← BioTransfer GEO Dataset Finder
GEO series

T Cell Transcriptome Alterations in Healthy Volunteers Exposed to Three Weeks of Simulated Microgravity

GSE301964 Homo sapiens (human) RNA-seq (gene expression) 50 samples Submitted 2025/12/09 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 50 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
50 samples: 50 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
Microgravity Impacts the Expression of Aging-Associated Candidate Gene Targets in the p53 Regulatory NetworkInternational journal of molecular sciences · 2025
Summary (written by the submitters)
Impairment or reduction of lymphocyte-mediated immune response has been observed during space flight or in microgravity simulation conditions, with the underlying mechanisms remaining unclear. T lymphocytes (T cells) play a critical role in human immune response. The immunosuppression encountered by humans in microgravity may be linked to its impact on T cell global transcriptome networks, affecting immune cell-cell interactions.
Read the full summary ↓
This study involved a unique three-week microgravity simulation conducted with ten healthy male volunteers aged 25-40 using a dry immersion facility. The research aimed to explore the normal responses of the human body to long-term simulated microgravity (SMG) without any specific countermeasures implemented. To investigate the T cell response to SMG, total RNA isolated from T lymphocytes at different time points during the course of SMG was subjected to RNA sequencing. Bioinformatic analysis revealed the impact of SMG on multiple cell signaling pathways, influenced by key regulators that modulated the expression of different genes. The discovery of potential biomarker genes in T cells may offer valuable insights into studying human responses to microgravity, however, further validation of these findings in space is required.
Published in
Microgravity Impacts the Expression of Aging-Associated Candidate Gene Targets in the p53 Regulatory Network
Kuznetsov NV, Vlasova DD, Kotikova AA et al. · International journal of molecular sciences 2025 · PMID 41303625 · doi:10.3390/ijms262211140
This dataset
Open GSE301964 in finder → Find more human RNA-seq datasets →
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.

Series matrix ↓
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 GSE301964_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
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.

Raw reads on ENA ↗

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 PRJNA1287790. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41303625) ↗
Study design
50 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 50 sample titles: 50 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

+ 10 more — browse all 50 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.