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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2021-06-01
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Online Access: | https://doi.org/10.1038/s41598-021-92455-x |
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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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