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Single-cell transcriptomic atlas of the human fetal uveal tract reveals heterogeneity in melanocyte populations.

Overview

Authors: James Draper1, Ian R Reekie2, Lakshanie Wickramasinghe2, Srilakshmi Sharma2, Mark Coles2, Andrew D Dick3,4,5, Christopher Buckley2, Helen Kalirai1, Sarah E Coupland1
ORCID iDs: James Draper
  1. Department of Eye and Vision Science, Institute of Life Course and Medical Science, University of Liverpool, Liverpool, UK
  2. Kennedy Institute of Rheumatology, University of Oxford, Oxford, UK
  3. Institute of Ophthalmology, University College London, London, UK
  4. School of Cellular and Molecular Medicine, University of Bristol, Bristol, UK
  5. NIHR Biomedical Research Centre, Moorfields Eye Hospital, London, UK
Institutions: University of Liverpool (United Kingdom); University of Oxford (United Kingdom); Kennedy Institute of Rheumatology (United Kingdom); University of Bristol (United Kingdom); NIHR Moorfields Biomedical Research Centre (United Kingdom); Moorfields Eye Hospital (United Kingdom); University College London (United Kingdom)
Journal: iScience, volume 29, issue 10, article 117510
Dates: received 26 March 2026; accepted 27 August 2026; published online 12 September 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1016/j.isci.2026.117510 · PMID 42765034 · PMCID PMC13590050 · OpenAlex W7212362719
Open access: gold, a free copy (OpenAlex)
Status: code on request
Categories: genetics / omics (modality), human (organism), developmental (subfield)
Methods: Statistics, Smoothing, state filtering, decompositions, Preprocessing, Connectivity, Machine learning
Keywords: single-cell RNA sequencing, uveal tract, melanocyte heterogeneity, human fetal development, uveal melanoma, neural crest, cell-cell communication, choroid, transcriptomics, ocular development
Topic: Single-cell and spatial transcriptomics (Molecular Biology, Biochemistry, Genetics and Molecular Biology), according to OpenAlex
Funding: Kennedy Memorial Trust
Citations: not cited yet (Europe PMC); 64 references in the paper
Research resources: Anti-CD31 Clone JC70A Mouse Monoclonal RRID:AB_2114471, Anti-MITF Clone D5 Mouse Monoclonal RRID:AB_2142100, Anti-NR2F1 Rabbit Polyclonal RRID:AB_2879616, RRID:AB_2895675, RRID:AB_2916124, RStudio RRID:SCR_000432, Seurat R Package (v.5.3.0) RRID:SCR_007322, MSigDB Hallmark Gene Sets (v2024.1) RRID:SCR_016863, clusterProfilier R package (v.4.12.6) RRID:SCR_016884, Cell Ranger Pipeline (v7.0) RRID:SCR_017344, QuPath Software (v0.6.0) RRID:SCR_018257, Akoya inForm Software (v3.0.0) RRID:SCR_019155

Abstract

Uveal melanocytes are neural crest-derived cells contributing to ocular pigmentation, yet their developmental heterogeneity and microenvironmental roles remain poorly characterized. We present a single-cell transcriptomic atlas of the human fetal uveal tract, profiling 81,603 cells across 14 cell types from eight eyes at 12 and 20 post-conception weeks. Among 5,142 melanocytes, we identify four subpopulations, including a transcriptionally unique cluster enriched in posterior uveal tissue at later developmental stages. This population expresses NR2F1, FOXC1, and PITX2 alongside extracellular matrix and angiogenic genes and is predicted to communicate with Schwann cells, endothelial cells, and immune populations to modulate the uveal microenvironment. Multiplex immunofluorescence confirms MITF+/FOXC1+ co-expressing cells in fetal choroidal tissue, validating this population in situ. A refined gene signature from this cluster associates with high-metastatic risk across three independent uveal melanoma cohorts and is enriched in aggressive tumor cell states in single-cell data, implicating developmental program reactivation in disease progression.

Reproduced under the paper's license (CC BY), from the paper cited above.

Code

The paper says that its authors' code is available on request: it was not published with the paper, so there is nothing to verify.

The paper's code and data availability statement is in the Data section.

Tracing map

A tracing map links a paper to the code its authors published: this paper has none (its code is available on request), so it has no map.

Data

Datasets cited

Data and code availability

Single-cell RNA sequencing data reported in this paper, including raw FASTQ files and processed count matrices, have been deposited at NCBI’s Gene Expression Omnibus (GEO) and are publicly available as of the date of publication under accession number GEO: GSE325954 (https://ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE325954). TCGA-UVM data were accessed through the NCI Genomic Data Commons and are publicly available. External validation datasets GSE22138 (https://ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE22138) and GSE84976 (https://ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE84976) are publicly available through NCBI GEO. The Durante et al. uveal melanoma single-cell dataset is publicly available through NCBI GEO under accession number GEO: GSE139829 (https://ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE139829). All accession numbers are listed in the key resources table.

This paper does not report original code.

Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 3, 28 September 2026

  • Authors: added James Draper (0000-0002-6187-4567); removed James Draper
  • Funding: added Kennedy Memorial Trust

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 9 authors, 10 keywords, 63 references, 12 RRIDs.

Cite

This paper

Draper, J., Reekie, I. R., Wickramasinghe, L., Sharma, S., Coles, M., Dick, A. D., Buckley, C., Kalirai, H., & Coupland, S. E. (2026). Single-cell transcriptomic atlas of the human fetal uveal tract reveals heterogeneity in melanocyte populations. iScience, 29(10), 117510. https://doi.org/10.1016/j.isci.2026.117510

BibTeX

@article{draper2026single,
author = {Draper, James and Reekie, Ian R and Wickramasinghe, Lakshanie and Sharma, Srilakshmi and Coles, Mark and Dick, Andrew D and Buckley, Christopher and Kalirai, Helen and Coupland, Sarah E},
title = {{Single-cell transcriptomic atlas of the human fetal uveal tract reveals heterogeneity in melanocyte populations}},
journal = {iScience},
year = {2026},
month = sep,
volume = {29},
number = {10},
pages = {117510},
publisher = {Elsevier},
issn = {2589-0042},
doi = {10.1016/j.isci.2026.117510},
url = {https://doi.org/10.1016/j.isci.2026.117510},
pmid = {42765034},
pmcid = {PMC13590050}
}

RIS

TY - JOUR
AU - Draper, James
AU - Reekie, Ian R
AU - Wickramasinghe, Lakshanie
AU - Sharma, Srilakshmi
AU - Coles, Mark
AU - Dick, Andrew D
AU - Buckley, Christopher
AU - Kalirai, Helen
AU - Coupland, Sarah E
TI - Single-cell transcriptomic atlas of the human fetal uveal tract reveals heterogeneity in melanocyte populations
T2 - iScience
J2 - iScience
PY - 2026
DA - 2026/09/12
VL - 29
IS - 10
SP - 117510
SN - 2589-0042
PB - Elsevier
DO - 10.1016/j.isci.2026.117510
UR - https://doi.org/10.1016/j.isci.2026.117510
LA - en
ER -

CSL-JSON

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