美国德克萨斯西南医学中心Zhou Jian和普林斯顿大学Olga G. Troyanskaya研究组合作取得一项新成果。他们的最新研究基于整体序列活动调控图破译了人类遗传学。2022年7月11日出版的《自然-遗传学》发表了这项成果。
研究人员使用Sei解决了调控映射难题，Sei是一个将人类遗传学数据与序列信息相结合以发现性状和疾病调控基础的程序。Sei使用深度学习模型学习了一个名为序列类的调节活动数据库，该模型可以预测超过1,300个细胞系和组织的21,907个染色质谱。序列类别基于不同的调节活动（例如细胞类型特异性增强子功能）提供序列和变异效应的全局分类和量化。
这些预测得到了组织特异性表达、表达数量性状基因座和进化约束数据的支持。此外，序列类别能够表征复杂性状的组织特异性调控结构，并提供了个体调控致病突变的可能产生机制。该研究表明Sei可作为资源库来阐明人类健康和疾病的调控基础。
此外，表观基因组分析已经能够大规模的识别调控元件，但仍然缺乏从任何序列或变体到调控活动的系统映射。
附：英文原文
Title: A sequence-based global map of regulatory activity for deciphering human genetics
Author: Chen, Kathleen M., Wong, Aaron K., Troyanskaya, Olga G., Zhou, Jian
Issue&Volume: 2022-07-11
Abstract: Epigenomic profiling has enabled large-scale identification of regulatory elements, yet we still lack a systematic mapping from any sequence or variant to regulatory activities. We address this challenge with Sei, a framework for integrating human genetics data with sequence information to discover the regulatory basis of traits and diseases. Sei learns a vocabulary of regulatory activities, called sequence classes, using a deep learning model that predicts 21,907 chromatin profiles across >1,300 cell lines and tissues. Sequence classes provide a global classification and quantification of sequence and variant effects based on diverse regulatory activities, such as cell type-specific enhancer functions. These predictions are supported by tissue-specific expression, expression quantitative trait loci and evolutionary constraint data. Furthermore, sequence classes enable characterization of the tissue-specific, regulatory architecture of complex traits and generate mechanistic hypotheses for individual regulatory pathogenic mutations. We provide Sei as a resource to elucidate the regulatory basis of human health and disease.
DOI: 10.1038/s41588-022-01102-2
Source: https://www.nature.com/articles/s41588-022-01102-2
Nature Genetics：《自然—遗传学》，创刊于1992年。隶属于施普林格·自然出版集团，最新IF：41.307
官方网址：https://www.nature.com/ng/
投稿链接：https://mts-ng.nature.com/cgi-bin/main.plex
本期文章：《自然—遗传学》：Online/在线发表
