School of Environmental & Rural Science, University of New England, Armidale, NSW, 2351, Australia.
Genet Sel Evol. 2022 Jun 3;54(1):40. doi: 10.1186/s12711-022-00734-6.
Selection of livestock based on their robustness or sensitivity to environmental variation could help improve the efficiency of production systems, particularly in the light of climate change. Genetic variation in robustness arises from genotype-by-environment (G × E) interactions, with genotypes performing differently when animals are raised in contrasted environments. Understanding the nature of this genetic variation is essential to implement strategies to improve robustness. In this study, our aim was to explore the genetics of robustness in Australian sheep to different growth environments using linear reaction norm models (RNM), with post-weaning weight records of 22,513 lambs and 60 k single nucleotide polymorphisms (SNPs). The use of scale-corrected genomic estimated breeding values (GEBV) for the slope to account for scale-type G × E interactions was also investigated.
Additive genetic variance was observed for the slope of the RNM, with genetic correlations between low- and high-growth environments indicating substantial re-ranking of genotypes (0.44-0.49). The genetic variance increased from low- to high-growth environments. The heritability of post-weaning body weight ranged from 0.28 to 0.39. The genetic correlation between intercept and slope of the reaction norm for post-weaning body weight was low to moderate when based on the estimated (co)variance components but was much higher when based on back-solved SNP effects. An initial analysis suggested that a region on chromosome 11 affected both the intercept and the slope, but when the GEBV for the slope were conditioned on the GEBV for the intercept to remove the effect of scale-type G × E interactions on SNP effects for robustness, a single genomic region on chromosome 7 was found to be associated with robustness. This region included genes previously associated with growth traits and disease susceptibility in livestock.
This study shows a significant genetic variation in the slope of RNM that could be used for selecting for increased robustness of sheep. Both scale-type and rank-type G × E interactions contributed to variation in the slope. The correction for scale effects of GEBV for the slope should be considered when analysing robustness using RNM. Overall, robustness appears to be a highly polygenic trait.
基于家畜对环境变化的稳健性或敏感性进行选择，有助于提高生产系统的效率，特别是在气候变化的背景下。稳健性的遗传变异源于基因型与环境（G×E）的相互作用，当动物在不同环境中生长时，基因型的表现会有所不同。了解这种遗传变异的性质对于实施提高稳健性的策略至关重要。在这项研究中，我们的目的是使用线性反应规范模型（RNM）探索澳大利亚绵羊对不同生长环境的稳健性的遗传基础，该模型使用了 22513 只羔羊和 60k 个单核苷酸多态性（SNP）的断奶后体重记录。还研究了使用校正规模的基因组估计育种值（GEBV）来解释规模型 G×E 相互作用对斜率的影响。
RNM 的斜率存在加性遗传方差，低生长环境和高生长环境之间的遗传相关表明基因型的大量重新排序（0.44-0.49）。遗传方差从低生长环境增加到高生长环境。断奶后体重的遗传力范围在 0.28 到 0.39 之间。基于估计（协）方差分量，反应规范的截距和斜率之间的遗传相关性较低，但基于回溯 SNP 效应的遗传相关性较高。初步分析表明，11 号染色体上的一个区域影响了截距和斜率，但当斜率的 GEBV 基于截距的 GEBV 进行校正以消除规模型 G×E 相互作用对稳健性 SNP 效应的影响时，发现 7 号染色体上的一个单一基因组区域与稳健性相关。该区域包括先前与家畜生长性状和疾病易感性相关的基因。
本研究表明，RNM 的斜率存在显著的遗传变异，可用于选择提高绵羊的稳健性。规模型和排名型 G×E 相互作用都导致了斜率的变化。在使用 RNM 分析稳健性时，应考虑对斜率的 GEBV 进行规模效应的校正。总的来说，稳健性似乎是一个高度多基因性状。
