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Interest of using imputation for genomic evaluation in layer chicken

With the availability of the 600K Affymetrix Axiom high-density (HD) single nucleotide polymorphism (SNP) chip, genomic selection has been implemented in broiler and layer chicken. However, the cost of this SNP chip is too high to genotype all selection candidates. A solution is to develop a low-den...

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Autores principales: Herry, Florian, Druet, David Picard, Hérault, Frédéric, Varenne, Amandine, Burlot, Thierry, Le Roy, Pascale, Allais, Sophie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7597443/
https://www.ncbi.nlm.nih.gov/pubmed/32359567
http://dx.doi.org/10.1016/j.psj.2020.01.004
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author Herry, Florian
Druet, David Picard
Hérault, Frédéric
Varenne, Amandine
Burlot, Thierry
Le Roy, Pascale
Allais, Sophie
author_facet Herry, Florian
Druet, David Picard
Hérault, Frédéric
Varenne, Amandine
Burlot, Thierry
Le Roy, Pascale
Allais, Sophie
author_sort Herry, Florian
collection PubMed
description With the availability of the 600K Affymetrix Axiom high-density (HD) single nucleotide polymorphism (SNP) chip, genomic selection has been implemented in broiler and layer chicken. However, the cost of this SNP chip is too high to genotype all selection candidates. A solution is to develop a low-density SNP chip, at a lower price, and to impute all missing markers. But to routinely implement this solution, the impact of imputation on genomic evaluation accuracy must be studied. It is also interesting to study the consequences of the use of low-density SNP chips in genomic evaluation accuracy. In this perspective, the interest of using imputation in genomic selection was studied in a pure layer line. Two low-density SNP chip designs were compared: an equidistant methodology and a methodology based on linkage disequilibrium. Egg weight, egg shell color, egg shell strength, and albumen height were evaluated with single-step genomic best linear unbiased prediction methodology. The impact of imputation errors or the absence of imputation on the ranking of the male selection candidates was assessed with a genomic evaluation based on ancestry. Thus, genomic estimated breeding values (GEBV) obtained with imputed HD genotypes or low-density genotypes were compared with GEBV obtained with the HD SNP chip. The relative accuracy of GEBV was also investigated by considering as reference GEBV estimated on the offspring. A limited reordering of the breeders, selected on a multitrait index, was observed. Spearman correlations between GEBV on HD genotypes and GEBV on low-density genotypes (with or without imputation) were always higher than 0.94 with more than 3K SNP. For the genetically closer, top 150 individuals for a specific trait, with imputation, the reordering was reduced with correlation higher than 0.94 with more than 3K SNP. Without imputation, the correlations remained lower than 0.85 with less than 3K and 16K SNP for equidistant and linkage disequilibrium methodology, respectively. The differences in GEBV correlations between both methodologies were never significant. The conclusions were the same for all studied traits.
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spelling pubmed-75974432020-11-02 Interest of using imputation for genomic evaluation in layer chicken Herry, Florian Druet, David Picard Hérault, Frédéric Varenne, Amandine Burlot, Thierry Le Roy, Pascale Allais, Sophie Poult Sci Genetics and Molecular Biology With the availability of the 600K Affymetrix Axiom high-density (HD) single nucleotide polymorphism (SNP) chip, genomic selection has been implemented in broiler and layer chicken. However, the cost of this SNP chip is too high to genotype all selection candidates. A solution is to develop a low-density SNP chip, at a lower price, and to impute all missing markers. But to routinely implement this solution, the impact of imputation on genomic evaluation accuracy must be studied. It is also interesting to study the consequences of the use of low-density SNP chips in genomic evaluation accuracy. In this perspective, the interest of using imputation in genomic selection was studied in a pure layer line. Two low-density SNP chip designs were compared: an equidistant methodology and a methodology based on linkage disequilibrium. Egg weight, egg shell color, egg shell strength, and albumen height were evaluated with single-step genomic best linear unbiased prediction methodology. The impact of imputation errors or the absence of imputation on the ranking of the male selection candidates was assessed with a genomic evaluation based on ancestry. Thus, genomic estimated breeding values (GEBV) obtained with imputed HD genotypes or low-density genotypes were compared with GEBV obtained with the HD SNP chip. The relative accuracy of GEBV was also investigated by considering as reference GEBV estimated on the offspring. A limited reordering of the breeders, selected on a multitrait index, was observed. Spearman correlations between GEBV on HD genotypes and GEBV on low-density genotypes (with or without imputation) were always higher than 0.94 with more than 3K SNP. For the genetically closer, top 150 individuals for a specific trait, with imputation, the reordering was reduced with correlation higher than 0.94 with more than 3K SNP. Without imputation, the correlations remained lower than 0.85 with less than 3K and 16K SNP for equidistant and linkage disequilibrium methodology, respectively. The differences in GEBV correlations between both methodologies were never significant. The conclusions were the same for all studied traits. Elsevier 2020-03-18 /pmc/articles/PMC7597443/ /pubmed/32359567 http://dx.doi.org/10.1016/j.psj.2020.01.004 Text en © 2020 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Genetics and Molecular Biology
Herry, Florian
Druet, David Picard
Hérault, Frédéric
Varenne, Amandine
Burlot, Thierry
Le Roy, Pascale
Allais, Sophie
Interest of using imputation for genomic evaluation in layer chicken
title Interest of using imputation for genomic evaluation in layer chicken
title_full Interest of using imputation for genomic evaluation in layer chicken
title_fullStr Interest of using imputation for genomic evaluation in layer chicken
title_full_unstemmed Interest of using imputation for genomic evaluation in layer chicken
title_short Interest of using imputation for genomic evaluation in layer chicken
title_sort interest of using imputation for genomic evaluation in layer chicken
topic Genetics and Molecular Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7597443/
https://www.ncbi.nlm.nih.gov/pubmed/32359567
http://dx.doi.org/10.1016/j.psj.2020.01.004
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