289 Genome-wide association study and expression quantitative trait loci analysis identifies a single nucleotide polymorphism associated with both residual feed intake and GFRA2. (7th December 2018)

• Record Type: Journal Article
• Authors: Higgins, M; Fitzsimons, C; McClure, M; McKenna, C; Conroy, S; Kenny, D; McGee, M; Waters, S; Morris, D
• Is Part Of: Journal of animal science. Volume 96(2018)Supplement 3
• Page Start: 108
• Page End: 109
• Publication Date: 2018-12-07
• Subjects: Beef -- Genetics -- RFI; Livestock -- Periodicals; Livestock; Electronic journals; Periodicals; 636.005
• DOI: 10.1093/jas/sky404.238
• Languages: English
• ISSNs: 0021-8812

Abstract

Abstract: Residual feed intake (RFI), a measure of feed efficiency, is an important economic and environmental trait in beef production. Selection of low RFI (feed efficient) cattle could maintain levels of production, while decreasing feed costs and methane emissions. However, RFI is a difficult and expensive trait to measure. Identification of single nucleotide polymorphisms (SNPs) associated with RFI may enable rapid, cost effective genomic selection of feed efficient cattle. The objectives of this study were: to identify genetic variants associated with RFI and related traits (average daily gain (ADG) and feed intake (FI)) in a multi-breed population of Irish beef cattle (n=1492) and to investigate the functional effects of variants associated with the traits of interest. Genome-wide association studies (GWAS) were carried out for individual breeds of Irish beef cattle, followed by meta-analysis of results to identify genetic variants associated with RFI, ADG and FI in a multi-breed population. Previously generated RNA-Seq data from liver and muscle was collated and expression quantitative trait loci (eQTL) analysis was conducted to identify functional effects of GWAS-identified variants. Twenty-four SNPs were associated (P-5) with RFI, ADG or FI. The most associated marker for RFI was rs43555985 (P=8.28E-06). An eQTL was identified between this variant and GFRA2 (P=0.003) where the allele associated with lower RFI is associated with increased GFRA2 expression in liver. GFRA2 influencesbasal metabolic rates, suggesting a mechanism by which genetic variation may contribute to RFI. rs136457441, a SNP associated with ADG in this study, is the only variant identified that alters the protein coding sequence, causing a missense mutation in RPL26. Further investigation is required to uncover the biological role of this marker in ADG variation. This study identified SNPs that may be useful both for genomic selection of feed efficiency traits and for understanding the biology of feed efficiency.