Suppr超能文献

全基因组基因-环境相互作用分析确定肉牛生长性状的新型候选变异体。

Genome-Wide Gene-Environment Interaction Analysis Identifies Novel Candidate Variants for Growth Traits in Beef Cattle.

作者信息

Deng Tianyu, Li Keanning, Du Lili, Liang Mang, Qian Li, Xue Qingqing, Qiu Shiyuan, Xu Lingyang, Zhang Lupei, Gao Xue, Lan Xianyong, Li Junya, Gao Huijiang

机构信息

Institute of Animal Sciences, Chinese Academy of Agricultural Sciences, Beijing 100193, China.

Shaanxi Key Laboratory of Molecular Biology for Agriculture, College of Animal Science and Technology, Northwest A&F University, Yangling, Xianyang 712100, China.

出版信息

Animals (Basel). 2024 Jun 5;14(11):1695. doi: 10.3390/ani14111695.

Abstract

Complex traits are widely considered to be the result of a compound regulation of genes, environmental factors, and genotype-by-environment interaction (G × E). The inclusion of G × E in genome-wide association analyses is essential to understand animal environmental adaptations and improve the efficiency of breeding decisions. Here, we systematically investigated the G × E of growth traits (including weaning weight, yearling weight, 18-month body weight, and 24-month body weight) with environmental factors (farm and temperature) using genome-wide genotype-by-environment interaction association studies (GWEIS) with a dataset of 1350 cattle. We validated the robust estimator's effectiveness in GWEIS and detected 29 independent interacting SNPs with a significance threshold of 1.67 × 10, indicating that these SNPs, which do not show main effects in traditional genome-wide association studies (GWAS), may have non-additive effects across genotypes but are obliterated by environmental means. The gene-based analysis using MAGMA identified three genes that overlapped with the GEWIS results exhibiting G × E, namely , , and . Further, the results of functional exploration in gene-set analysis revealed the bio-mechanisms of how cattle growth responds to environmental changes, such as mitotic or cytokinesis, fatty acid β-oxidation, neurotransmitter activity, gap junction, and keratan sulfate degradation. This study not only reveals novel genetic loci and underlying mechanisms influencing growth traits but also transforms our understanding of environmental adaptation in beef cattle, thereby paving the way for more targeted and efficient breeding strategies.

摘要

复杂性状被广泛认为是基因、环境因素以及基因与环境相互作用(G×E)复合调控的结果。在全基因组关联分析中纳入G×E对于理解动物的环境适应性和提高育种决策效率至关重要。在此,我们使用全基因组基因与环境相互作用关联研究(GWEIS),利用1350头牛的数据集,系统地研究了生长性状(包括断奶体重、周岁体重、18月龄体重和24月龄体重)与环境因素(农场和温度)之间的G×E。我们验证了稳健估计器在GWEIS中的有效性,并检测到29个独立的相互作用单核苷酸多态性(SNP),其显著性阈值为1.67×10,这表明这些在传统全基因组关联研究(GWAS)中未显示出主效应的SNP,可能在不同基因型间具有非加性效应,但被环境因素掩盖了。使用MAGMA进行的基于基因的分析确定了三个与表现出G×E的GEWIS结果重叠的基因,即 、 和 。此外,基因集分析中的功能探索结果揭示了牛生长对环境变化作出反应的生物机制,如细胞有丝分裂或胞质分裂、脂肪酸β氧化、神经递质活性、间隙连接和硫酸角质素降解。本研究不仅揭示了影响生长性状的新遗传位点和潜在机制,还改变了我们对肉牛环境适应性的理解,从而为更具针对性和高效的育种策略铺平了道路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b1c5/11171348/1cf0395ae0bb/animals-14-01695-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验