一种可扩展和强大的差异组件方法揭示了基因环境相互作用架构的洞察力,这些相互作用是复杂特征的基础
Ali Pazokitoroudi1, Andrew Dahl2, Noah Zaitlen3,4
1Department of Computer Science, UCLA, Los Angeles, CA, USA.
bioRxiv : the preprint server for biology
|January 3, 2024
概括
基因与环境的相互作用 (GxE) 显著促进了复杂的特征变异,影响了疾病风险和遗传预测的准确性. 我们的新方法量化了GxE遗传性,揭示了它在整个基因组和特定组织中的结构.
科学领域:
- 遗传学和生物信息学
- 复杂的特征遗传学复杂的特征遗传学
- 统计基因组学 统计基因组学
背景情况:
- 基因环境相互作用 (GxE) 对于理解复杂的特征变异和疾病风险至关重要.
- 目前对大型生物银行的GxE架构的理解仍然有限.
- 精确估计GxE遗传性对于改善遗传风险预测至关重要.
研究的目的:
- 引入和验证一种用于估计全基因组GxE遗传性和附加遗传性的新方法.
- 将该方法应用于50个定量特征和4个环境变量的大规模英国生物库数据.
- 研究基因组架构和GxE效应的特定组织丰富.
主要方法:
- 开发了一种计算效率高的方法来估计GxE遗传性和附加遗传性.
- 将该方法应用于英国生物库数据 (约30万个体,约50万个数组SNP,50个特征,4个环境变量).
- 分析了归算的SNP (约800万) 和按MAF和LD得分分区GxE遗传性;测试了组织特异性丰富性.
主要成果:
- 确定了69个重要的特征-环境变量对,用于GxE遗传性.
- 平均GxE遗传率约为附加遗传率的6.8%,值得注意的例子包括与性别相关的WHR (19.6%) 和与年龄相关的LDL胆固醇 (9.8%).
- GxE遗传性随着归算的SNP增加,在特定组织 (例如大脑,脂肪,心血管) 显示丰富,GxE效应随着MAF和LD的减少而增加.
结论:
- 开发的方法准确地估计了生物库规模数据集中的GxE遗传性.
- 在复杂的特征变异中,GxE扮演着重要的角色,具体的基因-环境对和组织特异性影响的实质性贡献.
- 这些发现为GxE的架构提供了详细的见解,进步了我们对复杂特征和疾病风险的理解.
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