Transcriptomic reprogramming screen identifies SRSF1 as a regulator of aging
RNA-seq (gene expression) · mouse · 839 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
- 839 samples: 181 conditions, mostly in duplicateGroups 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.
Read the full summary ↓
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE325735_RAW.tar (it can run to tens of gigabytes).
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 PRJNA1441554 and SRA study SRP686727. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 362 samples.
How we read this: 181 replicated groups read from the first 400 of 839 sample titles; they account for 362 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.
- GSM9611422 M29 WT line
- GSM9611423 M69 WT line
- GSM9611424 M86 WT line
- GSM9611425 M94 WT line
- GSM9611426 F3 line with Dox-inducible GFP transgene, Dox_250ng/mL
- GSM9611427 F3 line with Dox-inducible GFP transgene, Dox_2000ng/mL
- GSM9611428 F3 line with Dox-inducible OTX2 transgene
- GSM9611429 F3 line with Dox-inducible ZGLP1 transgene
- GSM9611430 B6 line, P0
- GSM9611431 B6 line, P+2 B6 line, P+
- GSM9611432 B6 line, P+10 B6 line, P+
- GSM9611433 F3 line with Dox-inducible ZGLP1 transgene, Dox_2000ng/mL
- GSM9611434 M29 WT line, No Rapa
- GSM9611435 M29 WT line, Rapa_100, 3 days
- GSM9611436 M94 WT line, No Rapa
- GSM9611437 M94 WT line, 100ng/mL Rapa, 3 days
- GSM9611438 M36 WT line, No Rapa
- GSM9611439 M36 WT line, Rapa_100ng/mL, 24h
- GSM9611440 M36 WT line, Rapa_100ng/mL, 48h
- GSM9611441 M36 WT line, Rapa_100ng/mL, 72h
- GSM9611442 M55 WT line, No Rapa
- GSM9611443 M55 WT line, Rapa_100ng/mL, 24h
- GSM9611444 M55 WT line, Rapa_100ng/mL, 48h
- GSM9611445 M55 WT line, Rapa_100ng/mL, 72h
- GSM9611446 M73 WT line, No Rapa
- GSM9611447 M73 WT line, Rapa_100ng/mL, 24h
- GSM9611448 M73 WT line, Rapa_100ng/mL, 48h
- GSM9611449 M73 WT line, Rapa_100ng/mL, 72h
- GSM9611450 M92 WT line, No Rapa
- GSM9611451 M92 WT line, Rapa_100ng/mL, 24h
- GSM9611452 M92 WT line, Rapa_100ng/mL, 48h
- GSM9611453 M92 WT line, Rapa_100ng/mL, 72h
- GSM9611454 M41 WT line (isogenic with S34)
- GSM9611455 M55 WT line (isogenic with S33)
- GSM9611456 M52 WT line (isogenic with S36)
- GSM9611457 M68 WT line (isogenic with S35)
- GSM9611458 M60 WT line (isogenic with S38)
- GSM9611459 M79 WT line (isogenic with S37)
- GSM9611460 M66 WT line (isogenic with S40)
- GSM9611461 M66 WT iPSC line (isogenic with S39)
+ 799 more — browse all 839 samples with per-sample file links →
- GSE201710 Targeted partial reprogramming of age-associated cell states improves markers of health in mouse models of aging 49 samples shares reprogramming, aging
- GSE266329 Co-culture CRISPR screens reveal ATG9A as a regulator to macrophage-mediated cytotoxicity in cancer 8 samples shares regulator, screen
- GSE261742 Identification of epigenetic regulators of fibrotic transformation in cardiac fibroblasts through bulk and single-cell CRISPR screens 69 samples shares regulator, screen
- GSE29799 RNAi screen identifies Brd4 as a therapeutic target in acute myeloid leukemia 30 samples shares identifies, screen
- GSE303179 SRSF12 is a primate-specific splicing factor that induces a tissue-specific gene expression program 18 samples shares srsf1
- GSE202126 Single-cell Total-RNA Profiling Unveils Regulatory Hubs of Transcription Factors 1089 samples shares regulator
- GSE275278 Transplantation-induced reprogramming determines successful hepatocyte engraftment 37 samples shares reprogramming
- GSE306773 Myocardial Reprogramming by HMGN1 Underlies Heart Defects in Trisomy 21 [scRNA-seq] 29 samples shares reprogramming
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.