Loading...
Multi-breed, multi-tissue systems biology analysis of beef cattle divergent for feed efficiency
Files
Research Projects
Organizational Units
Journal Issue
Citation
0
Abstract
Provision of feed in beef production systems is a major determinant of profitability. Thus, the identification of genes
implicated in regulating feed efficiency may allow for the selection and subsequent breeding of more feed efficient
cattle, with obvious benefits for sustainability. It is also crucial that gene markers identified as contributing to feed
efficiency are robust across various factors including breed type as well as environmental influence such as diet.
In this study, gene co-expression network analysis was undertaken on RNAseq data generated from Longissimus
dorsi and liver tissue samples collected from steers of two contrasting breed types (Charolais and Holstein-Friesian)
divergent, within breed, for residual feed intake (RFI), across contrasting dietary phases: ((1) high-concentrate; (2)
zero-grazed grass; (3) high-concentrate). Differentially expressed genes (DEG) based on the contrasts of breed, diet
and RFI phenotype were utilised as nodes of the gene co-expression networks. Significant network connections were
identified using an algorithm that exploits the dual concepts of partial correlation and information theory (PCIT).
PCIT network analysis resulted in the formation of three RFI specific clusters of co-expressed genes which were
separated by tissue type. Pathway analysis revealed enrichment (P<0.05) of biological processes related to fatty
acid biosynthesis in both liver and muscle clusters as well as immune-related pathways in a separate muscle specific
cluster. Genes contained within the immune-related cluster were also breed specific DEGs highlighting a potential
role for these genes as robust biomarkers for RFI across varying breed type. Acknowledgement: This research was
funded by the Irish Department of Agriculture, Food and the Marine (RSF13/S/519). Kate Keogh received funding
from the Research Leaders 2025 programme (co-funded by Teagasc and the European Union’s Horizon 2020, Marie
Skłodowska-Curie grant agreement number 754380).