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Non-additive genetic variation in growth, carcass and fertility traits of beef cattle

BACKGROUND: A better understanding of non-additive variance could lead to increased knowledge on the genetic control and physiology of quantitative traits, and to improved prediction of the genetic value and phenotype of individuals. Genome-wide panels of single nucleotide polymorphisms (SNPs) have...

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Autores principales: Bolormaa, Sunduimijid, Pryce, Jennie E, Zhang, Yuandan, Reverter, Antonio, Barendse, William, Hayes, Ben J, Goddard, Michael E
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4382858/
https://www.ncbi.nlm.nih.gov/pubmed/25880217
http://dx.doi.org/10.1186/s12711-015-0114-8
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author Bolormaa, Sunduimijid
Pryce, Jennie E
Zhang, Yuandan
Reverter, Antonio
Barendse, William
Hayes, Ben J
Goddard, Michael E
author_facet Bolormaa, Sunduimijid
Pryce, Jennie E
Zhang, Yuandan
Reverter, Antonio
Barendse, William
Hayes, Ben J
Goddard, Michael E
author_sort Bolormaa, Sunduimijid
collection PubMed
description BACKGROUND: A better understanding of non-additive variance could lead to increased knowledge on the genetic control and physiology of quantitative traits, and to improved prediction of the genetic value and phenotype of individuals. Genome-wide panels of single nucleotide polymorphisms (SNPs) have been mainly used to map additive effects for quantitative traits, but they can also be used to investigate non-additive effects. We estimated dominance and epistatic effects of SNPs on various traits in beef cattle and the variance explained by dominance, and quantified the increase in accuracy of phenotype prediction by including dominance deviations in its estimation. METHODS: Genotype data (729 068 real or imputed SNPs) and phenotypes on up to 16 traits of 10 191 individuals from Bos taurus, Bos indicus and composite breeds were used. A genome-wide association study was performed by fitting the additive and dominance effects of single SNPs. The dominance variance was estimated by fitting a dominance relationship matrix constructed from the 729 068 SNPs. The accuracy of predicted phenotypic values was evaluated by best linear unbiased prediction using the additive and dominance relationship matrices. Epistatic interactions (additive × additive) were tested between each of the 28 SNPs that are known to have additive effects on multiple traits, and each of the other remaining 729 067 SNPs. RESULTS: The number of significant dominance effects was greater than expected by chance and most of them were in the direction that is presumed to increase fitness and in the opposite direction to inbreeding depression. Estimates of dominance variance explained by SNPs varied widely between traits, but had large standard errors. The median dominance variance across the 16 traits was equal to 5% of the phenotypic variance. Including a dominance deviation in the prediction did not significantly increase its accuracy for any of the phenotypes. The number of additive × additive epistatic effects that were statistically significant was greater than expected by chance. CONCLUSIONS: Significant dominance and epistatic effects occur for growth, carcass and fertility traits in beef cattle but they are difficult to estimate precisely and including them in phenotype prediction does not increase its accuracy.
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spelling pubmed-43828582015-04-03 Non-additive genetic variation in growth, carcass and fertility traits of beef cattle Bolormaa, Sunduimijid Pryce, Jennie E Zhang, Yuandan Reverter, Antonio Barendse, William Hayes, Ben J Goddard, Michael E Genet Sel Evol Research BACKGROUND: A better understanding of non-additive variance could lead to increased knowledge on the genetic control and physiology of quantitative traits, and to improved prediction of the genetic value and phenotype of individuals. Genome-wide panels of single nucleotide polymorphisms (SNPs) have been mainly used to map additive effects for quantitative traits, but they can also be used to investigate non-additive effects. We estimated dominance and epistatic effects of SNPs on various traits in beef cattle and the variance explained by dominance, and quantified the increase in accuracy of phenotype prediction by including dominance deviations in its estimation. METHODS: Genotype data (729 068 real or imputed SNPs) and phenotypes on up to 16 traits of 10 191 individuals from Bos taurus, Bos indicus and composite breeds were used. A genome-wide association study was performed by fitting the additive and dominance effects of single SNPs. The dominance variance was estimated by fitting a dominance relationship matrix constructed from the 729 068 SNPs. The accuracy of predicted phenotypic values was evaluated by best linear unbiased prediction using the additive and dominance relationship matrices. Epistatic interactions (additive × additive) were tested between each of the 28 SNPs that are known to have additive effects on multiple traits, and each of the other remaining 729 067 SNPs. RESULTS: The number of significant dominance effects was greater than expected by chance and most of them were in the direction that is presumed to increase fitness and in the opposite direction to inbreeding depression. Estimates of dominance variance explained by SNPs varied widely between traits, but had large standard errors. The median dominance variance across the 16 traits was equal to 5% of the phenotypic variance. Including a dominance deviation in the prediction did not significantly increase its accuracy for any of the phenotypes. The number of additive × additive epistatic effects that were statistically significant was greater than expected by chance. CONCLUSIONS: Significant dominance and epistatic effects occur for growth, carcass and fertility traits in beef cattle but they are difficult to estimate precisely and including them in phenotype prediction does not increase its accuracy. BioMed Central 2015-04-02 /pmc/articles/PMC4382858/ /pubmed/25880217 http://dx.doi.org/10.1186/s12711-015-0114-8 Text en © Bolormaa et al.; licensee BioMed Central. 2015 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 work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Bolormaa, Sunduimijid
Pryce, Jennie E
Zhang, Yuandan
Reverter, Antonio
Barendse, William
Hayes, Ben J
Goddard, Michael E
Non-additive genetic variation in growth, carcass and fertility traits of beef cattle
title Non-additive genetic variation in growth, carcass and fertility traits of beef cattle
title_full Non-additive genetic variation in growth, carcass and fertility traits of beef cattle
title_fullStr Non-additive genetic variation in growth, carcass and fertility traits of beef cattle
title_full_unstemmed Non-additive genetic variation in growth, carcass and fertility traits of beef cattle
title_short Non-additive genetic variation in growth, carcass and fertility traits of beef cattle
title_sort non-additive genetic variation in growth, carcass and fertility traits of beef cattle
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4382858/
https://www.ncbi.nlm.nih.gov/pubmed/25880217
http://dx.doi.org/10.1186/s12711-015-0114-8
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