GSE111902
Compendium of CD8+ T cell Data
Compendium of high-throughput sequencing datasets derived from murine CD8+ T cells responding to infection, profiled by RNA-seq, ChIP-seq, and ATAC-seq at Naïve, Effector, and Memory timepoints across the Kaech, Goldrath, and Pereira labs, and ChIP-seq of various transcription factors across several labs Submission contains both original data from the Kaech lab and reanalysis of data from the Pereira and Goldrath labs, as well as various other labs corresponding to individual transcription factor ChIP-seq datasets, totaling to 96 reanalyzed GSM samples across several GSE series Included GSE series are: GSE95237 (Genome-wide maps of chromatin state and chromatin accessibility in CD8 T cell subsets), GSE95238 (Epigenetic landscapes reveal transcription factors that regulate CD8+ T cell differentiation),   GSE88987 (Dynamic changes in chromatin accessibility in CD8+ T cells responding to viral infection), GSE58075 (Genome-wide mapping of Myc, AP4, and phosphorylated RNA polymerase II binding in activated CD8 T cells by ChIP sequencing), GSE54191 (ChIP-Seq analysis of BATF, IRF4, the Jun proteins, and histone modifications in effector CD8+ T cells), GSE20898 (Genome-wide Analyses of Transcription Factor GATA3-Mediated Gene Regulation in Distinct T Cell Types), GSE46943 (Transcription Factor Foxo1 Controls Memory CD8+ T Cell Responses To Infection [ChIP-Seq]), GSE72997 (ChIP-Seq analysis of Helios and histone modifications in CD4+ and CD8+ Tregs), GSE50128 (Genome-wide maps of Runx3 bound regions in splenic IL-2-activated CD8+ T cells), GSE72565 (Binding of STAT5 upon IL-2 treatment to genomic sites in mouse CD8 T cells costimulated in vivo through CD134 plus CD137), GSE49930 (The transcription factor IRF4 is essential for T cell receptor affinity mediated metabolic programming and clonal expansion of T cells [ChIP-seq]), and GSE52070 (Genome-wide maps of Tcf1 binding locations in splenic CD8 T cells) Overall design: CD8+ T cell data was combined from the Kaech, Goldrath, Pereira and various other laboratories to create a CD8+ T cell sequencing data compendium across multiple assay types. Cells were collected in the context of infection (primarily LCMV) at Naive (day 0), Effector (day 8 or day 10), or Memory (day 30+) time points, or in ''Special'' culture conditions corresponding primarily to ChIP-seq of transcription factors. Additional subsetted samples from the Effector timepoint, Memory Precursors (KLRG1lo IL7Rhi) and Terminal Effectors (KLRG1hi IL7Rlo) were also collected. Samples were analyzed by using ChIP-seq, ATAC-seq, and RNA-seq specific pipelines. ChIP-seq and ATAC-seq were first trimmed for adapters and low quality sequences with cutadapt, and subsequently aligned with bowtie2 v2.3.3.1 using `--very-sensitive-local` mode, `--no-mixed --nodiscordant`. ATAC-seq data additionally used `--maxins 2000`. ATAC-seq reads were shifted per the original Buenrostro protocol by +4/-5 bases, and filtered to remove mitochondrial mapping reads. ChIP-seq and ATAC-seq data were then called for peaks using MACS2 v2.1.0. ATAC-seq peaks were called using `--nomodel --shift -100 --extsize 200 --broad`. For H3K4me1 and H3K27me3 ChIP-seq data, `--broad --nomodel --broad-cutoff 0.1` was used. For H3K27ac and H3K4me3 ChIP-seq data, default (narrowPeak) settings were used. ChIP-seq data used control (input) data as available. ChIP-seq and ATAC-seq signal tracks were made using deepTools bamCoverage with `--binSize 5 --smoothLength 15 --normalizeTo1x 2150570000 --extendReads 200` for visualization. For RNA-seq data, kallisto v0.42 was used to quantify transcript counts directly from fastq files. All data was aligned to the Ensembl GRCm38 (mm10) reference genome, appending chromosome names with ''chr'' for maximal compatibility with downstream tools. Finally, all sample annotation, counts, and peak data were combined into an R package `ctlcon`, available at "https://bitbucket.com/robert_amezquita/ctlcon" with additional processed datasets and information. contributor: Pereira & Goldrath Labs (Histone mods and ATAC) contributor: Haining, Egawa, Li, Zhao, Cantor, Kallies, Groner, Vella, Xue Labs (ChIP-seq of TFs) The re-analyzed data is linked as Series supplementary file and the details (including sample-to-file associations, SRR accessions of the re-analyzed raw data etc.) are included in the ''readme_re-analyzed_samples.txt''.