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BMC Genomics

, 17:1027

First Online: 22 December 2016DOI: 10.1186-s12864-016-3326-6

Cite this article as: Su, SY., Chen, SH., Lu, IH. et al. BMC Genomics 2016 17Suppl 13: 1027. doi:10.1186-s12864-016-3326-6

Abstract

BackgroundBisulfite 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.

ResultsWe 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.

ConclusionsTEA 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.

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Autor: Sheng-Yao Su - Shu-Hwa Chen - I-Hsuan Lu - Yih-Shien Chiang - Yu-Bin Wang - Pao-Yang Chen - Chung-Yen Lin

Fuente: https://link.springer.com/







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