Publication: Integrated Spatial Genomics Reveals Global Architecture of Single Nuclei
No Thumbnail Available
Open/View Files
Date
2021-01-27
Published Version
Journal Title
Journal ISSN
Volume Title
Publisher
Springer Science and Business Media LLC
The Harvard community has made this article openly available. Please share how this access benefits you.
Citation
Takei, Yodai, Yun, Jina, Zheng, Shiwei, Ollikainen, Noah, Pierson, Nico, White, Jonathan, Shah, Sheel, Thomassie, Julian, Suo, Shengbao, Eng, Chee-Huat Linus, Guttman, Mitchell, Yuan, Guo-Cheng, and Cai, Long. "Integrated Spatial Genomics Reveals Global Architecture of Single Nuclei." Nature (London) 590, no. 7845 (2021): 344-50.
Research Data
Abstract
Identifying the relationships between chromosome structures, nuclear bodies, chromatin states, and gene expression is an overarching goal of nuclear organization studies1–4. Because individual cells appear to be highly variable at all these levels5, it is essential to map different modalities in the same cells. Here, we report the imaging of 3,660 chromosomal loci in single mouse embryonic stem cells (mESCs) by DNA seqFISH+, along with 17 chromatin marks and subnuclear structures by sequential immunofluorescence (IF) and the expression profile of 70 RNAs. We found many loci were invariantly associated with IF marks in single mESCs. These loci form “fixed points” in the nuclear organizations in single cells and often appear on the surfaces of nuclear bodies and zones defined by combinatorial chromatin marks. Furthermore, highly expressed genes appear to be pre-positioned to active nuclear zones, independent of bursting dynamics in single cells. Our analysis also uncovered several distinct mESCs subpopulations with characteristic combinatorial chromatin states. Using clonal analysis, we show that the global levels of some chromatin marks, such as H3K27me3 and macroH2A1 (mH2A1), are heritable over at least 3-4 generations, whereas other marks fluctuate on a faster time scale. This seqFISH+ based spatial multimodal approach can be used to explore nuclear organization and cell states in diverse biological systems.
Description
Other Available Sources
Keywords
Multidisciplinary
Terms of Use
Metadata Only