GEO series

Cell Type Differences in Human Cytomegalovirus Transcription and Epigenetic Regulation with Insights into Major Immediate-Early Enhancer-Promoter Control [RNA-seq]

GSE291635 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/07/22 Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 12 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: 12 samples: 6 conditions, mostly in duplicateGroups 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: Cell type differences in human cytomegalovirus transcription and epigenetic regulation with insights into major immediate-early enhancer-promoter controlPLoS pathogens · 2025

Summary (written by the submitters)

Cell type differences in the human cytomegalovirus (HCMV) transcriptome may result from variations in transcription and/or post-transcription. Here we report unexpected differences in transcription and epigenetic control in late-stage HCMV infection of human differentiated NTera2 cells (D-NT2) compared to fibroblasts, using integrated functional genomic approaches (PRO-Seq, RNA-Seq, DFF ChIP-Seq, rapid viral protein degradation, and promoter mutation and function assays).

Read the full summary ↓

In D-NT2, but not fibroblasts, RNA polymerase II initiation and elongation at several viral promoters requires viral DNA synthesis and are independent of host P-TEFb, viral IE2, or viral UL87 late transcription factor (LTF). This includes transcription from the enhancer for the major immediate early (MIE) promoter where GC-box sequence mutations increase transcription and mutations in CREB and NF-kB response elements decrease transcription. The GC-box sequence mutations also alter infected cell morphology and gene expression program, whereas mutations in CREB and NF-kB response elements do not. In D-NT2, LTF-driven promoters constitute a smaller proportion of the viral late promoter population and are generally less active. Additionally, viral genomes have more nucleosomes, potentially restricting LTF access. A TBP-IE2-nucleosome complex, with more nucleosome than in fibroblasts, covers the MIE promoter transcription start site, potentially contributing to epigenetically silence of the promoter.

Published in

Cell type differences in human cytomegalovirus transcription and epigenetic regulation with insights into major immediate-early enhancer-promoter control

Hu Q, Li M, Parida M et al. · PLoS pathogens 2025 · PMID 40758707 · doi:10.1371/journal.ppat.1013374

This dataset

Open GSE291635 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 GSE291635_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 PRJNA1234556 and SRA study SRP569585. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40758707) ↗

Study design

6 conditions, mostly in duplicate

RNA-Seq Mock ×2 RNA-Seq WT ×2 RNA-Seq WT PFA ×2 RNA-Seq N1 ×2 RNA-Seq NB ×2 RNA-Seq CK ×2

Supports a between-group comparison across 12 samples.

How we read this: 6 replicated groups read from 12 sample titles; they account for 12 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

GSM8839068 RNA-Seq Mock Rep1 RNA-Seq Mock
GSM8839069 RNA-Seq Mock Rep2 RNA-Seq Mock
GSM8839070 RNA-Seq WT Rep1 RNA-Seq WT
GSM8839071 RNA-Seq WT Rep2 RNA-Seq WT
GSM8839072 RNA-Seq WT PFA Rep1 RNA-Seq WT PFA
GSM8839073 RNA-Seq WT PFA Rep2 RNA-Seq WT PFA
GSM8839074 RNA-Seq N1 Rep1 RNA-Seq N1
GSM8839075 RNA-Seq N1 Rep2 RNA-Seq N1
GSM8839076 RNA-Seq NB Rep1 RNA-Seq NB
GSM8839077 RNA-Seq NB Rep2 RNA-Seq NB
GSM8839078 RNA-Seq CK Rep1 RNA-Seq CK
GSM8839079 RNA-Seq CK Rep2 RNA-Seq CK

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