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PiiL: visualization of DNA methylation and gene expression data in gene pathways

BACKGROUND: DNA methylation is a major mechanism involved in the epigenetic state of a cell. It has been observed that the methylation status of certain CpG sites close to or within a gene can directly affect its expression, either by silencing or, in some cases, up-regulating transcription. However...

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Autores principales: Moghadam, Behrooz Torabi, Zamani, Neda, Komorowski, Jan, Grabherr, Manfred
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5541427/
https://www.ncbi.nlm.nih.gov/pubmed/28768481
http://dx.doi.org/10.1186/s12864-017-3950-9
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author Moghadam, Behrooz Torabi
Zamani, Neda
Komorowski, Jan
Grabherr, Manfred
author_facet Moghadam, Behrooz Torabi
Zamani, Neda
Komorowski, Jan
Grabherr, Manfred
author_sort Moghadam, Behrooz Torabi
collection PubMed
description BACKGROUND: DNA methylation is a major mechanism involved in the epigenetic state of a cell. It has been observed that the methylation status of certain CpG sites close to or within a gene can directly affect its expression, either by silencing or, in some cases, up-regulating transcription. However, a vertebrate genome contains millions of CpG sites, all of which are potential targets for methylation, and the specific effects of most sites have not been characterized to date. To study the complex interplay between methylation status, cellular programs, and the resulting phenotypes, we present PiiL, an interactive gene expression pathway browser, facilitating analyses through an integrated view of methylation and expression on multiple levels. RESULTS: PiiL allows for specific hypothesis testing by quickly assessing pathways or gene networks, where the data is projected onto pathways that can be downloaded directly from the online KEGG database. PiiL provides a comprehensive set of analysis features that allow for quick and specific pattern searches. Individual CpG sites and their impact on host gene expression, as well as the impact on other genes present in the regulatory network, can be examined. To exemplify the power of this approach, we analyzed two types of brain tumors, Glioblastoma multiform and lower grade gliomas. CONCLUSION: At a glance, we could confirm earlier findings that the predominant methylation and expression patterns separate perfectly by mutations in the IDH genes, rather than by histology. We could also infer the IDH mutation status for samples for which the genotype was not known. By applying different filtering methods, we show that a subset of CpG sites exhibits consistent methylation patterns, and that the status of sites affect the expression of key regulator genes, as well as other genes located downstream in the same pathways. PiiL is implemented in Java with focus on a user-friendly graphical interface. The source code is available under the GPL license from https://github.com/behroozt/PiiL.git. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-017-3950-9) contains supplementary material, which is available to authorized users.
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spelling pubmed-55414272017-08-07 PiiL: visualization of DNA methylation and gene expression data in gene pathways Moghadam, Behrooz Torabi Zamani, Neda Komorowski, Jan Grabherr, Manfred BMC Genomics Software BACKGROUND: DNA methylation is a major mechanism involved in the epigenetic state of a cell. It has been observed that the methylation status of certain CpG sites close to or within a gene can directly affect its expression, either by silencing or, in some cases, up-regulating transcription. However, a vertebrate genome contains millions of CpG sites, all of which are potential targets for methylation, and the specific effects of most sites have not been characterized to date. To study the complex interplay between methylation status, cellular programs, and the resulting phenotypes, we present PiiL, an interactive gene expression pathway browser, facilitating analyses through an integrated view of methylation and expression on multiple levels. RESULTS: PiiL allows for specific hypothesis testing by quickly assessing pathways or gene networks, where the data is projected onto pathways that can be downloaded directly from the online KEGG database. PiiL provides a comprehensive set of analysis features that allow for quick and specific pattern searches. Individual CpG sites and their impact on host gene expression, as well as the impact on other genes present in the regulatory network, can be examined. To exemplify the power of this approach, we analyzed two types of brain tumors, Glioblastoma multiform and lower grade gliomas. CONCLUSION: At a glance, we could confirm earlier findings that the predominant methylation and expression patterns separate perfectly by mutations in the IDH genes, rather than by histology. We could also infer the IDH mutation status for samples for which the genotype was not known. By applying different filtering methods, we show that a subset of CpG sites exhibits consistent methylation patterns, and that the status of sites affect the expression of key regulator genes, as well as other genes located downstream in the same pathways. PiiL is implemented in Java with focus on a user-friendly graphical interface. The source code is available under the GPL license from https://github.com/behroozt/PiiL.git. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-017-3950-9) contains supplementary material, which is available to authorized users. BioMed Central 2017-08-02 /pmc/articles/PMC5541427/ /pubmed/28768481 http://dx.doi.org/10.1186/s12864-017-3950-9 Text en © The Author(s). 2017 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 Software
Moghadam, Behrooz Torabi
Zamani, Neda
Komorowski, Jan
Grabherr, Manfred
PiiL: visualization of DNA methylation and gene expression data in gene pathways
title PiiL: visualization of DNA methylation and gene expression data in gene pathways
title_full PiiL: visualization of DNA methylation and gene expression data in gene pathways
title_fullStr PiiL: visualization of DNA methylation and gene expression data in gene pathways
title_full_unstemmed PiiL: visualization of DNA methylation and gene expression data in gene pathways
title_short PiiL: visualization of DNA methylation and gene expression data in gene pathways
title_sort piil: visualization of dna methylation and gene expression data in gene pathways
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5541427/
https://www.ncbi.nlm.nih.gov/pubmed/28768481
http://dx.doi.org/10.1186/s12864-017-3950-9
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