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Lookup NU author(s): Dr Laura JardineORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© The Author(s) 2026.Children with Down syndrome have a 150-fold increased risk of developing myeloid leukaemia (ML-DS). Unusually for a childhood leukaemia, ML-DS arises from a preleukaemic state, termed transient abnormal myelopoiesis (TAM), via a conserved sequence of mutations. Here, we examine the relationship between the genetic and transcriptional evolution of ML-DS from natural variation; a rich collection of primary patient samples and foetal tissues with a range of constitutional karyotypes. We distil transcriptional consequences of each genetic step in ML-DS evolution, utilising single-cell mRNA sequencing, complemented by phylogenetic analyses in progressive disease. We find that transcriptional changes induced by the TAM-defining GATA1 mutations are retained in, and account for most of the ML-DS transcriptome. The GATA1 transcriptome pervades all stages of ML-DS, including progressive disease that had undergone genetic evolution. Our approach delineates the transcriptional evolution of ML-DS and provides an analytical blueprint for distiling consequences of mutations within their pathophysiological context.
Author(s): Trinh MK, Schuschel K, Issa H, Thomas R, Parks C, Oszlanczi A, Ogbonnah T, Zhou D, Mamanova L, Prigmore E, Robertson ER, Hodder A, Wenger A, Anderson ND, Whitfield HJ, Treger TD, Goncalves-Dias J, Straathof K, O'Connor D, Young MD, Jardine L, Adams S, Klusmann J-H, Bartram J, Behjati S
Publication type: Article
Publication status: Published
Journal: Nature Communications
Year: 2026
Volume: 17
Issue: 1
Print publication date: 23/04/2026
Online publication date: 23/04/2026
Acceptance date: 27/03/2026
Date deposited: 07/05/2026
ISSN (electronic): 2041-1723
Publisher: Nature Research
URL: https://doi.org/10.1038/s41467-026-71707-2
DOI: 10.1038/s41467-026-71707-2
Data Access Statement: WGS and single-cell mRNA sequencing data has been deposited in the European Genome-Phenome Archive (EGA) under the accession codes EGAD00001015453 (WGS; https://ega-archive.org/datasets/EGAD00001015453) and EGAD00001015452 (scRNA-seq; https://ega-archive.org/datasets/EGAD00001015452). Processed counts for bulk transcriptomic data are available as Supplementary Data 9; the corresponding raw sequencing data are available through the Zenodo repository at https://doi.org/10.5281/zenodo.19046231. Published foetal liver (Popescu, D-M. et al., 201910) and foetal bone marrow (Jardine, L. et al., 202111) datasets data were downloaded from https://developmental.cellatlas.io. Source data are provided with this paper. All code used to reproduce the analysis and figures described in this manuscript is available at https://github.com/miktrinh/ML-DS.
PubMed id: 42026063
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