Oral Presentation GENEMAPPERS 2026

Population scale single-cell multi-omic analysis of clonal haematopoiesis (#41)

Zhen Qiao 1 2 , Oscar A. Dong 3 4 , Peter C. Allen 2 3 , Jayden Fan 3 5 , Michael Geaghan 6 , Hao Huang 2 3 7 , Giulio Genovese 8 9 10 , Yves Fontaine 11 , Chi Tian 12 , Blake Bowen 2 3 , Hope A. Tanudisastro 2 5 13 14 , Anna S.E. Cuomo 2 3 7 13 14 , Albert Henry 2 3 , Drew Neavin 2 3 , Shannon Ji 11 , Anne Senabouth 2 3 , Michael Harper 2 13 14 , Zhili Zheng 8 15 , Etienne Masle-Farquhar 2 3 , Eleanor Spenceley 2 3 , Eszter Sagi-Zsigmond 3 , Caitlin Bartie 3 , Agota Tuzesi 3 , Julia Forkgen 2 11 , Michael Silk 2 13 14 , Matthew Hobbs 6 , Joseph Copty 6 , Matt A. Field 6 16 , Andrew D Calcino 16 , Caitlin Uren 2 13 14 , Hannah R Nicholas 13 14 , Kristof Wing 17 18 19 , Owen Tang 20 21 , Michael Gray 20 21 , Yuantian Zhang 22 , Boxiang Liu 22 23 24 , Katrina M. de Lange 13 14 , Alex W. Hewitt 17 18 19 , Gemma Figtree 5 20 21 , Angli Xue 2 3 , Daniel MacArthur 2 13 14 , Joseph E. Powell 2 3 7 , Owen M. Siggs 2 11
  1. Genomics and Inherited Disease Program, Garvan Institute of Medical Research, Sydney, NSW, Australia
  2. Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia
  3. Translational Genomics Program, Garvan Institute of Medical Research, Sydney, NSW, Australia
  4. Faculty of Science, University of Sydney, Sydney, NSW, USA
  5. Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
  6. Garvan Institute of Medical Research, Darlinghurst, NSW, Australia
  7. UNSW Cellular Genomics Futures Institute, University of New South Wales, Sydney, NSW, Australia
  8. Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
  9. Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
  10. Department of Genetics, Harvard Medical School, Boston, MA, USA
  11. Genomics and Inherited Disease Program, Garvan Institute of Medical Research, Sydney, NSW, Australia
  12. Department of Pharmacy and Pharmaceutical Sciences, Faculty of Science, National University of Singapore, Singapore
  13. Centre for Population Genomics, Garvan Institute of Medical Research, Sydney, NSW, Australia
  14. Centre for Population Genomics, Murdoch Children’s Research Institute, Melbourne, VIC, Australia
  15. Analytic and Translational Genetics Unit, Massachusetts General Hospital, Bosotn, MA, USA
  16. Australian Institute of Tropical Health and Medicine and Centre for Tropical Bioinformatics and Molecular Biology, James Cook University, Smithfield, QLD, Australia
  17. Menzies Institute for Medical Research, University of Tasmania, Hobart, TA, Australia
  18. Department of Ophthalmology, Royal Hobart Hospital, Hobart, TA, Australia
  19. Centre for Eye Research Australia, University of Melbourne, East Melbourne, VIC, Australia
  20. Charles Perkins Centre, University of Sydney, Sydney, NSW, Australia
  21. Kolling Institute of Medical Research, Royal North Shore Hospital, Sydney, NSW, Australia
  22. Department of Biomedical Informatics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
  23. Department of Pharmacy and Pharmaceutical Sciences, Faculty of Science, National University of Singapore, Singapore
  24. Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore

Clonal haematopoiesis (CH) is an age-related process characterised by the accumulation of somatic mutations in haematopoietic stem cells (HSCs) that drive clonal expansion. CH is associated with increased risks of haematological malignancies and cardiovascular disease, yet its cellular and regulatory mechanisms remain unclear. 

Here, as part of the TenK10K Phase 1 project, we generated a population scale multiomic resource comprising whole genome sequencing, genotyping arrays, single cell RNA sequencing, and single cell ATAC sequencing from more than 2,000 individuals and over 5 million peripheral blood mononuclear cells. This enabled systematic identification of diverse forms of CH at both the sample and single cell level.

We integrated summary statistics from CH genome-wide association studies with single cell transcriptomic profiles to map genetic risk to specific immune cell types. Using cell-type specific expression and chromatin accessibility QTL data, combined with colocalisation and causal inference, we identified CH associated genes and pathways and prioritised putative causal variants supported by fine mapping across multiple molecular layers. This generated the first catalogue of cell-type specific causal effects of gene expression on CH-related traits, yielding 4,515 associations across 260 genes and 28 cell types.

Leveraging matched scRNA-seq and scATAC-seq data, we characterised loss of the Y chromosome (LOY) across 974 male individuals. LOY was consistently enriched in monocytes, regulatory T cells, HSCs, and dendritic cells. Trajectory and expression analyses suggested that LOY may alter immune cell differentiation, including promoting the transition from naive CD4 T cells to regulatory T cells. This appears to be driven by increased FOXP3 expression that arises from compensatory upregulation of X-linked genes.

Together, this work provides a comprehensive multiomic framework for studying somatic variation and demonstrates how population scale single cell data can reveal the cellular contexts and regulatory mechanisms through which CH contributes to disease risk.