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bioRxiv · 10.1101/2022.11.07.515470

Measures of genetic diversification in somatic tissues at bulk and single cell resolution

Abstract

Intra-tissue genetic heterogeneity is universal to both healthy and cancerous tissues. It emerges from the stochastic accumulation of somatic mutations throughout development and homeostasis. By combining population genetics theory and genomic information, genetic heterogeneity can be exploited to infer tissue organisation and dynamics in vivo. However, many basic quantities, for example the dynamics of tissue specific stem cells remain difficult to quantify precisely. Here we show that single cell and bulk sequencing data inform on different aspects of the underlying stochastic processes. Bulk derived variant allele frequency spectra (VAF) show transitions from growing to constant stem cell populations with age in samples of healthy oesophagus epithelium. Single-cell mutational burden distributions allow a sample size independent measure of mutation and proliferation rates. Mutation rates in adult haematopietic stem cells are higher compared to inferences during development, suggesting additional proliferation independent effects. Furthermore, single cell derived VAF spectra contain information on the number of tissue specific stem cells. In haematopiesis, we find approximately 2x105 HSCs, if all stem cells divide symmetrically. However, the single cell mutational burden distribution is over-dispersed compared to a model of Poisson distributed random mutations suggesting. A time-associated model of mutation accumulation with a constant rate alone cannot generate such a pattern. At least one additional source of stochasticity would be needed. Possible candidates for these processes may be occasional bursts of stem cell divisions, potentially in response to injury, or non-constant mutation rates either through environmental exposures or cell intrinsic variation.

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BibTeXRIS

Moeller, M. E., Mon Pere, N. V., Werner, B., Huang, W.. 2022-11-08. Measures of genetic diversification in somatic tissues at bulk and single cell resolution. https://doi.org/10.1101/2022.11.07.515470

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