GEO series

Multiple subpopulations in medullary thymic epithelial cells are regulated by Aire with distinctive modes of gene regulations [deep single-cell RNA-seq]

GSE205991 Mus musculus (mouse) Single-cell RNA-seq 2148 samples Submitted 2025/03/12 Platform GPL28457Platform GPL17021

At a glance

Single-cell RNA-seq · mouse · 2148 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Mus musculus (mouse)
Samples: 2148 samples: 247 × mTEClo, adult, WT, cell vs 124 × mTEClo, neonate, WT, cellGroups 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: Role of PRC2 in the stochastic expression of Aire target genes and development of mimetic cells in the thymusThe Journal of experimental medicine · 2025

Summary (written by the submitters)

Aire, a transcriptional regulator whose defect results in the development of autoimmunity, controls the transcriptome in the bulk of medullary thymic epithelial cells (mTECs) including the genes for self-antigens. Mechanisms for this process, however, remained incompletely understood, especially regarding the effects of Aire in each subpopulation in mTECs.

Read the full summary ↓

Here, we combined single-cell multi-omics (scMulti-seq) technologies by which gene expression and open chromatin were simultaneously profiled from the same cell and deeper single-cell sequencing by RamDA-seq which enabled profiling of the minimum dropout. scMulti-seq effectively demonstrated the subpopulations among mTECs associated with diverse transcription factor activities which are affected by Aire and developmental stages, while RamDA-seq revealed the different modes of gene regulations by Aire in different subpopulations. Aire is not only essential for the development of a specific population in which Aire induces a set of genes in a stochastic manner but also promotes the development of multiple subpopulations in which Aire enhances the expressions of genes in a coordinated manner. The former group of Aire-induced genes was characterized by enhanced H3K27me3 chromatin modifications and Aire seems to unleash these silenced genes by deactivating polycomb repressive complex 2 (PRC2). We also found unique gene signatures for the neonatal stage such as high expression of chemokines and expression of cortical TEC (cTEC)-like genes in TECs, which were Aire-independent. Our approach has illuminated the multilayered transcriptional control in mTECs governing the multiple subpopulations organizing the thymic microenvironment.

Published in

Role of PRC2 in the stochastic expression of Aire target genes and development of mimetic cells in the thymus

Matsumoto M, Yoshida M, Oya T et al. · The Journal of experimental medicine 2025 · PMID 40244172 · doi:10.1084/jem.20240817

This dataset

Open GSE205991 in finder → Find more mouse 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 GSE205991_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA848770 and SRA study SRP379965. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40244172) ↗

Study design

247 × mTEClo, adult, WT, cell vs 124 × mTEClo, neonate, WT, cell

Supports a between-group comparison across 371 samples.

How we read this: 2 replicated groups read from the first 400 of 2148 sample titles; they account for 371 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.

Samples in this study

GSM6416167 mTEClo, neonate, WT, cell1 mTEClo, neonate, WT, ce…
GSM6416168 mTEClo, neonate, WT, cell2 mTEClo, neonate, WT, ce…
GSM6416169 mTEClo, neonate, WT, cell3 mTEClo, neonate, WT, ce…
GSM6416170 mTEClo, neonate, WT, cell4 mTEClo, neonate, WT, ce…
GSM6416171 mTEClo, neonate, WT, cell5 mTEClo, neonate, WT, ce…
GSM6416172 mTEClo, neonate, WT, cell6 mTEClo, neonate, WT, ce…
GSM6416173 mTEClo, neonate, WT, cell7 mTEClo, neonate, WT, ce…
GSM6416174 mTEClo, neonate, WT, cell8 mTEClo, neonate, WT, ce…
GSM6416175 mTEClo, neonate, WT, cell9 mTEClo, neonate, WT, ce…
GSM6416176 mTEClo, neonate, WT, cell10 mTEClo, neonate, WT, ce…
GSM6416177 mTEClo, neonate, WT, cell11 mTEClo, neonate, WT, ce…
GSM6416178 mTEClo, neonate, WT, cell12 mTEClo, neonate, WT, ce…
GSM6416179 mTEClo, neonate, WT, cell13 mTEClo, neonate, WT, ce…
GSM6416180 mTEClo, neonate, WT, cell14 mTEClo, neonate, WT, ce…
GSM6416181 mTEClo, neonate, WT, cell15 mTEClo, neonate, WT, ce…
GSM6416182 mTEClo, neonate, WT, cell16 mTEClo, neonate, WT, ce…
GSM6416183 mTEClo, neonate, WT, cell17 mTEClo, neonate, WT, ce…
GSM6416184 mTEClo, neonate, WT, cell18 mTEClo, neonate, WT, ce…
GSM6416185 mTEClo, neonate, WT, cell19 mTEClo, neonate, WT, ce…
GSM6416186 mTEClo, neonate, WT, cell20 mTEClo, neonate, WT, ce…
GSM6416187 mTEClo, neonate, WT, cell21 mTEClo, neonate, WT, ce…
GSM6416188 mTEClo, neonate, WT, cell22 mTEClo, neonate, WT, ce…
GSM6416189 mTEClo, neonate, WT, cell23 mTEClo, neonate, WT, ce…
GSM6416190 mTEClo, neonate, WT, cell24 mTEClo, neonate, WT, ce…
GSM6416191 mTEClo, neonate, WT, cell25 mTEClo, neonate, WT, ce…
GSM6416192 mTEClo, neonate, WT, cell26 mTEClo, neonate, WT, ce…
GSM6416193 mTEClo, neonate, WT, cell27 mTEClo, neonate, WT, ce…
GSM6416194 mTEClo, neonate, WT, cell28 mTEClo, neonate, WT, ce…
GSM6416195 mTEClo, neonate, WT, cell29 mTEClo, neonate, WT, ce…
GSM6416196 mTEClo, neonate, WT, cell30 mTEClo, neonate, WT, ce…
GSM6416197 mTEClo, neonate, WT, cell31 mTEClo, neonate, WT, ce…
GSM6416198 mTEClo, neonate, WT, cell32 mTEClo, neonate, WT, ce…
GSM6416199 mTEClo, neonate, WT, cell33 mTEClo, neonate, WT, ce…
GSM6416200 mTEClo, neonate, WT, cell34 mTEClo, neonate, WT, ce…
GSM6416201 mTEClo, neonate, WT, cell35 mTEClo, neonate, WT, ce…
GSM6416202 mTEClo, neonate, WT, cell36 mTEClo, neonate, WT, ce…
GSM6416203 mTEClo, neonate, WT, cell37 mTEClo, neonate, WT, ce…
GSM6416204 mTEClo, neonate, WT, cell38 mTEClo, neonate, WT, ce…
GSM6416205 mTEClo, neonate, WT, cell39 mTEClo, neonate, WT, ce…
GSM6416206 mTEClo, neonate, WT, cell40 mTEClo, neonate, WT, ce…

+ 2108 more — browse all 2148 samples with per-sample file links →

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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.