Using prior information from humans to prioritize genes and gene-associated variants for complex traits in livestock

Autoři: Biaty Raymond aff001;  Loic Yengo aff003;  Roy Costilla aff004;  Chris Schrooten aff005;  Aniek C. Bouwman aff001;  Ben J. Hayes aff004;  Roel F. Veerkamp aff001;  Peter M. Visscher aff003
Působiště autorů: Animal Breeding and Genomics, Wageningen University and Research, Wageningen, The Netherlands aff001;  Biometris, Wageningen University and Research, Wageningen, The Netherlands aff002;  Institute for Molecular Bioscience, University of Queensland, St. Lucia, Australia aff003;  Queensland Alliance for Agriculture and Food Innovation, University of Queensland, St. Lucia, Australia aff004;  CRV BV, AL Arnhem, The Netherlands aff005;  CRV BV, Arnhem, The Netherlands aff005
Vyšlo v časopise: Using prior information from humans to prioritize genes and gene-associated variants for complex traits in livestock. PLoS Genet 16(9): e32767. doi:10.1371/journal.pgen.1008780
Kategorie: Research Article
doi: 10.1371/journal.pgen.1008780


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.

Klíčová slova:

Cattle – Complex traits – Genetics – Genome-wide association studies – Genomics – Human genomics – Livestock – Single nucleotide polymorphisms


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Článek vyšel v časopise

PLOS Genetics

2020 Číslo 9

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