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Epigenomic and Functional Convergence Between Glucocorticoid- and IL4-Driven Macrophage Programming (ChIP-Seq)

GSE247447 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 28 samples Submitted 2024/09/03 Platform GPL19057
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 28 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
28 samples: 20 distinct titles, 4 of them repeatedGroups are read from the sample names, not from the paper. Check the list below.
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
Mechanisms of epigenomic and functional convergence between glucocorticoid- and IL4-driven macrophage programmingNature communications · 2024
Summary (written by the submitters)
Macrophage polarization is implicated in acute and chronic inflammatory settings, and central to diseases such as obesity, atherosclerosis and cancer. However, the transcription programs driving macrophage polarization are only partially known. Macrophage phenotypes exist on a spectrum, with anti-inflammatory (M2-like) and pro-inflammatory (M1-like) states viewed as polar opposite and relatively stable phenotype.
Read the full summary ↓
The main driver of the M2-like program in response to IL4 is the Krüppel-like factor 4(KLF4), which uses transcriptional coregulator GRIP1 as a co-activator. Coincidentally, glucocorticoid hormone (GC)-activated GC receptor (GR) also induces the M2-like state, and GRIP1 is a well-known co-factor of GR. We are investigating if GRIP1 facilitates transcriptional and phenotypic convergence of the M2-like state via the GR and KLF4-regulated pathways. Using RNA-seq on bone marrow-derived macrophages (BMDMs) from WT and GRIP1-cKO mice, we have shown that GR and KLF4-regulated pathways share common and distinct transcriptomes. A lot of the key M2 genes are GRIP1-dependent, and some key pro-inflammatory targets need GRIP1 for suppression in the M2–like state. Similarly, H3K27ac ChIP and ATAC-seq, which profile active and open chromatin regions respectively, revealed both specific and shared enhancers for these two pathways in the M2-like state. GR recruitment to the genomic binding sites was shown to be strictly GC-specific, whereas GRIP1 is recruited in both signal-specific and combinatorial manner. It is plausible that GRIP1 facilitates the binding of GR and KLF4 to the shared enhancers, thus leading to overlapping changes in gene expression. At the cellular level, GC- and particularly IL4-polarized GRIP1-cKO BMDMs exhibit reduced phagocytosis, an M2-characteristic activity, compared to the WT. Furthermore, in vivo, in the acute inflammatory setting of DSS-induced colitis, GRIP1-cKO mice exhibit greater colonic inflammation and tissue destruction, and fail to up-regulate M2 genes to the same degree as the WT. GRIP1 is therefore a crucial regulator of macrophage polarization to the anti-inflammatory state. The specific contribution of GRIP1 to the shared transcriptional phenotype is currently being assessed.
Published in
Mechanisms of epigenomic and functional convergence between glucocorticoid- and IL4-driven macrophage programming
Deochand DK, Dacic M, Bale MJ et al. · Nature communications 2024 · PMID 39424780 · doi:10.1038/s41467-024-52942-x
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 GSE247447_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 PRJNA1037575 and SRA study SRP471144. Searching any of these in the dataset finder brings you back here.

Study design
20 distinct titles, 4 of them repeated
H3K27 acetyl, vehicle, ×3 H3K27 acetyl, Corticosterone, 24 h, ×3 H3K27 acetyl, Dexamethasone, 24 h, ×3 H3K27 acetyl, IL4, 24 h, ×3

How we read this: Read from 28 sample titles: 20 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
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