Cut&RUN GCN5 Control Primary mouse hepatocytes

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 negativeATAC-seq signal mask, and subsequently removed from the overall coverage. CUT&RUNcoverage heatmaps and profiles around the TSS of expressed genes were produced usingcomputeMatrix, plotHeatmap functions from deepTools v3.5.2 package51. The list of expressedgenes was inferred from the mouse primary hepatocyte RNA-seq data using variancestabilizing transformation of the expression matrix and selecting genes with values > 0 for allreplicates. Peak calling on each replicate was performed using MACS252 v.2.2.7.1, and theconsensus overlapping peaks between all replicates were considered as reproducible for thecorresponding dataset. Number of overlapping peaks between conditions was calculated in Rwith subsetByOverlaps (GenomicRanges v.1.54.1)57, and nearest genes were annotated topeaks using biomaRt.For the correlation of ChIP peaks with gene expression, all expressed genes derived fromRNA-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 Rsubreadv.2.16.0)59 package, and the CUT&RUN signal was quantified with multiBigwigSummary fromdeepTools package

针对ACLY与GCN5的预处理CUT&RUN文件已按照有效基因组大小完成归一化处理。针对每份文件，研究人员通过阴性ATAC-seq信号掩码在异染色质区域计算背景信号，并随后从总覆盖度中去除该背景信号。研究人员借助deepTools v3.5.2工具包51的computeMatrix与plotHeatmap函数，绘制了表达基因转录起始位点（TSS）周边区域的CUT&RUN覆盖度热图与信号分布图。表达基因列表通过小鼠原代肝细胞的RNA测序（RNA-seq）数据推导得到：先对表达矩阵进行方差稳定变换，随后筛选出所有重复样本中表达量数值均大于0的基因。针对每份重复样本的峰识别工作采用MACS2 v.2.2.7.152完成，所有重复样本间的共识重叠峰被视为对应数据集的可重复峰。不同处理组间的重叠峰数量通过R语言中的subsetByOverlaps函数（GenomicRanges v.1.54.1）57计算得到，同时利用biomaRt工具为峰注释其邻近基因。为探究染色质免疫沉淀（ChIP）峰与基因表达的相关性，研究人员将RNA测序数据得到的所有表达基因按照表达水平分为4个均等分组（四分位组Q1至Q4）。研究人员借助Rsubread v.2.16.059工具包提取这些基因的启动子区域（转录起始位点上下游1kb范围），并利用deepTools工具包中的multiBigwigSummary函数对CUT&RUN信号进行定量分析。