Genome-wide association analyses identify genotype-by-environment interactions of growth traits in Simmental cattle

Abstract Understanding genotype-by-environment interactions (G × E) is crucial to understand environmental adaptation in mammals and improve the sustainability of agricultural production. Here, we present an extensive study investigating the interaction of genome-wide SNP markers with a vast assortm...

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Main Authors: Camila U. Braz, Troy N. Rowan, Robert D. Schnabel, Jared E. Decker
Format: Article
Language:English
Published: Nature Publishing Group 2021-06-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-021-92455-x
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spelling doaj-4cc7e0a66b394fe6b975ef62db6ca75d2021-06-27T11:32:41ZengNature Publishing GroupScientific Reports2045-23222021-06-0111111510.1038/s41598-021-92455-xGenome-wide association analyses identify genotype-by-environment interactions of growth traits in Simmental cattleCamila U. Braz0Troy N. Rowan1Robert D. Schnabel2Jared E. Decker3Division of Animal Sciences, University of MissouriDivision of Animal Sciences, University of MissouriDivision of Animal Sciences, University of MissouriDivision of Animal Sciences, University of MissouriAbstract Understanding genotype-by-environment interactions (G × E) is crucial to understand environmental adaptation in mammals and improve the sustainability of agricultural production. Here, we present an extensive study investigating the interaction of genome-wide SNP markers with a vast assortment of environmental variables and searching for SNPs controlling phenotypic variance (vQTL) using a large beef cattle dataset. We showed that G × E contribute 10.1%, 3.8%, and 2.8% of the phenotypic variance of birth weight, weaning weight, and yearling weight, respectively. G × E genome-wide association analysis (GWAA) detected a large number of G × E loci affecting growth traits, which the traditional GWAA did not detect, showing that functional loci may have non-additive genetic effects regardless of differences in genotypic means. Further, variance-heterogeneity GWAA detected loci enriched with G × E effects without requiring prior knowledge of the interacting environmental factors. Functional annotation and pathway analysis of G × E genes revealed biological mechanisms by which cattle respond to changes in their environment, such as neurotransmitter activity, hypoxia-induced processes, keratinization, hormone, thermogenic and immune pathways. We unraveled the relevance and complexity of the genetic basis of G × E underlying growth traits, providing new insights into how different environmental conditions interact with specific genes influencing adaptation and productivity in beef cattle and potentially across mammals.https://doi.org/10.1038/s41598-021-92455-x
collection DOAJ
language English
format Article
sources DOAJ
author Camila U. Braz
Troy N. Rowan
Robert D. Schnabel
Jared E. Decker
spellingShingle Camila U. Braz
Troy N. Rowan
Robert D. Schnabel
Jared E. Decker
Genome-wide association analyses identify genotype-by-environment interactions of growth traits in Simmental cattle
Scientific Reports
author_facet Camila U. Braz
Troy N. Rowan
Robert D. Schnabel
Jared E. Decker
author_sort Camila U. Braz
title Genome-wide association analyses identify genotype-by-environment interactions of growth traits in Simmental cattle
title_short Genome-wide association analyses identify genotype-by-environment interactions of growth traits in Simmental cattle
title_full Genome-wide association analyses identify genotype-by-environment interactions of growth traits in Simmental cattle
title_fullStr Genome-wide association analyses identify genotype-by-environment interactions of growth traits in Simmental cattle
title_full_unstemmed Genome-wide association analyses identify genotype-by-environment interactions of growth traits in Simmental cattle
title_sort genome-wide association analyses identify genotype-by-environment interactions of growth traits in simmental cattle
publisher Nature Publishing Group
series Scientific Reports
issn 2045-2322
publishDate 2021-06-01
description Abstract Understanding genotype-by-environment interactions (G × E) is crucial to understand environmental adaptation in mammals and improve the sustainability of agricultural production. Here, we present an extensive study investigating the interaction of genome-wide SNP markers with a vast assortment of environmental variables and searching for SNPs controlling phenotypic variance (vQTL) using a large beef cattle dataset. We showed that G × E contribute 10.1%, 3.8%, and 2.8% of the phenotypic variance of birth weight, weaning weight, and yearling weight, respectively. G × E genome-wide association analysis (GWAA) detected a large number of G × E loci affecting growth traits, which the traditional GWAA did not detect, showing that functional loci may have non-additive genetic effects regardless of differences in genotypic means. Further, variance-heterogeneity GWAA detected loci enriched with G × E effects without requiring prior knowledge of the interacting environmental factors. Functional annotation and pathway analysis of G × E genes revealed biological mechanisms by which cattle respond to changes in their environment, such as neurotransmitter activity, hypoxia-induced processes, keratinization, hormone, thermogenic and immune pathways. We unraveled the relevance and complexity of the genetic basis of G × E underlying growth traits, providing new insights into how different environmental conditions interact with specific genes influencing adaptation and productivity in beef cattle and potentially across mammals.
url https://doi.org/10.1038/s41598-021-92455-x
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