遗传分数omics回归和多特征元分析发现了广泛的cis调节效应,塑造了牛的复杂特征
Ruidong Xiang1,2,3, Lingzhao Fang4,5, Shuli Liu6
1Agriculture Victoria, AgriBio, Centre for AgriBiosciences, Bundoora, VIC 3083, Australia.
PNAS nexus
|July 21, 2025
概括
基因分数奥米克斯回归 (GSOR) 通过将基因表达与遗传预测的表型相关联,改善了基因特征关联发现. 这种方法优于TWAS,揭示了影响多个特征的基因,并为哺乳动物提供了新的生物见解.
科学领域:
- 基因组学和生物信息学
- 量化遗传学 量化遗传学
- 哺乳动物特征协会 哺乳动物特征协会
背景情况:
- 全转录组关联研究 (TWAS) 将遗传预测的基因表达与表型联系起来,但受到小表达训练种群的限制.
- 精确的基因组到现象映射需要克服当前基因表达关联研究的局限性的方法.
研究的目的:
- 引入基因评分奥米克斯回归 (GSOR) 以将观察到的基因表达与遗传预测的表型 (EBV / PGS) 相关联.
- 通过改进奥米克-表型关联来提高对复杂特征的因果基因和生物见解的检测.
主要方法:
- 开发了GSOR,利用cis-genetic分数 (cis-EBV或cis-PGS) 来将基因表达与表型联系起来.
- 将GSOR应用于16种组织和37种特征的大规模牛群数据集 (N~5,000个转录组,~120,000个个体).
- 进行了omics-associations (MTAO) 的多特征元分析,并使用孟德尔随机化和进化约束分析 (dN/dS) 验证了发现.
主要成果:
- 在模拟和真实数据中,GSOR在识别信息基因方面表现优于TWAS.
- 每一个显著的基因表达或拼接事件,平均而言,在8-10个特征中介导着cis-genetic效应.
- 确定了DGAT1,ABO和ACHE等关键基因,显示它们对包括牛奶产量,抗病能力和身体特征在内的多种特征的类效应.
结论:
- GSOR提供了一种强大的新方法来优先考虑奥米克 - 现象类型的关联,推进基因组到现象映射.
- 该研究表明,基因表达和RNA拼接显著影响多种特征,挑战了单基因位置的概念.
- 这些发现为哺乳动物的遗传研究提供了新的生物学见解和方法,对农业和医学有影响.
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