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RNA-sequencing from nasal curettes or swabs collected from young children aged 1-5

GSE290387 Homo sapiens (human) RNA-seq (gene expression) 60 samples Submitted 2026/02/25 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 60 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
60 samples: 60 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.
Paper
Host-microbial interactions at the nasal mucosa in young children and adults: A retrospective, cross-sectional studyCell reports · 2026
Summary (written by the submitters)
There is a paucity of data on how the mucosal immune system changes with age. Moreover, the link between nasal presence of bacteria and viruses with the immune system in young children is still poorly understood. To address these questions we collected nasal curettes, nasal swabs and filter papers from young children undergoing anesthesia for surgery unrelated to respiratory complaints.
Read the full summary ↓
Microbial and host parameters were analysed from these samples, including transcriptomics from nasal curettes and swabs. Results revealed strong differences in nasal mucosal immunity in children compared with adutls, as well as clear effects of the presence of bacteria such as pneumococcus and haemophilus on the local immune system
Published in
Host-microbial interactions at the nasal mucosa in young children and adults: A retrospective, cross-sectional study
Reiné J, King LA, Singh Y et al. · Cell reports 2026 · PMID 42189677 · doi:10.1016/j.celrep.2026.117346
This dataset
Open GSE290387 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 GSE290387_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 PRJNA1227868 and SRA study SRP566135. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42189677) ↗
Study design
60 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 60 sample titles: 60 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

+ 20 more — browse all 60 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.