure unambiguous clinical assessment of the variant in ethno-geographical context. Here we discuss a broad roadmap, the challenges and way forward in developing a universal pangenome reference including data visualization techniques and integration of prior knowledge base in the new graph based architecture and tools to submit, compare, query, annotate and retrieve relevant information from the pangenomes. The biggest challenge, however, will be the ethical, legal and social implications and the training of human resource to the new reference paradigm.
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Affiliation(s)
- Vipin Singh
- University Institute of Biotechnology, Chandigarh University, Mohali, India
| | - Shweta Pandey
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
- Bioinformatics Centre, CSIR-Institute of Microbial Technology, Chandigarh, India
| | - Anshu Bhardwaj
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
- Bioinformatics Centre, CSIR-Institute of Microbial Technology, Chandigarh, India
- *Correspondence: Anshu Bhardwaj,
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38
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Sveinbjornsson G, Ulfarsson MO, Thorolfsdottir RB, Jonsson BA, Einarsson E, Gunnlaugsson G, Rognvaldsson S, Arnar DO, Baldvinsson M, Bjarnason RG, Eiriksdottir T, Erikstrup C, Ferkingstad E, Halldorsson GH, Helgason H, Helgadottir A, Hindhede L, Hjorleifsson G, Jones D, Knowlton KU, Lund SH, Melsted P, Norland K, Olafsson I, Olafsson S, Oskarsson GR, Ostrowski SR, Pedersen OB, Snaebjarnarson AS, Sigurdsson E, Steinthorsdottir V, Schwinn M, Thorgeirsson G, Thorleifsson G, Jonsdottir I, Bundgaard H, Nadauld L, Bjornsson ES, Rulifson IC, Rafnar T, Norddahl GL, Thorsteinsdottir U, Sulem P, Gudbjartsson DF, Holm H, Stefansson K. Multiomics study of nonalcoholic fatty liver disease. Nat Genet 2022; 54:1652-1663. [PMID: 36280732 PMCID: PMC9649432 DOI: 10.1038/s41588-022-01199-5] [Citation(s) in RCA: 62] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 09/02/2022] [Indexed: 11/09/2022]
Abstract
Nonalcoholic fatty liver (NAFL) and its sequelae are growing health problems. We performed a genome-wide association study of NAFL, cirrhosis and hepatocellular carcinoma, and integrated the findings with expression and proteomic data. For NAFL, we utilized 9,491 clinical cases and proton density fat fraction extracted from 36,116 liver magnetic resonance images. We identified 18 sequence variants associated with NAFL and 4 with cirrhosis, and found rare, protective, predicted loss-of-function variants in MTARC1 and GPAM, underscoring them as potential drug targets. We leveraged messenger RNA expression, splicing and predicted coding effects to identify 16 putative causal genes, of which many are implicated in lipid metabolism. We analyzed levels of 4,907 plasma proteins in 35,559 Icelanders and 1,459 proteins in 47,151 UK Biobank participants, identifying multiple proteins involved in disease pathogenesis. We show that proteomics can discriminate between NAFL and cirrhosis. The present study provides insights into the development of noninvasive evaluation of NAFL and new therapeutic options.
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Affiliation(s)
| | - Magnus O Ulfarsson
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland.,Faculty of Electrical and Computer Engineering, University of Iceland, Reykjavik, Iceland
| | | | | | | | | | | | - David O Arnar
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland.,Faculty of Medicine, University of Iceland, Reykjavik, Iceland.,Internal Medicine and Emergency Services, Landspitali-The National University Hospital of Iceland, Reykjavik, Iceland
| | | | - Ragnar G Bjarnason
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland.,Children's Medical Center, Landspítali-The National University Hospital of Iceland, Reykjavík, Iceland
| | | | | | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark
| | | | | | | | | | - Lotte Hindhede
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark
| | | | - David Jones
- Intermountain Healthcare, St. George, UT, USA
| | | | | | - Pall Melsted
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland.,Faculty of Mechanical Engineering, Industrial Engineering and Computer Science, University of Iceland, Reykjavik, Iceland
| | | | - Isleifur Olafsson
- Clinical Laboratory Services, Diagnostics and Blood Bank, Landspitali-The National University Hospital of Iceland, Reykjavik, Iceland
| | - Sigurdur Olafsson
- Internal Medicine and Emergency Services, Landspitali-The National University Hospital of Iceland, Reykjavik, Iceland
| | | | - Sisse Rye Ostrowski
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Cophenhagen, Denmark.,Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Ole Birger Pedersen
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark.,Department of Clinical Immunology, Zealand University Hospital, Køge, Denmark
| | | | - Emil Sigurdsson
- Development Centre for Primary Health Care in Iceland, Reykjavík, Iceland.,Department of Family Medicine, University of Iceland, Reykjavik, Iceland
| | | | - Michael Schwinn
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Cophenhagen, Denmark
| | - Gudmundur Thorgeirsson
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland.,Internal Medicine and Emergency Services, Landspitali-The National University Hospital of Iceland, Reykjavik, Iceland
| | | | - Ingileif Jonsdottir
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland.,Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Henning Bundgaard
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark.,Department of Cardiology, The Heart Centre, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | | | - Einar S Bjornsson
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland.,Internal Medicine and Emergency Services, Landspitali-The National University Hospital of Iceland, Reykjavik, Iceland
| | | | | | | | - Unnur Thorsteinsdottir
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland.,Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | | | - Daniel F Gudbjartsson
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland.,Faculty of Electrical and Computer Engineering, University of Iceland, Reykjavik, Iceland.,School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Hilma Holm
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland
| | - Kari Stefansson
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland. .,Faculty of Medicine, University of Iceland, Reykjavik, Iceland.
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39
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Grytten I, Dagestad Rand K, Sandve GK. KAGE: fast alignment-free graph-based genotyping of SNPs and short indels. Genome Biol 2022; 23:209. [PMID: 36195962 PMCID: PMC9531401 DOI: 10.1186/s13059-022-02771-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Accepted: 09/09/2022] [Indexed: 11/10/2022] Open
Abstract
Genotyping is a core application of high-throughput sequencing. We present KAGE, a genotyper for SNPs and short indels that is inspired by recent developments within graph-based genome representations and alignment-free methods. KAGE uses a pan-genome representation of the population to efficiently and accurately predict genotypes. Two novel ideas improve both the speed and accuracy: a Bayesian model incorporates genotypes from thousands of individuals to improve prediction accuracy, and a computationally efficient method leverages correlation between variants. We show that the accuracy of KAGE is at par with the best existing alignment-free genotypers, while being an order of magnitude faster.
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Affiliation(s)
- Ivar Grytten
- Department of Informatics, University of Oslo, Gaustadalleen 23 B, 0371, Oslo, Norway. .,Centre for Bioinformatics, University of Oslo, Gaustadalleen 30, 0373, Oslo, Norway.
| | - Knut Dagestad Rand
- Department of Informatics, University of Oslo, Gaustadalleen 23 B, 0371, Oslo, Norway.,Centre for Bioinformatics, University of Oslo, Gaustadalleen 30, 0373, Oslo, Norway
| | - Geir Kjetil Sandve
- Department of Informatics, University of Oslo, Gaustadalleen 23 B, 0371, Oslo, Norway.,Centre for Bioinformatics, University of Oslo, Gaustadalleen 30, 0373, Oslo, Norway
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40
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Ros-Freixedes R, Johnsson M, Whalen A, Chen CY, Valente BD, Herring WO, Gorjanc G, Hickey JM. Genomic prediction with whole-genome sequence data in intensely selected pig lines. GENETICS SELECTION EVOLUTION 2022; 54:65. [PMID: 36153511 PMCID: PMC9509613 DOI: 10.1186/s12711-022-00756-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 09/05/2022] [Indexed: 12/03/2022]
Abstract
Background Early simulations indicated that whole-genome sequence data (WGS) could improve the accuracy of genomic predictions within and across breeds. However, empirical results have been ambiguous so far. Large datasets that capture most of the genomic diversity in a population must be assembled so that allele substitution effects are estimated with high accuracy. The objectives of this study were to use a large pig dataset from seven intensely selected lines to assess the benefits of using WGS for genomic prediction compared to using commercial marker arrays and to identify scenarios in which WGS provides the largest advantage. Methods We sequenced 6931 individuals from seven commercial pig lines with different numerical sizes. Genotypes of 32.8 million variants were imputed for 396,100 individuals (17,224 to 104,661 per line). We used BayesR to perform genomic prediction for eight complex traits. Genomic predictions were performed using either data from a standard marker array or variants preselected from WGS based on association tests. Results The accuracies of genomic predictions based on preselected WGS variants were not robust across traits and lines and the improvements in prediction accuracy that we achieved so far with WGS compared to standard marker arrays were generally small. The most favourable results for WGS were obtained when the largest training sets were available and standard marker arrays were augmented with preselected variants with statistically significant associations to the trait. With this method and training sets of around 80k individuals, the accuracy of within-line genomic predictions was on average improved by 0.025. With multi-line training sets, improvements of 0.04 compared to marker arrays could be expected. Conclusions Our results showed that WGS has limited potential to improve the accuracy of genomic predictions compared to marker arrays in intensely selected pig lines. Thus, although we expect that larger improvements in accuracy from the use of WGS are possible with a combination of larger training sets and optimised pipelines for generating and analysing such datasets, the use of WGS in the current implementations of genomic prediction should be carefully evaluated against the cost of large-scale WGS data on a case-by-case basis. Supplementary Information The online version contains supplementary material available at 10.1186/s12711-022-00756-0.
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41
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Megquier K, Turner-Maier J, Morrill K, Li X, Johnson J, Karlsson EK, London CA, Gardner HL. The genomic landscape of canine osteosarcoma cell lines reveals conserved structural complexity and pathway alterations. PLoS One 2022; 17:e0274383. [PMID: 36099278 PMCID: PMC9469990 DOI: 10.1371/journal.pone.0274383] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 08/25/2022] [Indexed: 01/09/2023] Open
Abstract
The characterization of immortalized canine osteosarcoma (OS) cell lines used for research has historically been based on phenotypic features such as cellular morphology and expression of bone specific markers. With the increasing use of these cell lines to investigate novel therapeutic approaches prior to in vivo translation, a much more detailed understanding regarding the genomic landscape of these lines is required to ensure accurate interpretation of findings. Here we report the first whole genome characterization of eight canine OS cell lines, including single nucleotide variants, copy number variants and other structural variants. Many alterations previously characterized in primary canine OS tissue were observed in these cell lines, including TP53 mutations, MYC copy number gains, loss of CDKN2A, PTEN, DLG2, MAGI2, and RB1 and structural variants involving SETD2, DLG2 and DMD. These data provide a new framework for understanding how best to incorporate in vitro findings generated using these cell lines into the design of future clinical studies involving dogs with spontaneous OS.
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Affiliation(s)
- Kate Megquier
- 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
| | - Kathleen Morrill
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- University of Massachusetts Chan Medical School, Worcester, Massachusetts, United States of America
| | - Xue Li
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- University of Massachusetts Chan Medical School, Worcester, Massachusetts, United States of America
| | - Jeremy Johnson
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Elinor K Karlsson
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- University of Massachusetts Chan Medical School, Worcester, Massachusetts, United States of America
| | - Cheryl A London
- Cummings School of Veterinary Medicine at Tufts University, North Grafton, Massachusetts, United States of America
| | - Heather L Gardner
- Cummings School of Veterinary Medicine at Tufts University, North Grafton, Massachusetts, United States of America
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42
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Todd ET, Tonasso-Calvière L, Chauvey L, Schiavinato S, Fages A, Seguin-Orlando A, Clavel P, Khan N, Pérez Pardal L, Patterson Rosa L, Librado P, Ringbauer H, Verdugo M, Southon J, Aury JM, Perdereau A, Vila E, Marzullo M, Prato O, Tecchiati U, Bagnasco Gianni G, Tagliacozzo A, Tinè V, Alhaique F, Cardoso JL, Valente MJ, Telles Antunes M, Frantz L, Shapiro B, Bradley DG, Boulbes N, Gardeisen A, Horwitz LK, Öztan A, Arbuckle BS, Onar V, Clavel B, Lepetz S, Vahdati AA, Davoudi H, Mohaseb A, Mashkour M, Bouchez O, Donnadieu C, Wincker P, Brooks SA, Beja-Pereira A, Wu DD, Orlando L. The genomic history and global expansion of domestic donkeys. Science 2022; 377:1172-1180. [PMID: 36074859 DOI: 10.1126/science.abo3503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
Donkeys transformed human history as essential beasts of burden for long-distance movement, especially across semi-arid and upland environments. They remain insufficiently studied despite globally expanding and providing key support to low- to middle-income communities. To elucidate their domestication history, we constructed a comprehensive genome panel of 207 modern and 31 ancient donkeys, as well as 15 wild equids. We found a strong phylogeographic structure in modern donkeys that supports a single domestication in Africa ~5000 BCE, followed by further expansions in this continent and Eurasia and ultimately returning to Africa. We uncover a previously unknown genetic lineage in the Levant ~200 BCE, which contributed increasing ancestry toward Asia. Donkey management involved inbreeding and the production of giant bloodlines at a time when mules were essential to the Roman economy and military.
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Affiliation(s)
- Evelyn T Todd
- Centre d'Anthropobiologie et de Génomique de Toulouse (CAGT), CNRS UMR 5288, Université Paul Sabatier, Toulouse 31000, France
| | - Laure Tonasso-Calvière
- Centre d'Anthropobiologie et de Génomique de Toulouse (CAGT), CNRS UMR 5288, Université Paul Sabatier, Toulouse 31000, France
| | - Loreleï Chauvey
- Centre d'Anthropobiologie et de Génomique de Toulouse (CAGT), CNRS UMR 5288, Université Paul Sabatier, Toulouse 31000, France
| | - Stéphanie Schiavinato
- Centre d'Anthropobiologie et de Génomique de Toulouse (CAGT), CNRS UMR 5288, Université Paul Sabatier, Toulouse 31000, France
| | - Antoine Fages
- Centre d'Anthropobiologie et de Génomique de Toulouse (CAGT), CNRS UMR 5288, Université Paul Sabatier, Toulouse 31000, France
| | - Andaine Seguin-Orlando
- Centre d'Anthropobiologie et de Génomique de Toulouse (CAGT), CNRS UMR 5288, Université Paul Sabatier, Toulouse 31000, France
| | - Pierre Clavel
- Centre d'Anthropobiologie et de Génomique de Toulouse (CAGT), CNRS UMR 5288, Université Paul Sabatier, Toulouse 31000, France
| | - Naveed Khan
- Centre d'Anthropobiologie et de Génomique de Toulouse (CAGT), CNRS UMR 5288, Université Paul Sabatier, Toulouse 31000, France.,Department of Biotechnology, Abdul Wali Khan University, Mardan 23200, Pakistan
| | - Lucía Pérez Pardal
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, Universidade do Porto, Vairão 4485-661, Portugal.,BIOPOLIS Program in Genomics, Biodiversity and Land Planning, Campus de Vairão, Universidade do Porto, Vairão 4485-661, Portugal
| | | | - Pablo Librado
- Centre d'Anthropobiologie et de Génomique de Toulouse (CAGT), CNRS UMR 5288, Université Paul Sabatier, Toulouse 31000, France
| | - Harald Ringbauer
- Department of Archaeogenetics, Max Planck Institute for Evolutionary Anthropology, Leipzig 04103, Germany
| | - Marta Verdugo
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin D02 PN40, Ireland
| | - John Southon
- Earth System Science Department, University of California, Irvine, CA 92697, USA
| | - Jean-Marc Aury
- Genoscope, Institut de biologie François Jacob, CEA, Université d'Evry, Université Paris-Saclay, Evry 91042, France
| | - Aude Perdereau
- Genoscope, Institut de biologie François Jacob, CEA, Université d'Evry, Université Paris-Saclay, Evry 91042, France
| | - Emmanuelle Vila
- Laboratoire Archéorient, Université Lyon 2, Lyon 69007, France
| | - Matilde Marzullo
- Dipartimento di Beni Culturali e Ambientali, Università degli Studi di Milano, Milan 20122, Italy
| | - Ornella Prato
- Dipartimento di Beni Culturali e Ambientali, Università degli Studi di Milano, Milan 20122, Italy
| | - Umberto Tecchiati
- Dipartimento di Beni Culturali e Ambientali, Università degli Studi di Milano, Milan 20122, Italy
| | - Giovanna Bagnasco Gianni
- Dipartimento di Beni Culturali e Ambientali, Università degli Studi di Milano, Milan 20122, Italy
| | | | - Vincenzo Tinè
- Soprintendenza archeologia belle arti e paesaggio per le province di Verona, Rovigo e Vicenza, Verona 37121, Italy
| | | | - João Luís Cardoso
- ICArEHB, Campus de Gambelas, University of Algarve, Faro 8005-139, Portugal.,Universidade Aberta, Lisbon 1269-001, Portugal
| | - Maria João Valente
- Faculdade de Ciências Humanas e Sociais, Centro de Estudos de Arqueologia, Artes e Ciências do Património, Universidade do Algarve, Faro 8000-117, Portugal
| | - Miguel Telles Antunes
- Centre for Research on Science and Geological Engineering, Universidade NOVA de Lisboa, Lisbon 1099-085, Portugal
| | - Laurent Frantz
- Palaeogenomics Group, Department of Veterinary Sciences, Ludwig Maximilian University, Munich 80539, Germany.,School of Biological and Behavioural Sciences, Queen Mary University of London, London E1 4DQ, United Kingdom
| | - 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
| | - Daniel G Bradley
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin D02 PN40, Ireland
| | - Nicolas Boulbes
- Institut de Paléontologie Humaine, Fondation Albert Ier, Paris / UMR 7194 HNHP, MNHN-CNRS-UPVD / EPCC Centre Européen de Recherche Préhistorique, Tautavel 66720, France
| | - Armelle Gardeisen
- Archéologie des Sociétés Méditéranéennes, Université Paul Valéry - Site Saint-Charles 2, Montpellier 34090, France
| | - Liora Kolska Horwitz
- National Natural History Collections, Edmond J. Safra Campus, Givat Ram, The Hebrew University, Jerusalem 9190401, Israel
| | - Aliye Öztan
- Archaeology Department, Ankara University, Ankara 06100, Turkey
| | - Benjamin S Arbuckle
- Department of Anthropology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Vedat Onar
- Osteoarchaeology Practice and Research Center and Department of Anatomy, Faculty of Veterinary Medicine, Istanbul University-Cerrahpaşa, Istanbul 34320, Turkey
| | - Benoît Clavel
- Archéozoologie, Archéobotanique, Sociétés, Pratiques et Environnements, Muséum National d'Histoire Naturelle, Paris 75005, France
| | - Sébastien Lepetz
- Archéozoologie, Archéobotanique, Sociétés, Pratiques et Environnements, Muséum National d'Histoire Naturelle, Paris 75005, France
| | - Ali Akbar Vahdati
- Provincial Office of the Iranian Center for Cultural Heritage, Handicrafts and Tourism Organisation, North Khorassan, Bojnord 9416745775, Iran
| | - Hossein Davoudi
- Archaezoology section, Bioarchaeology Laboratory of the Central Laboratory, University of Tehran, Tehran CP1417634934, Iran
| | - Azadeh Mohaseb
- Archéozoologie, Archéobotanique, Sociétés, Pratiques et Environnements, Muséum National d'Histoire Naturelle, Paris 75005, France.,Archaezoology section, Bioarchaeology Laboratory of the Central Laboratory, University of Tehran, Tehran CP1417634934, Iran
| | - Marjan Mashkour
- Archéozoologie, Archéobotanique, Sociétés, Pratiques et Environnements, Muséum National d'Histoire Naturelle, Paris 75005, France.,Archaezoology section, Bioarchaeology Laboratory of the Central Laboratory, University of Tehran, Tehran CP1417634934, Iran.,Department of Osteology, National Museum of Iran, Tehran 1136918111, Iran
| | - Olivier Bouchez
- GeT-PlaGe - Génome et Transcriptome - Plateforme Génomique, GET - Plateforme Génome & Transcriptome, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Castaneet-Tolosan Cedex 31326, France
| | - Cécile Donnadieu
- GeT-PlaGe - Génome et Transcriptome - Plateforme Génomique, GET - Plateforme Génome & Transcriptome, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Castaneet-Tolosan Cedex 31326, France
| | - Patrick Wincker
- Genoscope, Institut de biologie François Jacob, CEA, Université d'Evry, Université Paris-Saclay, Evry 91042, France
| | - Samantha A Brooks
- Department of Animal Science, UF Genetics Institute, University of Florida, Gainesville, FL 32610, USA
| | - Albano Beja-Pereira
- CIBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO Laboratório Associado, Campus de Vairão, Universidade do Porto, Vairão 4485-661, Portugal.,BIOPOLIS Program in Genomics, Biodiversity and Land Planning, Campus de Vairão, Universidade do Porto, Vairão 4485-661, Portugal.,DGAOT, Faculty of Sciences, Universidade do Porto, Porto 4169-007, Portugal.,Sustainable Agrifood Production Research Centre (GreenUPorto), Universidade do Porto, Vairão 4485-646, Portugal
| | - Dong-Dong Wu
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650201, China.,Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China
| | - Ludovic Orlando
- Centre d'Anthropobiologie et de Génomique de Toulouse (CAGT), CNRS UMR 5288, Université Paul Sabatier, Toulouse 31000, France
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43
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Olafsdottir TA, Bjarnadottir K, Norddahl GL, Halldorsson GH, Melsted P, Gunnarsdottir K, Ivarsdottir E, Olafsdottir T, Arnthorsson AO, Theodors F, Eythorsson E, Helgason D, Eggertsson HP, Masson G, Bjarnadottir S, Saevarsdottir S, Runolfsdottir HL, Olafsson I, Saemundsdottir J, Sigurdsson MI, Ingvarsson RF, Palsson R, Thorgeirsson G, Halldorsson BV, Holm H, Kristjansson M, Sulem P, Thorsteinsdottir U, Jonsdottir I, Gudbjartsson DF, Stefansson K. HLA alleles, disease severity, and age associate with T-cell responses following infection with SARS-CoV-2. Commun Biol 2022; 5:914. [PMID: 36068292 PMCID: PMC9446630 DOI: 10.1038/s42003-022-03893-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 08/25/2022] [Indexed: 12/12/2022] Open
Abstract
Memory T-cell responses following SARS-CoV-2 infection have been extensively investigated but many studies have been small with a limited range of disease severity. Here we analyze SARS-CoV-2 reactive T-cell responses in 768 convalescent SARS-CoV-2-infected (cases) and 500 uninfected (controls) Icelanders. The T-cell responses are stable three to eight months after SARS-CoV-2 infection, irrespective of disease severity and even those with the mildest symptoms induce broad and persistent T-cell responses. Robust CD4+ T-cell responses are detected against all measured proteins (M, N, S and S1) while the N protein induces strongest CD8+ T-cell responses. CD4+ T-cell responses correlate with disease severity, humoral responses and age, whereas CD8+ T-cell responses correlate with age and functional antibodies. Further, CD8+ T-cell responses associate with several class I HLA alleles. Our results, provide new insight into HLA restriction of CD8+ T-cell immunity and other factors contributing to heterogeneity of T-cell responses following SARS-CoV-2 infection. A study of 768 convalescent SARS CoV-2-infected and 500 uninfected Icelanders reveals broad and stable T-cell responses 3-8 months from infection. HLA alleles, disease severity, and age contribute to the heterogeneity of cellular immunity.
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Affiliation(s)
| | | | | | | | - Pall Melsted
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.,School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | | | | | - Elias Eythorsson
- Internal Medicine and Emergency Services, Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland
| | - Dadi Helgason
- Internal Medicine and Emergency Services, Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland
| | | | | | - Sólveig Bjarnadottir
- Internal Medicine and Emergency Services, Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland.,Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Saedis Saevarsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.,Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland.,Department of Medicine, Landspitali, The National University Hospital of Iceland, Reykjavik, Iceland
| | - Hrafnhildur L Runolfsdottir
- Internal Medicine and Emergency Services, Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland
| | - Isleifur Olafsson
- Clinical Laboratory Services, Diagnostics and Blood Bank, Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland
| | | | - Martin I Sigurdsson
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland.,Perioperative Services, Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland
| | - Ragnar F Ingvarsson
- Internal Medicine and Emergency Services, Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland
| | - Runolfur Palsson
- Internal Medicine and Emergency Services, Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland.,Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Gudmundur Thorgeirsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.,Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Bjarni V Halldorsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.,School of Science and Engineering, Reykjavik University, Reykjavík, Iceland
| | - Hilma Holm
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
| | - Mar Kristjansson
- Internal Medicine and Emergency Services, Landspitali - The National University Hospital of Iceland, Reykjavik, Iceland
| | | | - Unnur Thorsteinsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.,Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Ingileif Jonsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.,Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Daniel F Gudbjartsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.,School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Kari Stefansson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland. .,Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland.
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44
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Booyse RP, Twesigomwe D, Hazelhurst S. Characterization of POR haplotype distribution in African populations and comparison with other global populations. Pharmacogenomics 2022; 23:771-782. [PMID: 36043428 PMCID: PMC9531186 DOI: 10.2217/pgs-2022-0082] [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: 06/22/2022] [Accepted: 08/08/2022] [Indexed: 11/21/2022] Open
Abstract
Background & aim: POR is an enzyme that mediates electron transfer to enable the drug-metabolizing activity of CYP450 proteins. However, POR has been understudied in pharmacogenomics despite this vital role. This study aimed to characterize the genetic variation in POR across African populations and to compare the star allele (haplotype) distribution with that in other global populations. Materials & methods: POR star alleles were called from whole-genome sequencing data using the StellarPGx pipeline. Results: In addition to the common POR*1 and *28 (defined by rs1057868), five novel rare haplotypes were computationally inferred. No significant frequency differences were observed among the majority of African populations. However, POR*28 was observed at a higher frequency in individuals of non-African ancestry. Conclusion: This study highlights the distribution of POR alleles in Africa and across global populations with a view toward informing future precision medicine implementation.
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Affiliation(s)
- Ross P Booyse
- Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - David Twesigomwe
- Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Scott Hazelhurst
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- School of Electrical and Information Engineering, University of the Witwatersrand, Johannesburg, South Africa
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45
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Hunt M, Letcher B, Malone KM, Nguyen G, Hall MB, Colquhoun RM, Lima L, Schatz MC, Ramakrishnan S, Iqbal Z. Minos: variant adjudication and joint genotyping of cohorts of bacterial genomes. Genome Biol 2022; 23:147. [PMID: 35791022 PMCID: PMC9254434 DOI: 10.1186/s13059-022-02714-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 06/20/2022] [Indexed: 12/30/2022] Open
Abstract
There are many short-read variant-calling tools, with different strengths and weaknesses. We present a tool, Minos, which combines outputs from arbitrary variant callers, increasing recall without loss of precision. We benchmark on 62 samples from three bacterial species and an outbreak of 385 Mycobacterium tuberculosis samples. Minos also enables joint genotyping; we demonstrate on a large (N=13k) M. tuberculosis cohort, building a map of non-synonymous SNPs and indels in a region where all such variants are assumed to cause rifampicin resistance. We quantify the correlation with phenotypic resistance and then replicate in a second cohort (N=10k).
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Affiliation(s)
- Martin Hunt
- EMBL-EBI, Cambridge, UK
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | | | | | | | | | - Rachel M Colquhoun
- Institute of Evolutionary Biology, Ashworth Laboratories, University of Edinburgh, Edinburgh, UK
| | | | - Michael C Schatz
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
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Halldorsson BV, Eggertsson HP, Moore KHS, Hauswedell H, Eiriksson O, Ulfarsson MO, Palsson G, Hardarson MT, Oddsson A, Jensson BO, Kristmundsdottir S, Sigurpalsdottir BD, Stefansson OA, Beyter D, Holley G, Tragante V, Gylfason A, Olason PI, Zink F, Asgeirsdottir M, Sverrisson ST, Sigurdsson B, Gudjonsson SA, Sigurdsson GT, Halldorsson GH, Sveinbjornsson G, Norland K, Styrkarsdottir U, Magnusdottir DN, Snorradottir S, Kristinsson K, Sobech E, Jonsson H, Geirsson AJ, Olafsson I, Jonsson P, Pedersen OB, Erikstrup C, Brunak S, Ostrowski SR, Thorleifsson G, Jonsson F, Melsted P, Jonsdottir I, Rafnar T, Holm H, Stefansson H, Saemundsdottir J, Gudbjartsson DF, Magnusson OT, Masson G, Thorsteinsdottir U, Helgason A, Jonsson H, Sulem P, Stefansson K. The sequences of 150,119 genomes in the UK Biobank. Nature 2022; 607:732-740. [PMID: 35859178 PMCID: PMC9329122 DOI: 10.1038/s41586-022-04965-x] [Citation(s) in RCA: 164] [Impact Index Per Article: 82.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 06/10/2022] [Indexed: 12/25/2022]
Abstract
Detailed knowledge of how diversity in the sequence of the human genome affects phenotypic diversity depends on a comprehensive and reliable characterization of both sequences and phenotypic variation. Over the past decade, insights into this relationship have been obtained from whole-exome sequencing or whole-genome sequencing of large cohorts with rich phenotypic data1,2. Here we describe the analysis of whole-genome sequencing of 150,119 individuals from the UK Biobank3. This constitutes a set of high-quality variants, including 585,040,410 single-nucleotide polymorphisms, representing 7.0% of all possible human single-nucleotide polymorphisms, and 58,707,036 indels. This large set of variants allows us to characterize selection based on sequence variation within a population through a depletion rank score of windows along the genome. Depletion rank analysis shows that coding exons represent a small fraction of regions in the genome subject to strong sequence conservation. We define three cohorts within the UK Biobank: a large British Irish cohort, a smaller African cohort and a South Asian cohort. A haplotype reference panel is provided that allows reliable imputation of most variants carried by three or more sequenced individuals. We identified 895,055 structural variants and 2,536,688 microsatellites, groups of variants typically excluded from large-scale whole-genome sequencing studies. Using this formidable new resource, we provide several examples of trait associations for rare variants with large effects not found previously through studies based on whole-exome sequencing and/or imputation.
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Affiliation(s)
- Bjarni V Halldorsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland. .,School of Technology, Reykjavik University, Reykjavik, Iceland.
| | | | | | | | | | - Magnus O Ulfarsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.,School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | - Marteinn T Hardarson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.,School of Technology, Reykjavik University, Reykjavik, Iceland
| | | | | | - Snaedis Kristmundsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.,School of Technology, Reykjavik University, Reykjavik, Iceland
| | - Brynja D Sigurpalsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.,School of Technology, Reykjavik University, Reykjavik, Iceland
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Helgi Jonsson
- Landspitali-University Hospital, Reykjavik, Iceland.,Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | - Palmi Jonsson
- Landspitali-University Hospital, Reykjavik, Iceland.,Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Ole Birger Pedersen
- Department of Clinical Immunology, Zealand University Hospital, Køge, Denmark
| | - Christian Erikstrup
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.,Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark
| | - Søren Brunak
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Sisse Rye Ostrowski
- Department of Clinical Immunology, Copenhagen University Hospital (Rigshospitalet), Copenhagen, Denmark.,Department of Clinical Medicine, Faculty of Health and Clinical Sciences, Copenhagen University, Copenhagen, Denmark
| | | | | | | | - Pall Melsted
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.,School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Ingileif Jonsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.,Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | | | - Hilma Holm
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
| | | | | | - Daniel F Gudbjartsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.,School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | - Unnur Thorsteinsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.,Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Agnar Helgason
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.,Department of Anthropology, University of Iceland, Reykjavik, Iceland
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The human "contaminome": bacterial, viral, and computational contamination in whole genome sequences from 1000 families. Sci Rep 2022; 12:9863. [PMID: 35701436 PMCID: PMC9198055 DOI: 10.1038/s41598-022-13269-z] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Accepted: 05/18/2022] [Indexed: 01/11/2023] Open
Abstract
The unmapped readspace of whole genome sequencing data tends to be large but is often ignored. We posit that it contains valuable signals of both human infection and contamination. Using unmapped and poorly aligned reads from whole genome sequences (WGS) of over 1000 families and nearly 5000 individuals, we present insights into common viral, bacterial, and computational contamination that plague whole genome sequencing studies. We present several notable results: (1) In addition to known contaminants such as Epstein-Barr virus and phiX, sequences from whole blood and lymphocyte cell lines contain many other contaminants, likely originating from storage, prep, and sequencing pipelines. (2) Sequencing plate and biological sample source of a sample strongly influence contamination profile. And, (3) Y-chromosome fragments not on the human reference genome commonly mismap to bacterial reference genomes. Both experiment-derived and computational contamination is prominent in next-generation sequencing data. Such contamination can compromise results from WGS as well as metagenomics studies, and standard protocols for identifying and removing contamination should be developed to ensure the fidelity of sequencing-based studies.
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48
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Genetic architecture of band neutrophil fraction in Iceland. Commun Biol 2022; 5:525. [PMID: 35650273 PMCID: PMC9160026 DOI: 10.1038/s42003-022-03462-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2021] [Accepted: 05/09/2022] [Indexed: 11/22/2022] Open
Abstract
The characteristic lobulated nuclear morphology of granulocytes is partially determined by composition of nuclear envelope proteins. Abnormal nuclear morphology is primarily observed as an increased number of hypolobulated immature neutrophils, called band cells, during infection or in rare envelopathies like Pelger-Huët anomaly. To search for sequence variants affecting nuclear morphology of granulocytes, we performed a genome-wide association study using band neutrophil fraction from 88,101 Icelanders. We describe 13 sequence variants affecting band neutrophil fraction at nine loci. Five of the variants are at the Lamin B receptor (LBR) locus, encoding an inner nuclear membrane protein. Mutations in LBR are linked to Pelger-Huët anomaly. In addition, we identify cosegregation of a rare stop-gain sequence variant in LBR and Pelger Huët anomaly in an Icelandic eight generation pedigree, initially reported in 1963. Two of the other loci include genes which, like LBR, play a role in the nuclear membrane function and integrity. These GWAS results highlight the role proteins of the inner nuclear membrane have as important for neutrophil nuclear morphology. A GWAS in Iceland reveals that variants in inner nuclear membrane proteins are associated with nuclear morphology of granulocytes and band neutrophil fraction.
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Quan C, Lu H, Lu Y, Zhou G. Population-scale genotyping of structural variation in the era of long-read sequencing. Comput Struct Biotechnol J 2022; 20:2639-2647. [PMID: 35685364 PMCID: PMC9163579 DOI: 10.1016/j.csbj.2022.05.047] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 05/24/2022] [Accepted: 05/24/2022] [Indexed: 11/29/2022] Open
Abstract
Population-scale studies of structural variation (SV) are growing rapidly worldwide with the development of long-read sequencing technology, yielding a considerable number of novel SVs and complete gap-closed genome assemblies. Herein, we highlight recent studies using a hybrid sequencing strategy and present the challenges toward large-scale genotyping for SVs due to the reference bias. Genotyping SVs at a population scale remains challenging, which severely impacts genotype-based population genetic studies or genome-wide association studies of complex diseases. We summarize academic efforts to improve genotype quality through linear or graph representations of reference and alternative alleles. Graph-based genotypers capable of integrating diverse genetic information are effectively applied to large and diverse cohorts, contributing to unbiased downstream analysis. Meanwhile, there is still an urgent need in this field for efficient tools to construct complex graphs and perform sequence-to-graph alignments.
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Affiliation(s)
- Cheng Quan
- Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, Beijing 100850, PR China
| | - Hao Lu
- Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, Beijing 100850, PR China
| | - Yiming Lu
- Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, Beijing 100850, PR China
- Hebei University, Baoding, Hebei Province 071002, PR China
- Corresponding authors at: Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing 100850, PR China (G. Zhou). Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing, 100850, PR China (Y. Lu).
| | - Gangqiao Zhou
- Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, Beijing 100850, PR China
- Collaborative Innovation Center for Personalized Cancer Medicine, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu Province 211166, PR China
- Medical College of Guizhou University, Guiyang, Guizhou Province 550025, PR China
- Hebei University, Baoding, Hebei Province 071002, PR China
- Corresponding authors at: Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing 100850, PR China (G. Zhou). Department of Genetics & Integrative Omics, State Key Laboratory of Proteomics, National Center for Protein Sciences, Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing, 100850, PR China (Y. Lu).
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50
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Einarsson H, Runarsdottir JR, Tryggvason T, Snaebjornsson P, Smaradottir A, Stefansdottir V, Thoroddsen A, Arngrimsson R, Jonasson JG, Haraldsdottir S. Universal tumor screening in a population with MSH6- and PMS2-associated Lynch syndrome. Genet Med 2022; 24:999-1007. [PMID: 35172941 DOI: 10.1016/j.gim.2022.01.012] [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: 08/30/2021] [Revised: 01/17/2022] [Accepted: 01/19/2022] [Indexed: 10/19/2022] Open
Abstract
PURPOSE Universal screening for Lynch syndrome (LS) on resected colorectal carcinomas (CRCs) and endometrial carcinomas (ECs) was implemented in Iceland in 2017 using immunohistochemistry (IHC) for mismatch repair (MMR) proteins. We examined the efficacy of the universal screening algorithm to detect LS and the diagnostic accuracy of MMR IHC by comparing results with a population-based genotype database. METHODS All patients diagnosed with CRC or EC per the Icelandic Cancer Registry from 2017 to 2019 who had tumor MMR IHC performed were included. Pathology reports and patient charts were reviewed. MMR IHC stains were crossmatched with genotyping results obtained from the deCODE database. RESULTS IHC staining was done on 404 patients with CRC and 74 patients with EC. A total of 61 (15.1%) patients with CRC and 15 (20.3%) patients with EC were MMR-deficient. MMR IHC had 88.9% sensitivity in identifying patients with LS and a positive predictive value of 10.7%. Only 50% of individuals were appropriately referred for genetic testing, leading to underdiagnosis of LS. CONCLUSION Universal screening for LS using MMR protein IHC in CRC and EC accurately identified patients appropriate for genetic testing in a population with MSH6 and PMS2 LS predominance. Because of lack of referral to genetic counseling, only 50% of patients with LS were identified through the screening algorithm.
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Affiliation(s)
- Haukur Einarsson
- Department of Pathology, Landspitali University Hospital of Iceland, Reykjavik, Iceland
| | | | - Thordur Tryggvason
- Department of Pathology, Landspitali University Hospital of Iceland, Reykjavik, Iceland
| | - Petur Snaebjornsson
- Department of Pathology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Agnes Smaradottir
- Department of Oncology, Landspitali University Hospital of Iceland, Reykjavik, Iceland
| | - Vigdis Stefansdottir
- Department of Genetics and Molecular Medicine, Landspitali University Hospital of Iceland, Reykjavik, Iceland
| | - Asgeir Thoroddsen
- Department of Obstetrics and Gynecology, Landspitali University Hospital of Iceland, Reykjavik, Iceland
| | - Reynir Arngrimsson
- Department of Genetics and Molecular Medicine, Landspitali University Hospital of Iceland, Reykjavik, Iceland; Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Jon Gunnlaugur Jonasson
- Department of Pathology, Landspitali University Hospital of Iceland, Reykjavik, Iceland; Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Sigurdis Haraldsdottir
- Department of Oncology, Landspitali University Hospital of Iceland, Reykjavik, Iceland; Faculty of Medicine, University of Iceland, Reykjavik, Iceland.
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