ImmuMethy, a database of DNA methylation plasticity at a single cytosine resolution in human blood and immune cells. (1st April 2022)

• Record Type: Journal Article
• Authors: Qi, Huiying; Song, Shibin; Wang, Pingzhang
• Is Part Of: Database. Volume 2022(2022)
• Publication Date: 2022-04-01
• Subjects: Biology -- Databases -- Periodicals; Bioinformatics -- Periodicals; 570.285
• DOI: 10.1093/database/baac020
• Languages: English
• ISSNs: 1758-0463

Abstract

Abstract: Differential DNA methylation is a feature of numerous physiological and pathological processes. However, the extent to which single-base cytosine methylation modifies cellular responses to various stimuli has not been well characterized. In this study, we carried out a systematic analysis of methylome data derived from human blood and immune cells and constructed the ImmuMethy database. ImmuMethy allows interrogation of DNA methylation plasticity (MPL) at the single cytosine level. MPL, which refers to the variability of DNA methylation, is quantitatively measured in multiple ways, such as quartiles and standard deviations. ImmuMethy comprises over 36 000 samples from the Human Methylation450 and MethylationEPIC BeadChips platforms and provides multiple applications, such as an overview of methylation status and plasticity, differential methylation analysis, identification of methylation markers and sample stratification. An analysis of all datasets revealed that DNA methylation is generally stable, with minimal changes in beta values. This further supports the characteristics of DNA methylation homeostasis. Based on the beta value distribution, we identified three types of methylation sites: methylation tendency sites, unmethylation tendency sites and dual tendency or nonbiased methylation sites. These sites represent different methylation tendentiousness of DNA methylation across samples. The occurrence of multiple methylation tendencies in a site means split methylation, which generally corresponds to high MPL. Inverted methylation tendencies from methylation tendency sites to unmethylation tendency sites, or vice versa, represent strong differential methylation in response to conditions. All these sites can be identified in ImmuMethy, making it a useful tool for omics-based data-driven knowledge discovery. Database URL : http://immudb.bjmu.edu.cn/immumethy/