GEO series

Remodeling of the chromatin landscape in peripheral blood cells in patients with severe Delta COVID-19

GSE282769 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 39 samples Submitted 2024/11/26 Platform GPL24676Platform GPL30173

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 39 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: 39 samples: 39 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.
Paper: Remodeling of the chromatin landscape in peripheral blood cells in patients with severe Delta COVID-19Frontiers in immunology · 2024

Summary (written by the submitters)

COVID-19 is characterized by systemic proinflammatory shifts with development of serious alterations in the functioning of the immune system. Investigations of the gene expression changes accompanying infection state provide insight towards understanding of the molecular and cellular processes depending on the sickness severity and virus variant.

Read the full summary ↓

Severe Delta COVID-19 have been characterized by the appearance of the monocyte subset enriched for the proinflammatory gene expression signatures and shift of the ligand-receptor interactions. We profiled the chromatin accessibility landscape of 140,000 nuclei of the PBMC samples from healthy people or individuals with COVID-19. We investigated cis-regulatory elements and identified core transcription factors governing the gene expression state in immune cells during COVID-19. For the severe cases we discovered that regulome and chromatin co-accessibility modules significantly altered across many cell types. Moreover, cases with the Delta variant are accompanied by specific monocyte subtype discovered with the scATAC-seq data. From our analysis follows that immune cells of individuals with severe Delta COVID-19 undergo significant remodeling of the chromatin accessibility landscape and development of the proinflammatory expression pattern. With a gene regulatory network modeling approach we investigated core transcription factors governing cell state and identified the most pronounced chromatin changes in CD14+ monocytes from individuals with severe Delta COVID-19. Together, our results provide novel insight into the cis-regulatory module organization and their impact on gene activity in immune cells during SARS-CoV-2 infection.

Published in

Remodeling of the chromatin landscape in peripheral blood cells in patients with severe Delta COVID-19

Akimov VE, Tychinin DI, Antonova OA et al. · Frontiers in immunology 2024 · PMID 39712003 · doi:10.3389/fimmu.2024.1415317

This dataset

Open GSE282769 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 GSE282769_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 PRJNA1190389 and SRA study SRP547454. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39712003) ↗

Study design

39 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 39 sample titles: 39 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

GSM8650243 108
GSM8650244 109
GSM8650245 110
GSM8650246 111
GSM8650247 113
GSM8650248 114
GSM8650249 115
GSM8650250 134
GSM8650251 144
GSM8650252 147
GSM8650253 148
GSM8650254 151
GSM8650255 165
GSM8650256 166
GSM8650257 167
GSM8650258 170
GSM8650259 172
GSM8650260 207
GSM8650261 208
GSM8650262 210
GSM8650263 212
GSM8650264 215
GSM8650265 218
GSM8650266 245
GSM8650267 413
GSM8650268 414
GSM8650269 415
GSM8650270 416
GSM8650271 417
GSM8650272 418
GSM8650273 419
GSM8650274 562
GSM8650275 563
GSM8650276 564
GSM8650277 567
GSM8650278 574
GSM8650279 67
GSM8650280 68
GSM8650281 69

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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.