作者
Feng Tian,Fan Zhou,Xiang Li,Wenping Ma,Honggui Wu,Ming Yang,Alec R. Chapman,David F. Lee,Longzhi Tan,Dong Xing,Guangjun Yin,Ayjan Semayel,Jing Wang,Jia Wang,Wenjie Sun,Runsheng He,Siwei Zhang,Zhi-Jie Cao,Wei Lin,Lu Shen,De-Chang Yang,Yunuo Mao,Yuan Gao,Kexuan Chen,Yu Zhang,Xixi Liu,Jun Yong,Liying Yan,Yanyi Huang,Jie Qiao,Fuchou Tang,Ge Gao,Xiaoliang Sunney Xie
摘要
Summary By circumventing cellular heterogeneity, single cell omics have now been widely utilized for cell typing in human tissues, culminating with the undertaking of human cell atlas aimed at characterizing all human cell types. However, more important are the probing of gene regulatory networks, underlying chromatin architecture and critical transcription factors for each cell type. Here we report the Genomic Architecture of Cells in Tissues (GeACT), a comprehensive genomic data base that collectively address the above needs with the goal of understanding the functional genome in action. GeACT was made possible by our novel single-cell RNA-seq (MALBAC-DT) and ATAC-seq (METATAC) methods of high detectability and precision. We exemplified GeACT by first studying representative organs in human mid-gestation fetus. In particular, correlated gene modules (CGMs) are observed and found to be cell-type-dependent. We linked gene expression profiles to the underlying chromatin states, and found the key transcription factors for representative CGMs. Highlights Genomic Architecture of Cells in Tissues (GeACT) data for human mid-gestation fetus Determining correlated gene modules (CGMs) in different cell types by MALBAC-DT Measuring chromatin open regions in single cells with high detectability by METATAC Integrating transcriptomics and chromatin accessibility to reveal key TFs for a CGM