A Single-Cell Atlas of In Vivo Mammalian Chromatin Accessibility.

By D. Cusanovich, Andrew J. Hill, Delasa Aghamirzaie, R. Daza, Hannah A. Pliner, J. B. Berletch, G. Filippova, Xingfan Huang, Lena Christiansen, William S. DeWitt and 7 more. Cell, 2018

708 citations recorded by the source corpus.

We applied a combinatorial indexing assay, sci-ATAC-seq, to profile genome-wide chromatin accessibility in ∼100,000 single cells from 13 adult mouse tissues. We identify 85 distinct patterns of chromatin accessibility, most of which can be assigned to cell types, and ∼400,000 differentially accessible elements. We use these data to link regulatory elements to their target genes, to define the transcription factor grammar specifying each cell type, and to discover in vivo correlates of heterogeneity in accessibility within cell types. We develop a technique for mapping single cell gene expression data to single-cell chromatin accessibility data, facilitating the comparison of atlases. By intersecting mouse chromatin accessibility with human genome-wide association summary statistics, we identify cell-type-specific enrichments of the heritability signal for hundreds of complex traits. These data define the in vivo landscape of the regulatory genome for common mammalian cell types at single-cell resolution.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/c5fe38a29bfe19d07940c9e9fdbe919ad5f967fb

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Molecular Biology

1. Tim Stuart
2. Avi Srivastava
3. Caleb A. Lareau
4. Shaista Madad
5. Rahul Satija

Citations in the corpus

• cisTopic: cis-Regulatory topic modelling on single-cell ATAC-seq data (2019, neutral): “…of 10 melanoma cell lines + http://brainome.org (Luo et al., 2017): scnmC-seq data from human neurons + http://atlas.gs.washington.edu/mouse-atac/ (Cusanovich et al., 2018): sciATAC-seq in several mouse tissues (Mouse Cell Atlas) + GSE96772 (Buenrostro et al., 2018): scATAC-seq in FAC-sorted…”
• Single-cell chromatin state analysis with Signac (2021, methodology): “For each downsampling, we re-ran each dimension reduction method (LSI (Signac), LSI (Cusanovich2018), LSI (log-TF), cisTopic (Warp-LDA), cisTopic (CGS), SnapATAC, SCALE), using default parameters for each method.”