GEO series

Air pollutant multiomics improves functional annotation of SNPs associated with lung disease

GSE327935 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 62 samples Submitted 2026/04/13 Platform GPL24676

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 62 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: 62 samples: 30 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.

Summary (written by the submitters)

Asthma and chronic obstructive pulmonary disease (COPD) are lung diseases strongly influenced by interactions between genetic background and environmental exposures, particularly air pollutants. However, the biological mechanisms by which genetic variation and pollutant exposure impact disease remain poorly understood. Interpretation of genome-wide association studies is limited because most disease-associated variants occur in noncoding regions and are difficult to connect to functional regulatory mechanisms and downstream gene targets.

Read the full summary ↓

Here, we integrate nascent RNA run-on sequencing with regulatory network inference to identify pollutant-responsive transcriptional regulatory elements and their upstream regulators in lung cells. Using newly generated and published datasets, we analyze multiomics responses to multiple air pollutants, including wood smoke particles, urban particulate matter, and Afghan dust particles. These analyses provide the first characterization of the nascent transcriptional response to urban particulate matter in primary lung cells and reveal both shared and pollutant-specific regulatory dynamics. We then integrate pollutant-responsive regulatory networks with genetic associations for asthma and COPD to prioritize noncoding variants for experimental validation. By linking these variants to candidate transcription factors and target genes, we identify mechanisms through which environmental exposures may interact with noncoding genetic variants to influence disease risk. This framework enables functional interpretation of noncoding variants through environmentally responsive transcriptional networks.

This dataset

Open GSE327935 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 GSE327935_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 PRJNA1453030 and SRA study SRP691580. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

30 conditions, mostly in duplicate

Bronchoscopy Brush5, ×4 B2B, TCDD120, ×2 B2B, TCDD30, ×2 Nasal Brush, ×2 NEC14, ALId0, UPM, ×2 NEC14, ALId0, VEH, ×2 NEC14, ALId21, UPM, ×2 NEC14, ALId21, VEH, ×2 +22 more

Supports a between-group comparison across 62 samples.

How we read this: 30 replicated groups read from 62 sample titles; they account for 62 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

GSM9668968 B2B, TCDD120, rep1 B2B, TCDD120,
GSM9668969 B2B, TCDD120, rep2 B2B, TCDD120,
GSM9668970 B2B, TCDD30, rep1 B2B, TCDD30,
GSM9668971 B2B, TCDD30, rep2 B2B, TCDD30,
GSM9668972 Nasal Brush, rep1 Nasal Brush,
GSM9668973 Nasal Brush, rep2 Nasal Brush,
GSM9668974 NEC14, ALId0, UPM, rep1 NEC14, ALId0, UPM,
GSM9668975 NEC14, ALId0, UPM, rep2 NEC14, ALId0, UPM,
GSM9668976 NEC14, ALId0, VEH, rep1 NEC14, ALId0, VEH,
GSM9668977 NEC14, ALId0, VEH, rep2 NEC14, ALId0, VEH,
GSM9668978 NEC14, ALId21, UPM, rep1 NEC14, ALId21, UPM,
GSM9668979 NEC14, ALId21, UPM, rep2 NEC14, ALId21, UPM,
GSM9668980 NEC14, ALId21, VEH, rep1 NEC14, ALId21, VEH,
GSM9668981 NEC14, ALId21, VEH, rep2 NEC14, ALId21, VEH,
GSM9668982 NEC14, ALId7, UPM, rep1 NEC14, ALId7, UPM,
GSM9668983 NEC14, ALId7, UPM, rep2 NEC14, ALId7, UPM,
GSM9668984 NEC14, ALId7, VEH, rep1 NEC14, ALId7, VEH,
GSM9668985 NEC14, ALId7, VEH, rep2 NEC14, ALId7, VEH,
GSM9668986 NEC32, ALId0, UPM, rep1 NEC32, ALId0, UPM,
GSM9668987 NEC32, ALId0, UPM, rep2 NEC32, ALId0, UPM,
GSM9668988 NEC32, ALId0, VEH, rep1 NEC32, ALId0, VEH,
GSM9668989 NEC32, ALId0, VEH, rep2 NEC32, ALId0, VEH,
GSM9668990 NEC32, ALId27, UPM, rep1 NEC32, ALId27, UPM,
GSM9668991 NEC32, ALId27, UPM, rep2 NEC32, ALId27, UPM,
GSM9668992 NEC32, ALId27, VEH, rep1 NEC32, ALId27, VEH,
GSM9668993 NEC32, ALId27, VEH, rep2 NEC32, ALId27, VEH,
GSM9668994 NEC32, ALId7, UPM, rep1 NEC32, ALId7, UPM,
GSM9668995 NEC32, ALId7, UPM, rep2 NEC32, ALId7, UPM,
GSM9668996 NEC32, ALId7, VEH, rep1 NEC32, ALId7, VEH,
GSM9668997 NEC32, ALId7, VEH, rep2 NEC32, ALId7, VEH,
GSM9668998 Sm25, submerged, WSP120, rep1 Sm25, submerged, WSP120,
GSM9668999 Sm25, submerged, WSP120, rep2 Sm25, submerged, WSP120,
GSM9669000 Sm25, submerged, WSP30, rep1 Sm25, submerged, WSP30,
GSM9669001 Sm25, submerged, WSP30, rep2 Sm25, submerged, WSP30,
GSM9669002 Sm36, submerged, WSP120, rep1 Sm36, submerged, WSP120,
GSM9669003 Sm36, submerged, WSP120, rep2 Sm36, submerged, WSP120,
GSM9669004 Sm36, submerged, WSP30, rep1 Sm36, submerged, WSP30,
GSM9669005 Sm36, submerged, WSP30, rep2 Sm36, submerged, WSP30,
GSM9669006 Sm36, ALId0, TCDD120, rep1 Sm36, ALId0, TCDD120,
GSM9669007 Sm36, ALId0, TCDD120, rep2 Sm36, ALId0, TCDD120,

+ 22 more — browse all 62 samples with per-sample file links →

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