©
Adobe Stock
Co-led by Prof Paresh Vyas and Prof Thomas Höfer, the study introduces SCIFER, a computational tool that detects and characterises clonal selection—a process where some cells, through random mutations or epigenetic change, gain an advantage over their neighbours and expand disproportionately. Over time, these mutant clones dominate a tissue and may change its function. This phenomenon, known as somatic evolution, occurs in all tissues and can change tissue function and, in some circumstances, lead to cancer.
Dr Verena Korber, first author of the study, said:
We were interested in characterising clonal selection in tissues in an unbiased way, i.e., without prior knowledge of the mutation driving selection. We also wanted to know when in life selected clones emerge and how quickly they grow over time.
Methods of tackling these questions already exist, but require analysis of the DNA of many single cells, which is laborious and very expensive.
Unlike these existing approaches, SCIFER works with bulk tissue samples, is much cheaper and quicker to use. It uses somatic mutations as natural barcodes to reconstruct the growth history of cells in a tissue. By applying evolutionary theory, the tool can determine whether a group of cells expanded unusually fast, when this expansion began, and how quickly it progressed.
The research team applied SCIFER to:
- Blood samples from 21 healthy individuals, finding widespread evidence of clonal selection across all age groups, even in people without known cancer mutations.
- Brain tissue samples from over 130 individuals were analysed, discovering that selection also occurs in the brain but tends to begin in early life. In two cases, the mutations matched those seen in brain cancers, suggesting the presence of pre-malignant clones.
While SCIFER is primarily a research tool, the team hopes it could eventually improve understanding of how diseases like cancer begin and progress, possibly informing future efforts in early diagnosis and predicting disease progression.
Professor Paresh Vyas said:
SCIFER provides a tool which can be widely used to detect selection of cell populations in tissues. This will open up wider investigation into how tissues adapt to their environment and with age. Thus, SCIFER will be of general interest to many fields.
Read the full Nature Genetics article here: https://www.nature.com/articles/s41588-025-02217-y
SCIFER is freely available to the research community at https://github.com/VerenaK90/SCIFER.