Gene networks for three feed efficiency criteria reveal shared and specific biological processes

Abstract

Background French beef producers suffer from the decrease in profitability of their farms mainly because of the continuous increase in feed costs. Selection for feed efficiency in beef cattle represents a relevant solution to face this problem. However, feed efficiency is a complex trait that can be assessed by three major criteria: residual feed intake (RFI), residual gain (RG) and feed efficiency ratio (FE), which involve different genetic determinisms. An analysis that combines phenotype and whole-genome sequence data provides a unique framework for genomic studies. The aim of our study was to identify the gene networks and the biological processes that are responsible for the genetic determinism that is shared between these three feed efficiency criteria. Results A population of 1477 French Charolais young bulls was phenotyped for feed intake (FI), average daily gain (ADG) and final weight (FW) to estimate RFI, RG and FE. A subset of 789 young bulls was genotyped on the BovineSNP50 single nucleotide polymorphism (SNP) array and imputed at the sequence level using RUN6 of the 1000 Bull Genomes Project. We conducted a genome-wide association study (GWAS) to estimate the individual effect of 8.5 million SNPs and applied an association weight matrix (AWM) approach to analyse the results, one for each feed efficiency criterion. The results highlighted co-association networks including 626 genes for RFI, 426 for RG and 564 for FE. Enrichment assessment revealed the biological processes that show the strongest association with RFI, RG and FE, i.e. digestive tract (salivary, gastric and mucin secretion) and metabolic processes (cellular and cardiovascular). Energetic functions were more associated with RFI and FE and cardio-vascular and cellular processes with RG. Several hormones such as apelin, glucagon, insulin, aldosterone, the gonadotrophin releasing hormone and the thyroid hormone were also identified, and these should be tested in future studies as candidate biomarkers for feed efficiency. Conclusions The combination of network and pathway analyses at the sequence level led to the identification of both common and specific mechanisms that are involved in RFI, RG and FE, and to a better understanding of the genetic determinism underlying these three criteria. The effects of the genes involved in each of the identified processes need to be tested in genomic evaluations to confirm the potential gain in reliability of using functional variants to select animals for feed efficiency.

Genomic characterization of the world’s longest selection experiment in mouse reveals the complexity of polygenic traits

“…In line with the obese phenotype, DU6 candidate genes overlapping RDDs regulate energy metabolism and food intake ( Hcrt [ 79 ]) and are linked to feed efficiency ( Wdr27 [ 80 ]) and body composition in other species ( Atp11b [ 81 ]). DU6 mice also exhibit larger bones [ 21 ], and the analysis of SVs detected Smad5 , a modulator of bone formation [ 82 ], to be partially overlapped by a heterozygous deletion and a heterozygous inversion.…”

Genomic characterization of world’s longest selection experiment in mouse reveals the complexity of polygenic traits

“…The “giant” DU6 line (selected for body mass at 6 weeks of age) exhibits an obese phenotype 7 while the protein-mass line DU6P (selected for protein mass in the carcass) is lean and muscular 93 . In line with the obese phenotype, DU6 candidate genes overlapping RDDs regulate energy metabolism and food intake ( Hcrt 94 ) and are linked to feed efficiency and body composition in other species ( Atp11 95 , Wdr27 96 ). On the other hand, DU6 mice also exhibit larger bones 59 and the analysis of SVs detected Smad5 , a modulator of bone formation 97 , to be partially overlapped by a heterozygous deletion and a heterozygous inversion.…”

Genome-Wide Association Study of Feed Efficiency Related Traits in Ducks

“…However, the FE trait is a complex phenotype that can be difficult to assess as compared with other traits [ 33 ]. Some signaling pathways have been related to FE, but very few candidate genes have been identified [ 34 , 35 , 36 ]. One possible explanation for this lack of knowledge is that FE is a complicated economic trait that may be controlled by many different genes.…”