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Comparative Single-Cell Analyses in Infants Revealed RSV-Specific Declines in NK Cell Responses and COVID-19-Specific Increases in Inflammatory Responses [COVID_RSV_scRNA]

GSE283746 Homo sapiens (human) Single-cell RNA-seq 68 samples Submitted 2026/01/15 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 68 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Samples
68 samples: 8 conditions, mostly with about 7 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
A systems immunology approach reveals divergent immune profiles of RSV and SARS-CoV-2 infections in infantsScience translational medicine · 2026
Summary (written by the submitters)
The clinical phenotype of infants infected with respiratory syncytial virus (RSV) differs from that of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. RSV is the leading cause of hospitalization for lower respiratory tract infection and carries a significant higher risk of respiratory failure compared to SARS-CoV-2, which has been generally linked to fever and croup in young infants.
Read the full summary ↓
The underlying mechanisms these differences remain unclear. We analyzed peripheral blood mononuclear cells (PBMCs) and serum from infants infected with SARS-CoV-2 (n=30), RSV (n=19), and healthy controls (n=17) using single-cell RNA sequencing, single-nucleus ATAC sequencing and cytokine profiling. Both viruses triggered type I interferon responses across PBMC subsets but differed in their NK cell and inflammatory responses. Severe RSV cases were characterized by lower NK cell percentages, lower IFNG expression and diminished chromatin accessibility at T-BET and EOMES binding sites in NK cells. Furthermore, RSV infections were associated with increased frequencies of CD4+ TEMRA and memory Treg cells. In contrast, SARS-CoV-2 infections were marked by more pronounced pro-inflammatory signatures, including increased transcriptional and epigenetic activity at NFKB factors and higher serum TNF concentrations. These findings highlight distinct immune response pathways in RSV and SARS-CoV-2 infections that may inform future therapeutic strategies.
Published in
A systems immunology approach reveals divergent immune profiles of RSV and SARS-CoV-2 infections in infants
Thibodeau A, Mejias A, Nehar-Belaid D et al. · Science translational medicine 2026 · PMID 41739901 · doi:10.1126/scitranslmed.aea7097
This dataset
Open GSE283746 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 GSE283746_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1195123. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41739901) ↗
Study design
8 conditions, mostly with about 7 replicates each
PBMC, Healthy, pHC ×17 PBMC, Moderate COVID-19, pCoV ×12 PBMC, Convalescent COVID-19, pCoV ×10 PBMC, Severe RSV, pRSV ×7 PBMC, Moderate RSV, pRSV ×7 PBMC, Severe COVID-19, pCoV ×5 PBMC, Mild RSV, pRSV ×5 PBMC, Severe Steroid Treated COVID-19, pCoV ×4 +1 more

Supports a case/control comparison: 4 samples read as cases, 17 as controls.

How we read this: 8 replicated groups read from 68 sample titles; they account for 67 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

+ 28 more — browse all 68 samples with per-sample file links →

Datasets on a similar topic

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