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Both normal tissue development and cancer growth are driven by a branching process of cell division and mutation accumulation that leads to intra-tissue genetic heterogeneity. However, quantifying somatic evolution in humans remains challenging. Here, we show that multi-sample genomic data from a single time point of normal and cancer tissues contains information on single-cell divisions. We present a new theoretical framework that, applied to whole-genome sequencing data of healthy tissue and cancer, allows inferring the mutation rate and the cell survival/death rate per division. On average, we found that cells accumulate 1.14 mutations per cell division in healthy haematopoiesis and 1.37 mutations per division in brain development. In both tissues, cell survival was maximal during early development. Analysis of 131 biopsies from 16 tumours showed 4 to 100 times increased mutation rates compared to healthy development and substantial inter-patient variation of cell survival/death rates.

Original publication




Journal article


Nat Commun

Publication Date





Bayes Theorem, Brain, Cell Division, Cell Survival, Genetic Heterogeneity, Hematopoiesis, Humans, Models, Genetic, Mutation Accumulation, Mutation Rate, Neoplasms, Neurons, Reproducibility of Results, Single-Cell Analysis, Whole Genome Sequencing