Dissection of beef quality phenotypes using a myogenin network-anchored systems biology approach
A. Reverter A B , E. K. F. Chan A , S. A. Lehnert A , W. Barris A , S. M. McWilliam A , B. P. Dalrymple A and W. Barendse AA Cooperative Research Centre for Beef Genetic Technologies, CSIRO Livestock Industries, Queensland Bioscience Precinct, 306 Carmody Road, St. Lucia, Qld 4067, Australia.
B Corresponding author. Email: Toni.Reverter-Gomez@csiro.au
Australian Journal of Experimental Agriculture 48(8) 1053-1061 https://doi.org/10.1071/EA08052
Submitted: 23 January 2008 Accepted: 5 May 2008 Published: 14 July 2008
Abstract
In order to uncover genes with transcriptional activity linked to various beef quality phenotypes of interest, we designed a systems biology approach. We focussed on traits representing the three major categories of growth and development, fat depots and meat quality phenotypes. We proceeded by linking bovine gene expression data derived from 147 microarray hybridisation experiments and high density marker data from 9260 single nucleotide polymorphisms (SNP) on 189 steers. The individuals in the genotyping study were unrelated to the samples used for expression profiling. The linkage was performed by anchoring these data to a gene network for myogenin (MYOG), a muscle-specific transcription factor essential for the development of skeletal muscle. This approach was able to identify and estimate the strength of the relationship between the statistical association of a SNP to a phenotype of interest with the transcriptional activity of genes in the network. The genes from the MYOG-centred network that were significantly associated with the largest number of meat quality traits were PDLIM3, CALM1 and CRYAB. Among our findings, a novel association between desmin and meat colour points to an alternative biochemical basis for meat colour differences involving costameric structures and their previously reported relationship with tenderness. These newly generated hypotheses can help formulate sound research to further illuminate the genetic architecture of beef quality phenotypes.
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