Nature NeuroscienceGenomicsPeer-reviewed journal article
Single nucleus analysis of the chromatin landscape in mouse forebrain development
Sebastian PreißliD, Rongxin FangiD, Hui HuangiD, Yuan ZhaoiD, Ramya RaviramiD, David U. GorkiniD, Yanxiao ZhangiD, Brandon Chin Sos, Veena AfzaliD, Diane E. DickeliD, Samantha KuaniD, Axel ViseliD, Len A. PennacchioiD, Kun ZhangiD, Bing ReniD
Abstract
Genome-wide analysis of chromatin accessibility in primary tissues has uncovered millions of candidate regulatory sequences in the human and mouse genomes1-4. However, the heterogeneity of biological samples used in previous studies has prevented a precise understanding of the dynamic chromatin landscape in specific cell types. Here, we show that analysis of the transposase-accessible-chromatin in single nuclei isolated from frozen tissue samples can resolve cellular heterogeneity and delineate transcriptional regulatory sequences in the constituent cell types. Our strategy is based on a combinatorial barcoding assisted single cell assay for transposase-accessible chromatin5 and is optimized for nuclei from flash-frozen primary tissue samples (snATAC-seq). We used this method to examine the mouse forebrain at seven development stages and in adults. From snATAC-seq profiles of more than 15,000 high quality nuclei, we identify 20 distinct cell populations corresponding to major neuronal and non-neuronal cell-types in foetal and adult forebrains. We further define cell-type specific cis regulatory sequences and infer potential master transcriptional regulators of each cell population. Our results demonstrate the feasibility of a general approach for identifying cell-type-specific cis regulatory sequences in heterogeneous tissue samples, and provide a rich resource for understanding forebrain development in mammals.
- organism: mouse
- assay: scATAC-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: experimental assay
- Citations
- 332
- FWCI
- 15.46
- Field percentile
- top 1%
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