GEO series

Human long noncoding RNA, VILMIR, is induced by major respiratory viral infections and modulates the host interferon response

GSE288251 Homo sapiens (human) Single-cell RNA-seq 24 samples Submitted 2025/03/20 Platform GPL23525

At a glance

Single-cell RNA-seq · human · 24 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism: Homo sapiens (human)
Samples: 24 samples
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: Human long noncoding RNA VILMIR is induced by major respiratory viral infections and modulates the host interferon responseJournal of virology · 2025

Summary (written by the submitters)

Long noncoding RNAs (lncRNAs) are a newer class of noncoding transcripts identified as key regulators of biological processes. Here we aimed to identify novel lncRNA targets that play critical roles in major human respiratory viral infections by systematically mining large-scale transcriptomic datasets.

Read the full summary ↓

Using bulk RNA-sequencing (RNA-seq) analysis, we identified a previously uncharacterized lncRNA, named virus inducible lncRNA modulator of interferon response (VILMIR), that was consistently upregulated after in vitro influenza infection across multiple human epithelial cell lines and influenza A virus subtypes. VILMIR was also upregulated after SARS-CoV-2 and RSV infections in vitro. We experimentally confirmed the response of VILMIR to influenza infection and interferon-beta (IFN-β) treatment in the A549 human epithelial cell line and found the expression of VILMIR was robustly induced by IFN-β treatment in a dose and time-specific manner. Single cell RNA-seq analysis of bronchoalveolar lavage fluid (BALF) samples from COVID-19 patients uncovered that VILMIR was upregulated across various cell types including at least five immune cells. The upregulation of VILMIR in immune cells was further confirmed in the human T cell and monocyte cell lines, SUP-T1 and THP-1, after IFN-β treatment. Finally, we found that knockdown of VILMIR expression reduced the magnitude of host transcriptional responses to both IFN-β treatment and influenza A virus infection in A549 cells. Together, our results show that VILMIR is a novel interferon-stimulated gene (ISG) that regulates the host interferon response and may be a potential therapeutic target for human respiratory viral infections upon further mechanistic investigation.

Published in

Human long noncoding RNA VILMIR is induced by major respiratory viral infections and modulates the host interferon response

John K, Huntress I, Smith E et al. · Journal of virology 2025 · PMID 40130878 · doi:10.1128/jvi.00141-25

This dataset

Open GSE288251 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 GSE288251_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 PRJNA1216628 and SRA study SRP560415. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40130878) ↗

Samples in this study

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+ 24 more — browse all 24 samples with per-sample file links →

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