Detecting and quantifying clonal selection in somatic stem cells

As DNA variants accumulate in somatic stem cells, become selected or evolve neutrally, they may ultimately alter tissue function. When, and how, selection occurs in homeostatic tissues is incompletely understood. Here, we introduce SCIFER, a scalable method that identifies selection in an individual tissue, without requiring knowledge of the driver event. SCIFER also infers self-renewal and mutation dynamics of the tissue's stem cells, and the size and age of selected clones. Probing bulk whole-genome sequencing data of nonmalignant human bone marrow and brain, we detected pervasive selection in both tissues. Selected clones in hematopoiesis, with or without known drivers, were initiated uniformly across life. In the brain, we found pre-malignant clones with glioma-initiating mutations and clones without known drivers. In contrast to hematopoiesis, selected clones in the brain originated preferentially from childhood to young adulthood. SCIFER is broadly applicable to renewing somatic tissues to detect and quantify selection.

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Publication Details

Journal
Nature Genetics
Published
2025-07-01
DOI
https://doi.org/10.1038/s41588-025-02217-y
Citations
5
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
4.68

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article

Detecting and quantifying clonal selection in somatic stem cells

Marlen Metzner, Nina Claudino, Stephanie G. Dakin, Debra Beazley et al.
5 citations
Nature Genetics
Cancer Genomics and Diagnostics
4.68
article

Detecting and quantifying clonal selection in somatic stem cells

Marlen Metzner, Nina Claudino, Stephanie G. Dakin, Debra Beazley, Andrew Carr, Thomas Höfer, Naser Ansari‐Pour, Antony Palmer, Mirian Angulo Salazar, Rachel Moore, Rasheed Afinowi-Luitz, Roger Gundle, Niels Asger Jakobsen, Verena Körber, Paresh Vyas, Kim Wheway, Batchimeg Usukhbayar, Simon Newman, Bridget Watkins, Adrian Taylor, Benjamin Kendrick, Eva Thielecke, Franziska Esau
article en
5 citations

Abstract

As DNA variants accumulate in somatic stem cells, become selected or evolve neutrally, they may ultimately alter tissue function. When, and how, selection occurs in homeostatic tissues is incompletely understood. Here, we introduce SCIFER, a scalable method that identifies selection in an individual tissue, without requiring knowledge of the driver event. SCIFER also infers self-renewal and mutation dynamics of the tissue's stem cells, and the size and age of selected clones. Probing bulk whole-genome sequencing data of nonmalignant human bone marrow and brain, we detected pervasive selection in both tissues. Selected clones in hematopoiesis, with or without known drivers, were initiated uniformly across life. In the brain, we found pre-malignant clones with glioma-initiating mutations and clones without known drivers. In contrast to hematopoiesis, selected clones in the brain originated preferentially from childhood to young adulthood. SCIFER is broadly applicable to renewing somatic tissues to detect and quantify selection.

Nature GeneticsVol. 57(7)
German Cancer Research Center (DE), Heidelberg University (DE), Nuffield Orthopaedic Centre (GB), Cambridge University Hospitals NHS Foundation Trust (GB), University of Oxford (GB), Bridge University (SS), MRC Weatherall Institute of Molecular Medicine (GB), MRC Human Immunology Unit (GB), Oxford BioMedica (United Kingdom) (GB)
National Science Foundation, Gordon and Betty Moore Foundation, Deutsches Krebsforschungszentrum, Leukaemia UK, National Institute for Health and Care Research, Deutsche Forschungsgemeinschaft, Bundesministerium für Bildung und Forschung, Blood Cancer UK, Medical Research Council, Kavli Institute for Theoretical Physics, University of California, Santa Barbara
Openalex Percentile: Top 5%
Cancer Genomics and Diagnostics
4.68
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