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Genome-wide detection of genetic markers associated with growth and fatness in four pig populations using four approaches
BACKGROUND: Genome-wide association studies (GWAS) have been extensively used to identify genomic regions associated with a variety of phenotypic traits in pigs. Until now, most GWAS have explored single-trait association models. Here, we conducted both single- and multi-trait GWAS and a meta-analys...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5307927/ https://www.ncbi.nlm.nih.gov/pubmed/28196480 http://dx.doi.org/10.1186/s12711-017-0295-4 |
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author | Guo, Yuanmei Huang, Yixuan Hou, Lijuan Ma, Junwu Chen, Congying Ai, Huashui Huang, Lusheng Ren, Jun |
author_facet | Guo, Yuanmei Huang, Yixuan Hou, Lijuan Ma, Junwu Chen, Congying Ai, Huashui Huang, Lusheng Ren, Jun |
author_sort | Guo, Yuanmei |
collection | PubMed |
description | BACKGROUND: Genome-wide association studies (GWAS) have been extensively used to identify genomic regions associated with a variety of phenotypic traits in pigs. Until now, most GWAS have explored single-trait association models. Here, we conducted both single- and multi-trait GWAS and a meta-analysis for nine fatness and growth traits on 2004 pigs from four diverse populations, including a White Duroc × Erhualian F(2) intercross population and Chinese Sutai, Laiwu and Erhualian populations. RESULTS: We identified 44 chromosomal regions that were associated with the nine traits, including four genome-wide significant single nucleotide polymorphisms (SNPs) on SSC2 (SSC for Sus scrofa chromosome), 4, 7 and X. Compared to the single-population GWAS, the meta-analysis was less powerful for the identification of SNPs with population-specific effects but more powerful for the detection of SNPs with population-shared effects. Multiple-trait analysis reduced the power to detect trait-specific SNPs but significantly enhanced the power to identify common SNPs across traits. The SNP on SSC7 had pleiotropic effects on the nine traits in the F(2) and Erhualian populations. Another pleiotropic SNP was observed on SSCX for these traits in the F(2) and Sutai populations. Both population-specific and shared SNPs were identified in this study, thus reflecting the complex genetic architecture of pig growth and fatness traits. CONCLUSIONS: We demonstrate that the multi-trait method and the meta-analysis on multiple populations can be used to increase the power of GWAS. The two significant SNPs on SSC7 and X had pleiotropic effects in the F(2), Erhualian and Sutai populations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12711-017-0295-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5307927 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-53079272017-03-13 Genome-wide detection of genetic markers associated with growth and fatness in four pig populations using four approaches Guo, Yuanmei Huang, Yixuan Hou, Lijuan Ma, Junwu Chen, Congying Ai, Huashui Huang, Lusheng Ren, Jun Genet Sel Evol Research Article BACKGROUND: Genome-wide association studies (GWAS) have been extensively used to identify genomic regions associated with a variety of phenotypic traits in pigs. Until now, most GWAS have explored single-trait association models. Here, we conducted both single- and multi-trait GWAS and a meta-analysis for nine fatness and growth traits on 2004 pigs from four diverse populations, including a White Duroc × Erhualian F(2) intercross population and Chinese Sutai, Laiwu and Erhualian populations. RESULTS: We identified 44 chromosomal regions that were associated with the nine traits, including four genome-wide significant single nucleotide polymorphisms (SNPs) on SSC2 (SSC for Sus scrofa chromosome), 4, 7 and X. Compared to the single-population GWAS, the meta-analysis was less powerful for the identification of SNPs with population-specific effects but more powerful for the detection of SNPs with population-shared effects. Multiple-trait analysis reduced the power to detect trait-specific SNPs but significantly enhanced the power to identify common SNPs across traits. The SNP on SSC7 had pleiotropic effects on the nine traits in the F(2) and Erhualian populations. Another pleiotropic SNP was observed on SSCX for these traits in the F(2) and Sutai populations. Both population-specific and shared SNPs were identified in this study, thus reflecting the complex genetic architecture of pig growth and fatness traits. CONCLUSIONS: We demonstrate that the multi-trait method and the meta-analysis on multiple populations can be used to increase the power of GWAS. The two significant SNPs on SSC7 and X had pleiotropic effects in the F(2), Erhualian and Sutai populations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12711-017-0295-4) contains supplementary material, which is available to authorized users. BioMed Central 2017-02-14 /pmc/articles/PMC5307927/ /pubmed/28196480 http://dx.doi.org/10.1186/s12711-017-0295-4 Text en © The Author(s) 2017 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 Guo, Yuanmei Huang, Yixuan Hou, Lijuan Ma, Junwu Chen, Congying Ai, Huashui Huang, Lusheng Ren, Jun Genome-wide detection of genetic markers associated with growth and fatness in four pig populations using four approaches |
title | Genome-wide detection of genetic markers associated with growth and fatness in four pig populations using four approaches |
title_full | Genome-wide detection of genetic markers associated with growth and fatness in four pig populations using four approaches |
title_fullStr | Genome-wide detection of genetic markers associated with growth and fatness in four pig populations using four approaches |
title_full_unstemmed | Genome-wide detection of genetic markers associated with growth and fatness in four pig populations using four approaches |
title_short | Genome-wide detection of genetic markers associated with growth and fatness in four pig populations using four approaches |
title_sort | genome-wide detection of genetic markers associated with growth and fatness in four pig populations using four approaches |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5307927/ https://www.ncbi.nlm.nih.gov/pubmed/28196480 http://dx.doi.org/10.1186/s12711-017-0295-4 |
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