Additional file 1 of Universal NicE-seq for high-resolution accessible chromatin profiling for formaldehyde-fixed and FFPE tissues

Additional file 1: Supp Fig. 1 Optimization of universal NicE-seq (A) A schematic diagram of accessible chromatin labeling using dCTP or 5-mdCTP in the labeling reaction along with biotinylated-dCTP in the nucleotide mix. On-bead and off-bead represented presence of streptavidin magnetic beads for DNA capture and library preparation. (B) FRiP comparison between all 4 methods generated library that map to TSSs (+/-500 bp of TSS) and distal elements (>500 bp from TSS) from HCT116 cells. C and 5mC represents use of dCTP and 5-dCTP in the reaction mix. Supp Fig. 2: Optimization of accessible chromatin sequencing and comparison between UniNicE-seq, ATAC-seq and DNase-seq. (A) IGV screen shot of the normalized read density of the four NicE-seq conditions in HCT116 cells. (B) Distribution of the number of normalized HCT116 NicE-seq reads at transcription start sites (TSS) of human genes and the surrounding 2 Kb (- and +) regions. (C) Pearson correlation of normalized read densities in UniNicE-seq peaks of the 2 technical replicates in HCT116 demonstrating reproducibility. (D) IGV screen shot of the normalized read density of UniNicE-seq (top track), ATAC-seq (middle track) and DNase-seq (bottom track) in HCT116 (F) Overlap of HCT116 peaks called from 15 M unique alignments using UniNicE-seq, ATAC-seq and DNase-seq. Supp Fig. 3: Venn Diagram showing common and cell-type specific UniNicE-seq peaks between the three cell types. (A) HCT116, K562 and MCF7 accessible chromatin regions were analyzed. Peaks are called from 11 million random sampled deduplicated alignment pairs. Supp Fig. 4: UniNicE-seq of mouse T cells cells. (A) IGV screen shot of the normalized read density of the technical duplicates of UniNicE-seq libraries of HCT116 cells at different cell numbers. (B) Pairwise comparison between all Universal NicE-seq reads between different T cell numbers from 500, 5 and 25 K. Pearson’s correlation is indicated. Supp Fig. 5: Comparison between UniNicE-seq, ATAC-seq, Omini ATAC-seq and DNase-seq of mouse kidney cells. (A) Venn diagram of accessible chromatin regions derived from UniNicE-seq, ATAC-seq, Omini ATAC-seq and DNase-seq of mouse kidney cells. (B) Distribution of fold change (FC) values (derived from MACS2) of the common accessible chromatin peaks of UniNicE-seq, ATAC-seq, Omni ATAC-seq and DNase-seq. (C) FRiP score of UniNicE-seq 25 K, 0.5 K and 0.25 K compared with data obtained from ATAC-seq and OmniATAC-seq using 50 K cells, and DNase-seq. (D) Heatmap showing comparison of normalized RPKM of 25 K fixed, 0.5 K nonfixed and 0.25 K mouse kidney UniNicE-seq, 50 K omni ATAC-seq, 50 K ATAC-seq and DNase-seq data at TSS, PolII and random. (E) Similar comparison like (D) along with chromatin features including CTCF, H3K4me3, H3K27Ac and random fragments. Supp Fig. 6: Comparison between accessible chromatin sequences two liver FFPE tissue section (A) Venn diagram demonstrating common accessible regions in two different human 5-10 μm lung normal tissue sections. (B) Pearson’s correlation analysis of total reads between two different human 5-10 μm lung normal tissue sections. (C) Pearson’s correlation analysis of common reads between two different human 5-10 μm lung normal tissue sections demonstrating quality of accessible peaks. (D) Principle Component Analysis and heat map of TSS across fetal and adult tissue for normalized read density of the consensus peaks between the samples from fetal and adult tissue. (E) Heat map of TSS (-/+ 2 kb) between various tissue samples. Supp Fig. 7: UniNicE-seq of normal human liver FFPE tissue section. Pearson’s correlation analysis by pairwise comparison between two different liver samples, R1 and R2. Supp Fig. 8: GC content of HCT116 peaks called from 15 M unique alignment pairs using UniNicE-seq, ATAC-seq and DNase-seq. The last box represents the GC content of random genomic regions sampled from the human reference genome (hg38).