一个以染色体结构为导向的框架,用于预测和可解释的调控基因组学
1Center for Bioinformatics and Quantitative Biology, and Richard and Loan Hill Department of Bioengineering, University of Illinois Chicago, Chicago, IL 60607, USA.
bioRxiv : the preprint server for biology
|November 24, 2025
概括
CHROME从Hi-C数据中识别了特定的3D染色质接触点,改善了基因调节和变异效应预测. 这个框架整合了物理相互作用,以实现更准确和可解释的基因组建模.
科学领域:
- 基因组学就是基因组学.
- 计算生物学 计算生物学
- 分子生物学分子生物学
背景情况:
- 基因调节受3D染色体组织的影响,但线性基因组模型不足.
- 现有的高温接触地图是平均的,杂的,并掩盖了特定的生物相互作用.
研究的目的:
- 开发一个框架 (CHROME) 来从Hi-C数据中识别物理特定的染色质接触.
- 将这些联系整合到图形表示中,以改善基因组预测.
- 提高基因调节和变异效应建模的可解释性.
主要方法:
- 利用一种自我避开的聚合物组合无效模型来识别非随机的Hi-C接触.
- 开发了一个集序,可访问性和预训练嵌入的图表注意力架构.
- 应用框架来预测细胞系特定的ChIP-seq配置文件,eQTL和变异性致病性.
主要成果:
- CHROME成功地确定了物理特异性的染色质相互作用.
- 该框架在预测ChIP-seq配置文件方面表现优于局部编码器基线,可将其推广到新的细胞系.
- 图形嵌入改善了eQTL和变异致病性的预测,超过了基于序列的方法.
- 注意力机制提供了对多兆数据库监管影响的解释性.
结论:
- 纳入物理验证的染色体相互作用显著提高了基因组学中的预测准确性和可解释性.
- 通过利用3D基因组结构,CHROME提供了一种新的方法来建模基因调节和变异效应.
- 这项工作弥合了基因组构造和功能性基因组预测之间的差距.
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