A phosphorylation switch within the Mediator subunit MED15 controls cellular senescence and cognitive decline
RNA-seq (gene expression) · mouse · 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
- Mus musculus (mouse)
- Samples
- 24 samples: 8 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
- A phosphorylation switch in the Mediator MED15 controls cellular senescence and cognitive declineCell discovery · 2025
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 GSE285138_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 PRJNA1201231 and SRA study SRP553068. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 24 samples.
How we read this: 8 replicated groups read from 24 sample titles; they account for 24 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.
- GSM8697150 WT HaCaT, TGFβ-0h, RNA-seq, rep1 WT HaCaT, TGFβ-0h, RNA-…
- GSM8697151 WT HaCaT, TGFβ-0h, RNA-seq, rep2 WT HaCaT, TGFβ-0h, RNA-…
- GSM8697152 WT HaCaT, TGFβ-0h, RNA-seq, rep3 WT HaCaT, TGFβ-0h, RNA-…
- GSM8697153 WT HaCaT, TGFβ-3h, RNA-seq, rep1 WT HaCaT, TGFβ-3h, RNA-…
- GSM8697154 WT HaCaT, TGFβ-3h, RNA-seq, rep2 WT HaCaT, TGFβ-3h, RNA-…
- GSM8697155 WT HaCaT, TGFβ-3h, RNA-seq, rep3 WT HaCaT, TGFβ-3h, RNA-…
- GSM8697156 MED15 T603A HaCaT, TGFβ-0h, RNA-seq, rep1 MED15 T603A HaCaT, TGFβ…
- GSM8697157 MED15 T603A HaCaT, TGFβ-0h, RNA-seq, rep2 MED15 T603A HaCaT, TGFβ…
- GSM8697158 MED15 T603A HaCaT, TGFβ-0h, RNA-seq, rep3 MED15 T603A HaCaT, TGFβ…
- GSM8697159 MED15 T603A HaCaT, TGFβ-3h, RNA-seq, rep1 MED15 T603A HaCaT, TGFβ…
- GSM8697160 MED15 T603A HaCaT, TGFβ-3h, RNA-seq, rep2 MED15 T603A HaCaT, TGFβ…
- GSM8697161 MED15 T603A HaCaT, TGFβ-3h, RNA-seq, rep3 MED15 T603A HaCaT, TGFβ…
- GSM8697162 WT MCF7, TGFβ-0h, RNA-seq, rep1 WT MCF7, TGFβ-0h, RNA-s…
- GSM8697163 WT MCF7, TGFβ-0h, RNA-seq, rep2 WT MCF7, TGFβ-0h, RNA-s…
- GSM8697164 WT MCF7, TGFβ-0h, RNA-seq, rep3 WT MCF7, TGFβ-0h, RNA-s…
- GSM8697165 MED15 T603D MCF7, TGFβ-0h, RNA-seq, rep1 MED15 T603D MCF7, TGFβ-…
- GSM8697166 MED15 T603D MCF7, TGFβ-0h, RNA-seq, rep2 MED15 T603D MCF7, TGFβ-…
- GSM8697167 MED15 T603D MCF7, TGFβ-0h, RNA-seq, rep3 MED15 T603D MCF7, TGFβ-…
- GSM8697168 WT C57 mouse hippocamous tissue, RNA-seq, rep1 WT C57 mouse hippocamou…
- GSM8697169 WT C57 mouse hippocamous tissue, RNA-seq, rep2 WT C57 mouse hippocamou…
- GSM8697170 WT C57 mouse hippocamous tissue, RNA-seq, rep3 WT C57 mouse hippocamou…
- GSM8697171 MED15 T604A C57 mouse hippocamous tissue, RNA-seq, rep1 MED15 T604A C57 mouse h…
- GSM8697172 MED15 T604A C57 mouse hippocamous tissue, RNA-seq, rep2 MED15 T604A C57 mouse h…
- GSM8697173 MED15 T604A C57 mouse hippocamous tissue, RNA-seq, rep3 MED15 T604A C57 mouse h…
- GSE247586 RIG-I sensing of self-RNA in aged endothelial cells links cellular senescence with an interferon gene signature 7 samples shares senescence, cellular
- GSE277861 Enalapril mitigates senescence and aging-related phenotypes by targeting antioxidative genes via phosphorylated Smad1/5/9 [RNA-seq] 68 samples shares senescence
- GSE296209 Effects of hyperbaric oxygen on tissue-specific aging and senescence in mice and human stromal cells 45 samples shares senescence
- GSE302307 PP2A Regulates Senescence and Immunogenicity in Medulloblastoma 24 samples shares senescence
- GSE275233 Circadian Gene BMAL1 Regulation of Cell Senescence in Thyroid aging [scRNA-Seq] 10 samples shares senescence
- GSE226008 Histone Lactylation Antagonizes Senescence and Skeletal Muscle Aging by Modulating Aging-Related Pathways 72 samples shares senescence
- GSE277684 Premature senescence impairs hematopoietic stem cell function during sickle cell disease in mice and humans 52 samples shares senescence
- GSE220722 Primary cilia as a targetable node between biliary injury, senescence and regeneration 12 samples shares senescence
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.