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Cell and state-specific eQTL analysis in human endometrial mesenchymal cells uncovers candidate susceptibility genes for reproductive diseases and traits

GSE251756 Homo sapiens (human) Single-cell RNA-seq 59 samples Submitted 2024/09/01 Platform GPL20301
At a glance

Single-cell RNA-seq · human · 59 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
59 samples: 59 × Endometrial stromal cells from ESCGroups 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)
The functional consequence of genetic variants and how they contribute to disease remains elusive. Studying genetic variants in disease-relevant cells captures variations in effects in cell types and states. The endometrium is a heterogenic tissue with critical reproduction roles considered complex genetic traits. We assessed the association between genetic variants and gene expression in purified endometrial mesenchymal cells using both bulk and single-cell RNA-sequencing data from patients with endometria-driven reproductive disorders.
Read the full summary ↓
We compared these to those identified in whole endometrium and to reproductive disease-associated genetic loci. We identified cis-eQTLs for 947 unique eGenes in isolated endometrial mesenchymal cells of which 50% had not previously been identified in whole endometrium. Single-cell RNA-sequencing data stratifying by differentiation state we found a further 25 and 26 unique eGenes in stem and mature mesenchymal cells respectively. Comparison with reproductive disease-associated variants identified overlaps with COG6 and AC012313.10 with age of menarche and HELB with age of menopause. Summary Mendelian Randomisation (SMR) identified potential causal effects of RPS2 on age of menarche and KANSLI on age at first birth, as well as a mesenchymal stem cell state-specific influence of GATD3A on uterine fibroid formation. Identifying functional consequences of genetic variants critical to disease can be enhanced with disease-relevant, purified cells. We provide evidence for critical roles for COG6 and HELB in age-related traits of reproduction and a causal role for GATD3A on uterine fibroid formation during early cell development supporting that genetic influences on early stem cell state and subsequent differentiation can contribute to disease pathology.
This dataset
Open GSE251756 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 GSE251756_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 PRJNA1055169 and SRA study SRP479273. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
59 × Endometrial stromal cells from ESC

Supports a between-group comparison across 59 samples.

How we read this: 1 replicated groups read from 59 sample titles; they account for 59 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

+ 19 more — browse all 59 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.