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Endogenous fine-mapping of functional regulatory elements in complex genetic loci in HAP1 [scRNA-seq]

GSE285461 Homo sapiens (human) Single-cell RNA-seq 18 samples Submitted 2024/12/31 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 18 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
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
Endogenous fine-mapping and prioritization of functional regulatory elements in complex genetic lociCell genomics · 2025
Summary (written by the submitters)
The majority of genetic loci linked to polygenic complex traits are found in non-coding regions of the human genome. These loci often exhibit complex gene regulatory relationships and linkage disequilibrium (LD) configurations, making it challenging to accurately identify causal variants and their target genes. We used multiplexed single-cell CRISPR interference and activation perturbations to investigate cis-regulatory element (CRE) and target gene expression relationships within tight LD in the endogenous chromatin context.
Read the full summary ↓
We demonstrated the prevalence of multiple causality in perfect LD (pLD) for independent expression quantitative trait locus (eQTL) and uncovered fine-grained genetic effects on gene expression within pLD, which are difficult to decipher using traditional eQTL fine-mapping or existing computational methods. We found that over one third of the causal CREs lack classical epigenetic markers, and we functionally validated one of these hidden regulatory mechanisms. Leveraging Multiome single-cell epigenetic and sequence perturbations, we highlighted the regulatory plasticity of the human genome. Our study will guide the exploration of missing causal mechanisms in molecular trait formation and disease development.
Published in
Endogenous fine-mapping and prioritization of functional regulatory elements in complex genetic loci
Zhao K, Zhou Y, Wang X et al. · Cell genomics 2025 · PMID 40882622 · doi:10.1016/j.xgen.2025.100982
This dataset
Open GSE285461 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 GSE285461_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 PRJNA1203673 and SRA study SRP554139. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40882622) ↗
Study design
6 conditions, mostly in triplicate
CRISPRi, transcriptomes scRNA-seq, ×3 CRISPRko, transcriptomes scRNA-seq, ×3 CRISPRa, transcriptomes scRNA-seq, ×3 CRISPRa, sgRNA enrichment scRNA-seq, ×3 CRISPRko, sgRNA enrichment scRNA-seq, ×3 CRISPRi, sgRNA enrichment scRNA-seq, ×2 CRISPRi, sgRNA enrichment scRNA-seq, ×1

Supports a between-group comparison across 17 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 17 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

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