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. Author manuscript; available in PMC: 2022 Sep 24.
Published in final edited form as: Nat Biotechnol. 2022 Mar 24;40(8):1220–1230. doi: 10.1038/s41587-022-01250-0

Figure 4: Extensive heterogeneity in repressive chromatin encodes cellular identity.

Figure 4:

(A) Remodeling of repressive chromatin during CD8 T cell maturation. Heatmap shows the posterior probabilities (repressive state) in single cells for 14,585 genomic loci, as returned by scChromHMM. Cells are ordered by their progression along pseudotime (Figure 2C). (B) ChromVar deviation scores for the TBX21 and LEF1 motifs in single cells, ordered by their progression along pseudotime. We used the scChromHMM-derived posterior probabilities as input to ChromVar, instead of chromatin accessibility levels. (C) Unsupervised analysis of scChromHMM-derived probabilities (repressive state) separates granular cell types. (D) Single-cell correlation matrix based on repressive chromatin at TSS (Supplementary Methods) when using all TSS (left heatmap), or after excluding the top 3,000 transcriptionally variable genes (right heatmap). In each case, the observed correlation structure is fully consistent with cell type labels, suggesting that there is extensive heterogeneity in repressive chromatin even for genes that do not vary transcriptionally. (E) Scatter plot showing average gene expression levels for all genes in CD14 monocytes (x-axis) and other cell types (y-axis). Colored points represent 1,597 loci where we detect changes in repressive chromatin for monocytes (Supplementary Methods). Blue points represent 1,340 loci where we do not detect an accompanying transcriptional change. Red points represent 257 genes where we detect a transcriptional shift. TPM: Transcripts Per Kilobase Million. (F) Four representative examples of individual genes shown as blue points in (E).