DNA methylation is a biochemical process where a methyl group is added to the cytosine or adenine DNA nucleotides. The rate of cytosine DNA methylation differs strongly between species, e.g. absolute quantification by mass spectrometry revealed 14% of cytosines methylated in Arabidopsis thaliana, 8% in Mus musculus, 2.3% in Escherichia coli, 0.03% in Drosophila, and virtually none (< 0.0002%) in yeast species. DNA methylation may stably alter the expression of genes in cells as cells divide and differentiate from embryonic stem cells into specific tissues. The resulting change is normally permanent and unidirectional, preventing a cell from reverting to a stem cell or converting into a different cell type. DNA methylation is typically removed during zygote formation and re-established through successive cell divisions during development. However, the latest research shows that hydroxylation of methyl groups occurs rather than complete removal of methyl groups in the zygote. Some methylation modifications that regulate gene expression are heritable and cause genomic imprinting.
DNA methylation suppresses the expression of endogenous retroviral genes and other harmful stretches of DNA that have been incorporated into the host genome over time. DNA methylation also forms the basis of chromatin structure, which enables a single cell to grow into multiple organs or perform multiple functions. DNA methylation also plays a crucial role in the development of nearly all types of cancer.
DNA methylation at the 5 position of cytosine has the specific effect of reducing gene expression and has been found in every vertebrate examined. In adult somatic cells (cells in the body, not used for reproduction), DNA methylation typically occurs in a CpG dinucleotide context; non-CpG methylation is prevalent in embryonic stem cells, and has also been indicated in neural development.
- 1 In mammals
- 2 DNA methyltransferases
- 3 In plants
- 4 In fungi
- 5 In insects
- 6 In bacteria
- 7 Detection
- 8 Differentially methylated regions (DMRs)
- 9 Computational prediction
- 10 See also
- 11 References
- 12 Further reading
- 13 External links
- For significant overlapping coverage, see also Methylation.
DNA methylation is essential for normal development and is associated with a number of key processes including genomic imprinting, X-chromosome inactivation, suppression of repetitive elements, and carcinogenesis.
Between 60% and 90% of all CpGs are methylated in mammals. Methylated C residues spontaneously deaminate to form T residues over time; hence CpG dinucleotides steadily deaminate to TpG dinucleotides, which is evidenced by the under-representation of CpG dinucleotides in the human genome (they occur at only 21% of the expected frequency). (On the other hand, spontaneous deamination of unmethylated C residues gives rise to U residues, a change that is quickly recognized and repaired by the cell.)
Unmethylated CpGs are often grouped in clusters called CpG islands, which are present in the 5' regulatory regions of many genes. In many disease processes, such as cancer, gene promoter CpG islands acquire abnormal hypermethylation, which results in transcriptional silencing that can be inherited by daughter cells following cell division. Alterations of DNA methylation have been recognized as an important component of cancer development. Hypomethylation, in general, arises earlier and is linked to chromosomal instability and loss of imprinting, whereas hypermethylation is associated with promoters and can arise secondary to gene (oncogene suppressor) silencing, but might be a target for epigenetic therapy.
DNA methylation may affect the transcription of genes in two ways. First, the methylation of DNA itself may physically impede the binding of transcriptional proteins to the gene, and second, and likely more important, methylated DNA may be bound by proteins known as methyl-CpG-binding domain proteins (MBDs). MBD proteins then recruit additional proteins to the locus, such as histone deacetylases and other chromatin remodeling proteins that can modify histones, thereby forming compact, inactive chromatin, termed heterochromatin. This link between DNA methylation and chromatin structure is very important. In particular, loss of methyl-CpG-binding protein 2 (MeCP2) has been implicated in Rett syndrome; and methyl-CpG-binding domain protein 2 (MBD2) mediates the transcriptional silencing of hypermethylated genes in cancer.
DNA methylation is an important regulator of gene transcription and a large body of evidence has demonstrated that genes with high levels of 5-methylcytosine in their promoter region are transcriptionally silent, and that DNA methylation gradually accumulates upon long-term gene silencing. DNA methylation is essential during embryonic development, and in somatic cells, patterns of DNA methylation are generally transmitted to daughter cells with a high fidelity. Aberrant DNA methylation patterns – hypermethylation and hypomethylation compared to normal tissue – have been associated with a large number of human malignancies. Hypermethylation typically occurs at CpG islands in the promoter region and is associated with gene inactivation. A lower level of leukocyte DNA methylation is associated with many types of cancer. Global hypomethylation has also been implicated in the development and progression of cancer through different mechanisms. Typically, there is hypermethylation of tumor suppressor genes and hypomethylation of oncogenes.
Epigenetic modifications such as DNA methylation have been implicated in cardiovascular disease, including atherosclerosis. In animal models of atherosclerosis, vascular tissue as well as blood cells such as mononuclear blood cells exhibit global hypomethylation with gene-specific areas of hypermethylation. DNA methylation polymorphisms may be used as an early biomarker of atherosclerosis since they are present before lesions are observed, which may provide an early tool for detection and risk prevention.
Two of the cell types targeted for DNA methylation polymorphisms are monocytes and lymphocytes, which experience an overall hypomethylation. One proposed mechanism behind this global hypomethylation is elevated homocysteine levels causing hyperhomocysteinemia, a known risk factor for cardiovascular disease. High plasma levels of homocysteine inhibit DNA methyltransferases, which causes hypomethylation. Hypomethylation of DNA affects gene that alter smooth muscle cell proliferation, cause endothelial cell dysfunction, and increase inflammatory mediators, all of which are critical in forming atherosclerotic lesions. High levels of homocysteine also result in hypermethylation of CpG islands in the promoter region of the estrogen receptor alpha (ERα) gene, causing its down regulation. ERα protects against atherosclerosis due to its action as a growth suppressor, causing the smooth muscle cells to remain in a quiescent state. Hypermethylation of the ERα promoter thus allows intimal smooth muscle cells to proliferate excessively and contribute to the development of the atherosclerotic lesion.
Another gene that experiences a change in methylation status in atherosclerosis is the monocarboxylate transporter (MCT3), which produces a protein responsible for the transport of lactate and other ketone bodies out of many cell types, including vascular smooth muscle cells. In atherosclerosis patients, there is an increase in methylation of the CpG islands in exon 2, which decreases MCT3 protein expression. The down regulation of MCT3 impairs lactate transport, and significantly increases smooth muscle cell proliferation, which further contributes to the atherosclerotic lesion. An ex vivo experiment using the demethylating agent Decitabine (5-aza-2 -deoxycytidine) was shown to induce MCT3 expression in a dose dependant manner, as all hypermethylated sites in the exon 2 CpG island became demethylated after treatment. This may serve as a novel therapeutic agent to treat atherosclerosis, although no human studies have been conducted thus far.
A longitudinal study of twin children showed that, between the ages of 5 and 10, there was divergence of methylation patterns due to environmental rather than genetic influences. There is a global loss of DNA methylation during aging. However, some genes become hypermethylated with age, including genes for the estrogen receptor, p16, and insulin-like growth factor 2. Biological clocks, such as an epigenetic clock, are promising biomarkers of aging.
High intensity exercise has been shown to result in reduced DNA methylation in skeletal muscle. Promoter methylation of PGC-1α and PDK4 were immediately reduced after high intensity exercise, whereas PPAR-γ methylation was not reduced until three hours after exercise. By contrast, six months of exercise in previously sedentary middle-age men resulted in increased methylation in adipose tissue. One study showed a possible increase in global genomic DNA methylation of white blood cells with more physical activity in non-Hispanics.
In mammalian cells, DNA methylation occurs mainly at the C5 position of CpG dinucleotides and is carried out by two general classes of enzymatic activities – maintenance methylation and de novo methylation.
Maintenance methylation activity is necessary to preserve DNA methylation after every cellular DNA replication cycle. Without the DNA methyltransferase (DNMT), the replication machinery itself would produce daughter strands that are unmethylated and, over time, would lead to passive demethylation. DNMT1 is the proposed maintenance methyltransferase that is responsible for copying DNA methylation patterns to the daughter strands during DNA replication. Mouse models with both copies of DNMT1 deleted are embryonic lethal at approximately day 9, due to the requirement of DNMT1 activity for development in mammalian cells.
It is thought that DNMT3a and DNMT3b are the de novo methyltransferases that set up DNA methylation patterns early in development. DNMT3L is a protein that is homologous to the other DNMT3s but has no catalytic activity. Instead, DNMT3L assists the de novo methyltransferases by increasing their ability to bind to DNA and stimulating their activity. Finally, DNMT2 (TRDMT1) has been identified as a DNA methyltransferase homolog, containing all 10 sequence motifs common to all DNA methyltransferases; however, DNMT2 (TRDMT1) does not methylate DNA but instead methylates cytosine-38 in the anticodon loop of aspartic acid transfer RNA.
Since many tumor suppressor genes are silenced by DNA methylation during carcinogenesis, there have been attempts to re-express these genes by inhibiting the DNMTs. 5-Aza-2'-deoxycytidine (decitabine) is a nucleoside analog that inhibits DNMTs by trapping them in a covalent complex on DNA by preventing the β-elimination step of catalysis, thus resulting in the enzymes' degradation. However, for decitabine to be active, it must be incorporated into the genome of the cell, which can cause mutations in the daughter cells if the cell does not die. In addition, decitabine is toxic to the bone marrow, which limits the size of its therapeutic window. These pitfalls have led to the development of antisense RNA therapies that target the DNMTs by degrading their mRNAs and preventing their translation. However, it is currently unclear whether targeting DNMT1 alone is sufficient to reactivate tumor suppressor genes silenced by DNA methylation.
Significant progress has been made in understanding DNA methylation in the model plant Arabidopsis thaliana. DNA methylation in plants differs from that of mammals: while DNA methylation in mammals mainly occurs on the cytosine nucleotide in a CpG site, in plants the cytosine can be methylated at CpG, CpHpG, and CpHpH sites, where H represents any nucleotide but guanine. Overall, Arabidopsis DNA is highly methylated, mass spectrometry analysis estimated 14% of cytosines to be modified.
The principal Arabidopsis DNA methyltransferase enzymes, which transfer and covalently attach methyl groups onto DNA, are DRM2, MET1, and CMT3. Both the DRM2 and MET1 proteins share significant homology to the mammalian methyltransferases DNMT3 and DNMT1, respectively, whereas the CMT3 protein is unique to the plant kingdom. There are currently two classes of DNA methyltransferases: 1) the de novo class, or enzymes that create new methylation marks on the DNA; and 2) a maintenance class that recognizes the methylation marks on the parental strand of DNA and transfers new methylation to the daughters strands after DNA replication. DRM2 is the only enzyme that has been implicated as a de novo DNA methyltransferase. DRM2 has also been shown, along with MET1 and CMT3 to be involved in maintaining methylation marks through DNA replication. Other DNA methyltransferases are expressed in plants but have no known function (see the Chromatin Database).
It is not clear how the cell determines the locations of de novo DNA methylation, but evidence suggests that, for many (though not all) locations, RNA-directed DNA methylation (RdDM) is involved. In RdDM, specific RNA transcripts are produced from a genomic DNA template, and this RNA forms secondary structures called double-stranded RNA molecules. The double-stranded RNAs, through either the small interfering RNA (siRNA) or microRNA (miRNA) pathways direct de-novo DNA methylation of the original genomic location that produced the RNA. This sort of mechanism is thought to be important in cellular defense against RNA viruses and/or transposons, both of which often form a double-stranded RNA that can be mutagenic to the host genome. By methylating their genomic locations, through an as yet poorly understood mechanism, they are shut off and are no longer active in the cell, protecting the genome from their mutagenic effect.
Many fungi have low levels (0.1 to 0.5%) of cytosine methylation, whereas other fungi have as much as 5% of the genome methylated. This value seems to vary both among species and among isolates of the same species. There is also evidence that DNA methylation may be involved in state-specific control of gene expression in fungi. However, at a detection limit of 250 attomoles by using ultra-high sensitive mass spectrometry DNA methylation was not confirmed in single cellular yeast species such as Saccharomyces cerevisiae or Schizosaccharomyces pombe, indicating that yeasts do not possess this DNA modification.
Although brewers' yeast (Saccharomyces) and fission yeast (Schizosaccharomyces) have no detectable DNA methylation, the model filamentous fungus Neurospora crassa has a well-characterized methylation system. Several genes control methylation in Neurospora and mutation of the DNA methyl transferase, dim-2, eliminates all DNA methylation but does not affect growth or sexual reproduction. While the Neurospora genome has very little repeated DNA, half of the methylation occurs in repeated DNA including transposon relics and centromeric DNA. The ability to evaluate other important phenomena in a DNA methylase-deficient genetic background makes Neurospora an important system in which to study DNA methylation.
DNA methylation is debated in insects, Drosophila melanogaster for instance seems to possess a very low level of DNA methylation only  that is however too low to be studied by methods such as bisulphite sequencing. Takayama et al. developed a sensitive method that allowed to find that the fly genome DNA sequence patterns that associate with methylation are very different from the patterns seen in humans, or in other animal or plant species to date. Genome methylation in D. melanogaster was found at specific short motifs (concentrated in specific 5-base sequence motifs that are CA- and CT-rich but depleted of guanine) and is independent of DNMT2 activity.
Adenine or cytosine methylation is part of the restriction modification system of many bacteria, in which specific DNA sequences are methylated periodically throughout the genome. A methylase is the enzyme that recognizes a specific sequence and methylates one of the bases in or near that sequence. Foreign DNAs (which are not methylated in this manner) that are introduced into the cell are degraded by sequence-specific restriction enzymes and cleaved. Bacterial genomic DNA is not recognized by these restriction enzymes. The methylation of native DNA acts as a sort of primitive immune system, allowing the bacteria to protect themselves from infection by bacteriophage.
E. coli DNA adenine methyltransferase (Dam) is an enzyme of ~32 kDa that does not belong to a restriction/modification system. The target recognition sequence for E. coli Dam is GATC, as the methylation occurs at the N6 position of the adenine in this sequence (G meATC). The three base pairs flanking each side of this site also influence DNA–Dam binding. Dam plays several key roles in bacterial processes, including mismatch repair, the timing of DNA replication, and gene expression. As a result of DNA replication, the status of GATC sites in the E. coli genome changes from fully methylated to hemimethylated. This is because adenine introduced into the new DNA strand is unmethylated. Re-methylation occurs within two to four seconds, during which time replication errors in the new strand are repaired. Methylation, or its absence, is the marker that allows the repair apparatus of the cell to differentiate between the template and nascent strands. It has been shown that altering Dam activity in bacteria results in increased spontaneous mutation rate. Bacterial viability is compromised in dam mutants that also lack certain other DNA repair enzymes, providing further evidence for the role of Dam in DNA repair.
One region of the DNA that keeps its hemimethylated status for longer is the origin of replication, which has an abundance of GATC sites. This is central to the bacterial mechanism for timing DNA replication. SeqA binds to the origin of replication, sequestering it and thus preventing methylation. Because hemimethylated origins of replication are inactive, this mechanism limits DNA replication to once per cell cycle.
Expression of certain genes, for example those coding for pilus expression in E. coli, is regulated by the methylation of GATC sites in the promoter region of the gene operon. The cells' environmental conditions just after DNA replication determine whether Dam is blocked from methylating a region proximal to or distal from the promoter region. Once the pattern of methylation has been created, the pilus gene transcription is locked in the on or off position until the DNA is again replicated. In E. coli, these pilus operons have important roles in virulence in urinary tract infections. It has been proposed[by whom?] that inhibitors of Dam may function as antibiotics.
On the other hand, DNA cytosine methylase targets CCAGG and CCTGG sites to methylate cytosine at the C5 position (C meC(A/T) GG). The other methylase enzyme, EcoKI, causes methylation of adenines in the sequences AAC(N6)GTGC and GCAC(N6)GTT.
Most strains used by molecular biologists are derivatives of E. coli K-12, and possess both Dam and Dcm, but there are commercially available strains that are dam-/dcm- (lack of activity of either methylase). In fact, it is possible to unmethylate the DNA extracted from dam+/dcm+ strains by transforming it into dam-/dcm- strains. This would help digest sequences that are not being recognized by methylation-sensitive restriction enzymes.
The Restriction enzyme DpnI can recognize 5'-GmeATC-3' sites and digest the methylated DNA. Being such a short motif, it occurs frequently in sequences by chance, and as such its primary use for researchers is to degrade template DNA following PCRs (PCR products lack methylation, as no methylases are present in the reaction). Similarly, some commercially available restriction enzymes are sensitive to methylation at their cognate restriction sites, and must as mentioned previously be used on DNA passed through a dam-/dcm- strain to allow cutting.
DNA methylation can be detected by the following assays currently used in scientific research:
- Mass spectrometry is a very sensitive and reliable analytical method to detect DNA methylation. MS in general is however not informative about the sequence context of the methylation, thus limited in studying the function of this DNA modification.
- Methylation-Specific PCR (MSP), which is based on a chemical reaction of sodium bisulfite with DNA that converts unmethylated cytosines of CpG dinucleotides to uracil or UpG, followed by traditional PCR. However, methylated cytosines will not be converted in this process, and primers are designed to overlap the CpG site of interest, which allows one to determine methylation status as methylated or unmethylated.
- Whole genome bisulfite sequencing, also known as BS-Seq, which is a high-throughput genome-wide analysis of DNA methylation. It is based on aforementioned sodium bisulfite conversion of genomic DNA, which is then sequenced on a Next-generation sequencing platform. The sequences obtained are then re-aligned to the reference genome to determine methylation states of CpG dinucleotides based on mismatches resulting from the conversion of unmethylated cytosines into uracil.
- The HELP assay, which is based on restriction enzymes' differential ability to recognize and cleave methylated and unmethylated CpG DNA sites.
- ChIP-on-chip assays, which is based on the ability of commercially prepared antibodies to bind to DNA methylation-associated proteins like MeCP2.
- Restriction landmark genomic scanning, a complicated and now rarely used assay based upon restriction enzymes' differential recognition of methylated and unmethylated CpG sites; the assay is similar in concept to the HELP assay.
- Methylated DNA immunoprecipitation (MeDIP), analogous to chromatin immunoprecipitation, immunoprecipitation is used to isolate methylated DNA fragments for input into DNA detection methods such as DNA microarrays (MeDIP-chip) or DNA sequencing (MeDIP-seq).
- Pyrosequencing of bisulfite treated DNA. This is sequencing of an amplicon made by a normal forward primer but a biotinylated reverse primer to PCR the gene of choice. The Pyrosequencer then analyses the sample by denaturing the DNA and adding one nucleotide at a time to the mix according to a sequence given by the user. If there is a mis-match, it is recorded and the percentage of DNA for which the mis-match is present is noted. This gives the user a percentage methylation per CpG island.
- Molecular break light assay for DNA adenine methyltransferase activity – an assay that relies on the specificity of the restriction enzyme DpnI for fully methylated (adenine methylation) GATC sites in an oligonucleotide labeled with a fluorophore and quencher. The adenine methyltransferase methylates the oligonucleotide making it a substrate for DpnI. Cutting of the oligonucleotide by DpnI gives rise to a fluorescence increase.
- Methyl Sensitive Southern Blotting is similar to the HELP assay, although uses Southern blotting techniques to probe gene-specific differences in methylation using restriction digests. This technique is used to evaluate local methylation near the binding site for the probe.
- MethylCpG Binding Proteins (MBPs) and fusion proteins containing just the Methyl Binding Domain (MBD) are used to separate native DNA into methylated and unmethylated fractions. The percentage methylation of individual CpG islands can be determined by quantifying the amount of the target in each fraction. Extremely sensitive detection can be achieved in FFPE tissues with abscription-based detection.
- High Resolution Melt Analysis (HRM or HRMA), is a post-PCR analytical technique. The target DNA is treated with sodium bisulfite, which chemically converts unmethylated cytosines into uracils, while methylated cytosines are preserved. PCR amplification is then carried out with primers designed to amplify both methylated and unmethylated templates. After this amplification, highly methylated DNA sequences contain a higher number of CpG sites compared to unmethylated templates, which results in a different melting temperature that can be used in quantitative methylation detection.
Differentially methylated regions (DMRs)
Differentially methylated regions (DMRs), are genomic regions with different methylation statuses among multiple samples (tissues, cells, individuals or others), are regarded as possible functional regions involved in gene transcriptional regulation. The identification of DMRs among multiple tissues (T-DMRs) provides a comprehensive survey of epigenetic differences among human tissues. DMRs between cancer and normal samples (C-DMRs) demonstrate the aberrant methylation in cancers. It is well known that DNA methylation is associated with cell differentiation and proliferation. Many DMRs have been found in the development stages (D-DMRs)  and in the reprogrammed progress (R-DMRs). In addition, there are intra-individual DMRs (Intra-DMRs) with longitudinal changes in global DNA methylation along with the increase of age in a given individual. There are also inter-individual DMRs (Inter-DMRs) with different methylation patterns among multiple individuals.
QDMR (Quantitative Differentially Methylated Regions) is a quantitative approach to quantify methylation difference and identify DMRs from genome-wide methylation profiles by adapting Shannon entropy (http://bioinfo.hrbmu.edu.cn/qdmr). The platform-free and species-free nature of QDMR makes it potentially applicable to various methylation data. This approach provides an effective tool for the high-throughput identification of the functional regions involved in epigenetic regulation. QDMR can be used as an effective tool for the quantification of methylation difference and identification of DMRs across multiple samples.
Gene-set analysis (a.k.a. pathway analysis; usually performed tools such as DAVID, GoSeq or GSEA) has been shown to be severely biased when applied to high-throughput methylation data (e.g. MeDIP-seq, MeDIP-ChIP, HELP-seq etc.), and a wide range of studies have thus mistakenly reported hyper-methylation of genes related to development and differentiation; it has been suggested that this can be corrected using sample label permutations or using a statistical model to control for differences in the numberes of CpG probes / CpG sites that target each gene.
DNA methylation can also be detected by computational models through sophisticated algorithms and methods. Computational models can facilitate the global profiling of DNA methylation across chromosomes, and often such models are faster and cheaper to perform than biological assays. Such up-to-date computational models include Bhasin, et al., Bock, et al., and Zheng, et al.  Together with biological assay, these methods greatly facilitate the DNA methylation analysis.
- Demethylating agent
- DNA demethylation
- DNA methylation age
- Epigenetics, of which DNA methylation is a significant contributor
- Genomic imprinting, an inherited repression of an allele, relying on DNA methylation
- MethDB DNA Methylation database
- Capuano, F; Muelleder, M; Kok, R. M.; Blom, H. J.; Ralser, M (2014). "Cytosine DNA methylation is found in Drosophila melanogaster but absent in Saccharomyces cerevisiae, Schizosaccharomyces pombe and other yeast species". Analytical Chemistry 86 (8): 140318143747008. doi:10.1021/ac500447w. PMC 4006885. PMID 24640988.
- Iqbal, K.; Jin, S. -G.; Pfeifer, G. P.; Szabo, P. E. (2011). "Reprogramming of the paternal genome upon fertilization involves genome-wide oxidation of 5-methylcytosine". Proceedings of the National Academy of Sciences 108 (9): 3642–3647. doi:10.1073/pnas.1014033108. PMC 3048122. PMID 21321204.
- Wossidlo, M.; Nakamura, T.; Lepikhov, K.; Marques, C. J.; Zakhartchenko, V.; Boiani, M.; Arand, J.; Nakano, T.; Reik, W.; Walter, J. R. (2011). "5-Hydroxymethylcytosine in the mammalian zygote is linked with epigenetic reprogramming". Nature Communications 2: 241. doi:10.1038/ncomms1240. PMID 21407207.
- Jaenisch, R.; Bird, A. (2003). "Epigenetic regulation of gene expression: how the genome integrates intrinsic and environmental signals". Nature Genetics. 33 Suppl (3s): 245–254. doi:10.1038/ng1089. PMID 12610534.
- Dodge JE, Ramsahoye BH, Wo ZG, Okano M, Li E (2002). "De novo methylation of MMLV provirus in embryonic stem cells: CpG versus non-CpG methylation". Gene 289 (1–2): 41–48. doi:10.1016/S0378-1119(02)00469-9.
- Haines TR, Rodenhiser DI, Ainsworth PJ (2001). "Allele-Specific Non-CpG Methylation of the Nf1 Gene during Early Mouse Development". Developmental Biology 240 (2): 585–598. doi:10.1006/dbio.2001.0504. PMID 11784085.
- Lister R, Pelizzola M, Dowen RH et al. (October 2009). "Human DNA methylomes at base resolution show widespread epigenomic differences". Nature 462 (7271): 315–22. doi:10.1038/nature08514. PMC 2857523. PMID 19829295.
- Lister, R.; Mukamel, E. A.; Nery, J. R.; Urich, M.; Puddifoot, C. A.; Johnson, N. D.; Lucero, J.; Huang, Y.; Dwork, A. J.; Schultz, M. D.; Yu, M.; Tonti-Filippini, J.; Heyn, H.; Hu, S.; Wu, J. C.; Rao, A.; Esteller, M.; He, C.; Haghighi, F. G.; Sejnowski, T. J.; Behrens, M. M.; Ecker, J. R. (4 July 2013). "Global Epigenomic Reconfiguration During Mammalian Brain Development". Science 341 (6146): 1237905. doi:10.1126/science.1237905.
- Ehrlich M, Gama Sosa MA, Huang L-H., Midgett RM, Kuo KC, McCune RA, Gehrke C (April 1982). "Amount and distribution of 5-methylcytosine in human DNA from different types of tissues or cells". Nucleic Acids Research 10 (8): 2709–2721. doi:10.1093/nar/10.8.2709. PMC 320645. PMID 7079182.
- Tucker KL (June 2001). "Methylated cytosine and the brain: a new base for neuroscience". Neuron 30 (3): 649–652. doi:10.1016/S0896-6273(01)00325-7. PMID 11430798.
- International Human Genome Sequencing Consortium et al. (February 2001). "Initial sequencing and analysis of the human genome". Nature 409 (6822): 860–921. doi:10.1038/35057062. PMID 11237011.
- Daura-Oller E, Cabre M, Montero MA, Paternain JL, Romeu A (2009). "Specific gene hypomethylation and cancer: New insights into coding region feature trends". Bioinformation 3 (8): 340–343. doi:10.6026/97320630003340. PMC 2720671. PMID 19707296.
- Choy MK, Movassagh M, Goh HG, Bennett M, Down T, Foo R (2010). "Genome-wide conserved consensus transcription factor binding motifs are hyper-methylated". BMC Genomics 11 (1): 519. doi:10.1186/1471-2164-11-519. PMC 2997012. PMID 20875111.
- Miller C, Sweatt J (2007-03-15). "Covalent modification of DNA regulates memory formation". Neuron 53 (6): 857–869. doi:10.1016/j.neuron.2007.02.022. PMID 17359920.
- Powell, Devin (2008-12-02). "Memories may be stored on your DNA". New Scientist. Retrieved 2008-12-02.
- Horvath S (2013). "DNA methylation age of human tissues and cell types". Genome Biology 14 (R115): R115. doi:10.1186/gb-2013-14-10-r115. PMC 4015143. PMID 24138928.
- Zhang FF1, Cardarelli R, Carroll J, Zhang S, Fulda KG, Gonzalez K, Vishwanatha JK, Morabia A, Santella RM (2011). "Physical activity and global genomic DNA methylation in a cancer-free population". EPIGENETICS 6 (3): 293–299. doi:10.4161/epi.6.3.14378. PMC 3092677. PMID 21178401.
- Craig, JM; Wong, NC (editor) (2011). Epigenetics: A Reference Manual. Caister Academic Press. ISBN 978-1-904455-88-2.
- Gonzalo S (2010). "Epigenetic alterations in aging". Journal of Applied Physiology 109 (2): 586–597. doi:10.1152/japplphysiol.00238.2010. PMC 2928596. PMID 20448029.
- Lund, G.L.; Andersson, L.; Lauria, M.; Lindholm, M.; Fraga, M.F.; Villar-Garea, A.; Ballestar, E.; Estellar, M.; Zaina, S. (2004). "DNA methylation polymorphisms precede any histological sign of atherosclerosis in mice lacking Apolipoprotein E.". J Biol Chem 279 (28): 29147–29154. doi:10.1074/jbc.m403618200.
- Castro, R.; Rivera, I.; Struys, E.A.; Jansen, E.E.; Ravasco, P.; Camilo, M.E.; Blom, H.J.; Jakobs, C.; Tavares; de Almeida, T. (2003). "Increased homocysteine concentrations and S-adenosylhomocysteine concentrations and DNA hypomethylation in vascular disease". Clin Chem 49 (8): 1292–1296. doi:10.1373/49.8.1292.
- Huang, Y.S.; Zhi, Y.F.; Wang, S.R. (2009). "Hypermethylation of estrogen receptor-α gene in atheromatosis patients and its correlation with homocysteine". Pathophysiology 16 (4): 259–265. doi:10.1016/j.pathophys.2009.02.010.
- Dong, C.D.; Yoon, W.; Goldschmidt-Clermont, P.J. (2002). "DNA methylation and atherosclerosis". J Nutr 132 (8): 2406S–2409S.
- Ying, A.K.; Hassanain, H.H.; Roos, C.M.; Smiraglia, D.J.; Issa, J.J.; Michler, R.E.; Caligiuri, M.; Plass, C.; Goldschmidt-Clermont, P.J. (2000). "Methylation of the estrogen receptor- α gene promoter is selectively increased in proliferating human aortic smooth muscle cells". Cardiovas Res 46 (1): 172–179. doi:10.1016/s0008-6363(00)00004-3.
- Zhu, S.; Goldschmidt-Clermont, P.J.; Dong, C. (2005). "Inactivation of Monocarboxylate Transporter MCT3 by DNA methylation in atherosclerosis". Circulation 112 (9): 1353–1361. doi:10.1161/circulationaha.104.519025.
- Wong CC1, Caspi A, Williams B, Craig IW, Houts R, Ambler A, Moffitt TE, Mill J (2010). "A longitudinal study of epigenetic variation in twins". EPIGENETICS 5 (6): 516–526. doi:10.4161/epi.5.6.12226. PMC 3322496. PMID 20505345.
- Horvath S (2013). "DNA methylation age of human tissues and cell types". Genome Biology 14 (10): R115. doi:10.1186/gb-2013-14-10-r115. PMC 4015143. PMID 24138928.
- Barrès R1, Yan J, Egan B, Treebak JT, Rasmussen M, Fritz T, Caidahl K, Krook A, O'Gorman DJ, Zierath JR (2012). "Acute exercise remodels promoter methylation in human skeletal muscle". Cell Metabolism 15 (3): 405–411. doi:10.1016/j.cmet.2012.01.001. PMID 22405075.
- Gratchev, Alexei. Review on DNA Methylation. (n.d.) Retrieved from http://www.methods.info/Methods/DNA_methylation/Methylation_review.html
- Goll MG, Kirpekar F, Maggert KA, Yoder JA, Hsieh CL, Zhang X, Golic KG, Jacobsen SE, Bestor TH (January 2006). "Methylation of tRNAAsp by the DNA methyltransferase homolog Dnmt2". Science 311 (5759): 395–398. doi:10.1126/science.1120976. PMID 16424344.
- Cao X and Jacobsen SE (December 2002). "Locus-specific control of asymmetric and CpNpG methylation by the DRM and CMT3 methyltransferase genes". PNAS 99 (Suppl 4): 16491–16498. doi:10.1073/pnas.162371599. PMC 139913. PMID 12151602.
- Aufsatz W, Mette MF, van der Winden J, Matzke AJM, Matzke M (2002). "RNA-directed DNA methylation in Arabidopsis". PNAS 99 (90004): 16499–16506. doi:10.1073/pnas.162371499. PMC 139914. PMID 12169664.
- Antequera F, Tamame M, Villanueva JR, Santos T (July 1984). "DNA methylation in the fungi". J. Biol. Chem. 259 (13): 8033–8036. PMID 6330093.
- Binz T, D'Mello N, Horgen PA (1998). "A comparison of DNA methylation levels in selected isolates of higher fungi". Mycologia (Mycological Society of America) 90 (5): 785–790. doi:10.2307/3761319. JSTOR 3761319.
- Selker EU, Tountas NA, Cross SH, Margolin BS, Murphy JG, Bird AP, Freitag M (2003). "The methylated component of the Neurospora crassa genome". Nature 422 (6934): 893–897. doi:10.1038/nature01564. PMID 12712205.
- S. Takayama, J. Dhahbi, A. Roberts, G. Mao, S.-J. Heo, L. Pachter, D. I. K. Martin, D. Boffelli (2014). Genome methylation in D. melanogaster is found at specific short motifs and is independent of DNMT2 activity. Genome Research, doi:10.1101/gr.162412.113
- Palmer BR and Marinus MG (1994). "The dam and dcm strains of Escherichia coli—a review". Gene 143 (1): 1–12. doi:10.1016/0378-1119(94)90597-5. PMID 8200522.
- "Making unmethylated (dam-/dcm-) DNA".
- Hernández, H. G.; Tse, M. Y.; Pang, S. C.; Arboleda, H.; Forero, D. A. (2013). "Optimizing methodologies for PCR-based DNA methylation analysis". BioTechniques 55 (4): 181–197. doi:10.2144/000114087. PMID 24107250.
- Wood RJ, Maynard-Smith MD, Robinson VL, Oyston PC, Titball RW, Roach PL (2007). Fugmann, Sebastian, ed. "Kinetic analysis of Yersinia pestis DNA adenine methyltransferase activity using a hemimethylated molecular break light oligonucleotide". PLoS ONE 2 (8): e801. doi:10.1371/journal.pone.0000801. PMC 1949145. PMID 17726531.
- Li J, Yan H, Wang K, Tan W, Zhou X (February 2007). "Hairpin fluorescence DNA probe for real-time monitoring of DNA methylation". Anal. Chem. 79 (3): 1050–1056. doi:10.1021/ac061694i. PMID 17263334.
- ^ David R. McCarthy, Philip D. Cotter, and Michelle M. Hanna (2012). MethylMeter(r): A Quantitative, Sensitive, and Bisulfite-Free Method for Analysis of DNA Methylation, DNA Methylation - From Genomics to Technology, Dr. Tatiana Tatarinova (Ed.), ISBN 978-953-51-0320-2, InTech, DOI: 10.5772/36090. Available from: http://www.intechopen.com/books/dna-methylation-from-genomics-to-technology/methylmeter-a-quantitative-sensititive-and-bisulfite-free-method-for-analysis-of-dna-methylation
- Wojdacz, TK; Dobrovic, A (2007). "Methylation-sensitive high resolution melting (MS-HRM): a new approach for sensitive and high-throughput assessment of methylation". Nucleic Acids Res. 35 (6): e41. doi:10.1093/nar/gkm013. PMC 1874596. PMID 17289753.
- Malentacchi, F; Forni, G; Vinci, S; Orlando, C (2009). "Quantitative evaluation of DNA methylation by optimization of a differential-high resolution melt analysis protocol". Nucleic Acids Res. 37 (12): e86. doi:10.1093/nar/gkp383. PMC 2709587. PMID 19454604.
- Rakyan, VK; Down, TA; Thorne, NP; Flicek, P; Kulesha, E; Gräf, S; Tomazou, EM; Bäckdahl, L; Johnson, N; Herberth, M; Howe, KL; Jackson, DK; Miretti, MM; Fiegler, H; Marioni, JC; Birney, E; Hubbard, TJ; Carter, NP; Tavaré, S; Beck, S (September 2008). "An integrated resource for genome-wide identification and analysis of human tissue-specific differentially methylated regions (tDMRs).". Genome Research 18 (9): 1518–29. doi:10.1101/gr.077479.108. PMC 2527707. PMID 18577705.
- Irizarry, RA; Ladd-Acosta, C; Wen, B; Wu, Z; Montano, C; Onyango, P; Cui, H; Gabo, K; Rongione, M; Webster, M; Ji, H; Potash, JB; Sabunciyan, S; Feinberg, AP (February 2009). "The human colon cancer methylome shows similar hypo- and hypermethylation at conserved tissue-specific CpG island shores.". Nature Genetics 41 (2): 178–86. doi:10.1038/ng.298. PMC 2729128. PMID 19151715.
- Reik, W; Dean, W; Walter, J (Aug 10, 2001). "Epigenetic reprogramming in mammalian development.". Science 293 (5532): 1089–93. doi:10.1126/science.1063443. PMID 11498579.
- Meissner, A; Mikkelsen, TS; Gu, H; Wernig, M; Hanna, J; Sivachenko, A; Zhang, X; Bernstein, BE; Nusbaum, C; Jaffe, DB; Gnirke, A; Jaenisch, R; Lander, ES (Aug 7, 2008). "Genome-scale DNA methylation maps of pluripotent and differentiated cells.". Nature 454 (7205): 766–70. doi:10.1038/nature07107. PMC 2896277. PMID 18600261.
- Doi, A; Park, IH; Wen, B; Murakami, P; Aryee, MJ; Irizarry, R; Herb, B; Ladd-Acosta, C; Rho, J; Loewer, S; Miller, J; Schlaeger, T; Daley, GQ; Feinberg, AP (December 2009). "Differential methylation of tissue- and cancer-specific CpG island shores distinguishes human induced pluripotent stem cells, embryonic stem cells and fibroblasts.". Nature Genetics 41 (12): 1350–3. doi:10.1038/ng.471. PMC 2958040. PMID 19881528.
- Bjornsson, HT; Sigurdsson, MI; Fallin, MD; Irizarry, RA; Aspelund, T; Cui, H; Yu, W; Rongione, MA; Ekström, TJ; Harris, TB; Launer, LJ; Eiriksdottir, G; Leppert, MF; Sapienza, C; Gudnason, V; Feinberg, AP (Jun 25, 2008). "Intra-individual change over time in DNA methylation with familial clustering.". JAMA: the Journal of the American Medical Association 299 (24): 2877–83. doi:10.1001/jama.299.24.2877. PMC 2581898. PMID 18577732.
- Bock, C; Walter, J; Paulsen, M; Lengauer, T (June 2008). "Inter-individual variation of DNA methylation and its implications for large-scale epigenome mapping.". Nucleic Acids Research 36 (10): e55. doi:10.1093/nar/gkn122. PMC 2425484. PMID 18413340.
- Zhang, Y; Liu, H; Lv, J; Xiao, X; Zhu, J; Liu, X; Su, J; Li, X; Wu, Q; Wang, F; Cui, Y (May 2011). "QDMR: a quantitative method for identification of differentially methylated regions by entropy.". Nucleic Acids Research 39 (9): e58. doi:10.1093/nar/gkr053. PMC 3089487. PMID 21306990.
- Geeleher P, Hartnett L, Egan LJ, Golden A, Raja Ali RA, Seoighe C (June 2013). "Gene-Set Analysis is Severely Biased When Applied to Genome-wide Methylation Data". Bioinformatics 29 (15): 1851–7. doi:10.1093/bioinformatics/btt311. PMID 23732277.
- Bhasin M, Zhang H, Reinherz EL, Reche PA. (Aug 2005). "Prediction of methylated CpGs in DNA sequences using a support vector machine". FEBS Lett. 579 (20): 4302–8. doi:10.1016/j.febslet.2005.07.002. PMID 16051225.
- Bock C, Paulsen M, Tierling S, Mikeska T, Lengauer T, Walter J. (Mar 2006). "CpG island methylation in human lymphocytes is highly correlated with DNA sequence, repeats, and predicted DNA structure". PLoS Genet. 2 (3): e26. doi:10.1371/journal.pgen.0020026. PMC 1386721. PMID 16520826.
- Zheng H, Jiang SW, Wu H (2011). "Enhancement on the predictive power of the prediction model for human genomic DNA methylation". International Conference on Bioinformatics and Computational Biology (BIOCOMP'11).
- Zheng H, Jiang SW, Li J, Wu H (2013). "CpGIMethPred: computational model for predicting methylation status of CpG islands in human genome". BMC Medical Genomics).
- Law J, Jacobsen SE (2010). "Establishing, maintaining and modifying DNA methylation patterns in plants and animals". Nat. Rev. Genet. 11 (3): 204–220. doi:10.1038/nrg2719. PMC 3034103. PMID 20142834.
- Straussman R, Nejman D, Roberts D et al. (2009). "Developmental programming of CpG island methylation profiles in the human genome". Nat. Struct. Mol. Biol. 16 (5): 564–571. doi:10.1038/nsmb.1594. PMID 19377480.
- Patra SK (2008). "Ras regulation of DNA-methylation and cancer". Exp Cell Res 314 (6): 1193–1201. doi:10.1016/j.yexcr.2008.01.012. PMID 18282569.
- Patra SK, Patra A, Ghosh TC et al. (2008). "Demethylation of (cytosine-5-C-methyl) DNA and regulation of transcription in the epigenetic pathways of cancer development". Cancer Metast. Rev. 27 (2): 315–334. doi:10.1007/s10555-008-9118-y. PMID 18246412.
|Wikimedia Commons has media related to DNA methylation.|
- DNA Methylation at the US National Library of Medicine Medical Subject Headings (MeSH)
- ENCODE threads explorer Non-coding RNA characterization. Nature (journal)
- PCMdb Pancreatic Cancer Methylation Database. Nature Scientific Report 4:4197