Cut&RUN ACSS2 on liver tissue

Pre-processed CUT&RUN files for ACLY and GCN5 were normalized to effective genome size. For each file, background signal was calculated in heterochromatin regions using negative ATAC-seq signal mask, and subsequently removed from the overall coverage. CUT&RUN coverage heatmaps and profiles around the TSS of expressed genes were produced using computeMatrix, plotHeatmap functions from deepTools v3.5.2 package51. The list of expressed genes was inferred from the mouse primary hepatocyte RNA-seq data using variance stabilizing transformation of the expression matrix and selecting genes with values > 0 for all replicates. Peak calling on each replicate was performed using MACS252 v.2.2.7.1, and the consensus overlapping peaks between all replicates were considered as reproducible for the corresponding dataset. Number of overlapping peaks between conditions was calculated in R with subsetByOverlaps (GenomicRanges v.1.54.1)57, and nearest genes were annotated to peaks using biomaRt. For the correlation of ChIP peaks with gene expression, all expressed genes derived from RNA-seq data were divided into 4 equal groups based on their expression levels (quartiles (Q) 1 to 4). Promoter regions of those genes (± 1kb TSS) were extracted using the Rsubread v.2.16.0)59 package, and the CUT&RUN signal was quantified with multiBigwigSummary from deepTools package