Gene expression profile of microglia following traumatic brain injury and nasal anti-CD3 treatment at acute and chronic timepoints
RNA-seq (gene expression) · mouse · 54 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
- 54 samples: 54 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
- Nasal anti-CD3 monoclonal antibody ameliorates traumatic brain injury, enhances microglial phagocytosis and reduces neuroinflammation via IL-10-dependent T(reg)-microglia crosstalkNature neuroscience · 2025
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 GSE276647_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 PRJNA1154944 and SRA study SRP531222. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 54 sample titles: 54 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.
- GSM8503560 Sham_Iso_1_7d
- GSM8503561 Sham_Iso_2_7d
- GSM8503562 Sham_Iso_3_7d
- GSM8503563 Sham_Iso_4_7d
- GSM8503564 TBI_Iso_1_7d
- GSM8503565 TBI_Iso_2_7d
- GSM8503566 TBI_Iso_3_7d
- GSM8503567 TBI_Iso_4_7d
- GSM8503568 TBI_aCD3_1_7d
- GSM8503569 TBI_aCD3_2_7d
- GSM8503570 TBI_aCD3_3_7d
- GSM8503571 TBI_aCD3_4_7d
- GSM8503572 Sham_Iso_1_1m
- GSM8503573 Sham_Iso_2_1m
- GSM8503574 Sham_Iso_3_1m
- GSM8503575 Sham_Iso_4_1m
- GSM8503576 TBI_Iso_1_1m
- GSM8503577 TBI_Iso_2_1m
- GSM8503578 TBI_Iso_3_1m
- GSM8503579 TBI_Iso_4_1m
- GSM8503580 TBI_aCD3_1_1m
- GSM8503581 TBI_aCD3_2_1m
- GSM8503582 TBI_aCD3_3_1m
- GSM8503583 TBI_aCD3_4_1m
- GSM8503584 Sham_Iso_1_1m_delayed
- GSM8503585 Sham_Iso_2_1m_delayed
- GSM8503586 Sham_Iso_3_1m_delayed
- GSM8503587 Sham_Iso_4_1m_delayed
- GSM8503588 Sham_Iso_5_1m_delayed
- GSM8503589 TBI_Iso_1_1m_delayed
- GSM8503590 TBI_Iso_2_1m_delayed
- GSM8503591 TBI_Iso_3_1m_delayed
- GSM8503592 TBI_Iso_4_1m_delayed
- GSM8503593 TBI_Iso_5_1m_delayed
- GSM8503594 TBI_aCD3_1_1m_delayed
- GSM8503595 TBI_aCD3_2_1m_delayed
- GSM8503596 TBI_aCD3_3_1m_delayed
- GSM8503597 TBI_aCD3_4_1m_delayed
- GSM8503598 TBI_aCD3_5_1m_delayed
- GSM8503599 Sham_Iso_1_1m_Female_Severe_TBI
+ 14 more — browse all 54 samples with per-sample file links →
- GSE332646 Bulk RNA-seq of juvenile mouse liver following NDMA or saline treatment in WT and Mgmt-/- genotypes across multiple timepoints 214 samples shares timepoints, following, treatment
- GSE302808 Depletion of Peripheral Monocytes Alters Long-Term Gene Expression in Microglia in a Murine Model of Traumatic Brain Injury 84 samples shares microglia, traumatic, injury
- GSE300113 Heterogenous microglial reactivity contrasts with stable vascular transcriptional programs in mouse models of Alzheimer’s, CADASIL, and Traumatic Brain Injury (Main dataset) 59 samples shares microglia, traumatic, injury
- GSE277487 Single-nucleus RNA-seq of mouse cortex following CCI-induced traumatic brain injury across multiple time points 12 samples shares following, traumatic, injury
- GSE276682 Single-cell transcriptome analysis revealed cellular reprogramming following Tetramethylpyrazine treatment in LPS-induced acute lung injury 12 samples shares following, treatment, injury
- GSE326452 Bulk RNA-seq of mouse brain following closed head injury: role of IL-1R1 signaling 200 samples shares following, injury
- GSE306281 RNA-seq of kidney transcriptome following UUO injury 75 samples shares following, injury
- GSE285895 Simulating Neonatal Microglial Pan-Programmed Cell Death to Unlock Regenerative Potential in Adult Mice Spinal Cord Injury [RNA-seq] 21 samples shares microglia, injury
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.