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TEA: the epigenome platform for Arabidopsis methylome study
BACKGROUND: Bisulfite sequencing (BS-seq) has become a standard technology to profile genome-wide DNA methylation at single-base resolution. It allows researchers to conduct genome-wise cytosine methylation analyses on issues about genomic imprinting, transcriptional regulation, cellular development...
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/PMC5260138/ https://www.ncbi.nlm.nih.gov/pubmed/28155665 http://dx.doi.org/10.1186/s12864-016-3326-6 |
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author | Su, Sheng-Yao Chen, Shu-Hwa Lu, I-Hsuan Chiang, Yih-Shien Wang, Yu-Bin Chen, Pao-Yang Lin, Chung-Yen |
author_facet | Su, Sheng-Yao Chen, Shu-Hwa Lu, I-Hsuan Chiang, Yih-Shien Wang, Yu-Bin Chen, Pao-Yang Lin, Chung-Yen |
author_sort | Su, Sheng-Yao |
collection | PubMed |
description | BACKGROUND: Bisulfite sequencing (BS-seq) has become a standard technology to profile genome-wide DNA methylation at single-base resolution. It allows researchers to conduct genome-wise cytosine methylation analyses on issues about genomic imprinting, transcriptional regulation, cellular development and differentiation. One single data from a BS-Seq experiment is resolved into many features according to the sequence contexts, making methylome data analysis and data visualization a complex task. RESULTS: We developed a streamlined platform, TEA, for analyzing and visualizing data from whole-genome BS-Seq (WGBS) experiments conducted in the model plant Arabidopsis thaliana. To capture the essence of the genome methylation level and to meet the efficiency for running online, we introduce a straightforward method for measuring genome methylation in each sequence context by gene. The method is scripted in Java to process BS-Seq mapping results. Through a simple data uploading process, the TEA server deploys a web-based platform for deep analysis by linking data to an updated Arabidopsis annotation database and toolkits. CONCLUSIONS: TEA is an intuitive and efficient online platform for analyzing the Arabidopsis genomic DNA methylation landscape. It provides several ways to help users exploit WGBS data. TEA is freely accessible for academic users at: http://tea.iis.sinica.edu.tw. |
format | Online Article Text |
id | pubmed-5260138 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-52601382017-01-30 TEA: the epigenome platform for Arabidopsis methylome study Su, Sheng-Yao Chen, Shu-Hwa Lu, I-Hsuan Chiang, Yih-Shien Wang, Yu-Bin Chen, Pao-Yang Lin, Chung-Yen BMC Genomics Research BACKGROUND: Bisulfite sequencing (BS-seq) has become a standard technology to profile genome-wide DNA methylation at single-base resolution. It allows researchers to conduct genome-wise cytosine methylation analyses on issues about genomic imprinting, transcriptional regulation, cellular development and differentiation. One single data from a BS-Seq experiment is resolved into many features according to the sequence contexts, making methylome data analysis and data visualization a complex task. RESULTS: We developed a streamlined platform, TEA, for analyzing and visualizing data from whole-genome BS-Seq (WGBS) experiments conducted in the model plant Arabidopsis thaliana. To capture the essence of the genome methylation level and to meet the efficiency for running online, we introduce a straightforward method for measuring genome methylation in each sequence context by gene. The method is scripted in Java to process BS-Seq mapping results. Through a simple data uploading process, the TEA server deploys a web-based platform for deep analysis by linking data to an updated Arabidopsis annotation database and toolkits. CONCLUSIONS: TEA is an intuitive and efficient online platform for analyzing the Arabidopsis genomic DNA methylation landscape. It provides several ways to help users exploit WGBS data. TEA is freely accessible for academic users at: http://tea.iis.sinica.edu.tw. BioMed Central 2016-12-22 /pmc/articles/PMC5260138/ /pubmed/28155665 http://dx.doi.org/10.1186/s12864-016-3326-6 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 Su, Sheng-Yao Chen, Shu-Hwa Lu, I-Hsuan Chiang, Yih-Shien Wang, Yu-Bin Chen, Pao-Yang Lin, Chung-Yen TEA: the epigenome platform for Arabidopsis methylome study |
title | TEA: the epigenome platform for Arabidopsis methylome study |
title_full | TEA: the epigenome platform for Arabidopsis methylome study |
title_fullStr | TEA: the epigenome platform for Arabidopsis methylome study |
title_full_unstemmed | TEA: the epigenome platform for Arabidopsis methylome study |
title_short | TEA: the epigenome platform for Arabidopsis methylome study |
title_sort | tea: the epigenome platform for arabidopsis methylome study |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5260138/ https://www.ncbi.nlm.nih.gov/pubmed/28155665 http://dx.doi.org/10.1186/s12864-016-3326-6 |
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