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Vaccine based on immune evasion mutations integrated RBD protein have broad protection against SARS-CoV-2 [mRNA-seq]

GSE261311 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2024/03/15 Platform GPL28330
At a glance

RNA-seq (gene expression) · mouse · 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
Mus musculus (mouse)
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)
Variants of SARS-CoV-2 continue to emerge and evade immunity, resulting in breakthrough infections in vaccinated populations. Continued vaccination with vaccines based on the antigens of newly emerged variants does not necessarily result in long-lasting protection. Thus, there is an urgent need for the development of vaccines with a broad spectrum of protective effects.
Read the full summary ↓
In this study, we selected hotspot mutations in the receptor binding domain (RBD) based on immune escape properties and integrated them into the original RBD protein to obtain a complexed RBD protein (cRBD). We designed a total of three cRBD (cRBD1-3) and thoroughly evaluated their immunological properties. Compared with the BA.1 RBD protein, the cRBDs induced higher levels and broader spectrum of neutralizing antibodies, with cRBD3 being the best performer. In vivo protective capacity of cRBDs was further validated in Balb/c mice attacked by live virus. In order to investigate the reason for the broad protective efficacy of cRBD, whole blood from mice that had completed the immunization process was subjected to RNA sequencing. Transcriptome analysis revealed that the vaccine was able to stimulate an immune response.
This dataset
Open GSE261311 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 GSE261311_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 PRJNA1086470 and SRA study SRP494535. 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

Search all mouse 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.