转录因子合作性的全基因组规则通过in silico结合位移除被揭示
Xuening He1,2, Hjörleifur Einarsson1,2, Petra Páleníková2,3
1Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Denmark.
bioRxiv : the preprint server for biology
|July 16, 2025
概括
大多数转录因子 (TF) 结合部位独立起作用,但有些人表现出协同作用或冗余性. DeepCompARE量化了这些TF合作效应,揭示了对基因调节的洞察力.
科学领域:
- 基因组学就是基因组学.
- 分子生物学分子生物学
- 生物信息学是一种生物信息学.
背景情况:
- 转录因子 (TF) 的合作性对于基因调节至关重要.
- 管理TF结合站点 (动机) 语法的基因组规则尚未完全理解.
- 需要可扩展的方法来分析调节序列和TF相互作用.
研究的目的:
- 引入DeepCompARE,这是一个用于全基因组分析TF合作性的新计算框架.
- 准确地解释图案语法及其在染色质可访问性,增强剂和促进剂功能中的作用.
- 量化TF合作性,了解其与基因调控逻辑的关系.
主要方法:
- 开发了DeepCompARE,一个轻量级的计算模型.
- 在基因组范围进行全基因组分析时,应用一套"in silico"剥离 (ISA) 框架.
- 使用定义的合作性得分量化TF合作性的量化.
主要成果:
- 大多数TF图案都表现出对独立性,暗示了默认的添加TF行为.
- 确定了一系列合作方式,包括协同效应和冗余.
- TF冗余与促进体活性和广泛的基因表达相关.
- TF协同作用与增强剂活性,物理相互作用和细胞类型特异性有关.
结论:
- DeepCompARE提供了一个TF合作性的定量模型.
- 这项研究揭示了TF协同效应和冗余在基因调节中的不同作用.
- 提供了对由TF相互作用支配的复杂基因调节逻辑的新见解.
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