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Chromatin disruptions in pathophysiologically relevant gene promoters underlie unique SARS-Cov-2 nucleocapsid-mediated gene regulation

GSE290042 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 48 samples Submitted 2025/02/26 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 48 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Homo sapiens (human)
Samples
48 samples: 48 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)
SARS-CoV-2, the causative agent of COVID-19, is a positive-sense, single-stranded RNA virus that causes a spectrum of disease severity, from asymptomatic infection to severe illness to long-term sequelae. Similar to other human coronaviruses, SARS-CoV-2 proteins modulate host genomic responses through epigenomic modifications, facilitating viral replication and immune evasion.
Read the full summary ↓
While the nucleocapsid protein is well known for its role in RNA stability and immune modulation, its impact on host chromatin organization remains unclear. To investigate this, we generated stable human alveolar cell lines expressing nucleocapsid proteins from endemic and pandemic human coronaviruses. Our analysis revealed that nucleocapsid proteins from all tested coronaviruses induced changes in nucleosome positioning and occupancy at specific gene promoters involved in coagulation pathways, hormone signaling, and innate immune responses. Additionally, SARS-CoV-2-specific alterations were identified in genes dysregulated in severe infections, such as suggesting a direct role for epigenomic modifications in disease pathophysiology. We also observed extensive changes in nucleosome susceptibility to nuclease digestion in SARS-CoV and SARS-CoV-2 samples that were not observed in common cold cell lines. Promoters with altered sensitivity and resistance to nuclease were linked to innate immune, metabolic, olfactory, and signaling pathways known to be dysregulated in severe COVID-19 and post-acute sequelae (PASC). These findings demonstrate that nucleocapsid protein expression alters chromatin structure at specific loci, implicating viral proteins in host genome dysregulation. Furthermore, we identified both shared and unique chromatin targets of SARS-CoV-2 and common cold coronaviruses, highlighting pathways for further investigation and potential therapeutic intervention.
This dataset
Open GSE290042 in finder → Find more human ChIP / ATAC / CUT&Tag 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 GSE290042_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1226091 and SRA study SRP565631. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
48 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 48 sample titles: 48 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

+ 8 more — browse all 48 samples with per-sample file links →

Datasets on a similar topic

Search all human ChIP / ATAC / CUT&Tag datasets in GEO →

Share this dataset

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.