对转录因子与非编码变体的结合的系统分析
Jian Yan1,2,3,4, Yunjiang Qiu5,6, André M Ribeiro Dos Santos5,7
1School of Medicine, Northwest University, Xi'an, China. jian.yan@cityu.edu.hk.
Nature
|January 28, 2021
概括
研究人员使用SNP-SELEX将转录因子结合到95,886种非编码变体. 这通过改进预测模型来提高对人类特征和疾病的遗传变异的理解.
科学领域:
- 基因组学
- 分子生物学
- 生物信息学
背景情况:
- 非编码DNA变异与人类的特征和疾病有关,但它们的功能影响很难确定.
- 了解转录因子结合对于破译非编码变体的作用至关重要.
研究的目的:
- 系统地评估对大量人类非编码变体的转录因子结合.
- 评估和改进用于预测转录因子结合的变异效应的计算方法.
- 开发转录因子结合的预测模型,并将其应用于人类疾病研究.
主要方法:
- 通过指数式丰富 (SNP-SELEX) 系统演化对象的单核酸多态性评估,是一种超高通量测试.
- 测量了270个人类转录因子与95,886个非编码变体的结合,产生了8. 28亿次相互作用测量.
- 位置重量矩阵与有间隙 k-mer 表示的支向量机器的预测性能比较.
主要成果:
- 在预测转录因子结合方面,证明具有间隙k-mer表示的支持向量机显著优于传统的位置重量矩阵.
- 开发了94种人类转录因子的高度预测模型.
- 在61,020个独立的序列变异中验证了改进的预测模型.
结论:
- 开发的模型为理解非编码变体的功能后果提供了强大的工具.
- 这项工作增强了全基因组关联研究 (GWAS) 的实用性,并揭示了人类特征和疾病中的分子途径.
- 改进转录因子-DNA相互作用的预测是将非编码变体与生物功能联系起来的关键.
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