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Bouwman AC, Daetwyler HD, Chamberlain AJ, Ponce CH, Sargolzaei M, Schenkel FS, Sahana G, Govignon-Gion A, Boitard S, Dolezal M, Pausch H, Brøndum RF, Bowman PJ, Thomsen B, Guldbrandtsen B, Lund MS, Servin B, Garrick DJ, Reecy J, Vilkki J, Bagnato A, Wang M, Hoff JL, Schnabel RD, Taylor JF, Vinkhuyzen AAE, Panitz F, Bendixen C, Holm LE, Gredler B, Hozé C, Boussaha M, Sanchez MP, Rocha D, Capitan A, Tribout T, Barbat A, Croiseau P, Drögemüller C, Jagannathan V, Vander Jagt C, Crowley JJ, Bieber A, Purfield DC, Berry DP, Emmerling R, Götz KU, Frischknecht M, Russ I, Sölkner J, Van Tassell CP, Fries R, Stothard P, Veerkamp RF, Boichard D, Goddard ME, Hayes BJ. Meta-analysis of genome-wide association studies for cattle stature identifies common genes that regulate body size in mammals. Nat Genet 2018; 50:362-367. [PMID: 29459679 DOI: 10.1038/s41588-018-0056-5] [Citation(s) in RCA: 173] [Impact Index Per Article: 28.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2016] [Accepted: 01/03/2018] [Indexed: 11/09/2022]
Abstract
Stature is affected by many polymorphisms of small effect in humans 1 . In contrast, variation in dogs, even within breeds, has been suggested to be largely due to variants in a small number of genes2,3. Here we use data from cattle to compare the genetic architecture of stature to those in humans and dogs. We conducted a meta-analysis for stature using 58,265 cattle from 17 populations with 25.4 million imputed whole-genome sequence variants. Results showed that the genetic architecture of stature in cattle is similar to that in humans, as the lead variants in 163 significantly associated genomic regions (P < 5 × 10-8) explained at most 13.8% of the phenotypic variance. Most of these variants were noncoding, including variants that were also expression quantitative trait loci (eQTLs) and in ChIP-seq peaks. There was significant overlap in loci for stature with humans and dogs, suggesting that a set of common genes regulates body size in mammals.
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Affiliation(s)
- Aniek C Bouwman
- Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, Wageningen, the Netherlands
| | - Hans D Daetwyler
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport and Resources, Bundoora, Victoria, Australia.,School of Applied Systems Biology, La Trobe University, Bundoora, Victoria, Australia
| | - Amanda J Chamberlain
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport and Resources, Bundoora, Victoria, Australia
| | - Carla Hurtado Ponce
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport and Resources, Bundoora, Victoria, Australia.,Faculty of Land and Food Resources, University of Melbourne, Parkville, Victoria, Australia
| | - Mehdi Sargolzaei
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, Ontario, Canada.,The Semex Alliance, Guelph, Ontario, Canada
| | - Flavio S Schenkel
- Centre for Genetic Improvement of Livestock, Department of Animal Biosciences, University of Guelph, Guelph, Ontario, Canada
| | - Goutam Sahana
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
| | | | - Simon Boitard
- Section for Molecular Genetics and Systems Biology. Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
| | - Marlies Dolezal
- Platform of Bioinformatics and Statistics, University of Veterinary Medicine, Vienna, Austria
| | - Hubert Pausch
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport and Resources, Bundoora, Victoria, Australia.,Chair of Animal Breeding, Technische Universität München, Freising-Weihenstephan, Germany.,Animal Genomics, ETH Zurich, Zurich, Switzerland
| | - Rasmus F Brøndum
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
| | - Phil J Bowman
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport and Resources, Bundoora, Victoria, Australia
| | - Bo Thomsen
- Section for Molecular Genetics and Systems Biology. Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
| | - Bernt Guldbrandtsen
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
| | - Mogens S Lund
- Center for Quantitative Genetics and Genomics, Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
| | - Bertrand Servin
- GenPhySE, Université de Toulouse, INRA, INPT, INP-ENVT, Castanet-Tolosan, France
| | - Dorian J Garrick
- Department of Animal Science, Iowa State University, Ames, IA, USA
| | - James Reecy
- Department of Animal Science, Iowa State University, Ames, IA, USA
| | - Johanna Vilkki
- Green Technology, Natural Resources Institute Finland (Luke), Jokioinen, Finland
| | | | - Min Wang
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport and Resources, Bundoora, Victoria, Australia.,School of Applied Systems Biology, La Trobe University, Bundoora, Victoria, Australia
| | - Jesse L Hoff
- Division of Animal Sciences, University of Missouri, Columbia, MO, USA
| | - Robert D Schnabel
- Division of Animal Sciences, University of Missouri, Columbia, MO, USA
| | - Jeremy F Taylor
- Division of Animal Sciences, University of Missouri, Columbia, MO, USA
| | - Anna A E Vinkhuyzen
- University of Queensland, Institute for Molecular Bioscience, St Lucia, Queensland, Australia.,University of Queensland, Queensland Brain Institute, St Lucia, Queensland, Australia
| | - Frank Panitz
- Section for Molecular Genetics and Systems Biology. Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
| | - Christian Bendixen
- Section for Molecular Genetics and Systems Biology. Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
| | - Lars-Erik Holm
- Section for Molecular Genetics and Systems Biology. Department of Molecular Biology and Genetics, Aarhus University, Tjele, Denmark
| | | | - Chris Hozé
- GABI, INRA, AgroParisTech, Université Paris Saclay, Jouy-en-Josas, France.,Allice, Paris, France
| | - Mekki Boussaha
- GABI, INRA, AgroParisTech, Université Paris Saclay, Jouy-en-Josas, France
| | | | - Dominique Rocha
- GABI, INRA, AgroParisTech, Université Paris Saclay, Jouy-en-Josas, France
| | - Aurelien Capitan
- GABI, INRA, AgroParisTech, Université Paris Saclay, Jouy-en-Josas, France.,Allice, Paris, France
| | - Thierry Tribout
- GABI, INRA, AgroParisTech, Université Paris Saclay, Jouy-en-Josas, France
| | - Anne Barbat
- GABI, INRA, AgroParisTech, Université Paris Saclay, Jouy-en-Josas, France
| | - Pascal Croiseau
- GABI, INRA, AgroParisTech, Université Paris Saclay, Jouy-en-Josas, France
| | | | | | - Christy Vander Jagt
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport and Resources, Bundoora, Victoria, Australia
| | | | - Anna Bieber
- Research Institute of Organic Agriculture (FiBL), Frick, Switzerland
| | - Deirdre C Purfield
- Animal & Grassland Research and Innovation Centre, Teagasc, Moorepark, Ireland
| | - Donagh P Berry
- Animal & Grassland Research and Innovation Centre, Teagasc, Moorepark, Ireland
| | - Reiner Emmerling
- Institute of Animal Breeding, Bavarian State Research Centre for Agriculture, Poing, Germany
| | - Kay-Uwe Götz
- Institute of Animal Breeding, Bavarian State Research Centre for Agriculture, Poing, Germany
| | | | | | - Johann Sölkner
- University of Natural Resources and Life Sciences, Vienna, Austria
| | - Curtis P Van Tassell
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, US Department of Agriculture, Beltsville, MD, USA
| | - Ruedi Fries
- Chair of Animal Breeding, Technische Universität München, Freising-Weihenstephan, Germany
| | - Paul Stothard
- Department of Agricultural, Food and Nutritional Science/Livestock Gentec, University of Alberta, Edmonton, Alberta, Canada
| | - Roel F Veerkamp
- Animal Breeding and Genomics Centre, Wageningen UR Livestock Research, Wageningen, the Netherlands
| | - Didier Boichard
- GABI, INRA, AgroParisTech, Université Paris Saclay, Jouy-en-Josas, France
| | - Mike E Goddard
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport and Resources, Bundoora, Victoria, Australia.,Faculty of Land and Food Resources, University of Melbourne, Parkville, Victoria, Australia
| | - Ben J Hayes
- AgriBio, Centre for AgriBioscience, Department of Economic Development, Jobs, Transport and Resources, Bundoora, Victoria, Australia. .,Queensland Alliance for Agriculture and Food Innovation, Centre for Animal Science, University of Queensland, St Lucia, Queensland, Australia.
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Sanchez MP, Govignon-Gion A, Croiseau P, Fritz S, Hozé C, Miranda G, Martin P, Barbat-Leterrier A, Letaïef R, Rocha D, Brochard M, Boussaha M, Boichard D. Within-breed and multi-breed GWAS on imputed whole-genome sequence variants reveal candidate mutations affecting milk protein composition in dairy cattle. Genet Sel Evol 2017; 49:68. [PMID: 28923017 PMCID: PMC5604355 DOI: 10.1186/s12711-017-0344-z] [Citation(s) in RCA: 77] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2017] [Accepted: 08/30/2017] [Indexed: 01/06/2023] Open
Abstract
Background Genome-wide association studies (GWAS) were performed at the sequence level to identify candidate mutations that affect the expression of six major milk proteins in Montbéliarde (MON), Normande (NOR), and Holstein (HOL) dairy cattle. Whey protein (α-lactalbumin and β-lactoglobulin) and casein (αs1, αs2, β, and κ) contents were estimated by mid-infrared (MIR) spectrometry, with medium to high accuracy (0.59 ≤ R2 ≤ 0.92), for 848,068 test-day milk samples from 156,660 cows in the first three lactations. Milk composition was evaluated as average test-day measurements adjusted for environmental effects. Next, we genotyped a subset of 8080 cows (2967 MON, 2737 NOR, and 2306 HOL) with the BovineSNP50 Beadchip. For each breed, genotypes were first imputed to high-density (HD) using HD single nucleotide polymorphisms (SNPs) genotypes of 522 MON, 546 NOR, and 776 HOL bulls. The resulting HD SNP genotypes were subsequently imputed to the sequence level using 27 million high-quality sequence variants selected from Run4 of the 1000 Bull Genomes consortium (1147 bulls). Within-breed, multi-breed, and conditional GWAS were performed. Results Thirty-four distinct genomic regions were identified. Three regions on chromosomes 6, 11, and 20 had very significant effects on milk composition and were shared across the three breeds. Other significant effects, which partially overlapped across breeds, were found on almost all the autosomes. Multi-breed analyses provided a larger number of significant genomic regions with smaller confidence intervals than within-breed analyses. Combinations of within-breed, multi-breed, and conditional analyses led to the identification of putative causative variants in several candidate genes that presented significant protein–protein interactions enrichment, including those with previously described effects on milk composition (SLC37A1, MGST1, ABCG2, CSN1S1, CSN2, CSN1S2, CSN3, PAEP, DGAT1, AGPAT6) and those with effects reported for the first time here (ALPL, ANKH, PICALM). Conclusions GWAS applied to fine-scale phenotypes, multiple breeds, and whole-genome sequences seems to be effective to identify candidate gene variants. However, although we identified functional links between some candidate genes and milk phenotypes, the causality between candidate variants and milk protein composition remains to be demonstrated. Nevertheless, the identification of potential causative mutations that underlie milk protein composition may have immediate applications for improvements in cheese-making. Electronic supplementary material The online version of this article (doi:10.1186/s12711-017-0344-z) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Marie-Pierre Sanchez
- GABI, INRA, AgroParisTech, Université Paris Saclay, 78350, Jouy-en-Josas, France.
| | - Armelle Govignon-Gion
- GABI, INRA, AgroParisTech, Université Paris Saclay, 78350, Jouy-en-Josas, France.,Institut de l'Elevage, 75012, Paris, France
| | - Pascal Croiseau
- GABI, INRA, AgroParisTech, Université Paris Saclay, 78350, Jouy-en-Josas, France
| | - Sébastien Fritz
- GABI, INRA, AgroParisTech, Université Paris Saclay, 78350, Jouy-en-Josas, France.,Allice, 75012, Paris, France
| | - Chris Hozé
- GABI, INRA, AgroParisTech, Université Paris Saclay, 78350, Jouy-en-Josas, France.,Allice, 75012, Paris, France
| | - Guy Miranda
- GABI, INRA, AgroParisTech, Université Paris Saclay, 78350, Jouy-en-Josas, France
| | - Patrice Martin
- GABI, INRA, AgroParisTech, Université Paris Saclay, 78350, Jouy-en-Josas, France
| | | | - Rabia Letaïef
- GABI, INRA, AgroParisTech, Université Paris Saclay, 78350, Jouy-en-Josas, France
| | - Dominique Rocha
- GABI, INRA, AgroParisTech, Université Paris Saclay, 78350, Jouy-en-Josas, France
| | | | - Mekki Boussaha
- GABI, INRA, AgroParisTech, Université Paris Saclay, 78350, Jouy-en-Josas, France
| | - Didier Boichard
- GABI, INRA, AgroParisTech, Université Paris Saclay, 78350, Jouy-en-Josas, France
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