GEO series

Functional interrogation of lymphocyte subsets in alopecia areata using single-cell RNA sequencing

GSE233906 Homo sapiens (human) Single-cell RNA-seq 14 samples Submitted 2023/07/25 Platform GPL18573Platform GPL19057

At a glance

Single-cell RNA-seq · human · 14 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Homo sapiens (human)
Samples: 14 samples
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.

Summary (written by the submitters)

Alopecia areata (AA) is among the most prevalent autoimmune diseases, but the development of innovative therapeutic strategies has lagged due to an incomplete understanding of the immunological underpinnings of disease. Here, we performed single-cell RNA sequencing (scRNAseq) of skin-infiltrating immune cells from the graft-induced C3H/HeJ mouse model of AA, coupled with antibody-based depletion to interrogate the functional role of specific cell types in AA in vivo.

Read the full summary ↓

Since AA is predominantly T cell-mediated, we focused on dissecting lymphocyte function in AA. Both our scRNAseq and functional studies established CD8+ T cells as the primary disease-driving cell type in AA. Only the depletion of CD8+ T cells, but not CD4+ T cells, NK, B, or γδ T cells, was sufficient to prevent and reverse AA. Selective depletion of regulatory T cells (Treg) showed that Treg are protective against AA in C3H/HeJ mice, suggesting that AA failure of Treg-mediated immunosuppression is not a major disease mechanism. Focused analyses of CD8+ T cells revealed five subsets, whose heterogeneity is defined by an ‘effectorness gradient’ of interrelated transcriptional states that culminate in increased effector function and tissue residency. scRNAseq of human AA skin showed that CD8+ T cells in human AA follow a similar trajectory, underscoring that shared mechanisms drive disease in both murine and human AA. Our study represents a comprehensive, systematic interrogation of lymphocyte heterogeneity in AA, and uncovers a framework for AA-associated CD8+ T cells with implications for the design of future therapeutics.

This dataset

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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 GSE233906_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 PRJNA978553 and SRA study SRP440689. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 37428932) ↗

Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 14 more — browse all 14 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.