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Rapid boosting increases germinal center responses to sequential vaccines

GSE309127 Mus musculus (mouse) RNA-seq (gene expression) 33 samples Submitted 2026/05/07 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 33 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
Mus musculus (mouse)
Samples
33 samples: 33 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)
Germinal centers (GCs) are a complex and important aspect of humoral immunity. How germinal centers deal with changing antigens remains unclear, yet this biology could be central to next-generation vaccine strategies such as germline-targeting. Here we demonstrate, in a mouse model with protein immunogens, that rapid delivery of homologous or heterologous boosts results in highly positive outcomes.
Read the full summary ↓
Rapid reimmunization expands on-target GC B cell (BGC) populations, which emerge almost exclusively from existing BGC cells. Early homologous boosting avoids prohibitive antibody titers and utilizes off-target antibodies to maximize the BGC response, with 24-fold increases in on-target VRC01gHL cell numbers. Heterologous rapid boosting shifts affinity maturation towards the new antigen. The ‘refueled’ GCs are sustained, developing large affinity gains, and rapidly evolving to bind wild-type HIV trimer within 56 days, even when using as few as two distinct antigens. These findings provide new insights into GC biology and translatable paths to leveraging accelerated GC functions.
This dataset
Open GSE309127 in finder → Find more mouse 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 GSE309127_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 PRJNA1334009 and SRA study SRP626456. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
33 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 33 sample titles: 33 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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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.