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Human intraepithelial mast cell differentiation and effector function are directed by TGF-b signaling

GSE279240 Homo sapiens (human) RNA-seq (gene expression) 36 samples Submitted 2024/12/11 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 36 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
36 samples: 18 conditions, mostly in duplicateGroups 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.
Summary (written by the submitters)
Mast cells (MCs) expressing a distinctive protease phenotype (MCTs) selectively expand within the epithelium of human mucosal tissues during type 2 (T2) inflammation. While MCTs are phenotypically distinct from subepithelial MCs (MCTCs), signals driving human MCT differentiation and this subset’s contribution to inflammation remain unexplored.
Read the full summary ↓
Here, we identify TGF-b as a key driver of the MCT transcriptome in nasal polyps. We find that short-term TGF-b signaling alters MC cell surface receptor expression and partially recapitulates the in vivo MCT transcriptome, while TGF-β signaling during MC differentiation upregulates a larger number of MCT-associated transcripts and inhibits the hallmark MCTC proteases chymase and cathepsin G at both the transcript and protein level, allowing selective in vitro differentiation of MCTs for functional study. We identify discrete differences in effector phenotype between in vitro-derived MCTs and MCTCs, with MCTs greatly enhancing pro-inflammatory lipid mediator generation while selectively modifying cytokine, chemokine, and growth factor production in response to both innate and adaptive stimuli, recapitulating functional features of their tissue-associated counterpart MC subsets. Thus, our findings support a role for TGF-β in promoting human MCT differentiation and identify a discrete contribution of this cell type to T2 inflammation.
This dataset
Open GSE279240 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 GSE279240_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 PRJNA1171463 and SRA study SRP537808. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
18 conditions, mostly in duplicate
MC_D1_PBS_24h ×2 MC_D2_PBS_24h ×2 MC_D3_PBS_24h ×2 MC_D1_TGF_24h ×2 MC_D2_TGF_24h ×2 MC_D3_TGF_24h ×2 MC_D1_PBS_6d ×2 MC_D2_PBS_6d ×2 +10 more

Supports a between-group comparison across 36 samples.

How we read this: 18 replicated groups read from 36 sample titles; they account for 36 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
Datasets on a similar topic

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