Literature DB >> 35363305

ImmuMethy, a database of DNA methylation plasticity at a single cytosine resolution in human blood and immune cells.

Huiying Qi1, Shibin Song2, Pingzhang Wang3,4.   

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/.
© The Author(s) 2022. Published by Oxford University Press.

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Year:  2022        PMID: 35363305      PMCID: PMC9216548          DOI: 10.1093/database/baac020

Source DB:  PubMed          Journal:  Database (Oxford)        ISSN: 1758-0463            Impact factor:   4.462


  52 in total

1.  Distinct DNA methylation patterns characterize differentiated human embryonic stem cells and developing human fetal liver.

Authors:  Alayne L Brunner; David S Johnson; Si Wan Kim; Anton Valouev; Timothy E Reddy; Norma F Neff; Elizabeth Anton; Catherine Medina; Loan Nguyen; Eric Chiao; Chuba B Oyolu; Gary P Schroth; Devin M Absher; Julie C Baker; Richard M Myers
Journal:  Genome Res       Date:  2009-03-09       Impact factor: 9.043

2.  Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays.

Authors:  Martin J Aryee; Andrew E Jaffe; Hector Corrada-Bravo; Christine Ladd-Acosta; Andrew P Feinberg; Kasper D Hansen; Rafael A Irizarry
Journal:  Bioinformatics       Date:  2014-01-28       Impact factor: 6.937

3.  Positional effects revealed in Illumina methylation array and the impact on analysis.

Authors:  Chuan Jiao; Chunling Zhang; Rujia Dai; Yan Xia; Kangli Wang; Gina Giase; Chao Chen; Chunyu Liu
Journal:  Epigenomics       Date:  2018-02-22       Impact factor: 4.778

4.  DNA methylation and mRNA expression of imprinted genes in blastocysts derived from an improved in vitro maturation method for oocytes from small antral follicles in polycystic ovary syndrome patients.

Authors:  M D Saenz-de-Juano; E Ivanova; S Romero; F Lolicato; F Sánchez; H Van Ranst; F Krueger; A Segonds-Pichon; M De Vos; S Andrews; J Smitz; G Kelsey; E Anckaert
Journal:  Hum Reprod       Date:  2019-09-29       Impact factor: 6.918

5.  MethHC: a database of DNA methylation and gene expression in human cancer.

Authors:  Wei-Yun Huang; Sheng-Da Hsu; Hsi-Yuan Huang; Yi-Ming Sun; Chih-Hung Chou; Shun-Long Weng; Hsien-Da Huang
Journal:  Nucleic Acids Res       Date:  2014-11-14       Impact factor: 16.971

6.  Single-cell methylome landscapes of mouse embryonic stem cells and early embryos analyzed using reduced representation bisulfite sequencing.

Authors:  Hongshan Guo; Ping Zhu; Xinglong Wu; Xianlong Li; Lu Wen; Fuchou Tang
Journal:  Genome Res       Date:  2013-10-31       Impact factor: 9.043

7.  Identification of methylation states of DNA regions for Illumina methylation BeadChip.

Authors:  Ximei Luo; Fang Wang; Guohua Wang; Yuming Zhao
Journal:  BMC Genomics       Date:  2020-03-05       Impact factor: 3.969

8.  Age-related profiling of DNA methylation in CD8+ T cells reveals changes in immune response and transcriptional regulator genes.

Authors:  Liina Tserel; Raivo Kolde; Maia Limbach; Konstantin Tretyakov; Silva Kasela; Kai Kisand; Mario Saare; Jaak Vilo; Andres Metspalu; Lili Milani; Pärt Peterson
Journal:  Sci Rep       Date:  2015-08-19       Impact factor: 4.379

9.  A reference methylome database and analysis pipeline to facilitate integrative and comparative epigenomics.

Authors:  Qiang Song; Benjamin Decato; Elizabeth E Hong; Meng Zhou; Fang Fang; Jianghan Qu; Tyler Garvin; Michael Kessler; Jun Zhou; Andrew D Smith
Journal:  PLoS One       Date:  2013-12-06       Impact factor: 3.240

10.  Parkinson's disease is associated with DNA methylation levels in human blood and saliva.

Authors:  Yu-Hsuan Chuang; Kimberly C Paul; Jeff M Bronstein; Yvette Bordelon; Steve Horvath; Beate Ritz
Journal:  Genome Med       Date:  2017-08-30       Impact factor: 11.117

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