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: ebisu@riken.jp (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, http://www.riken.jp/engn/r-world/research/lab/unit/ 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 (http://www.arabidopsis.org/) and MIPS (http://mips.gsf.de/proj/plant/jsf/index.jsp) 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. References 1 Hatada I, Hayashizaki Y, Hirotsune S, Komatsubara H & Mukai T (1991) A genomic scanning method for higher organisms using restriction sites as landmarks. Proc Natl Acad Sci USA 88, 9523–9527. 2 Hayashizaki Y & Watanabe S (1997) Restriction Land- mark Genomic Scanning (RLGS). Springer, Tokyo. 3 Hirotsune S, Hatada I, Komatsubara H, Nagai H, Kuma K, Kobayakawa K, Kawara T, Nakagawara A, Fujii K, Mukai T et al. (1992) New approach for detec- tion of amplification in cancer DNA using restriction landmark genomic scanning. Cancer Res 52, 3642–3647. Application of Vi-RLGS K. Koike et al. 1614 FEBS Journal 275 (2008) 1608–1616 ª 2008 The Authors Journal compilation ª 2008 FEBS 4 Costello JF, Fru ¨ hwald MC, Smiraglia DJ, Rush LJ, Robertson GP, Gao X, Wright FA, Feramisco JD, Pelt- oma ¨ ki P, Lang JC et al. (2000) Aberrant CpG-island methylation has non-random and tumour-type-specific patterns. Nat Genet 24 , 132–138. 5 Zardo G, Tiirikainen MI, Hong C, Misra A, Feuerstein BG, Volik S, Collins CC, Lamborn KR, Bollen A, Pin- kel D et al. (2002) Integrated genomic and epigenomic analyses pinpoint biallelic gene inactivation in tumors. Nat Genet 32, 453–458. 6 Smiraglia DJ & Plass C (2002) The study of aberrant methylation in cancer via restriction landmark genomic scanning. Oncogene 21, 5414–5426. 7 Hayashizaki Y, Shibata H, Hirotsune S, Sugino H, Okazaki Y, Sasaki N, Hirose K, Imoto H, Okuizumi H, Muramatsu M et al. (1994) Identification and char- acterization of an imprinted U2af binding protein related sequences on mouse chromosome 11 detected by efficient genomic screening using restriction landmark genomic scanning (RLGS-M). Nat Genet 6, 33–40. 8 Plass C, Shibata H, Kalcheva I, Mullins L, Kotelevts- eva N, Mullins J, Okazaki Y, Held WA, Hayashizaki Y & Chapman VM (1996) Identification of Grf1 on mouse chromosome 9 as an imprinted gene by RLGS-M. Nat Genet 14, 106–109. 9 Hayashizaki Y, Hirotsune S, Okazaki Y, Shibata H, Akasako A, Muramatsu M, Kawai J, Hirasawa T, Shiroishi T, Watanabe S et al. (1994) A genetic linkage map of the mouse using restriction landmark genomic scanning (RLGS). Genetics 138, 1207–1238. 10 Okazaki Y, Okuizumi H, Ohsumi T, Nomura O, Tak- ada S, Kamiya M, Sasaki N, Matsuda Y, Nishimura M, Takagi O et al. (1996) A genetic linkage map of the Syrian hamster and localization of cardiomyopathy locus on chromosome 9qa2.1-b1 using RLGS spot- mapping. Nat Genet 13, 87–90. 11 Kawai J, Hirotsune S, Hirose K, Fushiki S, Watanabe S & Hayashizaki Y (1993) Methylation profiles of geno- mic DNA of mouse developmental brain detected by restriction landmark genomic scanning (RLGS) method. Nucleic Acids Res 21, 5604–5608. 12 Ohsumi T, Okazaki Y, Hirotsune S, Shibata H, Mura- matsu M, Suzuki H, Taga C, Watanabe S & Hayashi- zaki Y (1995) A spot cloning method for restriction landmark genomic scanning. Electrophoresis 16, 203– 209. 13 Hayashizaki Y, Hirotune S, Hatada I, Takamatsu S, Miyamoto C, Furuichi Y & Mukai T (1992) A new method for constructing NotI linking and boundary libraries using a restriction trapper. Genomics 14, 733– 739. 14 Matsuyama T, Kimura MT, Koike K, Abe T, Nakano T, Asami T, Ebisuzaki T, Held WA, Yoshida S & Nagase H (2003) Global methylation screening in the Arabidopsis thaliana and Mus musculus genome: applications of virtual image restriction landmark geno- mic scanning (Vi-RLGS). Nucleic Acids Res 31, 4490– 4496. 15 Arabidopsis Genome Initiative (2000) Analysis of the genome sequence of the flowering plant Arabidopsis tha- liana. Nature 408, 796–815. 16 Southern EM (1979) Measurement of DNA length by gel electrophoresis. Anal Biochem 100, 319–323. 17 Okuizumi H, Matsuyama T & Hayashizaki Y (2004) Restriction landmark genome scanning method. In Encyclopedia of Molecular Cell Biology and Molecular Medicine, Vol. 5, 2nd edn (Meyers RA, ed), pp. 413– 439. Wiley–VCH Verlag, Weinheim. 18 Matsuyama T, Abe T, Bae C-H, Takahashi Y, Kiuchi R, Nakano T, Asami T & Yoshida S (2000) Adaptation of restriction landmark genomic scanning (RLGS) to plant genome analysis. Plant Mol Biol Rep 18, 331– 338. 19 Suzuki H, Kawai J, Taga C, Ozawa N & Watanabe S (1994) A PCR-mediated method for cloning spot DNA on restriction landmark genomic scanning (RLGS) gel. DNA Res 1, 245–250. 20 Chan SW-L, Henderson IR & Jacobson SE (2005) Gar- dening the genome: DNA methylation in Arabidopsis thaliana. Nat Rev 6, 351–360. 21 Zhang X, Yazaki J, Sundaresan A, Cokus S, Chan SW, Chen H, Henderson IR, Shinn P, Pellegrini M, Jacob- sen SE et al. (2006) Genome-wide high-resolution map- ping and functional analysis of DNA methylation in Arabidopsis. Cell 126, 1189–1201. 22 Bird A (2007) DNA methylation patterns and epigenetic memory. Genes Devel 16, 6–21. 23 Messeguer R, Ganal MW, Steffens JC & Tanksley SD (1991) Characterization of the level, target sites and inheritance of cytosine methylation in tomato nuclear DNA. Plant Mol Biol 16, 753–770. 24 Marini JC, Levene SD, Crothers DM & Englund PT (1982) Bent helical structure in kinetoplast DNA. Proc Natl Acad Sci USA 79, 7664–7668. 25 Hattori N, Abe T, Hattori N, Suzuki M, Matsuyama T, Yoshida S, Li E & Shiota K (2004) Preference of DNA methyltransferases for CpG islands in mouse embryonic stem cells. Genome Res 14, 1733–1740. 26 Song F, Smith JF, Kimura MT, Morrow AD, Matsuy- ama T, Nagase H & Held WA (2005) Association of tis- sue-specific differentially methylated regions (TDMs) with differential gene expression. Proc Natl Acad Sci USA 102, 3336–3341. 27 Rouillard JM, Erson AE, Kuick R, Asakawa J, Wim- mer K, Muleris M, Petty EM & Hanash S (2001) Vir- tual genome scan: a tool for restriction landmark-based scanning of the human genome. Genome Res 11, 1453– 1459. 28 Smiraglia D, Kazhiyur-Mannar R, Oakes C, Wu Y, Liang P, Ansari T, Su J, Rush L, Smith L, Yu L et al. K. Koike et al. Application of Vi-RLGS FEBS Journal 275 (2008) 1608–1616 ª 2008 The Authors Journal compilation ª 2008 FEBS 1615 (2007) Restriction landmark genomic scanning (RLGS) spot identification by second generation virtual RLGS in multiple genomes with multiple enzyme combina- tions. BMC Genomics 8, 446. 29 Ratel D, Ravanat JL, Berger F & Wion D (2006) N6-methyladenine: the other methylated base of DNA. BioEssays 28, 309–315. 30 Ichida H, Matsuyama T, Abe T & Koba T (2007) DNA adenine methylation changes dramatically during establishment of symbiosis. FEBS J 274, 951–962. 31 Ichida H, Maeda K, Ichise H, Matsuyama T, Abe T, Yoneyama K & Koba T (2007) In silico restriction landmark genome scanning analysis of Xanthomonas oryzae pathovar oryzae MAFF 311018. Biochem Bio- phys Res Commun 363, 852–856. 32 Zilberman D, Gehring M, Tran RK, Ballinger T & Henikoff S (2007) Genome-wide analysis of Arabidopsis thaliana DNA methylation uncovers an interdependence between methylation and transcription. Nat Genet 39, 61–69. Application of Vi-RLGS K. Koike et al. 1616 FEBS Journal 275 (2008) 1608–1616 ª 2008 The Authors Journal compilation ª 2008 FEBS . MINIREVIEW Epigenetics: application of virtual image restriction landmark genomic scanning (Vi-RLGS) Kuniaki Koike 1 , Tomoki Matsuyama 2 and. profiling of Arabidopsis thaliana. Abbreviations 5mC, 5¢-methylcytosine; RLGS, restriction landmark genomic scanning; RLGSSIM, restriction landmark genomic scanning