表观基因组
表观遗传学
转录组
生物
表观遗传学
染色质
计算生物学
H3K4me3
基因表达谱
组蛋白
DNA甲基化
遗传学
基因表达
基因
发起人
作者
Di Zhang,Yanxiang Deng,Petra Kukanja,Eneritz Agirre,Marek Bartošovič,Mingze Dong,Cong Ma,Sai Ma,Graham Su,Shuozhen Bao,Yang Liu,Yang Xiao,Gorazd Rosoklija,Andrew J. Dwork,J. John Mann,Kam W. Leong,Maura Boldrini,Liya Wang,Maximilian Haeussler,Benjamin J. Raphael,Yuval Kluger,Gonçalo Castelo‐Branco,Rong Fan
出处
期刊:Nature
[Springer Nature]
日期:2023-03-15
卷期号:616 (7955): 113-122
被引量:117
标识
DOI:10.1038/s41586-023-05795-1
摘要
Abstract Emerging spatial technologies, including spatial transcriptomics and spatial epigenomics, are becoming powerful tools for profiling of cellular states in the tissue context 1–5 . However, current methods capture only one layer of omics information at a time, precluding the possibility of examining the mechanistic relationship across the central dogma of molecular biology. Here, we present two technologies for spatially resolved, genome-wide, joint profiling of the epigenome and transcriptome by cosequencing chromatin accessibility and gene expression, or histone modifications (H3K27me3, H3K27ac or H3K4me3) and gene expression on the same tissue section at near-single-cell resolution. These were applied to embryonic and juvenile mouse brain, as well as adult human brain, to map how epigenetic mechanisms control transcriptional phenotype and cell dynamics in tissue. Although highly concordant tissue features were identified by either spatial epigenome or spatial transcriptome we also observed distinct patterns, suggesting their differential roles in defining cell states. Linking epigenome to transcriptome pixel by pixel allows the uncovering of new insights in spatial epigenetic priming, differentiation and gene regulation within the tissue architecture. These technologies are of great interest in life science and biomedical research.
科研通智能强力驱动
Strongly Powered by AbleSci AI