The stem cell population of the human colon crypt: analysis via methylation patterns.

The stem cell population of the human colon crypt: analysis via methylation patterns. Research Abstract Details 

Research Abstract Table of Contents

Jump to the:

The stem cell population of the human colon crypt: analysis via methylation patterns. Abstract Text:

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

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.

The stem cell population of the human colon crypt: analysis via methylation patterns. Publishing Authors By Initials

P Nicolas,KM Kim,D Shibata,S ,

For similar cells: stem cells research abstracts see: cells: stem cells research

PUBMED ID PMID:

MEDLINE DATE:

The stem cell population of the human colon crypt: analysis via methylation patterns. Journal Published:

PUBLICATION TYPE: Research Support, Non-U.S. Gov

Journal: PLoS computational biology

VOLUME: 3

Page Numbers: e28

Journal Abbreviation: PLoS Comput. Biol.

ISSN: 1553-7358

DAY: 2

MONTH: 01

YEAR: 2007

The stem cell population of the human colon crypt: analysis via methylation patterns. Information

Number of References:

LANGUAGE: eng

NlmUniqueID: 101238922

The stem cell population of the human colon crypt: analysis via methylation patterns. Keywords Mesh Terms:

KEYWORDS: Stem Cells

MESH TERMS: physiology

Chemical & Substance for Abstract: The stem cell population of the human colon crypt: analysis via methylation patterns. Information

Substance Name:

Registry Number:

Grant and Affiliation Information for The stem cell population of the human colon crypt: analysis via methylation patterns.

AFFILIATION: Unité Mathématique Informatique et Génome UR1077, Institut National de la Recherche Agronomique, Jouy-en-Josas, France. pierre.nicolas@jouy.inra.fr

Country: United States

AGENCY: United States NCI

GRANT: R33 CA111940

ACRONYM: CA

MEDLINETA: PLoS Comput Biol

REFSOURCE:

DATABASENAME:

ACCESSION NUMBER:

Number Hits: 0

The stem cell population of the human colon crypt: analysis via methylation patterns Related Publications

• Effects of tyrosine kinase inhibitors on protein kinase-independent systems.
• Explaining differences in saturation levels for Affymetrix GeneChip arrays.
• Genome-wide mapping of ORC and Mcm2p binding sites on tiling arrays and identification of essential ARS consensus sequences in S. cerevisiae.
• O fly, where art thou?
• Rip11 is a Rab11- and AS160-RabGAP-binding protein required for insulin-stimulated glucose uptake in adipocytes.
• The stem cell population of the human colon crypt: analysis via methylation patterns.
• Using expression arrays for copy number detection: an example from E. coli.