对全基因组的烯碳化合物受体-DNA结合的可解释的预测模型揭示了组织特异性的结合决定因素
David Filipovic1,2,3, Wenjie Qi1,2,3, Omar Kana3,4,5
1Department of Biomedical Engineering, Michigan State University, East Lansing, Michigan 48824, USA.
Toxicological sciences : an official journal of the Society of Toxicology
|September 14, 2023
概括
基碳化合物受体 (AhR) 通过二氧化物反应元素 (DREs) 结合DNA,但结合因组织而异. 可解释的机器学习揭示了序列和染色质上下文驱动这种特定于组织的AhR结合.
科学领域:
- 分子生物学分子生物学
- 基因组学就是基因组学.
- 毒理学 毒理学 毒理学
背景情况:
- 基碳化合物受体 (AhR) 是一种可诱导的转录因子.
- AhR配体包括环境污染物,如2,3,7,8-四二子-p-二氧化物 (TCDD).
- AhR与具有核心5'-GCGTG-3'动图的二氧化碳反应元件 (DREs) 结合DNA,但结合是组织特异性的.
研究的目的:
- 开发可解释的机器学习模型,用于预测AhR与DREs的结合.
- 探索跨组织转录因子结合模型性能差的原因.
- 为了确定影响组织特异AhR结合的序列和染色质上下文模式.
主要方法:
- 开发可解释的机器学习模型.
- 对MCF-7,GM17212,HepG2细胞和人类初级肝细胞中的AhR结合的分析.
- 检查与AhR结合状态相关的序列和染色质特征.
主要成果:
- 可解释的机器学习模型准确地预测了特定组织中的AhR结合.
- 鉴定了围绕DREs的组织不可知DNA序列和组织特异的局部染色质上下文作为AhR结合的关键驱动因素.
- 证明跨组织TF-DNA结合模型通常由于未解决的复杂性而表现不佳.
结论:
- AhR结合是由DNA序列和局部染色体环境的组合调节的.
- 可解释机器学习为诱导转录因子DNA结合提供了新的,可测试的见解.
- 了解特定组织的结合对于评估AhR配体的影响至关重要.
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