Literature DB >> 18987809

Differential methylation hybridization: profiling DNA methylation with a high-density CpG island microarray.

Pearlly S Yan1, Dustin Potter, Daniel E Deatherage, Tim H-M Huang, Shili Lin.   

Abstract

Differential methylation hybridization (DMH) is a high-throughput DNA methylation screening tool that utilizes methylation-sensitive restriction enzymes to profile methylated fragments by hybridizing them to a CpG island microarray. This array contains probes spanning all the 27,800 islands annotated in the UCSC Genome Browser. Herein we describe a revised DMH protocol with clearly identified quality control points. In this manner, samples that are unlikely to provide good readouts for differential methylation profiles between the test and the control samples will be identified and repeated with appropriate modifications. In addition to the step-by-step laboratory DMH protocol, we also provide a detailed description regarding DMH data analysis. The suggested microarray platform contains 244,000 probes and it can be a daunting barrier for researchers with no prior experience in analyzing DNA methylation data. We have created a data analysis pipeline available in a user friendly, publicly available interface, the Broad Institute's GenePattern software, which can be accessed at http://bisr.osumc.edu :8080/gp. This permits scientists to use our existing data analysis modules on their own data. As we continue to update our analysis algorithm and approaches to integrate high-throughput methylation data with other large-scale data types, we will make these new computation protocols available through the GenePattern platform.

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Year:  2009        PMID: 18987809     DOI: 10.1007/978-1-59745-522-0_8

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  16 in total

Review 1.  Principles and challenges of genomewide DNA methylation analysis.

Authors:  Peter W Laird
Journal:  Nat Rev Genet       Date:  2010-03       Impact factor: 53.242

2.  High-throughput method for analyzing methylation of CpGs in targeted genomic regions.

Authors:  Shivani Nautiyal; Victoria E H Carlton; Yontao Lu; James S Ireland; Diane Flaucher; Martin Moorhead; Joe W Gray; Paul Spellman; Michael Mindrinos; Paul Berg; Malek Faham
Journal:  Proc Natl Acad Sci U S A       Date:  2010-06-23       Impact factor: 11.205

3.  Expression of miR-196b is not exclusively MLL-driven but is especially linked to activation of HOXA genes in pediatric acute lymphoblastic leukemia.

Authors:  Diana Schotte; Ellen A M Lange-Turenhout; Dominique J P M Stumpel; Ronald W Stam; Jessica G C A M Buijs-Gladdines; Jules P P Meijerink; Rob Pieters; Monique L Den Boer
Journal:  Haematologica       Date:  2010-05-21       Impact factor: 9.941

4.  Epigenetic methodologies for behavioral scientists.

Authors:  Danielle S Stolzenberg; Patrick A Grant; Stefan Bekiranov
Journal:  Horm Behav       Date:  2010-10-15       Impact factor: 3.587

Review 5.  Bioinformatic approaches to augment study of epithelial-to-mesenchymal transition in lung cancer.

Authors:  Tim N Beck; Adaeze J Chikwem; Nehal R Solanki; Erica A Golemis
Journal:  Physiol Genomics       Date:  2014-08-05       Impact factor: 3.107

6.  In Silico Enhanced Restriction Enzyme Based Methylation Analysis of the Human Glioblastoma Genome Using Agilent 244K CpG Island Microarrays.

Authors:  Anh Tran; Cameron Escovedo; Justine Migdall-Wilson; Arthur P Chou; Weidong Chen; Timothy Cloughesy; Stanley Nelson; Albert Lai
Journal:  Front Neurosci       Date:  2010-01-04       Impact factor: 4.677

7.  Array-based profiling of the differential methylation status of CpG islands in hepatocellular carcinoma cell lines.

Authors:  Bin-Bin Liu; Dan Zheng; Yin-Kun Liu; Xiao-Nan Kang; Lu Sun; Kun Guo; Rui-Xia Sun; Jie Chen; Yan Zhao
Journal:  Oncol Lett       Date:  2010-09-01       Impact factor: 2.967

8.  Methylation analysis by microarray.

Authors:  Daniel E Deatherage; Dustin Potter; Pearlly S Yan; Tim H-M Huang; Shili Lin
Journal:  Methods Mol Biol       Date:  2009

9.  Identifying differentially methylated genes using mixed effect and generalized least square models.

Authors:  Shuying Sun; Pearlly S Yan; Tim H M Huang; Shili Lin
Journal:  BMC Bioinformatics       Date:  2009-12-09       Impact factor: 3.169

10.  Probe signal correction for differential methylation hybridization experiments.

Authors:  Dustin P Potter; Pearlly Yan; Tim H M Huang; Shili Lin
Journal:  BMC Bioinformatics       Date:  2008-10-23       Impact factor: 3.169

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