GEO series

[RelA ChIP-seq]: Characterization of transcriptional and chromatin accessibility landscape of human bronchial epithelial cells treated with synergistic immunostimulatory ligands.

GSE299702 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 13 samples Submitted 2025/06/15 Platform GPL18573

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 13 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: 13 samples: 13 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: cJun-assisted loading of RelA DNA-binding promotes synergistic lung epithelial antimicrobial responsesiScience · 2026

Summary (written by the submitters)

Lower respiratory tract infections remain a leading cause of death worldwide. The increasing prevalence of antibiotic-resistant respiratory pathogens has been a key driver of efforts to develop host-directed therapies that protect patients against pneumonia. Our laboratory has previously reported discovery of an immunostimulatory therapeutic comprised of a synthetic diacetylated lipopeptide, Pam2CSK4 (Pam2), and a class C CpG oligodeoxynucleotide, ODN M362 (ODN).

Read the full summary ↓

When delivered by inhalation, this dyad protects synergistically against pneumonias caused by Gram-positive and -negative bacteria, seasonal and pandemic viruses, and multiple fungi. Protection is achieved by manipulating the immune defense response from lung epithelial cells. Here, we dissect the lung epithelial transcriptional response to explain the observed synergistic signaling, using RNA-seq and dual transcription factor ChIP-seq. We find cooperation of RelA and cJun following Pam2+ODN treatment that synergistically confers broad inducible resistance against respiratory pathogens. Specifically, transcription factor binding site (TFBS) analysis revealed that cJun occupancy at promoter regions of Pam2+ODN-induced genes facilitated increased RelA occupancy during differential expression, demonstrating cJUN-assisted loading of RelA as a key mechanism of the synergistic signaling events. Increased or decreased RelA occupancy at promoter sites dictated gene up- or down-regulation, respectively, while increased or decreased cJun occupancy at promoter sites directed synergistic or antagonistic gene expression patterns. Together, RelA and cJun work at promoter regions to control directionality and magnitude of gene expression after Pam2+ODN stimulation, rapidly reprograming the lung epithelial transcriptome to combat respiratory infections.

Published in

cJun-assisted loading of RelA DNA-binding promotes synergistic lung epithelial antimicrobial responses

Pantaleón García J, Bhoda K, Burch-Eapen M et al. · iScience 2026 · PMID 42063563 · doi:10.1016/j.isci.2026.115592

This dataset

Open GSE299702 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 GSE299702_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 PRJNA1276097 and SRA study SRP591719. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42063563) ↗

Study design

13 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 13 sample titles: 13 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

GSM9044244 00_Pooled_Input_0
GSM9044245 01_ID-57-PBS_RelA_1
GSM9044246 02_ID-58-PBS_RelA_2
GSM9044247 03_ID-59-PBS_RelA_3
GSM9044248 04_ID-64-PAM2_RelA_1
GSM9044249 05_ID-65-PAM2_RelA_2
GSM9044250 06_ID-66-PAM2_RelA_3
GSM9044251 07_ID-71-ODN_RelA_1
GSM9044252 08_ID-72-ODN_RelA_2
GSM9044253 09_ID-73-ODN_RelA_3
GSM9044254 10_ID-78-PAM2-ODN_RelA_1
GSM9044255 11_ID-79-PAM2-ODN_RelA_2
GSM9044256 12_ID-80-PAM2-ODN_RelA_3

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