GEO series

Germinal center-mediated broadening of B cell responses to SARS-CoV-2 booster immunization

GSE292810 Homo sapiens (human) RNA-seq (gene expression) 10 samples Submitted 2025/09/16 Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 10 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: 10 samples: 5 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.
Paper: Germinal center-mediated broadening of B cell responses to SARS-CoV-2 booster immunizationScience immunology · 2025

Summary (written by the submitters)

Germinal centers (GC) are key sites for antibody diversification and affinity maturation. SARS-CoV-2 mRNA vaccines elicit robust GC B cell responses in humans, but how these influence the breadth of immunity against viral variants remains unclear. We analyzed GC B cell responses in nine healthy adults following mRNA booster immunization.

Read the full summary ↓

We show that 77.8% of the B cell clones in the GC expressed representative monoclonal antibodies (mAbs) recognizing the spike protein, with 37.8% of these targeting the receptor-binding domain (RBD). One RBD-targeting mAb, mAb-52, neutralized all tested SARS-CoV-2 strains, including the recent XEC variant. mAb-52 utilized the IGHV3-66 public clonotype, protected hamsters challenged against the EG.5.1 variant, and targeted the class I/II RBD epitope, closely mimicking the binding footprint of ACE2. Its broad reactivity was driven by extensive somatic hypermutation, underscoring the critical role of GC reactions in shaping cross-variant B cell immunity following SARS-CoV-2 booster vaccination.

Published in

Germinal center-mediated broadening of B cell responses to SARS-CoV-2 booster immunization

Malladi SK, Jaiswal D, Ying B et al. · Science immunology 2025 · PMID 41071904 · doi:10.1126/sciimmunol.adu4107

This dataset

Open GSE292810 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 GSE292810_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 PRJNA1185243 and SRA study SRP544739. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41071904) ↗

Study design

5 conditions, mostly in duplicate

382-65 d57 lymph node, ×2 382-67 d57 lymph node, ×2 382-69 d57 lymph node, ×2 382-70 d57 lymph node, ×2 382-71 d57 lymph node, ×2

Supports a between-group comparison across 10 samples.

How we read this: 5 replicated groups read from 10 sample titles; they account for 10 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

GSM8865726 scRNA-seq of Homo sapiens: 382-65 d57 lymph node, bio rep 1 382-65 d57 lymph node,
GSM8865727 scRNA-seq of Homo sapiens: 382-65 d57 lymph node, bio rep 2 382-65 d57 lymph node,
GSM8865728 scRNA-seq of Homo sapiens: 382-67 d57 lymph node, bio rep 1 382-67 d57 lymph node,
GSM8865729 scRNA-seq of Homo sapiens: 382-67 d57 lymph node, bio rep 2 382-67 d57 lymph node,
GSM8865730 scRNA-seq of Homo sapiens: 382-69 d57 lymph node, bio rep 1 382-69 d57 lymph node,
GSM8865731 scRNA-seq of Homo sapiens: 382-69 d57 lymph node, bio rep 2 382-69 d57 lymph node,
GSM8865732 scRNA-seq of Homo sapiens: 382-70 d57 lymph node, bio rep 1 382-70 d57 lymph node,
GSM8865733 scRNA-seq of Homo sapiens: 382-70 d57 lymph node, bio rep 2 382-70 d57 lymph node,
GSM8865734 scRNA-seq of Homo sapiens: 382-71 d57 lymph node, bio rep 1 382-71 d57 lymph node,
GSM8865735 scRNA-seq of Homo sapiens: 382-71 d57 lymph node, bio rep 2 382-71 d57 lymph node,

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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.