Literature DB >> 24388878

An expression QTL of closely linked candidate genes affects pH of meat in chickens.

Javad Nadaf1, Cecile Berri, Ian Dunn, Estelle Godet, Elisabeth Le Bihan-Duval, Dirk Jan De Koning.   

Abstract

Genetical genomics has been suggested as a powerful approach to study the genotype-phenotype gap. However, the relatively low power of these experiments (usually related to the high cost) has hindered fulfillment of its promise, especially for loci (QTL) of moderate effects.One strategy with which to overcome the issue is to use a targeted approach. It has two clear advantages: (i) it reduces the problem to a simple comparison between different genotypic groups at the QTL and (ii) it is a good starting point from which to investigate downstream effects of the QTL. In this study, from 698 F2 birds used for QTL mapping, gene expression profiles of 24 birds with divergent homozygous QTL genotypes were investigated. The targeted QTL was on chromosome 1 and affected initial pH of breast muscle. The biological mechanisms controlling this trait can be similar to those affecting malignant hyperthermia or muscle fatigue in humans. The gene expression study identified 10 strong local signals that were markedly more significant compared to any genes on the rest of the genome. The differentially expressed genes all mapped to a region <1 Mb, suggesting a remarkable reduction of the QTL interval. These results, combined with analysis of downstream effect of the QTL using gene network analysis, suggest that the QTL is controlling pH by governing oxidative stress. The results were reproducible with use of as few as four microarrays on pooled samples (with lower significance level). The results demonstrate that this cost-effective approach is promising for characterization of QTL.

Entities:  

Keywords:  chicken muscle; eQTL; gene expression; genetical genomics; quantitative trait loci (QTL)

Mesh:

Year:  2014        PMID: 24388878      PMCID: PMC3948812          DOI: 10.1534/genetics.113.160440

Source DB:  PubMed          Journal:  Genetics        ISSN: 0016-6731            Impact factor:   4.562


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