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Systematic investigation reveals extensive Epstein-Barr virus transcriptional regulation of the human genome

GSE303478 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 217 samples Submitted 2026/06/08 Platform GPL24676Platform GPL34284
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 217 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
217 samples: 65 conditions, mostly in triplicateGroups 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
Systematic investigation reveals extensive Epstein-Barr virus transcriptional regulation of the human genomeCell genomics · 2026
Summary (written by the submitters)
We systematically investigate interactions between Epstein-Barr virus (EBV) transcriptional regulators (vTRs) and the human genome. Starting with 16 known and candidate vTRs, we identify nine whose introduction into human cells results in substantial alterations to host gene expression. Genome-scale determination of vTR genomic binding events and alterations to chromatin accessibility reveals a detailed map of EBV's functional interactions with the human genome, including >100,000 vTR binding events impacting almost a quarter of all human genes.
Read the full summary ↓
BMRF1 emerges as a potent regulator, impacting >7,000 genes and altering >37,000 chromatin regions. Our results provide new evidence that EBV RTA interacts with and stabilizes the binding of human RBPJ. Network analysis reveals that many human genes are targeted by multiple EBV vTRs, highlighting the vast coordinated impact of EBV on human gene expression. This study provides a valuable, extensive resource for examining EBV-induced alterations to human gene regulation, with data available on multiple platforms.
Published in
Systematic investigation reveals extensive Epstein-Barr virus transcriptional regulation of the human genome
Dexheimer PJ, Hass MR, Edsall LE et al. · Cell genomics 2026 · PMID 42456663 · doi:10.1016/j.xgen.2026.101303
This dataset
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.

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 GSE303478_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1295495 and SRA study SRP602723. Searching any of these in the dataset finder brings you back here.

Study design
65 conditions, mostly in triplicate
cGFP tagged BMRF1 stable transfection ×6 nGFP tagged EBNA1 stable transfection ×6 nGFP tagged EBNA2 stable transfection ×6 nGFP tagged EBNA3A stable transfection ×6 nGFP tagged EBNA3B stable transfection ×6 nGFP tagged EBNA3C stable transfection ×6 nGFP tagged EBNALP stable transfection (TREx) ×6 cGFP tagged RTA stable transfection ×6 +57 more

Supports a between-group comparison across 217 samples.

How we read this: 65 replicated groups read from 217 sample titles; they account for 217 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

+ 177 more — browse all 217 samples with per-sample file links →

Datasets on a similar topic

Search all human ChIP / ATAC / CUT&Tag 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.