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Detecting and quantifying clonal selection in somatic stem cells
Verena Körber1,2, Niels Asger Jakobsen3, Naser Ansari-Pour3,4
1Division of Theoretical Systems Biology, German Cancer Research Center (DKFZ), Heidelberg, Germany. verena.korber@ndcls.ox.ac.uk.
Nature Genetics
|July 3, 2025
Summary
Researchers developed SCIFER, a method to detect genetic selection in stem cells within tissues like bone marrow and brain. This tool helps understand how selected clones emerge and grow, offering insights into tissue aging and disease risk.
Area of Science:
- Somatic cell genetics
- Stem cell biology
- Computational biology
Background:
- Accumulation of DNA variants in somatic stem cells can alter tissue function.
- The mechanisms and timing of selection in homeostatic tissues remain poorly understood.
- Detecting selection in non-malignant tissues is crucial for understanding aging and disease initiation.
Purpose of the Study:
- To introduce SCIFER, a scalable computational method for identifying genetic selection in individual tissues.
- To infer stem cell dynamics, clone size, and age without prior knowledge of driver events.
- To analyze selection patterns in human bone marrow and brain tissues.
Main Methods:
- Development of SCIFER, a scalable computational method.
- Application of SCIFER to bulk whole-genome sequencing data from nonmalignant human bone marrow and brain.
- Analysis of DNA variant accumulation, selection, and clone dynamics in stem cell populations.
Main Results:
- Pervasive genetic selection was detected in both human bone marrow and brain tissues.
- Selected clones in hematopoiesis initiated uniformly throughout life, regardless of known drivers.
- Selected clones in the brain, including pre-malignant ones, originated predominantly in early life (childhood to young adulthood).
Conclusions:
- SCIFER is a broadly applicable tool for detecting and quantifying selection in renewing somatic tissues.
- Selection in human tissues occurs dynamically and varies between tissue types (e.g., bone marrow vs. brain).
- Understanding selection dynamics is key to comprehending tissue homeostasis, aging, and the early stages of diseases like glioma.

