美国德克萨斯大学
通过使用深度学习启发的可解释模型Puffin，以碱基对分辨率预测序列中的转录起始点，研究人员发现一小套简单的规则就能解释大多数人类启动子的转录起始点。研究人员确定了有助于人类启动子活性的关键序列模式，每种模式都以不同的位置特异性效应激活转录。
此外，研究人员还解释了启动子双向转录的序列基础，确定了不同细胞类型启动子序列与基因表达变异之间的联系，并探索了不同哺乳动物物种转录启动序列决定因素的保护。
据悉，转录起始是确保任何基因正常功能必不可少的一个过程，但人们仍然缺乏对序列模式和规则的统一认识，而这些模式和规则可以解释人类基因组中的大多数转录起始位点。
附：英文原文
Title: Sequence basis of transcription initiation in the human genome
Author: Kseniia Dudnyk, Donghong Cai, Chenlai Shi, Jian Xu, Jian Zhou
Issue&Volume: 2024-04-26
Abstract: Transcription initiation is a process that is essential to ensuring the proper function of any gene, yet we still lack a unified understanding of sequence patterns and rules that explain most transcription start sites in the human genome. By predicting transcription initiation at base-pair resolution from sequences with a deep learning–inspired explainable model called Puffin, we show that a small set of simple rules can explain transcription initiation at most human promoters. We identify key sequence patterns that contribute to human promoter activity, each activating transcription with distinct position-specific effects. Furthermore, we explain the sequence basis of bidirectional transcription at promoters, identify the links between promoter sequence and gene expression variation across cell types, and explore the conservation of sequence determinants of transcription initiation across mammalian species.
DOI: adj0116
Source: https://www.science.org/doi/10.1126/science.adj0116