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ht t p: //www. t andf onl i ne. com /l oi /kepi 20
Com pari son of m et hyl - DNA i m m unopreci pi t at i on
( MeDI P) and m et hyl - CpG bi ndi ng dom ai n ( MBD) prot ei n
capt ure f or genom e- wi de DNA m et hyl at i on anal ysi s
reveal CpG sequence cover age bi as
Shal i m a S. Nai r , Mar cel W. Cool en, Cl ar e St i r zaker , Jenny Z. Song, Aar on L. St at ham , Dar i o
St r benac, Mar k D. Robi nson & Susan J. Cl ar k
Publ i shed onl i ne: 01 Jan 2011.
To ci t e t hi s art i cl e: Shal i m a S. Nai r , Mar cel W. Cool en, Cl ar e St i r zaker , Jenny Z. Song, Aar on L. St at ham , Dar i o St r benac, Mar k
D. Robi nson & Susan J. Cl ar k ( 2011) Com par i son of m et hyl - DNA i m m unopr eci pi t at i on ( MeDI P) and m et hyl - CpG bi ndi ng dom ai n
( MBD) pr ot ei n capt ur e f or genom e- wi de DNA m et hyl at i on anal ysi s r eveal CpG sequence cover age bi as, Epi genet i cs, 6: 1, 34- 44,
DOI : 10. 4161/epi . 6. 1. 13313
To l i nk t o t hi s art i cl e: ht t p: //dx. doi . or g/10. 4161/epi . 6. 1. 13313
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Epigenetics 6:1, 34-44; January 2011; © 2011 Landes Bioscience
Comparison of methyl-DNA immunoprecipitation
(MeDIP) and methyl-CpG binding domain
(MBD) protein capture for genome-wide DNA
methylation analysis reveal CpG sequence
34 Epigenetics Volume 6 Issue 1
*Correspondence to: Susan J. Clark; Email: email@example.com
Submitted: 06/30/10; Accepted: 08/12/10
Previously published online: www.landesbioscience.com/journals/epigenetics/article/13313
A prerequisite for understanding the function of DNA methyla-
tion is knowledge of its distribution in the genome. In mammals,
5'-methylcytosine (5MeC) accounts for ~1% of total DNA bases
and therefore potentially affects 70–80% of all CpG dinucleo-
tides in the genome.1 However, DNA methylation patterns are
dynamic in nature and vary during development and across the
genome. The cycle of early embryonic demethylation followed
DNA methylation primarily occurs at CpG dinucleotides in mammals and is a common epigenetic mark that plays
a critical role in the regulation of gene expression. Profiling DNA methylation patterns across the genome is vital to
understand DNA methylation changes that occur during development and in disease phenotype. In this study, we
compared two commonly used approaches to enrich for methylated DNA regions of the genome, namely methyl-
DNA immunoprecipitation (MeDIP) that is based on enrichment with antibodies specific for 5’-methylcytosine (5MeC)
and capture of methylated DNA using a methyl-CpG binding domain-based (MBD) protein to discover differentially
methylated regions (DMRs) in cancer. The enriched methylated DNA fractions were interrogated on Affymetrix promoter
tiling arrays and differentially methylated regions were identified. A detailed validation study of 42 regions was
performed using Sequenom MassCLEAVE technique. This detailed analysis revealed that both enrichment techniques
are sensitive for detecting DMRs and preferentially identified different CpG rich regions of the prostate cancer genome,
with MeDIP commonly enriching for methylated regions with a low CpG density, while MBD capture favors regions
of higher CpG density and identifies the greatest proportion of CpG islands. This is the first detailed validation report
comparing different methylated DNA enrichment techniques for identifying regions of differential DNA methylation. Our
study highlights the importance of understanding the nuances of the methods used for DNA genome-wide methylation
analyses so that accurate interpretation of the biology is not overlooked.
Shalima S. Nair,1,† Marcel W. Coolen,1,3,† Clare Stirzaker,1,† Jenny Z. Song,1 Aaron L. Statham,1 Dario Strbenac,1
Mark D. Robinson1,2 and Susan J. Clark1,*
1Epigenetics Laboratory; Cancer Research Program; Garvan Institute of Medical Research; Darlinghurst, NSW Australia; 2Bioinformatics Division; Walter and Eliza Hall Institute
of Medical Research; Melbourne, VIC Australia; 3Department of Molecular Biology; Faculty of Science; Nijmegen Centre for Molecular Life Sciences;
Radboud University Nijmegen; Nijmegen, The Netherlands
†These authors contributed equally to this work.
Key words: DNA methylation, CpG dinucleotides, epigenetics, genome wide, differentially methylated regions, cancer
Abbreviations: WGA, whole genome amplification; MAT, model-based analysis of tiling arrays; IGB, integrated genome browser;
SAP, shrimp alkaline phosphatase; DMR, differentially methylated regions; MeDIP, methyl-DNA immunoprecipitation;
MBD, methyl-CpG binding domain; 5MeC, 5'-methylcytosine
by de novo methylation is critical in determining cell specific
DNA methylation patterns. Possibly the most notable feature of
mammalian DNA methylation patterns is the presence of CpG
islands, that is, unmethylated GC-rich regions that possess high
relative densities of CpG and are positioned at the 5' ends of many
human genes.2 There are approximately 29,000 CpG islands3,4 in
the human genome sequence and more than 60% of human genes
are associated with CpG islands, of which the great majority are
unmethylated at all stages of development and in all tissue types.5
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www.landesbioscience.com Epigenetics 43
serological DNA (Millipore) as a 100% methylated control and
whole genome amplified human blood DNA as a 0% methylated
control. The PCRs were optimized and performed in triplicate
using the conditions: 95°C for 2 min, 45 cycles of 95°C for 40
sec, 60°C for 1 min and 72°C for 1 min 30 sec and final exten-
sion at 72°C for 5 min. After PCR amplification, the triplicates
were pooled and a shrimp alkaline phosphatase (SAP) treatment
was performed using 5 μl of the PCR product as template. 2 μl of
the SAP-treated PCR product was taken and subjected to in vitro
transcription and RNaseA Cleavage for the T-cleavage reaction.
The samples were purified by resin treatment and spotted on a
384-well SpectroCHIP by a MassARRAY Nanodispenser. This
was followed by spectral acquisition on a MassARRAY Analyzer
Compact matrix-assisted laser desorption/ionization time-of-
flight mass spectrometry. The results were then analyzed by the
EpiTYPER software V 1.0, which gives quantitative methylation
levels for individual CpG sites. The average methylation ratio
was calculated by averaging the ratios obtained from each CpG
site from both LNCaP and PrEC and calculating the difference
between them. Methylation readings that had other signal over-
laps and silent peaks were eliminated from the calculation.
We thank Kate Patterson for help with preparation of the figures
and critical reviewing of the manuscript and Rebecca Hinshelwood
for critical reviewing of the manuscript. We thank the Ramaciotti
Centre, University of NSW (Sydney, Australia) for array hybrid-
izations. This work is supported by National Health and Medical
Research Council (NH&MRC) project (427614, 481347) and
Fellowship (S.J.C.), Cancer Institute NSW grants (CINSW:
S.J.C.; A.L.S.) and NBCF Program Grant (S.J.C.) and ACRF.
S.J.C. initiated and supervised the study and, with M.W.C., C.S.
and S.N., designed the experiments and wrote the paper; S.N.,
M.W.C., C.S. and J.Z.S. performed the experiments and S.N.,
A.L.S., D.S. and M.D.R. performed data analysis.
Supplementary materials can be found at:
was permuted and a trimmed mean of t-statistic was calculated,
which represented the null distribution. A false discovery rate
(FDR) analysis was performed to find the expected percentage of
false discoveries beyond a given cut off, for which the permuted
data was used. The selected cut off was as +4 or -4, with an esti-
mated FDR of 5%. Based on this cut off, regions of chromosome
7 were identified as regions of putative differential DNA methyla-
tion. Affymetrix promoter array signals and t-statistic scores were
visualized using Integrated Genome Browser (IGB-Affymetrix).
Calculation of local CpG density. We use the definition of
local CpG density given by Pellizola et al.35 with a window of
500 bp. Briefly, the local CpG density is a weighted count of CpG
sites in the genome upstream and downstream 500 bases from a
given point of interest (e.g., microarray probe location). Weight
decreases linearly from 1 at the center of the point of interest to
0 at 500 bases up or downstream. The score is a reflection of the
number of CpG sites in close proximity to the point of interest
and is a measure of GC content. The median CpG density score
for a CpG island (as defined by UCSC) was calculated and a
CpG density of 12 or greater represents a CpG island.
DNA extraction and bisulfite treatment. DNA was extracted
from PrEC and LNCaP cell lines using the Puragene extraction
kit (Gentra Systems). Bisulfite treatment was carried out on 2 μg
of DNA as described previously.36
Quantitative massARRAY methylation analysis. Sequenom
MassARRAY methylation analysis was performed as described
previously.21 Two μg of DNA extracted from PrEC and LNCaP
cell lines were bisulfite treated using the standard bisulfite pro-
tocol.36 As controls for the methylation analysis, whole genome
amplified (WGA) DNA (0% methylated) and M.SssI treated
DNA (100% methylated) were bisulfite treated in parallel. The
primers were designed using the EpiDesignerBETA software from
Sequenom (see Sup. Table S1 for sequences). Each reverse primer
has a T7-promoter tag (5-CAG TAA TAC GAC TCA CTA TAG
GGA GAA GGC T-3) and each forward primer has a 10-mer tag
(5-AGG AAG AGA G-3). A total of 50 primer pairs were designed
for the 42 regions at positions in regions where the three methods
showed the best t-stat score (Fig. 2B). Upon testing these prim-
ers on bisulfite treated DNA, all the primers gave specific PCR
products at a Tm of 60°C. In order to check for potential PCR
bias towards methylated or non-methylated sequences, we used
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