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Combinatorial identification of DNA methylation patterns over age in the human brain
BACKGROUND: DNA methylation plays a key role in developmental processes, which is reflected in changing methylation patterns at specific CpG sites over the lifetime of an individual. The underlying mechanisms are complex and possibly affect multiple genes or entire pathways. RESULTS: We applied a mu...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5034667/ https://www.ncbi.nlm.nih.gov/pubmed/27663458 http://dx.doi.org/10.1186/s12859-016-1259-3 |
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author | Torabi Moghadam, Behrooz Dabrowski, Michal Kaminska, Bozena Grabherr, Manfred G. Komorowski, Jan |
author_facet | Torabi Moghadam, Behrooz Dabrowski, Michal Kaminska, Bozena Grabherr, Manfred G. Komorowski, Jan |
author_sort | Torabi Moghadam, Behrooz |
collection | PubMed |
description | BACKGROUND: DNA methylation plays a key role in developmental processes, which is reflected in changing methylation patterns at specific CpG sites over the lifetime of an individual. The underlying mechanisms are complex and possibly affect multiple genes or entire pathways. RESULTS: We applied a multivariate approach to identify combinations of CpG sites that undergo modifications when transitioning between developmental stages. Monte Carlo feature selection produced a list of ranked and statistically significant CpG sites, while rule-based models allowed for identifying particular methylation changes in these sites. Our rule-based classifier reports combinations of CpG sites, together with changes in their methylation status in the form of easy-to-read IF-THEN rules, which allows for identification of the genes associated with the underlying sites. CONCLUSION: We utilized machine learning and statistical methods to discretize decision class (age) values to get a general pattern of methylation changes over the lifespan. The CpG sites present in the significant rules were annotated to genes involved in brain formation, general development, as well as genes linked to cancer and Alzheimer’s disease. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1259-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5034667 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-50346672016-09-29 Combinatorial identification of DNA methylation patterns over age in the human brain Torabi Moghadam, Behrooz Dabrowski, Michal Kaminska, Bozena Grabherr, Manfred G. Komorowski, Jan BMC Bioinformatics Research Article BACKGROUND: DNA methylation plays a key role in developmental processes, which is reflected in changing methylation patterns at specific CpG sites over the lifetime of an individual. The underlying mechanisms are complex and possibly affect multiple genes or entire pathways. RESULTS: We applied a multivariate approach to identify combinations of CpG sites that undergo modifications when transitioning between developmental stages. Monte Carlo feature selection produced a list of ranked and statistically significant CpG sites, while rule-based models allowed for identifying particular methylation changes in these sites. Our rule-based classifier reports combinations of CpG sites, together with changes in their methylation status in the form of easy-to-read IF-THEN rules, which allows for identification of the genes associated with the underlying sites. CONCLUSION: We utilized machine learning and statistical methods to discretize decision class (age) values to get a general pattern of methylation changes over the lifespan. The CpG sites present in the significant rules were annotated to genes involved in brain formation, general development, as well as genes linked to cancer and Alzheimer’s disease. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1259-3) contains supplementary material, which is available to authorized users. BioMed Central 2016-09-23 /pmc/articles/PMC5034667/ /pubmed/27663458 http://dx.doi.org/10.1186/s12859-016-1259-3 Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Torabi Moghadam, Behrooz Dabrowski, Michal Kaminska, Bozena Grabherr, Manfred G. Komorowski, Jan Combinatorial identification of DNA methylation patterns over age in the human brain |
title | Combinatorial identification of DNA methylation patterns over age in the human brain |
title_full | Combinatorial identification of DNA methylation patterns over age in the human brain |
title_fullStr | Combinatorial identification of DNA methylation patterns over age in the human brain |
title_full_unstemmed | Combinatorial identification of DNA methylation patterns over age in the human brain |
title_short | Combinatorial identification of DNA methylation patterns over age in the human brain |
title_sort | combinatorial identification of dna methylation patterns over age in the human brain |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5034667/ https://www.ncbi.nlm.nih.gov/pubmed/27663458 http://dx.doi.org/10.1186/s12859-016-1259-3 |
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