文献类型： 外文期刊

第一作者： Deng, Tianyu

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

作者机构：

关键词： genotype-by-environment interaction; robust estimator; cattle; gene-based analysis; gene-set analysis

期刊名称：ANIMALS （ 影响因子：2.7； 五年影响因子：3.0 ）

ISSN： 2076-2615

年卷期： 2024 年 14 卷 11 期

页码：

收录情况： SCI

摘要： Simple Summary Growth traits have been widely studied as economically important traits in the beef cattle industry. However, traditional studies often miss how these traits change under different environmental conditions, only focusing on single genetic changes that affect traits directly. In our study, we analyzed how genetics and environment interact to affect growth in beef cattle, considering four growth traits and two environmental factors. This analysis uncovered several genetic markers for growth traits that are not usually evident in standard studies, showing that some genes have effects that can be obliterated by environmental conditions Further testing showed whether these genetic markers are grouped in specific genes or functional pathways, helping us understand how genetics can influence growth under different environmental conditions. By uncovering novel genetic loci, genes, and candidate biological mechanisms associated with growth traits, our study provides valuable information for selection prediction and breeding decisions in the beef cattle industry.Abstract Complex traits are widely considered to be the result of a compound regulation of genes, environmental factors, and genotype-by-environment interaction (G x E). The inclusion of G x 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 x 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 x 10-6, 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 x E, namely SMAD2, PALMD, and MECOM. 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 beta-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.

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