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CHD7 promotes anti-viral short-lived effector CD8+ T cells

GSE274735 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 18 samples Submitted 2024/09/23 Platform GPL19057
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 18 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Mus musculus (mouse)
Samples
18 samples
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
In Vivo CRISPR Screening Reveals CHD7 as a Positive Regulator of Short-lived Effector CellsJournal of immunology (Baltimore, Md. : 1950) · 2024
Summary (written by the submitters)
CD8+ T cells differentiate into two subpopulations in response to acute viral infection: memory precursor effector cells (MPECs) and short-lived effector cells (SLECs). MPECs and SLECs are epigenetically distinct; however, the epigenetic regulators required for formation of these subpopulations are mostly unknown. Here we performed an in vivo CRISPR screen in murine naive CD8+ T cells to identify the epigenetic regulators required for MPEC and SLEC formation, using the acute lymphocytic choriomeningitis virus (LCMV) Armstrong infection model.
Read the full summary ↓
We identified the ATP-dependent chromatin remodeler chromodomain-helicase-DNA-binding-protein-7 (CHD7) as a positive regulator of SLEC formation, as knockout (KO) of Chd7 reduced SLECs numerically. In contrast, KO of Chd7 increased the formation of central memory T cells following pathogen clearance yet attenuated memory cell expansion following a rechallenge. These findings establish CHD7 as a novel positive regulator of SLEC and negative regulator of central memory T cell formation.
Published in
In Vivo CRISPR Screening Reveals CHD7 as a Positive Regulator of Short-lived Effector Cells
LaFleur MW, D'Andrea JM, Patterson DG et al. · Journal of immunology (Baltimore, Md. : 1950) 2024 · PMID 39373572 · doi:10.4049/jimmunol.2400213
This dataset
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE274735_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

What the files usually look like: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1147731 and SRA study SRP526193. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 18 more — browse all 18 samples with per-sample file links →

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