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Multibreed genome wide association can improve precision of mapping causative variants underlying milk production in dairy cattle

BACKGROUND: Genome wide association studies (GWAS) in most cattle breeds result in large genomic intervals of significant associations making it difficult to identify causal mutations. This is due to the extensive, low-level linkage disequilibrium within a cattle breed. As there is less linkage dise...

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Autores principales: Raven, Lesley-Ann, Cocks, Benjamin G, Hayes, Ben J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3905911/
https://www.ncbi.nlm.nih.gov/pubmed/24456127
http://dx.doi.org/10.1186/1471-2164-15-62
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author Raven, Lesley-Ann
Cocks, Benjamin G
Hayes, Ben J
author_facet Raven, Lesley-Ann
Cocks, Benjamin G
Hayes, Ben J
author_sort Raven, Lesley-Ann
collection PubMed
description BACKGROUND: Genome wide association studies (GWAS) in most cattle breeds result in large genomic intervals of significant associations making it difficult to identify causal mutations. This is due to the extensive, low-level linkage disequilibrium within a cattle breed. As there is less linkage disequilibrium across breeds, multibreed GWAS may improve precision of causal variant mapping. Here we test this hypothesis in a Holstein and Jersey cattle data set with 17,925 individuals with records for production and functional traits and 632,003 SNP markers. RESULTS: By using a cross validation strategy within the Holstein and Jersey data sets, we were able to identify and confirm a large number of QTL. As expected, the precision of mapping these QTL within the breeds was limited. In the multibreed analysis, we found that many loci were not segregating in both breeds. This was partly an artefact of power of the experiments, with the number of QTL shared between the breeds generally increasing with trait heritability. False discovery rates suggest that the multibreed analysis was less powerful than between breed analyses, in terms of how much genetic variance was explained by the detected QTL. However, the multibreed analysis could more accurately pinpoint the location of the well-described mutations affecting milk production such as DGAT1. Further, the significant SNP in the multibreed analysis were significantly enriched in genes regions, to a considerably greater extent than was observed in the single breed analyses. In addition, we have refined QTL on BTA5 and BTA19 to very small intervals and identified a small number of potential candidate genes in these, as well as in a number of other regions. CONCLUSION: Where QTL are segregating across breed, multibreed GWAS can refine these to reasonably small genomic intervals. However, such QTL appear to represent only a fraction of the genetic variation. Our results suggest a significant proportion of QTL affecting milk production segregate within rather than across breeds, at least for Holstein and Jersey cattle.
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spelling pubmed-39059112014-02-11 Multibreed genome wide association can improve precision of mapping causative variants underlying milk production in dairy cattle Raven, Lesley-Ann Cocks, Benjamin G Hayes, Ben J BMC Genomics Research Article BACKGROUND: Genome wide association studies (GWAS) in most cattle breeds result in large genomic intervals of significant associations making it difficult to identify causal mutations. This is due to the extensive, low-level linkage disequilibrium within a cattle breed. As there is less linkage disequilibrium across breeds, multibreed GWAS may improve precision of causal variant mapping. Here we test this hypothesis in a Holstein and Jersey cattle data set with 17,925 individuals with records for production and functional traits and 632,003 SNP markers. RESULTS: By using a cross validation strategy within the Holstein and Jersey data sets, we were able to identify and confirm a large number of QTL. As expected, the precision of mapping these QTL within the breeds was limited. In the multibreed analysis, we found that many loci were not segregating in both breeds. This was partly an artefact of power of the experiments, with the number of QTL shared between the breeds generally increasing with trait heritability. False discovery rates suggest that the multibreed analysis was less powerful than between breed analyses, in terms of how much genetic variance was explained by the detected QTL. However, the multibreed analysis could more accurately pinpoint the location of the well-described mutations affecting milk production such as DGAT1. Further, the significant SNP in the multibreed analysis were significantly enriched in genes regions, to a considerably greater extent than was observed in the single breed analyses. In addition, we have refined QTL on BTA5 and BTA19 to very small intervals and identified a small number of potential candidate genes in these, as well as in a number of other regions. CONCLUSION: Where QTL are segregating across breed, multibreed GWAS can refine these to reasonably small genomic intervals. However, such QTL appear to represent only a fraction of the genetic variation. Our results suggest a significant proportion of QTL affecting milk production segregate within rather than across breeds, at least for Holstein and Jersey cattle. BioMed Central 2014-01-24 /pmc/articles/PMC3905911/ /pubmed/24456127 http://dx.doi.org/10.1186/1471-2164-15-62 Text en Copyright © 2014 Raven et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Raven, Lesley-Ann
Cocks, Benjamin G
Hayes, Ben J
Multibreed genome wide association can improve precision of mapping causative variants underlying milk production in dairy cattle
title Multibreed genome wide association can improve precision of mapping causative variants underlying milk production in dairy cattle
title_full Multibreed genome wide association can improve precision of mapping causative variants underlying milk production in dairy cattle
title_fullStr Multibreed genome wide association can improve precision of mapping causative variants underlying milk production in dairy cattle
title_full_unstemmed Multibreed genome wide association can improve precision of mapping causative variants underlying milk production in dairy cattle
title_short Multibreed genome wide association can improve precision of mapping causative variants underlying milk production in dairy cattle
title_sort multibreed genome wide association can improve precision of mapping causative variants underlying milk production in dairy cattle
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3905911/
https://www.ncbi.nlm.nih.gov/pubmed/24456127
http://dx.doi.org/10.1186/1471-2164-15-62
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