Cargando…

The Stem Cell Population of the Human Colon Crypt: Analysis via Methylation Patterns

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 cel...

Descripción completa

Detalles Bibliográficos
Autores principales: Nicolas, Pierre, Kim, Kyoung-Mee, Shibata, Darryl, Tavaré, Simon
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1808490/
https://www.ncbi.nlm.nih.gov/pubmed/17335343
http://dx.doi.org/10.1371/journal.pcbi.0030028
_version_ 1782132549126979584
author Nicolas, Pierre
Kim, Kyoung-Mee
Shibata, Darryl
Tavaré, Simon
author_facet Nicolas, Pierre
Kim, Kyoung-Mee
Shibata, Darryl
Tavaré, Simon
author_sort Nicolas, Pierre
collection PubMed
description 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.
format Text
id pubmed-1808490
institution National Center for Biotechnology Information
language English
publishDate 2007
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-18084902007-03-03 The Stem Cell Population of the Human Colon Crypt: Analysis via Methylation Patterns Nicolas, Pierre Kim, Kyoung-Mee Shibata, Darryl Tavaré, Simon PLoS Comput Biol Research Article 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. Public Library of Science 2007-03 2007-03-02 /pmc/articles/PMC1808490/ /pubmed/17335343 http://dx.doi.org/10.1371/journal.pcbi.0030028 Text en © 2007 Nicolas et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Nicolas, Pierre
Kim, Kyoung-Mee
Shibata, Darryl
Tavaré, Simon
The Stem Cell Population of the Human Colon Crypt: Analysis via Methylation Patterns
title The Stem Cell Population of the Human Colon Crypt: Analysis via Methylation Patterns
title_full The Stem Cell Population of the Human Colon Crypt: Analysis via Methylation Patterns
title_fullStr The Stem Cell Population of the Human Colon Crypt: Analysis via Methylation Patterns
title_full_unstemmed The Stem Cell Population of the Human Colon Crypt: Analysis via Methylation Patterns
title_short The Stem Cell Population of the Human Colon Crypt: Analysis via Methylation Patterns
title_sort stem cell population of the human colon crypt: analysis via methylation patterns
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1808490/
https://www.ncbi.nlm.nih.gov/pubmed/17335343
http://dx.doi.org/10.1371/journal.pcbi.0030028
work_keys_str_mv AT nicolaspierre thestemcellpopulationofthehumancoloncryptanalysisviamethylationpatterns
AT kimkyoungmee thestemcellpopulationofthehumancoloncryptanalysisviamethylationpatterns
AT shibatadarryl thestemcellpopulationofthehumancoloncryptanalysisviamethylationpatterns
AT tavaresimon thestemcellpopulationofthehumancoloncryptanalysisviamethylationpatterns
AT nicolaspierre stemcellpopulationofthehumancoloncryptanalysisviamethylationpatterns
AT kimkyoungmee stemcellpopulationofthehumancoloncryptanalysisviamethylationpatterns
AT shibatadarryl stemcellpopulationofthehumancoloncryptanalysisviamethylationpatterns
AT tavaresimon stemcellpopulationofthehumancoloncryptanalysisviamethylationpatterns