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Genomic Selection Improves Response to Selection in Resilience by Exploiting Genotype by Environment Interactions

Genotype by environment interactions (GxE) are very common in livestock and hamper genetic improvement. On the other hand, GxE is a source of genetic variation: genetic variation in response to environment, e.g., environmental perturbations such as heat stress or disease. In livestock breeding, ther...

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Autor principal: Mulder, Han A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5062612/
https://www.ncbi.nlm.nih.gov/pubmed/27790246
http://dx.doi.org/10.3389/fgene.2016.00178
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author Mulder, Han A.
author_facet Mulder, Han A.
author_sort Mulder, Han A.
collection PubMed
description Genotype by environment interactions (GxE) are very common in livestock and hamper genetic improvement. On the other hand, GxE is a source of genetic variation: genetic variation in response to environment, e.g., environmental perturbations such as heat stress or disease. In livestock breeding, there is tendency to ignore GxE because of increased complexity of models for genetic evaluations and lack of accuracy in extreme environments. GxE, however, creates opportunities to increase resilience of animals toward environmental perturbations. The main aim of the paper is to investigate to which extent GxE can be exploited with traditional and genomic selection methods. Furthermore, we investigated the benefit of reaction norm (RN) models compared to conventional methods ignoring GxE. The questions were addressed with selection index theory. GxE was modeled according to a linear RN model in which the environmental gradient is the contemporary group mean. Economic values were based on linear and non-linear profit equations. Accuracies of environment-specific (G)EBV were highest in intermediate environments and lowest in extreme environments. RN models had higher accuracies of (G)EBV in extreme environments than conventional models ignoring GxE. Genomic selection always resulted in higher response to selection in all environments than sib or progeny testing schemes. The increase in response was with genomic selection between 9 and 140% compared to sib testing and between 11 and 114% compared to progeny testing when the reference population consisted of 1 million animals across all environments. When the aim was to decrease environmental sensitivity, the response in slope of the RN model with genomic selection was between 1.09 and 319 times larger than with sib or progeny testing and in the right direction in contrast to sib and progeny testing that still increased environmental sensitivity. This shows that genomic selection with large reference populations offers great opportunities to exploit GxE to increase resilience of animals.
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spelling pubmed-50626122016-10-27 Genomic Selection Improves Response to Selection in Resilience by Exploiting Genotype by Environment Interactions Mulder, Han A. Front Genet Genetics Genotype by environment interactions (GxE) are very common in livestock and hamper genetic improvement. On the other hand, GxE is a source of genetic variation: genetic variation in response to environment, e.g., environmental perturbations such as heat stress or disease. In livestock breeding, there is tendency to ignore GxE because of increased complexity of models for genetic evaluations and lack of accuracy in extreme environments. GxE, however, creates opportunities to increase resilience of animals toward environmental perturbations. The main aim of the paper is to investigate to which extent GxE can be exploited with traditional and genomic selection methods. Furthermore, we investigated the benefit of reaction norm (RN) models compared to conventional methods ignoring GxE. The questions were addressed with selection index theory. GxE was modeled according to a linear RN model in which the environmental gradient is the contemporary group mean. Economic values were based on linear and non-linear profit equations. Accuracies of environment-specific (G)EBV were highest in intermediate environments and lowest in extreme environments. RN models had higher accuracies of (G)EBV in extreme environments than conventional models ignoring GxE. Genomic selection always resulted in higher response to selection in all environments than sib or progeny testing schemes. The increase in response was with genomic selection between 9 and 140% compared to sib testing and between 11 and 114% compared to progeny testing when the reference population consisted of 1 million animals across all environments. When the aim was to decrease environmental sensitivity, the response in slope of the RN model with genomic selection was between 1.09 and 319 times larger than with sib or progeny testing and in the right direction in contrast to sib and progeny testing that still increased environmental sensitivity. This shows that genomic selection with large reference populations offers great opportunities to exploit GxE to increase resilience of animals. Frontiers Media S.A. 2016-10-13 /pmc/articles/PMC5062612/ /pubmed/27790246 http://dx.doi.org/10.3389/fgene.2016.00178 Text en Copyright © 2016 Mulder. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Mulder, Han A.
Genomic Selection Improves Response to Selection in Resilience by Exploiting Genotype by Environment Interactions
title Genomic Selection Improves Response to Selection in Resilience by Exploiting Genotype by Environment Interactions
title_full Genomic Selection Improves Response to Selection in Resilience by Exploiting Genotype by Environment Interactions
title_fullStr Genomic Selection Improves Response to Selection in Resilience by Exploiting Genotype by Environment Interactions
title_full_unstemmed Genomic Selection Improves Response to Selection in Resilience by Exploiting Genotype by Environment Interactions
title_short Genomic Selection Improves Response to Selection in Resilience by Exploiting Genotype by Environment Interactions
title_sort genomic selection improves response to selection in resilience by exploiting genotype by environment interactions
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5062612/
https://www.ncbi.nlm.nih.gov/pubmed/27790246
http://dx.doi.org/10.3389/fgene.2016.00178
work_keys_str_mv AT mulderhana genomicselectionimprovesresponsetoselectioninresiliencebyexploitinggenotypebyenvironmentinteractions