Transcriptomic Hallmarks of Mortality Reveal Universal and Specific Mechanisms of Aging, Chronic Disease, and Rejuvenation
RNA-seq (gene expression) · mouse · 210 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
- 210 samples: 46 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
- Universal transcriptomic hallmarks of mammalian ageing and mortalityNature · 2026
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 GSE292885_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 PRJNA1241802 and SRA study SRP572929. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 208 samples.
How we read this: 46 replicated groups read from 210 sample titles; they account for 208 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.
- GSM8866540 Kidney, WT, rep 1 Kidney, WT,
- GSM8866541 Kidney, WT, rep 2 Kidney, WT,
- GSM8866542 Kidney, WT, rep 3 Kidney, WT,
- GSM8866543 Kidney, WT, rep 4 Kidney, WT,
- GSM8866544 Kidney, WT, rep 5 Kidney, WT,
- GSM8866545 Kidney, WT, rep 6 Kidney, WT,
- GSM8866546 Kidney, Klotho KO, rep 1 Kidney, Klotho KO,
- GSM8866547 Kidney, Klotho KO, rep 2 Kidney, Klotho KO,
- GSM8866548 Kidney, Klotho KO, rep 3 Kidney, Klotho KO,
- GSM8866549 Kidney, Klotho KO, rep 4 Kidney, Klotho KO,
- GSM8866550 Kidney, Klotho KO, rep 5 Kidney, Klotho KO,
- GSM8866551 Kidney, Klotho KO, rep 6 Kidney, Klotho KO,
- GSM8866552 Skeletal muscle, WT, rep 1 Skeletal muscle, WT,
- GSM8866553 Skeletal muscle, WT, rep 2 Skeletal muscle, WT,
- GSM8866554 Skeletal muscle, WT, rep 3 Skeletal muscle, WT,
- GSM8866555 Skeletal muscle, WT, rep 4 Skeletal muscle, WT,
- GSM8866556 Skeletal muscle, WT, rep 5 Skeletal muscle, WT,
- GSM8866557 Skeletal muscle, WT, rep 6 Skeletal muscle, WT,
- GSM8866558 Skeletal muscle, Klotho KO, rep 1 Skeletal muscle, Klotho…
- GSM8866559 Skeletal muscle, Klotho KO, rep 2 Skeletal muscle, Klotho…
- GSM8866560 Skeletal muscle, Klotho KO, rep 3 Skeletal muscle, Klotho…
- GSM8866561 Skeletal muscle, Klotho KO, rep 4 Skeletal muscle, Klotho…
- GSM8866562 Skeletal muscle, Klotho KO, rep 5 Skeletal muscle, Klotho…
- GSM8866563 Skeletal muscle, Klotho KO, rep 6 Skeletal muscle, Klotho…
- GSM8868031 Female, Old, 1,3-butanediol, rep 1 Female, Old, 1,3-butane…
- GSM8868032 Female, Old, 1,3-butanediol, rep 2 Female, Old, 1,3-butane…
- GSM8868033 Female, Old, 1,3-butanediol, rep 3 Female, Old, 1,3-butane…
- GSM8868034 Female, Old, bGPA, rep 1 Female, Old, bGPA,
- GSM8868035 Female, Old, bGPA, rep 2 Female, Old, bGPA,
- GSM8868036 Female, Old, bGPA, rep 3 Female, Old, bGPA,
- GSM8868037 Female, Old, Canagliflozin, rep 1 Female, Old, Canagliflo…
- GSM8868038 Female, Old, Canagliflozin, rep 2 Female, Old, Canagliflo…
- GSM8868039 Female, Old, Canagliflozin, rep 3 Female, Old, Canagliflo…
- GSM8868040 Female, Old, Canagliflozin, rep 4 Female, Old, Canagliflo…
- GSM8868041 Female, Old, Canagliflozin, rep 5 Female, Old, Canagliflo…
- GSM8868042 Female, Old, Canagliflozin, rep 6 Female, Old, Canagliflo…
- GSM8868043 Female, Old, Canagliflozin, rep 7 Female, Old, Canagliflo…
- GSM8868044 Female, Old, Captopril, rep 1 Female, Old, Captopril,
- GSM8868045 Female, Old, Captopril, rep 2 Female, Old, Captopril,
- GSM8868046 Female, Old, Captopril, rep 3 Female, Old, Captopril,
+ 170 more — browse all 210 samples with per-sample file links →
- GSE324408 Single-cell transcriptional landscape of muscle-derived stem/progenitor cells reveal hallmarks of aging and rejuvenation 6 samples shares rejuvenation, hallmarks, aging
- GSE280382 Functional and multi-omic aging rejuvenation with GLP-1R agonism [bulk RNA-seq] 620 samples shares rejuvenation, aging
- GSE272841 Life-long microbiome rejuvenation improves intestinal metabolism and inflammaging in mice [bulk RNA-seq] 39 samples shares rejuvenation, aging
- GSE283764 Canagliflozin treatment prevents follicular exhaustion and attenuates hallmarks of ovarian aging in genetically heterogenous mice 15 samples shares hallmarks, aging
- GSE272842 Life-long microbiome rejuvenation improves intestinal metabolism and inflammaging in mice [scRNA-seq] 12 samples shares rejuvenation, aging
- GSE283393 Multinucleated giant cells are hallmarks of ovarian aging with unique immune and degradation-associated molecular signatures 12 samples shares hallmarks, aging
- GSE242038 The nucleolar aberrancies that drive ribosome impairment induced by RNA binding proteins are hallmarks of aging 9 samples shares hallmarks, aging
- GSE267445 Noninvasive focused ultrasound non-specifically activating spleen immunological function to universally suppress tumor proliferation: a new strategy for cancer immunotherapy -NK cells 6 samples shares universal, specific
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.