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. 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. 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.

中文翻译：

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三种饲料效率标准的基因网络揭示了共同的和特定的生物学过程

法国牛肉生产者的农场盈利能力下降，主要是因为饲料成本的持续上涨。选择肉牛饲料效率是解决此问题的一种相关解决方案。但是，饲料效率是一个复杂的特征，可以通过三个主要标准进行评估：残余饲料摄入量（RFI），残余增重（RG）和饲料效率比（FE），它们涉及不同的遗传确定性。结合表型和全基因组序列数据的分析为基因组研究提供了独特的框架。我们研究的目的是确定负责这三个饲料效率标准的遗传决定论的基因网络和生物学过程。对1477名法国夏洛来牛年轻公牛的表型进行了采食量（FI）的分析，平均每日增重（ADG）和最终体重（FW），以估算RFI，RG和FE。在BovineSNP50单核苷酸多态性（SNP）阵列上对789头小公牛的子集进行基因分型，并使用1000 Bull Genomes Project的RUN6在序列水平上进行估算。我们进行了全基因组关联研究（GWAS），以评估850万个SNP的个体作用，并应用了关联权重矩阵（AWM）方法来分析结果，其中一项针对每种饲料效率标准。结果强调了包括626个RFI基因，426个RG基因和564个FE基因的协同网络。富集评估揭示了与RFI，RG和FE具有最强关联的生物学过程，即消化道（唾液，胃和粘蛋白的分泌）和代谢过程（细胞和心血管）。精力充沛的功能与RFI和FE以及RG的心血管和细胞过程有关。还鉴定了几种激素，例如阿珀林，胰高血糖素，胰岛素，醛固酮，促性腺激素释放激素和甲状腺激素，这些激素应在以后的研究中作为饲料效率的候选生物标志物进行测试。网络和途径分析在序列水平上的结合导致对RFI，RG和FE涉及的常见机制和特定机制的鉴定，并更好地理解了这三个标准的遗传决定论。需要在基因组评估中测试参与每个已鉴定过程的基因的作用，以确认使用功能性变体选择动物饲料效率的可靠性的潜在提高。