Báo cáo khoa học: Epigenetics: application of virtual image restriction landmark genomic scanning (Vi-RLGS) pptx

MINIREVIEW
Epigenetics: application of virtual image restriction
landmark genomic scanning (Vi-RLGS)
Kuniaki Koike
1
, Tomoki Matsuyama
2
and Toshikazu Ebisuzaki
1
1 Computational Astrophysics Laboratory, Discovery Research Institute, RIKEN, Saitama, Japan
2 Plant Breeding and Cell Engineering Research Unit, Discovery Research Institute, RIKEN, Saitama, Japan
Restriction landmark genomic scanning (RLGS) uses
restriction enzyme sites as landmarks [1,2] and is used
in the detection of DNA polymorphisms caused by
genetic mutations and hyper- or hypomethylation
changes in cancer cells [3–6], imprinted genes [7,8] and
linkage maps [9,10]. This method is an especially
powerful tool in DNA methylation studies using
methylation-sensitive restriction enzymes, as it allows
genome-wide scanning to detect alterations in DNA
methylation after fractionation of DNA fragments by
high-resolution, 2D gel electrophoresis [4–8,11].
The RLGS procedure is shown in Fig. 1. First,
restriction landmarks, typically those of rare-cutter
enzymes, are labeled directly with a radioisotope and
subjected to 1D electrophoresis in an agarose gel. In
most cases, the DNA is digested with six-cutter
enzymes for clear fractionation in 1D electrophoresis
(step I, Fig. 1). Next, the fractionated DNA is digested
with a four-cutter enzyme and subjected to 2D gel
electrophoresis in a polyacrylamide gel (step II,

Fig. 1). The separated DNA is visualized as a pattern
of spots after exposure to X-ray film (step III, Fig. 1).
Thousands of spots can be identified with good repro-
ducibility. Different landmark restriction enzymes
allow further extension of the scanning field. In addi-
tion, the autoradiographic intensity of the spots clearly
reflects copy number and allows quantitative analysis,
as labeling occurs only at landmark enzyme sites.
Therefore, in contrast to PCR-mediated methods,
changes in epigenetic alterations caused by DNA
methylation can be analyzed using differences in
RLGS spots.
Keywords
Arabidopsis; DNA methylation; DNA
polymorphism; electrophoresis; epigenetics;
in silico; mutant; 5mC; N6-methyladenine;
Vi-RLGS
Correspondence
T. Ebisuzaki, Computational Astrophysics
Laboratory, Discovery Research Institute,
RIKEN, 2-1 Hirosawa, Wako,
Saitama 351-0198, Japan
Fax: +81 48 467 4078
Tel: +81 48 467 9414
E-mail:
(Received 30 November 2007, revised
28 January 2008, accepted 1 February 2008)
doi:10.1111/j.1742-4658.2008.06329.x
Restriction landmark genomic scanning (RLGS) is a powerful method for
the systematic detection of genetic mutations in DNA length and epigenetic

alteration due to DNA methylation. However, the identification of poly-
morphic spots is difficult because the resulting RLGS spots contain very
little target DNA and many non-labeled DNA fragments. To overcome
this, we developed a virtual image restriction landmark genomic scanning
(Vi-RLGS) system to compare actual RLGS patterns with computer-simu-
lated RLGS patterns (virtual RLGS patterns). Here, we demonstrate in
detail the contents of the simulation program (rlgssim), based on the lin-
ear relationship between the reciprocal of mobility plotted against DNA
fragment length and Vi-RLGS profiling of Arabidopsis thaliana.
Abbreviations
5mC, 5¢-methylcytosine; RLGS, restriction landmark genomic scanning;
RLGSSIM, restriction landmark genomic scanning simulation software;
Vi-RLGS, virtual image restriction landmark genomic scanning.
1608 FEBS Journal 275 (2008) 1608–1616 ª 2008 The Authors Journal compilation ª 2008 FEBS
The most important step in developing analyses using
RLGS profiles is the cloning of target spots. However,
the amount of DNA available for cloning in a single
spot is very small. For example, 1.5 lg of mouse geno-
mic DNA used in an RLGS analysis results in atto-
moles (10
)18
) of target DNA available for ligation when
all of the DNA molecules are recovered from the poly-
acrylamide gel. In addition, the isolated gel fragment
contains 2000· more non-labeled than labeled DNA
fragments [12]. In most trials, non-target DNA has been
amplified using PCR-adapter methods. Restriction trap-
per-based methods are limited to the purification of
NotI landmarks [13]. Therefore, the most difficult step
in RLGS analysis is recovering the target DNA.

To overcome this problem, we developed a novel
in silico system for identifying spots using computer
simulation software (rlgssim ) and designated virtual
image restriction landmark genomic scanning
(Vi-RLGS) based on organisms for which the entire
genomic DNA sequence is known [14,15].
Simulation software: RLGSSIM
Algorithm
First, rlgssim reads sequences to generate a pattern.
The program can read sequences in GenBank or
FASTA format. Next, the program generates the elec-
trophoresis pattern.
Figure 2 illustrates the simulation procedure that
follows:
Step 1. The sequence is cut into fragments; for exam-
ple, ‘Fragment-A’ is cut with restriction enzyme A.
Step 2. Restriction enzyme B cuts Fragment-A into
‘Fragment-AB’ and ‘Fragment-BB’.
Step 3. The X-dimensional mobility of Fragment-AB is
calculated.
Step 4. Restriction enzyme C cuts Fragment-AB into
further fragments, including ‘Fragment-AC’.
Step 5. The Y-dimensional mobility of Fragment-AC
is calculated.
Fig. 1. RLGS procedure. The actual RLGS pattern is generated by NotI–EcoRV–MboI (restriction enzymes A–B–C, respectively) in rice. ‘a’,
‘b’ and ‘c’ indicate the respective restriction enzyme end sites.
K. Koike et al. Application of Vi-RLGS
FEBS Journal 275 (2008) 1608–1616 ª 2008 The Authors Journal compilation ª 2008 FEBS 1609
These steps generate 2D mobility (X,Y) values for
each fragment of a given DNA sequence and combina-

tion of restriction enzymes. Because the electrophoresis
time is constant for each fragment, we can plot the 2D
mobility (X,Y) of each fragment to generate a virtual
2D electrophoresis image.
A fragment containing the origin or end point of
each sequence might not be valid because each
sequence (clone) may be divided from a single long
sequence. Therefore, we added information to indicate
if a fragment included the origin or end point of each
sequence.
Implementation
The main components of the simulation engine are a
sequence-reading module and electrophoresis-simula-
tion module. We developed these modules in the
C++ language.
Sequence-reading module
We implemented the sequence multi-format reading
module, which is capable of reading GenBank, FASTA
and original sequence formats, in our laboratory.
This module is designed for object-oriented program-
ming. The sequence reader consists of a main reader
module and specific format (GenBank, FASTA and
original format) parsers. The main reader module is
completely separate from specific format parsers, allow-
ing us to easily add new format types to the sequence
reader module. The main reader module reads a
sequence file to a memory buffer, then determines the
sequence format using the format parsers. The format
parsers check the validity of the sequence, and send
this information to the main reader module. If the

sequence format can be determined, the main reader
module reads the sequence; otherwise, it reports error
information to the user. Unknown or discontinuous
parts of the sequence (such as ‘N’) are reported to the
user to help determine the validity of a result spot.
The 2D electrophoresis-simulation engine
The main components of the simulation engine are a
restriction enzyme component, mobility calculator and
2D electrophoresis component. The restriction enzyme
component splits a sequence into fragments using
given recognition sequences and cut positions as
parameters. The component finds the recognition
sequence in the main sequence, and then splits it into
fragments at the given position.
The mobility calculator calculates the mobility of
the fragment sequence. The mobility is determined
Fig. 2. Simulation procedure. The letters ‘i’, ‘j’ and ‘k’ indicate the DNA fragments resulting from digestion by restriction enzymes A, B and
C, respectively. ‘a’, ‘b’ and ‘c’ correspond to the restriction enzyme sites in Fig. 1. Figure 3 shows their computational handling.
Application of Vi-RLGS K. Koike et al.
1610 FEBS Journal 275 (2008) 1608–1616 ª 2008 The Authors Journal compilation ª 2008 FEBS
solely from the length of the fragment reported in
sequence databases. The reciprocal of mobility (m)
plotted against fragment length (l) is linear [16,17]. We
use the following formulae:
m
x
¼
76:368
l
x

½kBpþ1:032
þ 3:745 ð1Þ
m
y
¼
15850:043
l
y
½kBpþ476:068
À 3:521 ð2Þ
where l
x
is fragment length for the X direction, m
x
is
the mobility corresponding to the X direction of the
fragment, l
y
is fragment length for the Y direction and
m
y
is the mobility corresponding to the Y direction of
the fragment. Each coefficient is calculated from actual
surveys of actual RLGS patterns using 100-bp or 1-kb
ladder markers.
The 2D electrophoresis engine generates data for
each spot from the sequence and information on
restriction enzymes A, B and C. Each spot contains
the following data: (a) sequence of the fragment; (b)
X-direction mobility (m

x
); (c) Y-direction mobility
(m
y
); (d) marking flag (if set, the spot is visible); and
(e) an edge flag.
To visualize these spots, we plot (m
x
, m
y
)ona2D
plane for marked spots. In Fig. 3, we show how to
generate these spots from a given sequence and the
restriction enzymes.
The 2D electrophoresis flow
The flowchart in Fig. 3 summarizes the operation
using the designations: RezA, RezB and RezC, restric-
tion enzymes A, B and C, respectively; seq, sequence
data; wfrag, xfrag and yfrag, sequence array; wfrag[i],
ith sequence in the wfrag array; wfrag, fragments split
by restriction enzyme A; xfrag, fragments split by
restriction enzyme B; yfrag, fragments split by restric-
tion enzyme C; and the subscripts i, j and k denote
positions within the sequence.
First, the original sequence is split by restriction
enzyme A to yield wfrag. Next, wfrag fragments are
split by restriction enzyme B to yield xfrag. At this
stage, the X-direction mobility is calculated for each
fragment in xfrag. Next, the xfrag fragments are split
by restriction enzyme C to yfrag, and the Y-direction

mobility is calculated for yfrag fragments. A marked
flag is set if the fragment has an A-edge, and an edge
flag is set if the fragment contains an origin or end
point of the original sequence.
User interface
To set the parameters and view the result on the
screen, we built a graphical user interface (Fig. 4). We
can specify the restriction enzymes and the list
of sequences graphically and view the generated 2D
Fig. 3. Flowchart of the 2D electrophoresis simulation in virtual RLGS.
K. Koike et al. Application of Vi-RLGS
FEBS Journal 275 (2008) 1608–1616 ª 2008 The Authors Journal compilation ª 2008 FEBS 1611
electrophoresis pattern. We implemented the graphical
user interface using the Microsoft Foundation Classes
(MFC) library, which provides the framework for
standard Windows OS application programs. The user
interface layer also has a function that allows us to
load and store spot data in a storage file. This layer
can manage the relative positions of several sequences
and show their electrophoresis images in the same win-
dow. Thus, we can easily specify the clone to which a
selected spot belongs. This software can be accessed at
RIKEN DRI (contact T. Matsuyama or T. Ebisuzaki,
/>breeding/index.html).
RLGS profiling using the Vi-RLGS
system
The entire nuclear genomic DNA sequence of the
model plant Arabidopsis thaliana (L.) Heynh. (Colum-
bia) is known [15]. Because the information available
on TAIR ( and MIPS

( has a high
degree of accuracy and NotI is used as a universal
restriction landmark enzyme in animal and plant
RLGS analysis, we evaluated the system by first per-
forming a NotI–Arabidopsis simulation profile using
our Vi-RLGS system, and EcoRV and MboIas
enzymes B and C, respectively (NotI–EcoRV–MboI).
The actual pattern, which is in the range 0.6–7.5 kb
in the first dimension and 50–800 bp in the second
dimension, is shown in Fig. 5A. The virtual pattern
corresponding to the range enclosed by the broken line
is shown in Fig. 5B. The spots indicated by arrows in
Fig. 5A were cut from the gel and cloned using the
PCR-adapter ligation method [18,19]. Sequencing con-
firmed that their patterns concurred with those
expected from Vi-RLGS theory. The differences in
number and pattern of spots in Fig. 5A,B may have
Fig. 4. Screenshot of the 2D electrophoresis simulator (RLGSSIM). The right-hand panel is the image resulting from the simulation, and the
left-hand panel shows the processed sequence information. If the clone (sequence) is checked, the clone has spots in the right panel.
Clones (sequences) are categorized by group, and the relative position of each clone (sequence) is shown in the left-hand panel. The arrow
indicates a spot that was selected, and sequence information for the spot is displayed on the screen.
Application of Vi-RLGS K. Koike et al.
1612 FEBS Journal 275 (2008) 1608–1616 ª 2008 The Authors Journal compilation ª 2008 FEBS
been due to gaps in the Arabidopsis genomic DNA
sequence, for example, from highly repeated sequences
such as centromeres, telomeres, ribosomal RNA gene
clusters and their flanking-region DNA sequences that
have not yet been reported, and DNA modification by
DNA methylation.
In plant DNA, 5¢-methylcytosine (5mC) occurs at

cytosine residues in symmetrical sequences, CpG and
CpNpG (where N is any nucleotide), due to the
actions of MET1, DRM1 ⁄ 2 and CMT3 [20–22]. In
Arabidopsis, the 5mC content (5mC⁄ 5mC+C) is
$ 5.2% [14,23]. Because only NotI is sensitive to 5mC,
and EcoRV and MboI are insensitive, this difference
results in the recognition of DNA methylation at NotI
sites. The spots indicated by black arrowheads in
Fig. 5B were present in virtual RLGS patterns but
absent in actual RLGS patterns. The influence of 5mC
at NotI landmarks was confirmed using the bisulfite
sequencing method and Vi-RLGS analysis of $ 20%-
reduced 5mC hypomethylated Arabidopsis plants gen-
erated using 5-aza-2¢-deoxycytidine. Therefore, the
masked spots resulted mainly from DNA methylation.
However, genome-wide detection of methylated regions
in Arabidopsis genomic DNA can be realized only by
gathering information from spots present in virtual
RLGS patterns but absent in actual RLGS patterns
[14].
However, the spot indicated by the white arrowhead
in Fig. 5B has slightly different mobility in the 2D
Vi-RLGS profile. This phenomenon was observed
mainly in 2D high molecular mass regions ($ 500 bp).
We speculate that they resulted from sequence gaps or
sliding due to methylation in the flanking regions. In
addition, in 2D polyacrylamide gels, the electrophore-
sis mobility of short DNA fragments was affected by
their base composition and sequence. For example,
curved DNA caused by short adenine tracts may move

aberrantly. However, when we reduced the polyacryl-
II
1F10F5
5K18P6
3T4P13
5F2G14
5MPI10
5K18P6
1F7G19
5MDC12
4F13C5
5F18A17
1F19G10
4T11J8
3F4F8
5F2G14
2F24C20
5F2K13
4T16H5
5MTH12
5MIK19
1F1019
3MMB12
1T23F18
3T8H10
3K7M2
4T13J8
2T9F8
3F3C22
4T16H5

4T805
4FCA1
4F20M13
5MIK19
2F14M4
1T19D16
2T1014
3F15G16
3K10D20
4F17A13
3F16L2
3F1C9
1T14N5
3F3C22
1F12K11
1F3M18
2T9J23
3T7M13
4F4D11
1T14P4
3F9F8
1F9L1
4FI10
5MWF20
1F10K1
D
3K10D20
1F9L1
1F3M18
5MKD15

1F1019
4FCA1
1T3F24
1F2K11
3K7L4
1F16F4
5F502
5K17N15
4F4I10
3MYM9
5MWF20
5MWF20
5K19B1
5MKD15
3F26K24
1F19G10
2T29F13
1F25P22
4F26F21
5F8L15
5K17H15
5K19B13
1T23K23
1T3F24
5F7K24
3MFD22
2F3L12
3F8A24
4T805
4F17A13

4T30C3
3F16L2
2T29F13
3MLN21
4T15F16
3MYM9
2F3L12
3T18B22
3F17A17
3T4P13
I
C
2D (bp)
A
500
200
1.0
2.0
5.0
1D (kb)
I
II
B
T20O10
T26N6
F17A13
FCA2
F7A10
T300
F16L2

T29F13
MBK21
MLN21
T15F16 MYM9
F3L12
T22N4
F17A17
T18B22
F2O106
K17N1524
F4I10
MKD15
T18B22
T20J72
F26K24
F15F4
MYM9
J24
MWF20
MWF20
K19B1
00
7
MTH12
U22
Fig. 5. Vi-RLGS profiling of Arabidopsis. (A) Actual RLGS pattern, (B) virtual RLGS pattern, corresponding to the sequence indicated by the
broken line. The spots indicated by arrowheads are absent or have slightly different mobility in (C). (C,D) Vi-RLGS profiles generated by
matching the actual with the virtual RLGS patterns.
K. Koike et al. Application of Vi-RLGS
FEBS Journal 275 (2008) 1608–1616 ª 2008 The Authors Journal compilation ª 2008 FEBS 1613

amide gel concentration from 5 to 4%, the aberrant
motion was dispelled, and the actual RLGS spots were
similar to Vi-RLGS patterns. In addition, we con-
firmed that the DNA fragments of Arabidopsis chloro-
plast DNA (accession number: AP000426, position:
58 165–58 777), which showed aberrant mobility in
Vi-RLGS profiling, were used in PAGE with the usual
slab-style gels at a high temperature (45 °C) and the
differential mobility was also dispelled (data not
shown). These results demonstrate that Vi-RLGS pro-
filing of the actual pattern and the virtual pattern pos-
sess inherent problems caused by secondary structure;
these differences need to be noted for spot identifica-
tion. However, as the secondary structure of DNA,
such as DNA curvature caused by the architecture of
nucleoprotein complexes, is thought to be involved in
biological processes [24], Vi-RLGS analysis may also
be suitable for detecting regions that indicate a rela-
tionship with gene expression.
Despite these anomalies, a comparison of virtual and
actual RLGS patterns showed that Vi-RLGS identified
85.5% of the spots in the actual RLGS pattern, and
was able to generate Vi-RLGS profiles that allowed
effective and rapid quantitative analysis of 5mC status
at NotI sites and their flanking regions (Fig. 5C,D). In
theory, this method allows the study of epigenetic
changes caused by 5mC in all organisms, including
humans, animals, plants and micro-organisms such as
bacteria, fungi and algae that possess bulk DNA
sequences, even without detailed DNA sequence infor-

mation. In fact, many actual RLGS spots of mouse
genomic DNA have been verified, and the Vi-RLGS
system is effective for epigenetic studies of tissue-
specific differentially methylated regions and embryonic
stem cells [25,26]. Various in silico systems have been
developed and have demonstrated high validity in
RLGS analysis, similar to the Vi-RLGS system [27,28].
In addition, bacterial genomic DNA possesses N6-
methyladenine at GATC and GANTC sites caused by
deoxyadenosine methyltransferase and cell-cycle-regu-
lated methyltransferase [29]. Recently, Vi-RLGS analy-
ses of N6-methyladenine alterations in the genomic
DNA of the symbiont Mesorhizobium loti and the plant
pathogen Xanthomonas oryzae have been reported
[30,31]. Our system using N6-methyladenine-sensitive
restriction enzymes, such as MboI and HinfI, is capable
of expanding the genomic analysis of microorganisms
as their whole genomic DNA sequences are reported.
Conclusions
Cloning target RLGS spots is very time- and labor-
intensive. Vi-RLGS saves considerable time and effort,
and utilizes a simple procedure for identifying target
spots in RLGS analysis and screening of suitable
restriction enzymes. The typical RLGS analysis is lim-
ited to between 0.5 and 6.0 kb in the first dimension
and no more than 100 bp in the second dimension
because of constraints in cloning procedure efficiency
and the reproducibility of spot signal intensity. Our
Vi-RLGS analysis overcomes these limitations and
expands the scanning field and ability to detect

changes in genomic DNA.
Moreover, in typical analyses, the cloning step
requires a large amount of genomic DNA. Thus, in
plant studies, obtaining sufficient DNA for RLGS
analysis of particular tissues and organs at various
developmental stages is difficult. Vi-RLGS profiles
generated in advance overcome these problems and
allow instant analysis of genome status at each devel-
opmental stage, as target spots can be identified from
a single profile with a very small amount of applied
DNA.
The Vi-RLGS system, consisting of electrophoresis,
restriction enzyme digestion and in silico analysis, has
good reproducibility and high resolution ability at
both unique gene regions and methylated repetitive
sequences [21,32]. Thus, the Vi-RLGS system offers a
different spectrum of mutation detection than that of
microarrays and will be a valuable tool for detecting
both genetic mutations in DNA lengths and epigenetic
alterations with DNA modification in post-genomic
sequencing research.
Acknowledgements
We thank Dr D. J. Smiraglia for his critical reading of
this manuscript. This study was supported by a grant
from the Research Collaborations with Industry Pro-
gram, RIKEN. TM is supported by a grant for Basic
Science Research Projects from the Sumitomo Founda-
tion.
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