No abstract

In this study, biological networks were reconstructed from genes and metabolites significantly associated with residual feed intake (RFI) in beef cattle. The networks were then used to identify biological pathways associated with RFI. RFI is a measure of feed efficiency, which is independent of body size and growth; therefore selection for RFI is expected to result in cattle that consume less feed without adverse effects on growth rate and mature size. Although several studies have identified genes associated with RFI, the mechanisms of the biological processes are not well understood. In this study, we utilised the results obtained from two association studies, one using 24 genes and one using plasma metabolites to reconstruct biological networks associated with RFI using IPA software (Igenuity Systems). The results pointed to biological processes such as lipid and steroid biosynthesis, protein and carbohydrate metabolism and regulation of gene expression through DNA transcription, protein stability and degradation. The major canonical pathways included signaling of growth hormone, Oncostatin M, insulin-like growth factor and AMP activated protein kinase, and cholesterol biosynthesis. This study provides information on potential biological mechanisms, and genes and metabolites involved in feed efficiency in beef cattle.

The candidate gene approach was used to identify genes associated with residual feed intake (RFI) in beef steers. The approach uses prior knowledge of gene functions to predict their biological role in the variation observed in a trait. It is suited to identify genes associated with complex traits where each gene has a relatively small effect. First, positional candidate genes were identified within the genomic positions of previously reported QTL associated with component traits related to RFI such as dry matter intake (DMI), growth, feed conversion ratio (FCR), average daily gain (ADG), and energy balance. Secondly, the positional candidate genes were prioritized into functional candidate genes according to their biological functions and their relationship with the biological processes associated with RFI including carbohydrate, fat and protein metabolism, thermoregulation, immunity and muscle activity. Single nucleotide polymorphisms (SNPs) located within the functional candidate genes were identified using mRNA sequences and prioritized into functional classes such as non-synonymous (nsSNP), synonymous (sSNP) or intronic SNP. A total of 117 nsSNP were considered as functional SNP and genotyped in steers at the University of Alberta ranch in Kinsella. Multiple marker association analysis in ASReml was performed using RFI data obtained from 531 beef steers. Twenty-five SNP were significantly associated with RFI (P < 0.05) accounting for 19.7% of the phenotypic variation. Using SIFT program to predict the effect of the SNP on the function of the corresponding protein, 3 of the 25 SNP were predicted to cause a significant effect on protein function (P < 0.05). One of the 3 SNP was located in the GHR gene and was also associated with a significant effect on the tertiary structure of the GHR protein (P < 0.05) as modeled using SWISSModel software. Least square means for each genotype were estimated and an over-dominance effect was observed for the SNP located in the GHR, CAST, ACAD11 and UGT3A1 genes. In addition, 2 other SNP showed a dominance effect and 3 genes had an additive effect. Gene network analysis performed in Ingenuity pathway analysis (IPA) software (Ingenuity Systems, www.ingenuity.com) indicated that the significant genes were involved in biological pathways such as lipid, protein and energy metabolism, electron transport and membrane signaling. The genes in this study, if validated in other beef cattle populations, may be useful for marker assisted selection for feed efficiency.

The objective of this study was to develop and validate a customized cost-effective single nucleotide polymorphism (SNP) panel for genetic improvement of feed efficiency in beef cattle. The SNPs identified in previous association studies and through extensive analysis of candidate genomic regions and genes, were screened for their functional impact and allele frequency in Angus and Hereford breeds used as validation candidates for the panel. Association analyses were performed on genotypes of 159 SNPs from new samples of Angus (n = 160), Hereford (n = 329), and Angus-Hereford crossbred (n = 382) cattle using allele substitution and genotypic models in ASReml. Genomic heritabilities were estimated for feed efficiency traits using the full set of SNPs, SNPs associated with at least one of the traits (at P ≤ 0.05 and P < 0.10), as well as the Illumina bovine 50K representing a widely used commercial genotyping panel. A total of 63 SNPs within 43 genes showed association (P ≤ 0.05) with at least one trait. The minor alleles of SNPs located in the GHR and CAST genes were associated with decreasing effects on residual feed intake (RFI) and/or RFI adjusted for backfat (RFIf), whereas minor alleles of SNPs within MKI67 gene were associated with increasing effects on RFI and RFIf. Additionally, the minor allele of rs137400016 SNP within CNTFR was associated with increasing average daily gain (ADG). The SNPs genotypes within UMPS, SMARCAL, CCSER1, and LMCD1 genes showed significant over-dominance effects whereas other SNPs located in SMARCAL1, ANXA2, CACNA1G, and PHYHIPL genes showed additive effects on RFI and RFIf. Gene enrichment analysis indicated that gland development, as well as ion and cation transport are important physiological mechanisms contributing to variation in feed efficiency traits. The study revealed the effect of the Jak-STAT signaling pathway on feed efficiency through the CNTFR, OSMR, and GHR genes. Genomic heritability using the 63 significant (P ≤ 0.05) SNPs was 0.09, 0.09, 0.13, 0.05, 0.05, and 0.07 for ADG, dry matter intake, midpoint metabolic weight, RFI, RFIf, and backfat, respectively. These SNPs contributed to genetic variation in the studied traits and thus can potentially be used or tested to generate cost-effective molecular breeding values for feed efficiency in beef cattle.