Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 364-374 |
| Number of pages | 11 |
| Journal | PLoS Computational Biology |
| Volume | 3 |
| Issue number | 3 |
| DOIs | |
| State | Published - Mar 2007 |
| Externally published | Yes |
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