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Effect of conditional deletion of Bmal1 in pancreatic β-cells in modulating transcriptional islet response to STZ-mediated pro-inflammatory injury

GSE278711 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2024/10/31 Platform GPL21103
At a glance

RNA-seq (gene expression) · mouse · 12 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
12 samples: 12 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
Core circadian transcription factor Bmal1 mediates β cell response and recovery from pro-inflammatory injuryiScience · 2024
Summary (written by the submitters)
The circadian clock plays a vital role in modulating the cellular immune response. However, its role in mediating pro-inflammatory diabetogenic β-cell injury remains largely unexplored. Our studies demonstrate that conditional deletion of Bmal1 in mouse β-cells was shown to impair the ability of β-cells to recover from streptozotocin-mediated pro-inflammatory injury in vivo, leading to β-cell failure and the development of diabetes.
Read the full summary ↓
Our study suggests that the β-cell circadian clock mediates β-cell response and recovery from pro-inflammatory injury common to the pathogenesis of diabetes mellitus.
Published in
Core circadian transcription factor Bmal1 mediates β cell response and recovery from pro-inflammatory injury
Rakshit K, Brown MR, Javeed N et al. · iScience 2024 · PMID 39524327 · doi:10.1016/j.isci.2024.111179
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 GSE278711_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: 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 PRJNA1168494 and SRA study SRP536411. Searching any of these in the dataset finder brings you back here.

Study design
12 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 12 sample titles: 12 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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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.