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MiR-146a alleviates inflammatory bowel disease in mice through systematical regulation of multiple genetic networks

GSE247433 Mus musculus (mouse) RNA-seq (gene expression) 20 samples Submitted 2024/04/24 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 20 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
Mus musculus (mouse)
Samples
20 samples: 5 conditions, mostly in triplicateGroups 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
MiR-146a alleviates inflammatory bowel disease in mice through systematic regulation of multiple genetic networksFrontiers in immunology · 2024
Summary (written by the submitters)
Inflammatory bowel disease (IBD) is a multiple-genes-involved chronic disease and current available targeted drugs for IBD only deliver moderate efficacy. Whether there is a single gene that systematically regulates IBD is not yet known. Here we showed that the expression of miR-146a in colon was elevated in Dextran Sulfate Sodium Salt (DSS)-induced IBD mice and patients with IBD.
Read the full summary ↓
DSS induced dramatic body weight loss and much more rectal bleeding, shorter colon length and colitis in miR-146a knock-out mice than wild type (WT) mice. The miR-146a mimics alleviated DSS-induced symptoms in both DSS-induced miR-146a-/- and WT mice. Further RNA sequencing illustrated that deficiency of miR-146a de-repressed majority of DSS-induced IBD-related genes which cover multiple genetic regulatory networks in IBD, and supplement of miR-146a mimics inhibited expression of many IBD-related genes. DOI 10.3389/fimmu.2024.1366319
Published in
MiR-146a alleviates inflammatory bowel disease in mice through systematic regulation of multiple genetic networks
Zhu F, Yang T, Ning M et al. · Frontiers in immunology 2024 · PMID 38799464 · doi:10.3389/fimmu.2024.1366319
This dataset
Open GSE247433 in finder → Find more mouse 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 GSE247433_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 PRJNA1037549 and SRA study SRP471105. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38799464) ↗
Study design
5 conditions, mostly in triplicate
DSS+Saline treated, miR-146a-/ ×6 DSS+miR-146a mimics treated, miR-146a-/ ×5 untreated, WT ×3 DSS treated, WT ×3 DSS treated, miR-146a-/ ×3

Supports a between-group comparison across 20 samples.

How we read this: 5 replicated groups read from 20 sample titles; they account for 20 of them. 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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