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Using prior information from humans to prioritize genes and gene-associated variants for complex traits in livestock
Genome-Wide Association Studies (GWAS) in large human cohorts have identified thousands of loci associated with complex traits and diseases. For identifying the genes and gene-associated variants that underlie complex traits in livestock, especially where sample sizes are limiting, it may help to in...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514049/ https://www.ncbi.nlm.nih.gov/pubmed/32925905 http://dx.doi.org/10.1371/journal.pgen.1008780 |
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author | Raymond, Biaty Yengo, Loic Costilla, Roy Schrooten, Chris Bouwman, Aniek C. Hayes, Ben J. Veerkamp, Roel F. Visscher, Peter M. |
author_facet | Raymond, Biaty Yengo, Loic Costilla, Roy Schrooten, Chris Bouwman, Aniek C. Hayes, Ben J. Veerkamp, Roel F. Visscher, Peter M. |
author_sort | Raymond, Biaty |
collection | PubMed |
description | Genome-Wide Association Studies (GWAS) in large human cohorts have identified thousands of loci associated with complex traits and diseases. For identifying the genes and gene-associated variants that underlie complex traits in livestock, especially where sample sizes are limiting, it may help to integrate the results of GWAS for equivalent traits in humans as prior information. In this study, we sought to investigate the usefulness of results from a GWAS on human height as prior information for identifying the genes and gene-associated variants that affect stature in cattle, using GWAS summary data on samples sizes of 700,000 and 58,265 for humans and cattle, respectively. Using Fisher’s exact test, we observed a significant proportion of cattle stature-associated genes (30/77) that are also associated with human height (odds ratio = 5.1, p = 3.1e-10). Result of randomized sampling tests showed that cattle orthologs of human height-associated genes, hereafter referred to as candidate genes (C-genes), were more enriched for cattle stature GWAS signals than random samples of genes in the cattle genome (p = 0.01). Randomly sampled SNPs within the C-genes also tend to explain more genetic variance for cattle stature (up to 13.2%) than randomly sampled SNPs within random cattle genes (p = 0.09). The most significant SNPs from a cattle GWAS for stature within the C-genes did not explain more genetic variance for cattle stature than the most significant SNPs within random cattle genes (p = 0.87). Altogether, our findings support previous studies that suggest a similarity in the genetic regulation of height across mammalian species. However, with the availability of a powerful GWAS for stature that combined data from 8 cattle breeds, prior information from human-height GWAS does not seem to provide any additional benefit with respect to the identification of genes and gene-associated variants that affect stature in cattle. |
format | Online Article Text |
id | pubmed-7514049 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-75140492020-10-01 Using prior information from humans to prioritize genes and gene-associated variants for complex traits in livestock Raymond, Biaty Yengo, Loic Costilla, Roy Schrooten, Chris Bouwman, Aniek C. Hayes, Ben J. Veerkamp, Roel F. Visscher, Peter M. PLoS Genet Research Article Genome-Wide Association Studies (GWAS) in large human cohorts have identified thousands of loci associated with complex traits and diseases. For identifying the genes and gene-associated variants that underlie complex traits in livestock, especially where sample sizes are limiting, it may help to integrate the results of GWAS for equivalent traits in humans as prior information. In this study, we sought to investigate the usefulness of results from a GWAS on human height as prior information for identifying the genes and gene-associated variants that affect stature in cattle, using GWAS summary data on samples sizes of 700,000 and 58,265 for humans and cattle, respectively. Using Fisher’s exact test, we observed a significant proportion of cattle stature-associated genes (30/77) that are also associated with human height (odds ratio = 5.1, p = 3.1e-10). Result of randomized sampling tests showed that cattle orthologs of human height-associated genes, hereafter referred to as candidate genes (C-genes), were more enriched for cattle stature GWAS signals than random samples of genes in the cattle genome (p = 0.01). Randomly sampled SNPs within the C-genes also tend to explain more genetic variance for cattle stature (up to 13.2%) than randomly sampled SNPs within random cattle genes (p = 0.09). The most significant SNPs from a cattle GWAS for stature within the C-genes did not explain more genetic variance for cattle stature than the most significant SNPs within random cattle genes (p = 0.87). Altogether, our findings support previous studies that suggest a similarity in the genetic regulation of height across mammalian species. However, with the availability of a powerful GWAS for stature that combined data from 8 cattle breeds, prior information from human-height GWAS does not seem to provide any additional benefit with respect to the identification of genes and gene-associated variants that affect stature in cattle. Public Library of Science 2020-09-14 /pmc/articles/PMC7514049/ /pubmed/32925905 http://dx.doi.org/10.1371/journal.pgen.1008780 Text en © 2020 Raymond et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Raymond, Biaty Yengo, Loic Costilla, Roy Schrooten, Chris Bouwman, Aniek C. Hayes, Ben J. Veerkamp, Roel F. Visscher, Peter M. Using prior information from humans to prioritize genes and gene-associated variants for complex traits in livestock |
title | Using prior information from humans to prioritize genes and gene-associated variants for complex traits in livestock |
title_full | Using prior information from humans to prioritize genes and gene-associated variants for complex traits in livestock |
title_fullStr | Using prior information from humans to prioritize genes and gene-associated variants for complex traits in livestock |
title_full_unstemmed | Using prior information from humans to prioritize genes and gene-associated variants for complex traits in livestock |
title_short | Using prior information from humans to prioritize genes and gene-associated variants for complex traits in livestock |
title_sort | using prior information from humans to prioritize genes and gene-associated variants for complex traits in livestock |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514049/ https://www.ncbi.nlm.nih.gov/pubmed/32925905 http://dx.doi.org/10.1371/journal.pgen.1008780 |
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