scATAC-Seq analysis

Nuclei were isolated and washed according to the method supplied by the 10X Genomics: Nuclei Isolation for Single Cell ATAC Sequencing ({"type":"entrez-nucleotide","attrs":{"text":"CG000169","term_id":"33868817","term_text":"CG000169"}}CG000169). The isolated nuclei were re-suspended in chilled Diluted Nuclei Buffer (10X Genomics; 2000153) at a volume based on the number of starting cells and the final target concentration pf nuclei. Countstar (Rigel S2) was used to count the nuclei, and they were then immediately used to generate single-cell ATAC-seq libraries.

Following the 10X Genomics single-cell ATAC solution, by using the Chromium Chip E Single Cell Kit (Product Code 1000156) and Chromium Single Cell ATAC Library & Gel Bead Kit (Product Code 1000110), the nuclei in the bulk sample were partitioned into nanoliter-scale gel beads-in-emulsion, a pool of ~750,000 10 × barcodes was sampled to separately and uniquely index the transposed DNA of each individual nucleus, and libraries were generated (by CapitalBio Technology, Beijing). The libraries were sequenced using an Illumina Nova-seq sequencer with a sequencing depth of at least 25k read pairs per nucleus with a pair-end 50-bp reading strategy. Cell Ranger-ATAC pipeline Cell Ranger ATAC -1.2.0 and the mm10 reference genome were downloaded from the 10X Genomics website (https://support.10xgenomics.com/single-cell-atac/software/downloads/latest). Raw sequencing data were converted to fastq format using cell ranger-atac mkfastq. Cells with pct_reads_in_peaks >40, peak_region_fragments >3,000 and <80,000, TSS.enrichment >2.5, blacklist_ratio <0.01, and nucleosome_signal <4 were also filtered out. Peak calling, peak annotation, clustering visualization, TF motif enrichment analysis, and differential accessibility analysis were performed with the Signac package (https://satijalab.org/signac/index.html). Dimensionality was reduced using LSI, the top 2–30 principal components were used to generate clusters by calculating k-nearest neighbors and constructing the SNN graph and visualized via UMAP.