Characterization of Genes for Beef Marbling Based on Applying Gene Coexpression Network

Hye-Sun Park,Yong-Min Cho,Nam-Kuk Kim,Heebal Kim,Seung-Hwan Lee,Dajeong Lim,Han-Ha Chai

doi:10.1155/2014/708562

Abstract

Marbling is an important trait in characterization beef quality and a major factor for determining the price of beef in the Korean beef market. In particular, marbling is a complex trait and needs a system-level approach for identifying candidate genes related to the trait. To find the candidate gene associated with marbling, we used a weighted gene coexpression network analysis from the expression value of bovine genes. Hub genes were identified; they were topologically centered with large degree and BC values in the global network. We performed gene expression analysis to detect candidate genes in M. longissimus with divergent marbling phenotype (marbling scores 2 to 7) using qRT-PCR. The results demonstrate that transmembrane protein 60 (TMEM60) and dihydropyrimidine dehydrogenase (DPYD) are associated with increasing marbling fat. We suggest that the network-based approach in livestock may be an important method for analyzing the complex effects of candidate genes associated with complex traits like marbling or tenderness.

Highlights

Marbling is a major trait in characterzing beef quality and an important factor for determining the price of beef in the Korean beef market
A gene coexpression network (GCN) is a gene correlation network created from expression profiling, with each gene
The weighted gene coexpression analysis (WGCNA) software packages for R were used to identify coexpression values associated with marbling score [25]

Summary

Introduction

Marbling (intramuscular fat) is a major trait in characterzing beef quality and an important factor for determining the price of beef in the Korean beef market It is a complex trait, which is obtained from many genes like tenderness. A complex trait like marbling demands such an approach, because no single factor determines a large proportion of the trait variations in the population [1] For this reason, systems biology approach has been useful to identify genes that underlie complex trait from network of genetic interactions among all possible genes. System-oriented approaches have been applied by animal geneticists to investigate livestock traits [3,4,5], resulting in the identification and characterization of economically important causal transacting genes within QTL regions. We introduce a systemic approach involving network analysis of marbling score-related genes and experimental evidence confirming that highly connected genes (hubs) are significantly different between high- and low-marbling groups

Materials and Methods

Results and Discussion

Conclusion