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Prioritizing candidate genes post-GWAS using multiple sources of data for mastitis resistance in dairy cattle

BACKGROUND: Improving resistance to mastitis, one of the costliest diseases in dairy production, has become an important objective in dairy cattle breeding. However, mastitis resistance is influenced by many genes involved in multiple processes, including the response to infection, inflammation, and...

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Autores principales: Cai, Zexi, Guldbrandtsen, Bernt, Lund, Mogens Sandø, Sahana, Goutam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6127918/
https://www.ncbi.nlm.nih.gov/pubmed/30189836
http://dx.doi.org/10.1186/s12864-018-5050-x
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author Cai, Zexi
Guldbrandtsen, Bernt
Lund, Mogens Sandø
Sahana, Goutam
author_facet Cai, Zexi
Guldbrandtsen, Bernt
Lund, Mogens Sandø
Sahana, Goutam
author_sort Cai, Zexi
collection PubMed
description BACKGROUND: Improving resistance to mastitis, one of the costliest diseases in dairy production, has become an important objective in dairy cattle breeding. However, mastitis resistance is influenced by many genes involved in multiple processes, including the response to infection, inflammation, and post-infection healing. Low genetic heritability, environmental variations, and farm management differences further complicate the identification of links between genetic variants and mastitis resistance. Consequently, studies of the genetics of variation in mastitis resistance in dairy cattle lack agreement about the responsible genes. RESULTS: We associated 15,552,968 imputed whole-genome sequencing markers for 5147 Nordic Holstein cattle with mastitis resistance in a genome-wide association study (GWAS). Next, we augmented P-values for markers in genes in the associated regions using Gene Ontology terms, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and mammalian phenotype database. To confirm results of gene-based analyses, we used gene expression data from E. coli-challenged cow udders. We identified 22 independent quantitative trait loci (QTL) that collectively explained 14% of the variance in breeding values for resistance to clinical mastitis (CM). Using association test statistics with multiple pieces of independent information on gene function and differential expression during bacterial infection, we suggested putative causal genes with biological relevance for 12 QTL affecting resistance to CM in dairy cattle. CONCLUSION: Combining information on the nearest positional genes, gene-based analyses, and differential gene expression data from RNA-seq, we identified putative causal genes (candidate genes with biological evidence) in QTL for mastitis resistance in Nordic Holstein cattle. The same strategy can be applied for other traits. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-018-5050-x) contains supplementary material, which is available to authorized users.
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spelling pubmed-61279182018-09-10 Prioritizing candidate genes post-GWAS using multiple sources of data for mastitis resistance in dairy cattle Cai, Zexi Guldbrandtsen, Bernt Lund, Mogens Sandø Sahana, Goutam BMC Genomics Research Article BACKGROUND: Improving resistance to mastitis, one of the costliest diseases in dairy production, has become an important objective in dairy cattle breeding. However, mastitis resistance is influenced by many genes involved in multiple processes, including the response to infection, inflammation, and post-infection healing. Low genetic heritability, environmental variations, and farm management differences further complicate the identification of links between genetic variants and mastitis resistance. Consequently, studies of the genetics of variation in mastitis resistance in dairy cattle lack agreement about the responsible genes. RESULTS: We associated 15,552,968 imputed whole-genome sequencing markers for 5147 Nordic Holstein cattle with mastitis resistance in a genome-wide association study (GWAS). Next, we augmented P-values for markers in genes in the associated regions using Gene Ontology terms, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and mammalian phenotype database. To confirm results of gene-based analyses, we used gene expression data from E. coli-challenged cow udders. We identified 22 independent quantitative trait loci (QTL) that collectively explained 14% of the variance in breeding values for resistance to clinical mastitis (CM). Using association test statistics with multiple pieces of independent information on gene function and differential expression during bacterial infection, we suggested putative causal genes with biological relevance for 12 QTL affecting resistance to CM in dairy cattle. CONCLUSION: Combining information on the nearest positional genes, gene-based analyses, and differential gene expression data from RNA-seq, we identified putative causal genes (candidate genes with biological evidence) in QTL for mastitis resistance in Nordic Holstein cattle. The same strategy can be applied for other traits. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-018-5050-x) contains supplementary material, which is available to authorized users. BioMed Central 2018-09-06 /pmc/articles/PMC6127918/ /pubmed/30189836 http://dx.doi.org/10.1186/s12864-018-5050-x Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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 Article
Cai, Zexi
Guldbrandtsen, Bernt
Lund, Mogens Sandø
Sahana, Goutam
Prioritizing candidate genes post-GWAS using multiple sources of data for mastitis resistance in dairy cattle
title Prioritizing candidate genes post-GWAS using multiple sources of data for mastitis resistance in dairy cattle
title_full Prioritizing candidate genes post-GWAS using multiple sources of data for mastitis resistance in dairy cattle
title_fullStr Prioritizing candidate genes post-GWAS using multiple sources of data for mastitis resistance in dairy cattle
title_full_unstemmed Prioritizing candidate genes post-GWAS using multiple sources of data for mastitis resistance in dairy cattle
title_short Prioritizing candidate genes post-GWAS using multiple sources of data for mastitis resistance in dairy cattle
title_sort prioritizing candidate genes post-gwas using multiple sources of data for mastitis resistance in dairy cattle
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6127918/
https://www.ncbi.nlm.nih.gov/pubmed/30189836
http://dx.doi.org/10.1186/s12864-018-5050-x
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