Pierre Nicolas, Kyoung-Mee Kim, Darryl Shibata, Simon Tavaré

The analysis of methylation patterns is a promising approach to investigate the genealogy of cell populations in an organism. In a stem cell-niche scenario, sampled methylation patterns are the stochastic outcome of a complex interplay between niche structural features such as the number of stem cells within a niche and the niche succession time, the methylation/demethylation process, and the randomness due to sampling. As a consequence, methylation pattern studies can reveal niche characteristics but also require appropriate statistical methods. The analysis of methylation patterns sampled from colon crypts is a prototype of such a study. Previous analyses were based on forward simulation of the cell content of the whole crypt and subsequent comparisons between simulated and experimental data using a few statistics as a proxy to summarize the data. In this paper we develop a more powerful method to analyze these data based on coalescent modelling and Bayesian inference. Results support a scenario where the colon crypt is maintained by a high number of stem cells; the posterior indicates a number greater than eight and the posterior mode is between 15 and 20. The results also provide further evidence for synergistic effects in the methylation/demethylation process that could for the first time be quantitatively assessed through their long-term consequences such as the coexistence of hypermethylated and hypomethylated patterns in the same colon crypt.