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A Meta-Analysis Including Pre-selected Sequence Variants Associated With Seven Traits in Three French Dairy Cattle Populations

A within-breed genome-wide association study (GWAS) is useful when identifying the QTL that segregates in a breed. However, an across-breed meta-analysis can be used to increase the power of identification and precise localization of QTL that segregate in multiple breeds. Precise localization will a...

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Autores principales: Marete, Andrew G., Guldbrandtsen, Bernt, Lund, Mogens S., Fritz, Sébastien, Sahana, Goutam, Boichard, Didier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6232291/
https://www.ncbi.nlm.nih.gov/pubmed/30459810
http://dx.doi.org/10.3389/fgene.2018.00522
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author Marete, Andrew G.
Guldbrandtsen, Bernt
Lund, Mogens S.
Fritz, Sébastien
Sahana, Goutam
Boichard, Didier
author_facet Marete, Andrew G.
Guldbrandtsen, Bernt
Lund, Mogens S.
Fritz, Sébastien
Sahana, Goutam
Boichard, Didier
author_sort Marete, Andrew G.
collection PubMed
description A within-breed genome-wide association study (GWAS) is useful when identifying the QTL that segregates in a breed. However, an across-breed meta-analysis can be used to increase the power of identification and precise localization of QTL that segregate in multiple breeds. Precise localization will allow including QTL information from other breeds in genomic prediction due to the persistence of the linkage phase between the causal variant and the marker. This study aimed to identify and confirm QTL detected in within-breed GWAS through a meta-analysis in three French dairy cattle breeds. A set of sequence variants selected based on their functional annotations were imputed into 50 k genotypes for 46,732 Holstein, 20,096 Montbeliarde, and 11,944 Normande cows to identify QTL for milk production, the success rate at insemination of cows (fertility) and stature. We conducted within-breed GWAS followed by across-breed meta-analysis using a weighted Z-scores model on the GWAS summary data (i.e., P-values, effect direction, and sample size). After Bonferroni correction, the GWAS result identified 21,956 significantly associated SNP (P(FWER) < 0.05), while meta-analysis result identified 9,604 significant SNP (P(FWER) < 0.05) associated with the phenotypes. The meta-analysis identified 36 QTL for milk yield, 48 QTL for fat yield and percentage, 29 QTL for protein yield and percentage, 13 QTL for fertility, and 16 QTL for stature. Some of these QTL were not significant in the within-breed GWAS. Some previously identified causal variants were confirmed, e.g., BTA14:1802265 (fat percentage, P = 1.5 × 10(−760); protein percentage, P = 7.61 × 10(−348)) both mapping the DGAT1-K232A mutation and BTA14:25006125 (P = 8.58 × 10(−140)) mapping PLAG1 gene was confirmed for stature in Montbeliarde. New QTL lead SNP shared between breeds included the intronic variant rs109205829 (NFIB gene), and the intergenic variant rs41592357 (1.38 Mb upstream of the CNTN6 gene and 0.65 Mb downstream of the CNTN4 gene). Rs110425867 (ZFAT gene) was the top variant associated with fertility, and new QTL lead SNP included rs109483390 (0.1 Mb upstream of the TNFAIP3 gene and 0.07 Mb downstream of PERP gene), and rs42412333 (0.45 Mb downstream of the RPL10L gene). An across-breed meta-analysis had greater power to detect QTL as opposed to a within breed GWAS. The QTL detected here can be incorporated in routine genomic predictions.
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spelling pubmed-62322912018-11-20 A Meta-Analysis Including Pre-selected Sequence Variants Associated With Seven Traits in Three French Dairy Cattle Populations Marete, Andrew G. Guldbrandtsen, Bernt Lund, Mogens S. Fritz, Sébastien Sahana, Goutam Boichard, Didier Front Genet Genetics A within-breed genome-wide association study (GWAS) is useful when identifying the QTL that segregates in a breed. However, an across-breed meta-analysis can be used to increase the power of identification and precise localization of QTL that segregate in multiple breeds. Precise localization will allow including QTL information from other breeds in genomic prediction due to the persistence of the linkage phase between the causal variant and the marker. This study aimed to identify and confirm QTL detected in within-breed GWAS through a meta-analysis in three French dairy cattle breeds. A set of sequence variants selected based on their functional annotations were imputed into 50 k genotypes for 46,732 Holstein, 20,096 Montbeliarde, and 11,944 Normande cows to identify QTL for milk production, the success rate at insemination of cows (fertility) and stature. We conducted within-breed GWAS followed by across-breed meta-analysis using a weighted Z-scores model on the GWAS summary data (i.e., P-values, effect direction, and sample size). After Bonferroni correction, the GWAS result identified 21,956 significantly associated SNP (P(FWER) < 0.05), while meta-analysis result identified 9,604 significant SNP (P(FWER) < 0.05) associated with the phenotypes. The meta-analysis identified 36 QTL for milk yield, 48 QTL for fat yield and percentage, 29 QTL for protein yield and percentage, 13 QTL for fertility, and 16 QTL for stature. Some of these QTL were not significant in the within-breed GWAS. Some previously identified causal variants were confirmed, e.g., BTA14:1802265 (fat percentage, P = 1.5 × 10(−760); protein percentage, P = 7.61 × 10(−348)) both mapping the DGAT1-K232A mutation and BTA14:25006125 (P = 8.58 × 10(−140)) mapping PLAG1 gene was confirmed for stature in Montbeliarde. New QTL lead SNP shared between breeds included the intronic variant rs109205829 (NFIB gene), and the intergenic variant rs41592357 (1.38 Mb upstream of the CNTN6 gene and 0.65 Mb downstream of the CNTN4 gene). Rs110425867 (ZFAT gene) was the top variant associated with fertility, and new QTL lead SNP included rs109483390 (0.1 Mb upstream of the TNFAIP3 gene and 0.07 Mb downstream of PERP gene), and rs42412333 (0.45 Mb downstream of the RPL10L gene). An across-breed meta-analysis had greater power to detect QTL as opposed to a within breed GWAS. The QTL detected here can be incorporated in routine genomic predictions. Frontiers Media S.A. 2018-11-06 /pmc/articles/PMC6232291/ /pubmed/30459810 http://dx.doi.org/10.3389/fgene.2018.00522 Text en Copyright © 2018 Marete, Guldbrandtsen, Lund, Fritz, Sahana and Boichard. 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) and the copyright owner(s) 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
Marete, Andrew G.
Guldbrandtsen, Bernt
Lund, Mogens S.
Fritz, Sébastien
Sahana, Goutam
Boichard, Didier
A Meta-Analysis Including Pre-selected Sequence Variants Associated With Seven Traits in Three French Dairy Cattle Populations
title A Meta-Analysis Including Pre-selected Sequence Variants Associated With Seven Traits in Three French Dairy Cattle Populations
title_full A Meta-Analysis Including Pre-selected Sequence Variants Associated With Seven Traits in Three French Dairy Cattle Populations
title_fullStr A Meta-Analysis Including Pre-selected Sequence Variants Associated With Seven Traits in Three French Dairy Cattle Populations
title_full_unstemmed A Meta-Analysis Including Pre-selected Sequence Variants Associated With Seven Traits in Three French Dairy Cattle Populations
title_short A Meta-Analysis Including Pre-selected Sequence Variants Associated With Seven Traits in Three French Dairy Cattle Populations
title_sort meta-analysis including pre-selected sequence variants associated with seven traits in three french dairy cattle populations
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6232291/
https://www.ncbi.nlm.nih.gov/pubmed/30459810
http://dx.doi.org/10.3389/fgene.2018.00522
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