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Interferons and epigenetic mechanisms in training, priming and tolerance of monocytes and hematopoietic progenitors [RNA-seq]

GSE262911 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2024/05/22 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 24 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
24 samples: 24 samples, each with a distinct title — no replicated groupsGroups 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
Interferons and epigenetic mechanisms in training, priming and tolerance of monocytes and hematopoietic progenitorsImmunological reviews · 2024
Summary (written by the submitters)
Training and priming of innate immune cells involve preconditioning by PAMPs, DAMPs and/or cytokines that elicits stronger induction of inflammatory genes upon secondary challenge. Previous models distinguish training and priming based upon whether immune activation returns to baseline prior to secondary challenge. Tolerance is a protective mechanism whereby potent stimuli induce refractoriness to secondary challenge.
Read the full summary ↓
Training and priming are important for innate memory responses that protect against infection, efficacy of vaccines, and maintaining innate immune cells in a state of readiness; tolerance prevents toxicity from excessive immune activation. Dysregulation of these processes can contribute to pathogenesis of autoimmune/inflammatory conditions, post-COVID-19 hyperinflammatory states, or sepsis- associated immunoparalysis. Training, priming and tolerance regulate similar ‘signature’ inflammatory genes such as TNF, IL6 and IL1B and utilize overlapping epigenetic mechanisms. We review how interferons (IFNs), best known for activating Jak-STAT signaling and interferon- stimulated genes, also play a key role regulating training, priming and tolerance via chromatin- mediated mechanisms. We present new data on how monocyte-to-macrophage differentiation modulates IFN-g-mediated priming, changes AP-1 and CEBP activity, and attenuates superinduction of inflammatory genes. We present a ‘training-priming continuum’ model that integrates IFN-mediated priming into current concepts about training and tolerance and proposes a central role for STAT1 and IRF1.
Published in
Interferons and epigenetic mechanisms in training, priming and tolerance of monocytes and hematopoietic progenitors
Mishra B, Ivashkiv LB · Immunological reviews 2024 · PMID 38567833 · doi:10.1111/imr.13330
This dataset
Open GSE262911 in finder → Find more human RNA-seq datasets →
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.

Series matrix ↓
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 GSE262911_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
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.

Raw reads on ENA ↗

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1094892 and SRA study SRP498987. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38567833) ↗
Study design
24 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 24 sample titles: 24 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
Datasets on a similar topic

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