Animal Production Science Animal Production Science Society
Food, fibre and pharmaceuticals from animals
RESEARCH ARTICLE

Genome-wide association studies, meta-analyses and derived gene network for meat quality and carcass traits in pigs

Darlene Ana S. Duarte A , Marina Rufino S. Fortes B , Marcio de Souza Duarte A , Simone E. F. Guimarães A , Lucas L. Verardo A , Renata Veroneze A , André Mauric F. Ribeiro A , Paulo Sávio Lopes A , Marcos Deon V. de Resende C and Fabyano Fonseca e Silva A D
+ Author Affiliations
- Author Affiliations

A Department of Animal Science, Universidade Federal de Viçosa (UFV), Viçosa, MG, Brazil.

B School of Chemistry and Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia.

C Embrapa Florestas/Universidade Federal de Viçosa (UFV), Colombo, PR, Brazil.

D Corresponding author. Email: fabyanofonseca@ufv.br

Animal Production Science - https://doi.org/10.1071/AN16018
Submitted: 8 January 2016  Accepted: 15 November 2016   Published online: 21 March 2017

Abstract

A large number of quantitative trait loci (QTL) for meat quality and carcass traits has been reported in pigs over the past 20 years. However, few QTL have been validated and the biological meaning of the genes associated to these QTL has been underexploited. In this context, a meta-analysis was performed to compare the significant markers with meta-QTL previously reported in literature. Genome association studies were performed for 12 traits, from which 144 SNPs were found out to be significant (P < 0.05). They were validated in the meta-analysis and used to build the Association Weight Matrix, a matrix framework employed to investigate co-association of pairwise SNP across phenotypes enabling to derive a gene network. A total of 45 genes were selected from the Association Weight Matrix analysis, from which 25 significant transcription factors were identified and used to construct the networks associated to meat quality and carcass traits. These networks allowed the identification of key transcription factors, such as SOX5 and NKX25, gene–gene interactions (e.g. ATP5A1, JPH1, DPT and NEDD4) and pathways related to the regulation of adipose tissue metabolism and skeletal muscle development. Validated SNPs and knowledge of key genes driving these important industry traits might assist future strategies in pig breeding.

Additional keywords: biological pathways, post-GWAS, SNP-derived gene networks.


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