GET:跨人类细胞类型的转录的基础模型
Xi Fu1,2, Shentong Mo3,4, Alejandro Buendia1
1Department of Systems Biology, Columbia University, New York, NY, USA.
bioRxiv : the preprint server for biology
|July 15, 2024
概括
一个新的可解释的基础模型,GET,只使用染色质可访问性和序列数据,准确地预测人类多种细胞类型的基因表达. 它揭示了通用和细胞特异的转录因子相互作用,推进了我们对基因调节的理解.
科学领域:
- 基因组学和生物信息学
- 分子生物学分子生物学
- 计算生物学 计算生物学
背景情况:
- 转录调节对所有生物过程至关重要,但目前的计算模型缺乏通用性.
- 准确预测跨多种细胞类型和条件的基因表达仍然是一个挑战.
研究的目的:
- 介绍GET,一种可解释的基础模型,用于在213种人类细胞类型中发现基因调控语法.
- 使用染色体可访问性和序列数据,在未见的细胞类型中实现精确的基因表达预测.
- 为了使监管推断和发现转录因子相互作用网络.
主要方法:
- 开发了GET,这是一个利用染色体可访问性和序列信息的基础模型.
- 评估了GET在预测监管活动,推断监管元素/监管者以及识别转录因子相互作用方面的表现.
- 在不同的测序平台和测试中评估适应性.
主要成果:
- 在213种人类细胞类型的基因表达预测中,GET实现了实验级准确性,包括以前未见过的细胞类型.
- 该模型展示了适应新测序平台和测试的适应性.
- 确定了先前模型遗漏的远端调节区域,并发现了与白血病风险相关的B细胞中的特定转录因子相互作用.
结论:
- GET提供了一个可概括和准确的转录模型,改善了基因表达预测和调控推理.
- 这项研究提供了基因调节和转录因子相互作用与细胞类型特异性的宝贵目录.
- GET促进了对转录调节及其在生物过程和疾病中的作用的理解.
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