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Disease-associated loci share features with loci that regulate gene expression in response to environmental perturbations

GSE292909 Homo sapiens (human) Single-cell RNA-seq 47 samples Submitted 2025/06/24 Platform GPL34281
At a glance

Single-cell RNA-seq · human · 47 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
47 samples: 14 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
Disease-associated loci share properties with response eQTLs under common environmental exposuresResearch square · 2025
Summary (written by the submitters)
Many of the genetic loci associated with disease are expected to have context-dependent regulatory effects that are underrepresented in the transcriptomes of healthy, steady-state adult tissues. To understand genetic gene regulation across diverse environmental conditions and cellular contexts, we perturbed a broad array of human cell types with three environmental exposures in vitro.
Read the full summary ↓
With single-cell RNA-sequencing data from 1.4 million cells, we identified hundreds of dynamic eQTLs that regulate molecular responses to perturbation across multiple cellular contexts. These response eQTLs exhibit distinct signatures of regulatory complexity, evolutionary constraint, and functional enrichment that distinguish them from standard, steady- state eQTLs. Similar to GWAS loci, response eQTLs are enriched in distal enhancers and are linked to genes that experienced strong selective constraint, involve in complex regulatory landscapes, and diverse biological functions. We also observed that response eQTLs are more likely than standard eQTLs to colocalize with loci that affect complex traits. Our results highlight the complexity of genetic regulatory effects and suggest that our ability to interpret disease-associated loci may benefit from the pursuit of studies of gene-by-environment interactions in diverse biological contexts.
Published in
Disease-associated loci share properties with response eQTLs under common environmental exposures
Lin W, Li M, Allen O et al. · Research square 2025 · PMID 40470191 · doi:10.21203/rs.3.rs-6561377/v1
This dataset
Open GSE292909 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 GSE292909_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1241846 and SRA study SRP573116. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40470191) ↗
Study design
14 conditions, mostly in triplicate
batch4nicotine-1_S ×4 batch4nicotine-2_S ×4 batch4caffeine-1_S ×4 batch4caffeine-2_S ×4 batch4etoh-1_S ×4 batch4etoh-2_S ×4 batch3control-1_S ×3 batch3control-2_S ×3 +6 more

Supports a between-group comparison across 47 samples.

How we read this: 14 replicated groups read from 47 sample titles; they account for 47 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

+ 7 more — browse all 47 samples with per-sample file links →

Datasets on a similar topic

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