Global gene expression profiling reveals genes expressed differentially in cattle with high and low residual feed intake

Title
Global gene expression profiling reveals genes expressed differentially in cattle with high and low residual feed intake
Publication Date
2011
Author(s)
Chen, Yizhou
Gondro, Cedric
( author )
OrcID: https://orcid.org/0000-0003-0666-656X
Email: cgondro2@une.edu.au
UNE Id une-id:cgondro2
Quinn, Kim
Herd, Robert M
( author )
OrcID: https://orcid.org/0000-0003-4689-5519
Email: rherd3@une.edu.au
UNE Id une-id:rherd3
Parnell, P F
Vanselow, Barbara
Type of document
Journal Article
Language
en
Entity Type
Publication
Publisher
Wiley-Blackwell Publishing Ltd
Place of publication
United Kingdom
DOI
10.1111/j.1365-2052.2011.02182.x
UNE publication id
une:10317
Abstract
Feed efficiency is an economically important trait in beef production. It can be measured as residual feed intake. This is the difference between actual feed intake recorded over a test period and the expected feed intake of an animal based on its size and growth rate. DNA-based marker-assisted selection would help beef breeders to accelerate genetic improvement for feed efficiency by reducing the generation interval and would obviate the high cost of measuring residual feed intake. Although numbers of quantitative trait loci and candidate genes have been identified with the advance of molecular genetics, our understanding of the physiological mechanisms and the nature of genes underlying residual feed intake is limited. The aim of the study was to use global gene expression profiling by microarray to identify genes that are differentially expressed in cattle, using lines genetically selected for low and high residual feed intake, and to uncover candidate genes for residual feed intake. A long-oligo microarray with 24 000 probes was used to profile the liver transcriptome of 44 cattle selected for high or low residual feed intake. One hundred and sixty-one unique genes were identified as being differentially expressed between animals with high and low residual feed intake. These genes were involved in seven gene networks affecting cellular growth and proliferation, cellular assembly and organization, cell signalling, drug metabolism, protein synthesis, lipid metabolism, and carbohydrate metabolism. Analysis of functional data using a transcriptional approach allows a better understanding of the underlying biological processes involved in residual feed intake and also allows the identification of candidate genes for marker-assisted selection.
Link
Citation
Animal Genetics, 42(5), p. 475-490
ISSN
1365-2052
0268-9146
Start page
475
End page
490

Files:

NameSizeformatDescriptionLink