Animal Breeding and Genetic Program, Institute of Agriculture and Food Research and Technology, Caldes de Montbui, 08140, Spain.
GenPhySE, National Institute for Agronomic Research, Castanet-Tolosan, 31326, France.
Anim Genet. 2020 Oct;51(5):799-810. doi: 10.1111/age.12988. Epub 2020 Jul 22.
Feed efficiency (FE) is one of the most economically and environmentally relevant traits in the animal production sector. The objective of this study was to gain knowledge about the genetic control of FE in rabbits. To this end, GWASs were conducted for individual growth under two feeding regimes (full feeding and restricted) and FE traits collected from cage groups, using 114 604 autosome SNPs segregating in 438 rabbits. Two different models were implemented: (1) an animal model with a linear regression on each SNP allele for growth trait; and (2) a two-trait animal model, jointly fitting the performance trait and each SNP allele content, for FE traits. This last modeling strategy is a new tool applied to GWAS and allows information to be considered from non-genotyped individuals whose contribution is relevant in the group average traits. A total of 189 SNPs in 17 chromosomal regions were declared to be significantly associated with any of the five analyzed traits at a chromosome-wide level. In 12 of these regions, 20 candidate genes were proposed to explain the variation of the analyzed traits, including genes such as FTO, NDUFAF6 and CEBPA previously associated with growth and FE traits in monogastric species. Candidate genes associated with behavioral patterns were also identified. Overall, our results can be considered as the foundation for future functional research to unravel the actual causal mutations regulating growth and FE in rabbits.
饲料效率(FE)是动物生产领域中最具经济和环境相关性的特征之一。本研究的目的是了解兔子 FE 的遗传控制。为此,使用在 438 只兔子中分离的 114604 个常染色体 SNP,针对两种饲养方式(全饲和限饲)下的个体生长和 FE 特性进行了 GWASs 分析,共实施了两种不同的模型:(1)针对每个 SNP 等位基因的线性回归的动物模型,用于生长特性;(2)针对 FE 特性的两性状动物模型,共同拟合表现特性和每个 SNP 等位基因含量。后一种建模策略是应用于 GWAS 的新工具,允许考虑来自非基因型个体的信息,这些个体在群体平均特性中的贡献是相关的。在全染色体水平上,共在 17 个染色体区域的 189 个 SNP 被宣布与五个分析性状中的任何一个显著相关。在其中 12 个区域中,提出了 20 个候选基因来解释分析性状的变异,包括 FTO、NDUFAF6 和 CEBPA 等先前与单胃动物的生长和 FE 特性相关的基因。还鉴定了与行为模式相关的候选基因。总体而言,我们的结果可以被认为是未来功能研究的基础,以揭示调节兔子生长和 FE 的实际因果突变。