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RNA-seq profiling of resting naive and CD27bright memory B cells and in vitro activated CD27bright memory B cells reveals differences in B-cell activation patterns in common variable immunodeficiency (CVID)

GSE307095 Homo sapiens (human) RNA-seq (gene expression) 50 samples Submitted 2025/12/02 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 50 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
50 samples: 6 conditions, mostly with about 9 replicates eachGroups 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
Germinal center trajectories and transcriptional signatures define CLL subtypes and their pathway regulatorsPloS one · 2025
Summary (written by the submitters)
To investigate the transcriptional differences during resting state and B-cell activation in healthy donors and patients with CVID, we sorted naive B cells and CD27bright memory B cells from the two groups and examined the resting state and TLR9 agonist (CpG)-activated CD27bright memory B cells.
Published in
Germinal center trajectories and transcriptional signatures define CLL subtypes and their pathway regulators
Mohamed A, Giudice L, Basílio J et al. · PloS one 2025 · PMID 41124223 · doi:10.1371/journal.pone.0335069
This dataset
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.

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 GSE307095_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1314250 and SRA study SRP616648. Searching any of these in the dataset finder brings you back here.

Study design
6 conditions, mostly with about 9 replicates each
AB.CVID ×10 IB.CVID ×9 IB.HD ×9 IN.CVID ×9 IN.HD ×9 AB.HD ×4

Supports a between-group comparison across 50 samples.

How we read this: 6 replicated groups read from 50 sample titles; they account for 50 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

+ 10 more — browse all 50 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.