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Atlas of human gut-associated lymphoid tissue reveals immunomodulatory interactions of B cells

GSE327417 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2026/06/05 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 12 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
12 samples: 12 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.
Summary (written by the submitters)
Gut-associated lymphoid tissue (GALT) is organized lymphoid tissue that responds chronically to antigens, including whole bacteria, sampled from the gut lumen. The ensuing immunoglobulin A (IgA) plasma cell response disseminates to regulate bacterial populations and to mediate intestinal immune homeostasis. GALT has roles in the development of the innate-like marginal zone B cell population and is also associated with a B cell–mediated contribution to ulcerative colitis (UC) severity and response to therapy.
Read the full summary ↓
Applying integrated multiomics methodologies, we identified key spatially resolved interactions of B cell subsets including broad regulatory features of double negative 2 (DN2) B cells with potential to maintain homeostasis within microbe-rich mucosa. By contrast, GALT in UC is distorted in composition and spatial distribution of B cell subsets that have altered immunomodulatory potential compared to healthy GALT. Thus, we identify interactions of strategically located B cells as mediators of immunological equilibrium in human gut.
This dataset
Open GSE327417 in finder → Find more human 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 GSE327417_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 PRJNA1450669 and SRA study SRP690247. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
12 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 12 sample titles: 12 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
Datasets on a similar topic

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