Literature DB >> 28654059

Comprehensive DNA Methylation Analysis Using a Methyl-CpG-binding Domain Capture-based Method in Chronic Lymphocytic Leukemia Patients.

Santhilal Subhash1, Meena Kanduri2.   

Abstract

The role of long noncoding RNAs (lncRNAs) in cancer is coming to the forefront due to growing interest in understanding their mechanistic functions during cancer development and progression. Despite this, the global epigenetic regulation of lncRNAs and repetitive sequences in cancer has not been well investigated, particularly in chronic lymphocytic leukemia (CLL). This study focuses on a unique approach: the immunoprecipitation-based capture of double-stranded, methylated DNA fragments using methyl-binding domain (MBD) proteins, followed by next-generation sequencing (MBD-seq). CLL patient samples belonging to two prognostic subgroups (5 IGVH mutated samples + 5 IGVH unmutated samples) were used in this study. Analysis revealed 5,800 hypermethylated and 12,570 hypomethylated CLL-specific differentially methylated genes (cllDMGs) compared to normal healthy controls. Importantly, these results identified several CLL-specific, differentially methylated lncRNAs, repetitive elements, and protein-coding genes with potential prognostic value. This work outlines a detailed protocol for an MBD-seq and bioinformatics pipeline developed for the comprehensive analysis of global methylation profiles in highly CpG-rich regions using CLL patient samples. Finally, a protein-coding gene and an lncRNA were validated using pyrosequencing, which is a highly quantitative method to analyze CpG methylation levels to further corroborate the findings from the MBD-seq protocol.

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Year:  2017        PMID: 28654059      PMCID: PMC5608441          DOI: 10.3791/55773

Source DB:  PubMed          Journal:  J Vis Exp        ISSN: 1940-087X            Impact factor:   1.355


  19 in total

1.  Base-resolution analysis of 5-hydroxymethylcytosine in the mammalian genome.

Authors:  Miao Yu; Gary C Hon; Keith E Szulwach; Chun-Xiao Song; Liang Zhang; Audrey Kim; Xuekun Li; Qing Dai; Yin Shen; Beomseok Park; Jung-Hyun Min; Peng Jin; Bing Ren; Chuan He
Journal:  Cell       Date:  2012-05-17       Impact factor: 41.582

2.  Evaluation of affinity-based genome-wide DNA methylation data: effects of CpG density, amplification bias, and copy number variation.

Authors:  Mark D Robinson; Clare Stirzaker; Aaron L Statham; Marcel W Coolen; Jenny Z Song; Shalima S Nair; Dario Strbenac; Terence P Speed; Susan J Clark
Journal:  Genome Res       Date:  2010-11-02       Impact factor: 9.043

3.  Distinct transcriptional control in major immunogenetic subsets of chronic lymphocytic leukemia exhibiting subset-biased global DNA methylation profiles.

Authors:  Meena Kanduri; Millaray Marincevic; Anna M Halldórsdóttir; Larry Mansouri; Katarina Junevik; Stavroula Ntoufa; Hanna Göransson Kultima; Anders Isaksson; Gunnar Juliusson; Per-Ola Andersson; Hans Ehrencrona; Kostas Stamatopoulos; Richard Rosenquist
Journal:  Epigenetics       Date:  2012-11-15       Impact factor: 4.528

4.  Guidelines for the diagnosis and treatment of chronic lymphocytic leukemia: a report from the International Workshop on Chronic Lymphocytic Leukemia updating the National Cancer Institute-Working Group 1996 guidelines.

Authors:  Michael Hallek; Bruce D Cheson; Daniel Catovsky; Federico Caligaris-Cappio; Guillaume Dighiero; Hartmut Döhner; Peter Hillmen; Michael J Keating; Emili Montserrat; Kanti R Rai; Thomas J Kipps
Journal:  Blood       Date:  2008-01-23       Impact factor: 22.113

5.  Differential genome-wide array-based methylation profiles in prognostic subsets of chronic lymphocytic leukemia.

Authors:  Meena Kanduri; Nicola Cahill; Hanna Göransson; Camilla Enström; Fergus Ryan; Anders Isaksson; Richard Rosenquist
Journal:  Blood       Date:  2009-11-06       Impact factor: 22.113

6.  450K-array analysis of chronic lymphocytic leukemia cells reveals global DNA methylation to be relatively stable over time and similar in resting and proliferative compartments.

Authors:  N Cahill; A-C Bergh; M Kanduri; H Göransson-Kultima; L Mansouri; A Isaksson; F Ryan; K E Smedby; G Juliusson; C Sundström; A Rosén; R Rosenquist
Journal:  Leukemia       Date:  2012-08-27       Impact factor: 11.528

7.  Quantitative sequencing of 5-methylcytosine and 5-hydroxymethylcytosine at single-base resolution.

Authors:  Michael J Booth; Miguel R Branco; Gabriella Ficz; David Oxley; Felix Krueger; Wolf Reik; Shankar Balasubramanian
Journal:  Science       Date:  2012-04-26       Impact factor: 47.728

8.  edgeR: a Bioconductor package for differential expression analysis of digital gene expression data.

Authors:  Mark D Robinson; Davis J McCarthy; Gordon K Smyth
Journal:  Bioinformatics       Date:  2009-11-11       Impact factor: 6.937

9.  Model-based analysis of ChIP-Seq (MACS).

Authors:  Yong Zhang; Tao Liu; Clifford A Meyer; Jérôme Eeckhoute; David S Johnson; Bradley E Bernstein; Chad Nusbaum; Richard M Myers; Myles Brown; Wei Li; X Shirley Liu
Journal:  Genome Biol       Date:  2008-09-17       Impact factor: 13.583

10.  Trimmomatic: a flexible trimmer for Illumina sequence data.

Authors:  Anthony M Bolger; Marc Lohse; Bjoern Usadel
Journal:  Bioinformatics       Date:  2014-04-01       Impact factor: 6.937

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