Foundry120 atlas

← IBD single-cell transcriptomics

IBDverse multitissue atlasing cohort

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Dataset overview

Participants 421
Samples 732
Reuse readiness 8.9/10 evidence-backed score

Cell-type-resolved genetic variation shapes inflammatory bowel disease risk.

Alegbe T, Harris BT, Fachal L, Ramirez-Navarro L, Tutert M, Krzak M, Ghouraba M, Strickland M, et al. · Nature · 2026

Abstract

Most genetic variants associated with complex diseases lie in non-coding regions<sup>1</sup>, complicating efforts to identify effector genes and relevant cell types. Here we map cis-expression quantitative trait loci (eQTLs) across 2.2 million single cells using intestinal biopsies and blood from 421 individuals, including 125 with inflammatory bowel disease (IBD). Cell-type-level eQTLs were more distal to transcription start sites, enriched in enhancers, less likely to regulate the nearest gene, and more than 3.5-fold more likely to colocalize with IBD loci detected in genome-wide association studies (GWASs) than eQTLs detected at tissue-level resolution. We nominate effector genes at more than half of known IBD loci, including MAML2, PSEN2 and ZMIZ1 in myeloid cells, implicating reduced Notch signalling in intestinal immune dysfunction. We also identify Wnt-regulated genes, including MYC, in epithelial stem and progenitor cells, suggesting that impaired renewal contributes to barrier breakdown. Our results provide a mechanistic map that links genetic risk to specific genes and cell types in IBD, and a generalized framework for interpretation of GWAS loci using single-cell eQTL mapping of disease-relevant tissues in complex diseases.

doi:10.1038/s41586-026-10627-z ↗ PMID 42236949 ↗ PMC13441992 ↗

Study facts

Organism
Homo sapiens
Platform
10x Genomics Chromium
Age group
adult
Disease groups
—
Anatomical sites
blood, ileum, rectum

Data availability

  • Processed matrix
  • Analysis code

File types H5AD

Strengths & limitations for reuse

Strengths

  • Raw reads are advertised
  • Processed matrices are advertised
  • Cell metadata are advertised
  • Analysis code is available
  • Participant counts are documented

Limitations

  • Not documented: raw counts are advertised
Extraction evidence & provenance

Each extracted field is shown with the source excerpt and location used to resolve it.

Assay

FieldValueEvidence
assay.assay_type 10x 3' v3 from source
assay=10x 3' v3

Section structured repository metadata, offset —
assay.library_chemistry 10x 3' v3 from source
"assay": [{"label": "10x 3' v3", "ontology_term_id": "EFO:0009922"}]

Section dataset, offset —
assay.platform 10x Genomics Chromium
scRNA-seq was performed using 3′ 10X Genomics Chromium kits (v3.0 and v3.1)

Section Methods — Patient recruitment and single-cell sequencing, offset —
assay.reference_genome GRCh38 with Ensembl v93 transcript definitions
CellRanger (v7.2.0) was used to align reads to the GRCh38 human genome reference with Ensembl v93 transcript definitions

Section Methods — Patient recruitment and single-cell sequencing, offset —
assay.sequencing_type scrna_seq from source
sequencing_type=scrna_seq

Section structured repository metadata, offset —

Cohort

FieldValueEvidence
cohort.age_group adult inferred
"development_stage": [{"label": "60-79 year-old stage"}, {"label": "adult stage"}, {"label": "middle aged stage"}, {"label": "prime adult stage"}, {"label": "young adult stage"}]

Section dataset, offset —
cohort.crohns_disease_participants 125
296 individuals without IBD and 125 individuals with CD were recruited

Section Methods — Patient recruitment and single-cell sequencing, offset —
cohort.disease_activity_metadata_available True
Ileal biopsies from patients with CD included both inflamed and uninflamed tissue.

Section Methods — Patient recruitment and single-cell sequencing, offset —
cohort.non_ibd_controls 296
296 individuals without IBD and 125 individuals with CD were recruited

Section Methods — Patient recruitment and single-cell sequencing, offset —
cohort.total_participants 421
296 individuals without IBD and 125 individuals with CD were recruited

Section Methods — Patient recruitment and single-cell sequencing, offset —

Data_Assets

FieldValueEvidence
data_assets.analysis_code True
Code used to perform all analyses is available at https://github.com/andersonlab/IBDVerse-sc-eQTL-code

Section Code availability, offset —
data_assets.cell_metadata True from source
CELLxGENE dataset exposes cell metadata

Section structured repository metadata, offset —
data_assets.open_access True from source
public CELLxGENE dataset

Section structured repository metadata, offset —
data_assets.participant_metadata True from source
"donor_id": ["IBDverse-1-FB0463BF47ACA3", "IBDverse-1-C3245D4242DB7A", "IBDverse-1-2A825F3279742E"]

Section dataset, offset —
data_assets.processed_matrix True from source
CELLxGENE dataset exposes H5AD

Section structured repository metadata, offset —
data_assets.raw_reads True from source
"link_name": "EGAD00001015692", "link_type": "RAW_DATA"

Section dataset links, offset —

Processing

FieldValueEvidence
processing.ambient_rna_correction_reported True
corrected for ambient RNA using CellBender v2.1

Section Single-cell RNA-sequencing quality control and cell clustering, offset —
processing.batch_correction_reported True
Data were integrated using the scVI v0.16.3 function scvi.model.SCVI

Section Single-cell RNA-sequencing quality control and cell clustering, offset —
processing.cell_type_annotation_method CellTypist model trained on the atlasing dataset with expert manual annotation
a CellTypist v1.6.2 model was trained on the atlasing dataset

Section Single-cell RNA-sequencing quality control and cell clustering, offset —
processing.normalization_method Library-size normalization to 10,000 counts per cell followed by log1p transformation
normalizing to library sizes of 10,000 total counts using the function sc.pp.normalise_per_cell and log transformation using sc.pp.log1p

Section Single-cell RNA-sequencing quality control and cell clustering, offset —
processing.quality_control_reported True
A lineage-sensitive, relative quality control strategy was applied

Section Single-cell RNA-sequencing quality control and cell clustering, offset —

Specimens

FieldValueEvidence
specimens.anatomical_sites ['blood', 'ileum', 'rectum'] from source
tissues=blood, ileum, rectum

Section structured repository metadata, offset —
specimens.inflamed_status_available True
Ileal biopsies from patients with CD included both inflamed and uninflamed tissue.

Section Methods — Patient recruitment and single-cell sequencing, offset —
specimens.number_of_cells 1852681 from source
cell_count=1852681

Section structured repository metadata, offset —
specimens.number_of_samples 732 inferred
275 healthy rectal biopsies, 119 CD terminal ileal biopsies, 243 healthy terminal ileal biopsies and 95 blood samples

Section A cellular atlas of intestine and blood, offset —
specimens.specimen_type mixed inferred
During routine endoscopy, gastrointestinal biopsies were collected from the rectum and terminal ileum, and blood samples were drawn after the procedure.

Section Methods — Patient recruitment and single-cell sequencing, offset —