Transcriptomic profiling of young, replicative senescent, and premature senescent HUVECs
RNA-seq (gene expression) · human · 9 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
- Homo sapiens (human)
- Samples
- 9 samples: 3 × HUVEC young vs 3 × HUVEC replicative senescence vs 3 × HUVEC premature senescenceGroups 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
- Replicative and stress-induced premature senescence distinctively affect the endothelial anticoagulation capacityPloS one · 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 GSE312006_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 PRJNA1370608 and SRA study SRP649590. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 9 samples.
How we read this: 3 replicated groups read from 9 sample titles; they account for 9 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.
- GSM9336110 HUVEC young replicate 1 HUVEC young
- GSM9336111 HUVEC young replicate 2 HUVEC young
- GSM9336112 HUVEC young replicate 3 HUVEC young
- GSM9336113 HUVEC replicative senescence replicate 1 HUVEC replicative senes…
- GSM9336114 HUVEC replicative senescence replicate 2 HUVEC replicative senes…
- GSM9336115 HUVEC replicative senescence replicate 3 HUVEC replicative senes…
- GSM9336116 HUVEC premature senescence replicate 1 HUVEC premature senesce…
- GSM9336117 HUVEC premature senescence replicate 2 HUVEC premature senesce…
- GSM9336118 HUVEC premature senescence replicate 3 HUVEC premature senesce…
- GSE293225 Changes in gene expression patterns in young and senescent fibroblasts in glycated three-dimensional collagen matrices 36 samples shares senescent, young
- GSE330283 Endothelial transcriptome remodeling by young and senescent MSCs depends on co-culture mode, ECM, and secreted factors 27 samples shares senescent, young
- GSE311038 Multi-omics integrative approach of senescent endothelial cells and derived extracellular vesicles in a replicative senescence model [RNA-seq] 12 samples shares replicative, senescent
- GSE311040 Multi-omics integrative approach of senescent endothelial cells and derived extracellular vesicles in a replicative senescence model 18 samples shares replicative, senescent
- GSE284666 SenCat: Redefining human cell senescence through multiomic profiling of multiple senescent cell types 190 samples shares senescent
- GSE304272 Transcriptomic profiling of irradiated senescent IMR90 cells treated with CDK4/6 or JAK inhibitors 12 samples shares senescent
- GSE156448 Transcriptomic profiling of human senescent cells upon medicinal intervention with ginkgo boliba extract or rattan tea extract 12 samples shares senescent
- GSE329677 DNA damage drives a unique, Alzheimer’s disease-relevant senescent state in neurons 231 samples shares senescent
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.