← BioTransfer GEO Dataset Finder
GEO series

Germinal Center Cytokines Driven Epigenetic Control of Epstein-Barr Virus Latency Gene Expression

GSE252480 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2024/04/17 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 18 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
18 samples: 6 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
Germinal center cytokine driven epigenetic control of Epstein-Barr virus latency gene expressionPLoS pathogens · 2024
Summary (written by the submitters)
Epstein-Barr virus (EBV) persistently infects 95% of adults worldwide and is associated with multiple human lymphomas that express characteristic EBV latency programs used by the virus to navigate the B-cell compartment. Upon primary infection, the EBV latency III program, comprised of six Epstein-Barr Nuclear Antigens (EBNA) and two Latent Membrane Protein (LMP) antigens, drives infected B-cells into germinal center (GC).
Read the full summary ↓
By incompletely understood mechanisms, GC microenvironmental cues trigger the EBV genome to switch to the latency II program, comprised of EBNA1, LMP1 and LMP2A and observed in GC-derived Hodgkin lymphoma. To gain insights into pathways and epigenetic mechanisms that control EBV latency reprogramming as EBV-infected B-cells encounter microenvironmental cues, we characterized GC cytokine effects on EBV latency protein expression and on the EBV epigenome. We confirmed and extended prior studies highlighting GC cytokine effects in support of the latency II transition. The T-follicular helper cytokine interleukin 21 (IL-21), which is a major regulator of GC responses, and to a lesser extent IL-4 and IL-10, hyper-induced LMP1 expression, while repressing EBNA expression. However, follicular dendritic cell cytokines including IL-15 and IL-27 downmodulate EBNA but not LMP1 expression. CRISPR editing highlighted that STAT3 and STAT5 were necessary for cytokine mediated EBNA silencing via epigenetic effects at the EBV genomic C promoter. By contrast, STAT3 was instead necessary for LMP1 promoter epigenetic remodeling, including gain of activating histone chromatin marks and loss of repressive polycomb repressive complex silencing marks. Thus, EBV has evolved to coopt STAT signaling to oppositely regulate the epigenetic status of key viral genomic promoters in response to GC cytokine cues.
Published in
Germinal center cytokine driven epigenetic control of Epstein-Barr virus latency gene expression
Liao Y, Yan J, Beri NR et al. · PLoS pathogens 2024 · PMID 38683861 · doi:10.1371/journal.ppat.1011939
This dataset
Open GSE252480 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 GSE252480_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 PRJNA1060715 and SRA study SRP481147. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38683861) ↗
Study design
6 conditions, mostly in triplicate
MutuI_Ctrl_Day1 ×3 MutuI_IL4-CD40L_Day1 ×3 MutuI_IL21_Day1 ×3 GM_Ctrl_Day6 ×3 GM_IL15_Day6 ×3 GM_IL21_Day6 ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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
Datasets on a similar topic

Search all human RNA-seq 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.