Статті в журналах: "Method for DNA methylation"

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Majchrzak-Celińska, A., M. Naskret-Barciszewska, M. Giel-Pietraszuk, W. Nowak, P. Śron, and A. Barciszewska. "P02.08.A The relations of focal and total DNA methylation in gliomas." Neuro-Oncology 24, Supplement_2 (September 1, 2022): ii31. http://dx.doi.org/10.1093/neuonc/noac174.101.

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Abstract Background The role of epigenetic events in gliomagenesis is undoubtful. However, the role of specific pathological events is not so clear. It was shown that loss in total DNA methylation correlates with higher tumor malignancy and oxidative DNA damage. But promoter methylation of many genes was reported to be significant for gliomas’ malignancy and predictive for the treatment outcome. In carcinogenesis in general global DNA hypomethylation and focal hypermethylation coexist. The aim of our project was to evaluate the correlation between total DNA methylation and promoter methylation of selected genes. Material and Methods We analysed glioma tissues from 60 patients. For total DNA methylation analysis we used the radiolabelling method with TLC separation of nucleotides and content estimation with phosphoimager. For promoter methylation analysis we have chosen: MGMT (O-6-Methylguanine-DNA Methyltransferase), MPG (DNA-3-methyladenine glycosylase), GJA1 (Gap junction alpha-1 protein / connexin 43). The promoter methylation level was evaluated with the methylation-sensitive high-resolution melting (MS-HRM) method. Results Total DNA methylation was reversely correlated with brain tumor grade, confirming that 5-methylcytosine loss is important step in gliomagenesis. From 3 genes only MPG promoter methylation showed clear low reverse correlation with tumor grade. Promoter methylation in GJA1 show low correlation with both, MGMT and MPG, but there was no link between MGMT and MPG. IDHwt presence was significantly correlated with higher tumor grade. Promoter methylations in MPG and GJA1 were better correlated with IDH status than in MGMT. Conclusion There is a clear correlation between total DNA methylation and tumor malignancy. Gene promoter methylation is not highly correlated with total DNA methylation and shows low significance in selected cases. Promoter methylation showed clear correlation with tumor grade only in MPG case. That suggests diverse mechanisms steering DNA methylation in general and local changes. It also shows that total DNA methylation is best predictor of tumor grade.

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Kim, Sook Ho, Hae Jun Jung, and Seok-Cheol Hong. "Z-DNA as a Tool for Nuclease-Free DNA Methyltransferase Assay." International Journal of Molecular Sciences 22, no. 21 (November 5, 2021): 11990. http://dx.doi.org/10.3390/ijms222111990.

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Methylcytosines in mammalian genomes are the main epigenetic molecular codes that switch off the repertoire of genes in cell-type and cell-stage dependent manners. DNA methyltransferases (DMT) are dedicated to managing the status of cytosine methylation. DNA methylation is not only critical in normal development, but it is also implicated in cancers, degeneration, and senescence. Thus, the chemicals to control DMT have been suggested as anticancer drugs by reprogramming the gene expression profile in malignant cells. Here, we report a new optical technique to characterize the activity of DMT and the effect of inhibitors, utilizing the methylation-sensitive B-Z transition of DNA without bisulfite conversion, methylation-sensing proteins, and polymerase chain reaction amplification. With the high sensitivity of single-molecule FRET, this method detects the event of DNA methylation in a single DNA molecule and circumvents the need for amplification steps, permitting direct interpretation. This method also responds to hemi-methylated DNA. Dispensing with methylation-sensitive nucleases, this method preserves the molecular integrity and methylation state of target molecules. Sparing methylation-sensing nucleases and antibodies helps to avoid errors introduced by the antibody’s incomplete specificity or variable activity of nucleases. With this new method, we demonstrated the inhibitory effect of several natural bio-active compounds on DMT. All taken together, our method offers quantitative assays for DMT and DMT-related anticancer drugs.

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Li, W., A. Van Soom, and L. Peelman. "Repeats as global DNA methylation marker in bovine preimplantation embryos." Czech Journal of Animal Science 62, No. 2 (February 6, 2017): 43–50. http://dx.doi.org/10.17221/29/2016-cjas.

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DNA methylation undergoes dynamic changes and is a crucial part of the epigenetic regulation during mammalian early development. To determine the DNA methylation levels in bovine embryos, we applied a bisulfite sequencing based method aimed at repetitive sequences including three retrotransposons (L1_BT, BovB, and ERV1-1-I_BT) and Satellite I. A more accurate estimate of the global DNA methylation level compared to previous methods using only one repeat sequence, like Alu, could be made by calculation of the weighted arithmetic mean of multiple repetitive sequences, considering the copy number of each repetitive sequence. Satellite I and L1_BT showed significant methylation reduction at the blastocyst stage, while BovB and ERV1-1-I_BT showed no difference. The mean methylation level of the repetitive sequences during preimplantation development was the lowest at the blastocyst stage. No methylation difference was found between embryos cultured in 5% and 20% O<sub>2</sub>. Because mutations of CpGs negatively influence the calculation accuracy, we checked the mutation rate of the sequenced CpG sites. Satellite I and L1_BT showed a relatively low mutation rate (1.92 and 3.72% respectively) while that of ERV1-1-I_BT and BovB was higher (11.95 and 24% respectively). Therefore we suggest using a combination of repeats with low mutation rate, taking into account the proportion of each sequence, as a relatively quick marker for the global DNA methylation status of preimplantation stages and possibly also for other cell types.

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Kurdyukov, Sergey, and Martyn Bullock. "DNA Methylation Analysis: Choosing the Right Method." Biology 5, no. 1 (January 6, 2016): 3. http://dx.doi.org/10.3390/biology5010003.

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IMAMURA, TAKUYA. "DNA methylation analysis with bisulfite sequencing method." Newsletter of Japan Society for Comparative Endocrinology, no. 113 (2004): 25–29. http://dx.doi.org/10.5983/nl2001jsce.2004.113_25.

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Hou, Peng, Meiju Ji, Song Li, Nongyue He, and Zuhong Lu. "High-throughput method for detecting DNA methylation." Journal of Biochemical and Biophysical Methods 60, no. 2 (August 2004): 139–50. http://dx.doi.org/10.1016/j.jbbm.2004.05.001.

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Choi, Woo Lee, Young Geun Mok, and Jin Hoe Huh. "Application of 5-Methylcytosine DNA Glycosylase to the Quantitative Analysis of DNA Methylation." International Journal of Molecular Sciences 22, no. 3 (January 22, 2021): 1072. http://dx.doi.org/10.3390/ijms22031072.

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In higher eukaryotes DNA methylation is a prominent epigenetic mark important for chromatin structure and gene expression. Thus, profiling DNA methylation is important for predicting gene expressions associated with specific traits or diseases. DNA methylation is achieved by DNA methyltransferases and can be actively removed by specific enzymes in a replication-independent manner. DEMETER (DME) is a bifunctional 5-methylcytosine (5mC) DNA glycosylase responsible for active DNA demethylation that excises 5mC from DNA and cleaves a sugar-phosphate bond generating a single strand break (SSB). In this study, DME was used to analyze DNA methylation levels at specific epialleles accompanied with gain or loss of DNA methylation. DME treatment on genomic DNA generates SSBs in a nonsequence-specific fashion proportional to 5mC density, and thus DNA methylation levels can be easily measured when combined with the quantitative PCR (qPCR) method. The DME-qPCR analysis was applied to measure DNA methylation levels at the FWA gene in late-flowering Arabidopsis mutants and the CNR gene during fruit ripening in tomato. Differentially methylated epialleles were successfully distinguished corresponding to their expression levels and phenotypes. DME-qPCR is proven a simple yet effective method for quantitative DNA methylation analysis, providing advantages over current techniques based on methylation-sensitive restriction digestion.

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Khodadadi, Ehsan, Leila Fahmideh, Ehsaneh Khodadadi, Sounkalo Dao, Mehdi Yousefi, Sepehr Taghizadeh, Mohammad Asgharzadeh, Bahman Yousefi, and Hossein Samadi Kafil. "Current Advances in DNA Methylation Analysis Methods." BioMed Research International 2021 (March 20, 2021): 1–9. http://dx.doi.org/10.1155/2021/8827516.

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DNA methylation is one of the epigenetic changes, which plays a major role in regulating gene expression and, thus, many biological processes and diseases. There are several methods for determining the methylation of DNA samples. However, selecting the most appropriate method for answering biological questions appears to be a challenging task. The primary methods in DNA methylation focused on identifying the state of methylation of the examined genes and determining the total amount of 5-methyl cytosine. The study of DNA methylation at a large scale of genomic levels became possible following the use of microarray hybridization technology. The new generation of sequencing platforms now allows the preparation of genomic maps of DNA methylation at the single-open level. This review includes the majority of methods available to date, introducing the most widely used methods, the bisulfite treatment, biological identification, and chemical cutting along with their advantages and disadvantages. The techniques are then scrutinized according to their robustness, high throughput capabilities, and cost.

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Celik Uzuner, Selcen. "Mitochondrial DNA methylation misleads global DNA methylation detected by antibody-based methods." Analytical Biochemistry 601 (July 2020): 113789. http://dx.doi.org/10.1016/j.ab.2020.113789.

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Han, Pingping, and Sašo Ivanovski. "Effect of Saliva Collection Methods on the Detection of Periodontium-Related Genetic and Epigenetic Biomarkers—A Pilot Study." International Journal of Molecular Sciences 20, no. 19 (September 24, 2019): 4729. http://dx.doi.org/10.3390/ijms20194729.

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Different collection methods may influence the ability to detect and quantify biomarker levels in saliva, particularly in the expression of DNA/RNA methylation regulators of several inflammations and tissue turnover markers. This pilot study recruited five participants and unstimulated saliva were collected by either spitting or drooling, and the relative preference for each method was evaluated using a visual analogue scale. Subsequently, total RNA, gDNA and proteins were isolated using the Trizol method. Thereafter, a systematic evaluation was carried out on the potential effects of different saliva collection methods on periodontium-associated genes, DNA/RNA epigenetic factors and periodontium-related DNA methylation levels. The quantity and quality of DNA and RNA were comparable from different collection methods. Periodontium-related genes, DNA/RNA methylation epigenetic factors and periodontium-associated DNA methylation could be detected in the saliva sample, with a similar expression for both methods. The methylation of tumour necrosis factor-alpha gene promoter from drooling method showed a significant positive correlation (TNF α, r = 0.9) with clinical parameter (bleeding on probing-BOP). In conclusion, the method of saliva collection has a minimal impact on detecting periodontium-related genetic and epigenetic regulators in saliva. The pilot data shows that TNF α methylation may be correlated with clinical parameters.

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Ni, Peng, Neng Huang, Zhi Zhang, De-Peng Wang, Fan Liang, Yu Miao, Chuan-Le Xiao, Feng Luo, and Jianxin Wang. "DeepSignal: detecting DNA methylation state from Nanopore sequencing reads using deep-learning." Bioinformatics 35, no. 22 (April 17, 2019): 4586–95. http://dx.doi.org/10.1093/bioinformatics/btz276.

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Abstract Motivation The Oxford Nanopore sequencing enables to directly detect methylation states of bases in DNA from reads without extra laboratory techniques. Novel computational methods are required to improve the accuracy and robustness of DNA methylation state prediction using Nanopore reads. Results In this study, we develop DeepSignal, a deep learning method to detect DNA methylation states from Nanopore sequencing reads. Testing on Nanopore reads of Homo sapiens (H. sapiens), Escherichia coli (E. coli) and pUC19 shows that DeepSignal can achieve higher performance at both read level and genome level on detecting 6 mA and 5mC methylation states comparing to previous hidden Markov model (HMM) based methods. DeepSignal achieves similar performance cross different DNA methylation bases, different DNA methylation motifs and both singleton and mixed DNA CpG. Moreover, DeepSignal requires much lower coverage than those required by HMM and statistics based methods. DeepSignal can achieve 90% above accuracy for detecting 5mC and 6 mA using only 2× coverage of reads. Furthermore, for DNA CpG methylation state prediction, DeepSignal achieves 90% correlation with bisulfite sequencing using just 20× coverage of reads, which is much better than HMM based methods. Especially, DeepSignal can predict methylation states of 5% more DNA CpGs that previously cannot be predicted by bisulfite sequencing. DeepSignal can be a robust and accurate method for detecting methylation states of DNA bases. Availability and implementation DeepSignal is publicly available at https://github.com/bioinfomaticsCSU/deepsignal. Supplementary information Supplementary data are available at bioinformatics online.

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Zuo, Tao, Benjamin Tycko, Ta-Ming Liu, Huey-Jen L. Lin, and Tim H.-M. Huang. "Methods in DNA methylation profiling." Epigenomics 1, no. 2 (December 2009): 331–45. http://dx.doi.org/10.2217/epi.09.31.

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Shen, Lanlan, and Robert A. Waterland. "Methods of DNA methylation analysis." Current Opinion in Clinical Nutrition and Metabolic Care 10, no. 5 (September 2007): 576–81. http://dx.doi.org/10.1097/mco.0b013e3282bf6f43.

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Altaf, Adil, and Ahmad Zada. "DNA METHYLATION IN PLANTS." Journal of Global Innovations in Agriculture Sciences 9, no. 3 (September 27, 2021): 109–14. http://dx.doi.org/10.22194/jgias/9.954.

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Common DNA methylation controls gene expression and preserves genomic integrity. Mal methylation can cause developmental abnormalities in the plants. Multiple enzymes carrying out de novo methylation, methylation maintenance, and active demethylation culminate in a particular DNA methylation state. Next-generation sequencing advances and computational methods to analyze the data. The model plant Arabidopsis thaliana was used to study DNA methylation patterns, epigenetic inheritance, and plant methylation. Plant DNA methylation research reveals methylation patterns and describing variations in plant tissues. Determining the kinetics of DNA methylation in diverse plant tissues is also a new field. However, it is vital to understand regulatory and developmental decisions and use plant model species to develop new commercial crops; that are more resistant to stress and yield more. There are several methods available for assessing DNA methylation data. The performance of several techniques is assessed in A. thaliana, which has a smaller genome than hexaploid bread wheat. Keywords: DNA methylation, plants, process, use and benefits.

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Saheb, Amir, Stephanie Patterson, and Mira Josowicz. "Probing for DNA methylation with a voltammetric DNA detector." Analyst 139, no. 4 (2014): 786–92. http://dx.doi.org/10.1039/c3an02154h.

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Di Lena, Pietro, Claudia Sala, Andrea Prodi, and Christine Nardini. "Missing value estimation methods for DNA methylation data." Bioinformatics 35, no. 19 (February 23, 2019): 3786–93. http://dx.doi.org/10.1093/bioinformatics/btz134.

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Abstract Motivation DNA methylation is a stable epigenetic mark with major implications in both physiological (development, aging) and pathological conditions (cancers and numerous diseases). Recent research involving methylation focuses on the development of molecular age estimation methods based on DNA methylation levels (mAge). An increasing number of studies indicate that divergences between mAge and chronological age may be associated to age-related diseases. Current advances in high-throughput technologies have allowed the characterization of DNA methylation levels throughout the human genome. However, experimental methylation profiles often contain multiple missing values that can affect the analysis of the data and also mAge estimation. Although several imputation methods exist, a major deficiency lies in the inability to cope with large datasets, such as DNA methylation chips. Specific methods for imputing missing methylation data are therefore needed. Results We present a simple and computationally efficient imputation method, metyhLImp, based on linear regression. The rationale of the approach lies in the observation that methylation levels show a high degree of inter-sample correlation. We performed a comparative study of our approach with other imputation methods on DNA methylation data of healthy and disease samples from different tissues. Performances have been assessed both in terms of imputation accuracy and in terms of the impact imputed values have on mAge estimation. In comparison to existing methods, our linear regression model proves to perform equally or better and with good computational efficiency. The results of our analysis provide recommendations for accurate estimation of missing methylation values. Availability and implementation The R-package methyLImp is freely available at https://github.com/pdilena/methyLImp. Supplementary information Supplementary data are available at Bioinformatics online.

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Trinh, Binh N., Tiffany I. Long, and Peter W. Laird. "DNA Methylation Analysis by MethyLight Technology." Methods 25, no. 4 (December 2001): 456–62. http://dx.doi.org/10.1006/meth.2001.1268.

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Baránková, Kateřina, Anna Nebish, Jan Tříska, Jana Raddová, and Miroslav Baránek. "Comparison of DNA methylation landscape between Czech and Armenian vineyards show their unique character and increased diversity." Czech Journal of Genetics and Plant Breeding 57, No. 2 (April 9, 2021): 67–75. http://dx.doi.org/10.17221/90/2020-cjgpb.

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Grapevine is a worldwide crop and it is also subject to global trade in wine, berries and grape vine plants. Various countries, including the countries of the European Union, emphasize the role of product origin designation and suitable methods are sought, able to capture distinct origins. One of the biological matrices that can theoretically be driven by individual vineyards’ conditions represents DNA methylation. Despite this interesting hypothesis, there is a lack of respective information. The aim of this work is to examine whether DNA methylation can be used to relate a sample to a given vineyard and to access a relationship between a DNA methylation pattern and different geographical origin of analysed samples. For this purpose, DNA methylation landscapes of samples from completely different climatic conditions presented by the Czech Republic (Central Europe) and Armenia (Southern Caucasus) were compared. Results of the Methylation Sensitive Amplified Polymorphism method confirm uniqueness of DNA methylation landscape for individual vineyards. Factually, DNA methylation diversity within vineyards of Merlot and Pinot Noir cultivars represent only 16% and 14% of the overall diversity registered for individual cultivars. On the contrary, different geographical location of the Czech and Armenian vineyards was identified as the strongest factor affecting diversity in DNA methylation landscapes (79.9% and 70.7% for Merlot and Pinot Noir plants, respectively).

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Wojtczyk-Miaskowska, Anita, Malgorzata Presler, Jerzy Michajlowski, Marcin Matuszewski, Beata Schlichtholz, and Medical University of Gdansk. "Gene Expression, DNA Methylation and Prognostic Significance of DNA Repair Genes in Human Bladder Cancer." Cellular Physiology and Biochemistry 42, no. 6 (2017): 2404–17. http://dx.doi.org/10.1159/000480182.

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Background/Aims: This study investigated the gene expression and DNA methylation of selected DNA repair genes (MBD4, TDG, MLH1, MLH3) and DNMT1 in human bladder cancer in the context of pathophysiological and prognostic significance. Methods: To determine the relationship between the gene expression pattern, global methylation and promoter methylation status, we performed real-time PCR to quantify the mRNA of selected genes in 50 samples of bladder cancer and adjacent non-cancerous tissue. The methylation status was analyzed by methylation-specific polymerase chain reaction (MSP) or digestion of genomic DNA with a methylation-sensitive restriction enzyme and PCR with gene-specific primers (MSRE-PCR). The global DNA methylation level was measured using the antibody-based 5-mC detection method. Results: The relative levels of mRNA for MBD4, MLH3, and MLH1 were decreased in 28% (14/50), 34% (17/50) and 36% (18/50) of tumor samples, respectively. The MBD4 mRNA expression was decreased in 46% of non-muscle invasive tumors (Ta/T1) compared with 11% found in muscle invasive tumors (T2-T4) (P<0.003). Analysis of mRNA expression for TDG did not show any significant differences between Ta/T1 and T2-T4 tumors. The frequency of increased DNMT1 mRNA expression was higher in T2-T4 (52%) comparing to Ta/T1 (16%). The overall methylation rates in tumor tissue were 18% for MBD4, 25% for MLH1 and there was no evidence of MLH3 promoter methylation. High grade tumors had significantly lower levels of global DNA methylation (P=0.04). There was a significant association between shorter survival and increased expression of DNMT1 mRNA (P=0.002), decreased expression of MLH1 mRNA (P=0.032) and the presence of MLH1 promoter methylation (P=0.006). Conclusion: This study highlights the importance of DNA repair pathways and provides the first evidence of the role of MBD4 and MLH3 in bladder cancer. In addition, our findings suggest that DNMT1 mRNA and MLH1 mRNA expression, as well as the status of MLH1 promoter methylation, are attractive prognostic markers in this pathology.

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Martisova, Andrea, Jitka Holcakova, Nasim Izadi, Ravery Sebuyoya, Roman Hrstka, and Martin Bartosik. "DNA Methylation in Solid Tumors: Functions and Methods of Detection." International Journal of Molecular Sciences 22, no. 8 (April 19, 2021): 4247. http://dx.doi.org/10.3390/ijms22084247.

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DNA methylation, i.e., addition of methyl group to 5′-carbon of cytosine residues in CpG dinucleotides, is an important epigenetic modification regulating gene expression, and thus implied in many cellular processes. Deregulation of DNA methylation is strongly associated with onset of various diseases, including cancer. Here, we review how DNA methylation affects carcinogenesis process and give examples of solid tumors where aberrant DNA methylation is often present. We explain principles of methods developed for DNA methylation analysis at both single gene and whole genome level, based on (i) sodium bisulfite conversion, (ii) methylation-sensitive restriction enzymes, and (iii) interactions of 5-methylcytosine (5mC) with methyl-binding proteins or antibodies against 5mC. In addition to standard methods, we describe recent advances in next generation sequencing technologies applied to DNA methylation analysis, as well as in development of biosensors that represent their cheaper and faster alternatives. Most importantly, we highlight not only advantages, but also disadvantages and challenges of each method.

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Bonanno, Cinzia, Erlet Shehi, Daniel Adlerstein, and G. Mike Makrigiorgos. "MS-FLAG, a Novel Real-Time Signal Generation Method for Methylation-Specific PCR." Clinical Chemistry 53, no. 12 (December 1, 2007): 2119–27. http://dx.doi.org/10.1373/clinchem.2007.094011.

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Abstract Background: Aberrant promoter methylation is a major mechanism for silencing tumor suppressor genes in cancer. Detection of hypermethylation is used as a molecular marker for early cancer diagnosis, as a prognostic index, or to define therapeutic targets for reversion of aberrant methylation. We report on a novel signal generation technology for real-time PCR to detect gene promoter methylation. Methods: FLAG (fluorescent amplicon generation) is a homogeneous signal generation technology based on the exceptionally thermostable endonuclease PspGI. FLAG provides real-time signal generation during PCR by PspGI-mediated cleavage of quenched fluorophores at the 5′ end of double-stranded PCR products. Methylation-specific PCR (MSP) applied on bisulfite-treated DNA was adapted to a real-time format (methylation-specific FLAG; MS-FLAG) for quantifying methylation in the promoter of CDKN2A (p16), GATA5, and RASSF1. We validated MS-FLAG on plasmids and genomic DNA with known methylation status and applied it to detection of methylation in a limited number of clinical samples. We also conducted bisulfite sequencing on these samples. Results: Real-time PCR results obtained via MS-FLAG agreed with results obtained via conventional, gel-based MSP. The new technology showed high specificity, sensitivity (2–3 plasmid copies), and selectivity (0.01% of methylated DNA) on control samples. It enabled correct prediction of the methylation status of all 3 gene promoters in 21 lung adenocarcinoma samples, as confirmed by bisulfite sequencing. We also developed a multiplex MS-FLAG assay for GATA5 and RASSF1 promoters. Conclusion: MS-FLAG provides a new, quantitative, high-throughput method for detecting gene promoter methylation and is a convenient alternative to agarose gel-based MSP for screening methylation. In addition to methylation, FLAG-based real-time signal generation may have broad applications in DNA diagnostics.

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Kwon, Seulgi, Sang Mi An, Go Eun Yu, Jung Hye Hwang, Da Hye Park, Deok Gyeong Kang, Tae Wan Kim, Hwa Chun Park, Jeongim Ha, and Chul Wook Kim. "A prognostic method for the litter size in Berkshire pigs based on DNA methylation of IGFBP4 gene." Canadian Journal of Animal Science 98, no. 4 (December 1, 2018): 845–51. http://dx.doi.org/10.1139/cjas-2017-0160.

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Litter size is an important trait in the pig industry. Therefore, a lot of effort has been put into improving this trait. DNA methylation is an essential epigenetic modification present in unique DNA sequences. Alterations in methylation can affect transcription and phenotypic variation. The purpose of this study was to investigate the effect of DNA methylation on litter size. Methylation-specific restriction enzymes are simple and useful tools for detecting DNA methylation status. We used a pair of methylation-sensitive isoschizomers, which have the same recognition site, HpaII and MspI. Insulin-like growth factor binding protein 4 (IGFBP4) is a key regulator of ovarian follicular development and fetal growth in eutherian mammals. In this study, we discovered that IGFBP4 was hyper-methylated in the uterus tissue of a larger litter size group using bisulfite sequencing, and validated the positive relationship between the methylation status of IGFBP4 and the total number born of pigs using the porcine methylation-specific restriction enzyme polymerase chain reaction (PMP) assay. We suggest that the IGFPB4 gene can be used as a prognostic biomarker for hyperprolific sows and that the PMP assay is a useful tool for methylation status screening.

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Zhu, Tiansheng, Jihong Guan, Hui Liu, and Shuigeng Zhou. "RMDB: An Integrated Database of Single-cytosine-resolution DNA Methylation in Oryza Sativa." Current Bioinformatics 14, no. 6 (July 16, 2019): 524–31. http://dx.doi.org/10.2174/1574893614666190211161717.

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Background: Previous studies have revealed that DNA methylation plays a crucial role in eukaryotic growth and development via involvement in the regulation of gene expression and chromosomal instability. With the advancement of biotechnology, next-generation sequencing (NGS) is emerging as a popular method to explore the functions of DNA methylation, and an increasing number of genome-scale DNA methylation datasets have been published. Several DNA methylation databases, including MethDB, NGSmethDB and MENT have been developed for storing and analyzing the DNA methylation data. However, no public resource dedicated to DNA methylation of Oryza sativa is available to date. Methods & Results: We built a comprehensive database (RMDB) for integration and analysis of DNA methylation data of Oryza sativa. A couple of functional modules were developed to identify the connections between DNA methylation and phenotypes. Moreover, rich graphical visualization tools were employed to facilitate data presentation and interpretation. Conclusion: RMDB is an integrated database dedicated to rice DNA methylation. To the best of our knowledge, this is the first integrated rice DNA methylation database. We believe that RMDB will be helpful to understand the epigenetic mechanisms of Oryza sativa. RMDB is freely available at http://admis.fudan.edu.cn/rmdb.

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Aung, Hnin T., Dion K. Harrison, Ian Findlay, John S. Mattick, Nicholas G. Martin, and Bernard J. Carroll. "Stringent Programming of DNA Methylation in Humans." Twin Research and Human Genetics 13, no. 5 (October 1, 2010): 405–11. http://dx.doi.org/10.1375/twin.13.5.405.

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We describe a PCR-based method called Amplified Methylation Polymorphism (AMP) for scanning genomes for DNA methylation changes. AMP detects tissue-specific DNA methylation signatures often representing junctions between methylated and unmethylated DNA close to intronexon junctions and/or associated with CpG islands. Identical AMP profiles are detected for healthy, young, monozygotic twins.

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Usui, Fumitake, Yoshiaki Nakamura, Yasuhiro Yamamoto, Ayako Bitoh, Tamao Ono, and Hiroshi Kagami. "Analysis of Developmental Changes in Avian DNA Methylation Using a Novel Method for Quantifying Genome-wide DNA Methylation." Journal of Poultry Science 46, no. 4 (2009): 286–90. http://dx.doi.org/10.2141/jpsa.46.286.

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Bailey, Vasudev J., Yi Zhang, Brian P. Keeley, Chao Yin, Kristen L. Pelosky, Malcolm Brock, Stephen B. Baylin, James G. Herman, and Tza-Huei Wang. "Single-Tube Analysis of DNA Methylation with Silica Superparamagnetic Beads." Clinical Chemistry 56, no. 6 (June 1, 2010): 1022–25. http://dx.doi.org/10.1373/clinchem.2009.140244.

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Abstract Background: DNA promoter methylation is a signature for the silencing of tumor suppressor genes. Most widely used methods to detect DNA methylation involve 3 separate, independent processes: DNA extraction, bisulfite conversion, and methylation detection via a PCR method, such as methylation-specific PCR (MSP). This method includes many disconnected steps with associated losses of material, potentially reducing the analytical sensitivity required for analysis of challenging clinical samples. Methods: Methylation on beads (MOB) is a new technique that integrates DNA extraction, bisulfite conversion, and PCR in a single tube via the use of silica superparamagnetic beads (SSBs) as a common DNA carrier for facilitating cell debris removal and buffer exchange throughout the entire process. In addition, PCR buffer is used to directly elute bisulfite-treated DNA from SSBs for subsequent target amplifications. The diagnostic sensitivity of MOB was evaluated by methylation analysis of the CDKN2A [cyclin-dependent kinase inhibitor 2A (melanoma, p16, inhibits CDK4); also known as p16INK4a] promoter in serum DNA of lung cancer patients and compared with that of conventional methods. Results: Methylation analysis consisting of DNA extraction followed by bisulfite conversion and MSP was successfully carried out within 9 h in a single tube. The median pre-PCR DNA yield was 6.61-fold higher with the MOB technique than with conventional techniques. Furthermore, MOB increased the diagnostic sensitivity in our analysis of the CDKN2A promoter in patient serum by successfully detecting methylation in 74% of cancer patients, vs the 45% detection rate obtained with conventional techniques. Conclusions: The MOB technique successfully combined 3 processes into a single tube, thereby allowing ease in handling and an increased detection throughput. The increased pre-PCR yield in MOB allowed efficient, diagnostically sensitive methylation detection.

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Klobučar, Tajda, Elisa Kreibich, Felix Krueger, Maria Arez, Duarte Pólvora-Brandão, Ferdinand von Meyenn, Simão Teixeira da Rocha, and Melanie Eckersley-Maslin. "IMPLICON: an ultra-deep sequencing method to uncover DNA methylation at imprinted regions." Nucleic Acids Research 48, no. 16 (July 4, 2020): e92-e92. http://dx.doi.org/10.1093/nar/gkaa567.

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Abstract Genomic imprinting is an epigenetic phenomenon leading to parental allele-specific expression. Dosage of imprinted genes is crucial for normal development and its dysregulation accounts for several human disorders. This unusual expression pattern is mostly dictated by differences in DNA methylation between parental alleles at specific regulatory elements known as imprinting control regions (ICRs). Although several approaches can be used for methylation inspection, we lack an easy and cost-effective method to simultaneously measure DNA methylation at multiple imprinted regions. Here, we present IMPLICON, a high-throughput method measuring DNA methylation levels at imprinted regions with base-pair resolution and over 1000-fold coverage. We adapted amplicon bisulfite-sequencing protocols to design IMPLICON for ICRs in adult tissues of inbred mice, validating it in hybrid mice from reciprocal crosses for which we could discriminate methylation profiles in the two parental alleles. Lastly, we developed a human version of IMPLICON and detected imprinting errors in embryonic and induced pluripotent stem cells. We also provide rules and guidelines to adapt this method for investigating the DNA methylation landscape of any set of genomic regions. In summary, IMPLICON is a rapid, cost-effective and scalable method, which could become the gold standard in both imprinting research and diagnostics.

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Li, Zhandong, Wei Guo, Shijian Ding, Kaiyan Feng, Lin Lu, Tao Huang, and Yudong Cai. "Detecting Blood Methylation Signatures in Response to Childhood Cancer Radiotherapy via Machine Learning Methods." Biology 11, no. 4 (April 15, 2022): 607. http://dx.doi.org/10.3390/biology11040607.

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Radiotherapy is a helpful treatment for cancer, but it can also potentially cause changes in many molecules, resulting in adverse effects. Among these changes, the occurrence of abnormal DNA methylation patterns has alarmed scientists. To explore the influence of region-specific radiotherapy on blood DNA methylation, we designed a computational workflow by using machine learning methods that can identify crucial methylation alterations related to treatment exposure. Irrelevant methylation features from the DNA methylation profiles of 2052 childhood cancer survivors were excluded via the Boruta method, and the remaining features were ranked using the minimum redundancy maximum relevance method to generate feature lists. These feature lists were then fed into the incremental feature selection method, which uses a combination of deep forest, k-nearest neighbor, random forest, and decision tree to find the most important methylation signatures and build the best classifiers and classification rules. Several methylation signatures and rules have been discovered and confirmed, allowing for a better understanding of methylation patterns in response to different treatment exposures.

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Chen, Bao-An, Fan Zhang, Yan Wang, Chong Gao, Jia-Hua Ding, Yun Yu, Jian Cheng, et al. "Microarray-Based Method for Quantificationally Detecting Methylation Changes of E-Cadherin Gene in Acute Leukemia." Blood 108, no. 11 (November 16, 2006): 4406. http://dx.doi.org/10.1182/blood.v108.11.4406.4406.

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Abstract Aberrant DNA methylation of CpG sites is among the earliest and most frequent alterations in cancer. Several studies suggest that aberrant methylation of the CpG sites of the tumor suppressor gene is closely associated with carcinogenesis. So methylation detection is very important. The aim of this study was to describe a microarray-based method for quantificationally detecting changes of E-cadherin methylation in acute leukemia and to simply discuss the effect of microarray on detecting tumor methylation. This method used bisulfite-modified DNA as a template for PCR amplification, resulting in conversion of unmethylated cytosine, but not methylated cytosine, into thymine within CpG islands of interest. Five sets of oligonucleotide probes were designed to fabricate a DNA microarray to detect the methylation changes of E-cadherin gene CpG islands in acute leukemia. Each set contained a pair of methylated and unmethylated oligonucleotides for interrogating 3 or 4 CpG sites in close proximity. By TA cloning, PCR, sequencing, positive and negative DNA targets were obtained. A series of microarray hybridization were performed with mixtures of Cy3 labeled positive and negative DNA targets at different proportions. Next draw a standard curve by fluorescence intensity. Then leukemia samples DNA were abstracted and bisulfite-modified. Sample DNA targets were obtained by PCR amplification and were hybridized with the microarry. Finally the microarry was scanned with ScanArray Lite microarray analysis systems. Five linear relationships(R2=0.9660~0.9963) was established, which said the accuracy and reproducibility of the probes designed for microarray hybridization was good and could be used to eliminate background noise. The experimental results showed that the microarray assay could successfully detect five regions methylation changes of E-cadherin gene in every acute leukemia sample quantificationally. There were different degree of methylation in five acute leukemia samples and the hypermethylation region was the same. The test result was validated by gene sequencing. In tumors E-cadherin expression frequently is reduced, an event that contributes to tumor invasion and metastasis. The methylation of E-cadherin gene promoter is one important reason resulting in the silencing of expression. In normal peripheral blood mononuclear cells and bone marrow, E-cadherin is completely unmethylated. In our results, the methylation of E-cadherin is related to acute leukemia. And the same hypermethylation region may be the critical sites of methylation sites. As shown in this study, the use of a simple control system could test the accuracy and reproducibility of the probes designed for microarray hybridization. This control system can also be used to calibrate the levels of methylation changes detected in the investigated samples by microarray assay. With more and more methylated genes are found, microarray assay could be applied as a useful tool for mapping methylation changes in multiple CpG loci. It’s more time-saving and more labor-saving than gene sequencing and can be readily used to high throughput analysis of DNA methylation. It will contribute significant information to our understanding of CpG island methylation in acute leukemia.

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Chen, Bao-An, Bei-ming Shou, Dong-rui Zhou, De-long Liu, Jia-hua Ding, Chong Gao, Yun-Yu Sun, et al. "Quantitate Detect of the Methylation of Three Hematopathy Patients’ P16 Gene." Blood 112, no. 11 (November 16, 2008): 4499. http://dx.doi.org/10.1182/blood.v112.11.4499.4499.

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Abstract Objective: The changes of methylation of CpG Island are the frequent changes in epigenetic. Nowadays, there are many methods to detect the changes of methylation, but all these method are hard to quantitate precisely. In our experiment, we will establish a new precise method. Methods: Use hydrosulfite to handle the DNA, and then do PCR. The cytosine will change to thymine, if it hasn’t been methylation. On the other side, the cytosine will maintain its state if it has been methylation. Design a pair of probe, which contain one methylation probe and one un methylation probe. This pair of probe will detect three consecutive sites of CpG island in P16. Our experiment will use gene chip. Mix the the DNA of methylation and unmethylation with different ratio, then build the standard curve. Contrast the patient sample with standard curve will get the quantitate result. Results: We detected three patients, the methylation degree of the patients is 84.3%, 0%, 17.7%. Conclusion: The method we used can detect methylation degree of three consecutive sites of P16 quantitate precisely. Solve the problem of quantitate precisely.

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Minegishi, Ryu, Osamu Gotoh, Norio Tanaka, Reo Maruyama, Jeffrey T. Chang, and Seiichi Mori. "A method of sample-wise region-set enrichment analysis for DNA methylomics." Epigenomics 13, no. 14 (July 2021): 1081–93. http://dx.doi.org/10.2217/epi-2021-0065.

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Aim: Gene set analysis has commonly been used to interpret DNA methylome data. However, summarizing the DNA methylation level of a gene is challenging due to variability in the number, density and methylation levels of CpG sites, and the numerous intergenic CpGs. Instead, we propose to use region sets to annotate the DNA methylome. Methods: We developed single sample region-set enrichment analysis for DNA methylome (methyl-ssRSEA) to conduct sample-wise, region-set enrichment analysis. Results: Methyl-ssRSEA can handle both microarray- and sequencing-based platforms and reproducibly recover the known biology from the methylation profiles of peripheral blood cells and breast cancers. The performance was superior to existing tools for region-set analysis in discriminating blood cell types. Conclusion: Methyl-ssRSEA offers a novel way to functionally interpret the DNA methylome in the cell.

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Sina, Abu Ali Ibn, Laura G. Carrascosa, Ramkumar Palanisamy, Sakandar Rauf, Muhammad J. A. Shiddiky, and Matt Trau. "Methylsorb: A Simple Method for Quantifying DNA Methylation Using DNA–Gold Affinity Interactions." Analytical Chemistry 86, no. 20 (September 29, 2014): 10179–85. http://dx.doi.org/10.1021/ac502214z.

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Zhang, Yuanyuan, Shudong Wang, and Xinzeng Wang. "Data-Driven-Based Approach to Identifying Differentially Methylated Regions Using Modified 1D Ising Model." BioMed Research International 2018 (November 18, 2018): 1–8. http://dx.doi.org/10.1155/2018/1070645.

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Background. DNA methylation is essential for regulating gene expression, and the changes of DNA methylation status are commonly discovered in disease. Therefore, identification of differentially methylation patterns, especially differentially methylated regions (DMRs), in two different groups is important for understanding the mechanism of complex diseases. Few tools exist for DMR identification through considering features of methylation data, but there is no comprehensive integration of the characteristics of DNA methylation data in current methods. Results. Accounting for the characteristics of methylation data, such as the correlation characteristics of neighboring CpG sites and the high heterogeneity of DNA methylation data, we propose a data-driven approach for DMR identification through evaluating the energy of single site using modified 1D Ising model. Applied to both simulated and publicly available datasets, our approach is compared with other popular methods in terms of performance. Simulated results show that our method is more sensitive than competing methods. Applied to the real data, our method can identify more common DMRs than DMRcate, ProbeLasso, and Wang’s methods with a high overlapping ratio. Also, the necessity of integrating the heterogeneity and correlation characteristics in identifying DMR is shown through comparing results with only considering mean or variance signals and without considering relationship of neighboring CpG sites, respectively. Through analyzing the number of DMRs identified in real data located in different genomic regions, we find that about 90% DMRs are located in CGI which always regulates the expression of genes. It may help us understand the functional effect of DNA methylation on disease.

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Pennings, S. "DNA Methylation: Approaches, Methods and Applications." Briefings in Functional Genomics and Proteomics 4, no. 1 (January 1, 2005): 82–83. http://dx.doi.org/10.1093/bfgp/4.1.82.

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Bruce, Sara, Katariina Hannula-Jouppi, Cecilia M. Lindgren, Marita Lipsanen-Nyman, and Juha Kere. "Restriction Site–Specific Methylation Studies of Imprinted Genes with Quantitative Real-Time PCR." Clinical Chemistry 54, no. 3 (March 1, 2008): 491–99. http://dx.doi.org/10.1373/clinchem.2007.098491.

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Abstract Background: Epigenetic studies, such as the measurement of DNA methylation, are important in the investigation of syndromes influenced by imprinted genes. Quick and accurate quantification of methylation at such genes can be of appreciable diagnostic aid. Methods: We first digested genomic DNA with methylation-sensitive restriction enzymes and used DNA without digestion as a control and nonmethylated λ DNA as an internal control for digestion efficiency. We then performed quantitative real-time PCR analyses with 6 unique PCR assays to investigate 4 imprinting control regions on chromosomes 7 and 11 in individuals with uniparental disomy of chromosome 7 (UPD7) and in control individuals. Results: Our validation of the method demonstrated both quantitative recovery and low methodologic imprecision. The imprinted loci on chromosome 7 behaved as expected in maternal UPD7 (100% methylation) and paternal UPD7 (<10% methylation). In controls, the mean (SD) for percent methylation at 2 previously well-studied restriction sites were 46% (6%) for both H19 and KCNQ1OT1, a result consistent with the previously observed methylation rate of approximately 50%. The methylation percentages of all investigated imprinted loci were normally distributed, implying that the mean and SD can be used as a reference for screening methylation loss or gain. Conclusion: The investigated loci are of particular importance for investigating the congenital Silver–Russell and Beckwith–Wiedemann syndromes; however, the method can also be applied to other imprinted regions. This method is easy to set up, has no PCR bias, requires small amounts of DNA, and can easily be applied to large patient populations for screening the loss or gain of methylation.

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Farhana, Fatema Zerin, Muhammad Umer, Ayad Saeed, Amandeep Singh Pannu, Sediqa Husaini, Prashant Sonar, Shakhawat H. Firoz, and Muhammad J. A. Shiddiky. "e-MagnetoMethyl IP: a magnetic nanoparticle-mediated immunoprecipitation and electrochemical detection method for global DNA methylation." Analyst 146, no. 11 (2021): 3654–65. http://dx.doi.org/10.1039/d1an00345c.

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e-MagnetoMethyl IP is a new method for electrochemical analysis of global DNA methylation. It avoids bisulfite treatment, PCR amplification, and enzyme-based signal generation and can detect differences as low as 5% in global DNA methylation levels.

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Wang, Shi, Jia Lv, Lingling Zhang, Jinzhuang Dou, Yan Sun, Xue Li, Xiaoteng Fu, et al. "MethylRAD: a simple and scalable method for genome-wide DNA methylation profiling using methylation-dependent restriction enzymes." Open Biology 5, no. 11 (November 2015): 150130. http://dx.doi.org/10.1098/rsob.150130.

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Characterization of dynamic DNA methylomes in diverse phylogenetic groups has attracted growing interest for a better understanding of the evolution of DNA methylation as well as its function and biological significance in eukaryotes. Sequencing-based methods are promising in fulfilling this task. However, none of the currently available methods offers the ‘perfect solution’, and they have limitations that prevent their application in the less studied phylogenetic groups. The recently discovered Mrr-like enzymes are appealing for new method development, owing to their ability to collect 32-bp methylated DNA fragments from the whole genome for high-throughput sequencing. Here, we have developed a simple and scalable DNA methylation profiling method (called MethylRAD) using Mrr-like enzymes. MethylRAD allows for de novo (reference-free) methylation analysis, extremely low DNA input (e.g. 1 ng) and adjustment of tag density, all of which are still unattainable for most widely used methylation profiling methods such as RRBS and MeDIP. We performed extensive analyses to validate the power and accuracy of our method in both model (plant Arabidopsis thaliana ) and non-model (scallop Patinopecten yessoensis ) species. We further demonstrated its great utility in identification of a gene ( LPCAT1 ) that is potentially crucial for carotenoid accumulation in scallop adductor muscle. MethylRAD has several advantages over existing tools and fills a void in the current epigenomic toolkit by providing a universal tool that can be used for diverse research applications, e.g. from model to non-model species, from ordinary to precious samples and from small to large genomes, but at an affordable cost.

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Viswanathan, Ramya, Elsie Cheruba, and Lih Feng Cheow. "DNA Analysis by Restriction Enzyme (DARE) enables concurrent genomic and epigenomic characterization of single cells." Nucleic Acids Research 47, no. 19 (August 16, 2019): e122-e122. http://dx.doi.org/10.1093/nar/gkz717.

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Abstract Genome-wide profiling of copy number alterations and DNA methylation in single cells could enable detailed investigation into the genomic and epigenomic heterogeneity of complex cell populations. However, current methods to do this require complex sample processing and cleanup steps, lack consistency, or are biased in their genomic representation. Here, we describe a novel single-tube enzymatic method, DNA Analysis by Restriction Enzyme (DARE), to perform deterministic whole genome amplification while preserving DNA methylation information. This method was evaluated on low amounts of DNA and single cells, and provides accurate copy number aberration calling and representative DNA methylation measurement across the whole genome. Single-cell DARE is an attractive and scalable approach for concurrent genomic and epigenomic characterization of cells in a heterogeneous population.

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Mizoguchi, Beatriz A., and Nicole Valenzuela. "A Cautionary Tale of Sexing by Methylation: Hybrid Bisulfite-Conversion Sequencing of Immunoprecipitated Methylated DNA in Chrysemys picta Turtles with Temperature-Dependent Sex Determination Reveals Contrasting Patterns of Somatic and Gonadal Methylation, but No Unobtrusive Sex Diagnostic." Animals 13, no. 1 (December 28, 2022): 117. http://dx.doi.org/10.3390/ani13010117.

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Background: The gonads of Chrysemys picta, a turtle with temperature-dependent sex determination (TSD), exhibit differential DNA methylation between males and females, but whether the same is true in somatic tissues remains unknown. Such differential DNA methylation in the soma would provide a non-lethal sex diagnostic for TSD turtle hatchings who lack visually detectable sexual dimorphism when young. Methods: Here, we tested multiple approaches to study DNA methylation in tail clips of Chrysemys picta hatchlings, to identify differentially methylated candidate regions/sites that could serve as molecular sex markers To detect global differential methylation in the tails we used methylation-sensitive ELISA, and to test for differential local methylation we developed a novel hybrid method by sequencing immunoprecipitated and bisulfite converted DNA (MeDIP-BS-seq) followed by PCR validation of candidate regions/sites after digestion with a methylation-sensitive restriction enzyme. Results: We detected no global differences in methylation between males and females via ELISA. While we detected inter-individual variation in DNA methylation in the tails, this variation was not sexually dimorphic, in contrast with hatchling gonads. Conclusions: Results highlight that differential DNA methylation is tissue-specific and plays a key role in gonadal formation (primary sexual development) and maintenance post-hatching, but not in the somatic tail tissue.

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Koczor, Christopher A., Eva K. Lee, Rebecca A. Torres, Amy Boyd, J. David Vega, Karan Uppal, Fan Yuan, Earl J. Fields, Allen M. Samarel, and William Lewis. "Detection of differentially methylated gene promoters in failing and nonfailing human left ventricle myocardium using computation analysis." Physiological Genomics 45, no. 14 (July 15, 2013): 597–605. http://dx.doi.org/10.1152/physiolgenomics.00013.2013.

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Human dilated cardiomyopathy (DCM) is characterized by congestive heart failure and altered myocardial gene expression. Epigenetic changes, including DNA methylation, are implicated in the development of DCM but have not been studied extensively. Clinical human DCM and nonfailing control left ventricle samples were individually analyzed for DNA methylation and expressional changes. Expression microarrays were used to identify 393 overexpressed and 349 underexpressed genes in DCM (GEO accession number: GSE43435 ). Gene promoter microarrays were utilized for DNA methylation analysis, and the resulting data were analyzed by two different computational methods. In the first method, we utilized subtractive analysis of DNA methylation peak data to identify 158 gene promoters exhibiting DNA methylation changes that correlated with expression changes. In the second method, a two-stage approach combined a particle swarm optimization feature selection algorithm and a discriminant analysis via mixed integer programming classifier to identify differentially methylated gene promoters. This analysis identified 51 hypermethylated promoters and six hypomethylated promoters in DCM with 100% cross-validation accuracy in the group assignment. Generation of a composite list of genes identified by subtractive analysis and two-stage computation analysis revealed four genes that exhibited differential DNA methylation by both methods in addition to altered gene expression. Computationally identified genes ( AURKB, BTNL9, CLDN5, and TK1) define a central set of differentially methylated gene promoters that are important in classifying DCM. These genes have no previously reported role in DCM. This study documents that rigorous computational analysis applied to microarray analysis of healthy and diseased human heart samples helps to define clinically relevant DNA methylation and expressional changes in DCM.

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Wong, Hui-Lee, Hyang-Min Byun, Jennifer M. Kwan, Mihaela Campan, Sue A. Ingles, Peter W. Laird, and Allen S. Yang. "Rapid and quantitative method of allele-specific DNA methylation analysis." BioTechniques 41, no. 6 (December 2006): 734–39. http://dx.doi.org/10.2144/000112305.

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Karimi, Mohsen, Sofia Johansson, Dirk Stach, Martin Corcoran, Dan Grandér, Martin Schalling, Georgy Bakalkin, Frank Lyko, Catharina Larsson, and Tomas J. Ekström. "LUMA (LUminometric Methylation Assay)—A high throughput method to the analysis of genomic DNA methylation." Experimental Cell Research 312, no. 11 (July 2006): 1989–95. http://dx.doi.org/10.1016/j.yexcr.2006.03.006.

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Brown, Lucia, Gregory Brown, Pamela Vacek, and Stephen Brown. "Aneuploidy Detection in Mixed DNA Samples by Methylation-Sensitive Amplification and Microarray Analysis." Clinical Chemistry 56, no. 5 (May 1, 2010): 805–13. http://dx.doi.org/10.1373/clinchem.2009.137877.

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Abstract Background: Cell-free fetal nucleic acid, believed to be derived from the placenta/trophoblast, is present in the plasma of pregnant women; however, its use for predictive genetic testing has been severely limited because the circulating fetal DNA is present in a small quantity and mixed with a much larger quantity of maternal DNA. Methods for detecting fetal aneuploidy from the cell-free fetal DNA in plasma are highly sought after, but proposed methods must take into account the small quantity and highly contaminated nature of the available fetal DNA. Methods: We developed a method for methylation-sensitive amplification of DNA suitable for use with small (approximately 1 ng) samples. We used this method in conjunction with 2-color microarray analysis with a custom-made array to investigate whether relative amplification, and hence relative methylation, could be evaluated for a large number of genomic loci. Results: Microarray assessment of genomic methylation accurately predicted the degree of methylation measured with bisulfite-conversion PCR and confirmed that DNA from first-trimester trophoblast was generally hypomethylated compared with whole-blood DNA. With a series of 3 samples in which 1 ng of DNA from a trisomic first trimester placenta was mixed with 9 ng of chromosomally normal peripheral blood DNA, we observed that the microarray signal associated with the trisomic chromosome was significantly different from that of the other chromosomes (P < 0.001). Conclusions: This method has potential to be used for noninvasive detection of fetal aneuploidy.

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Wee, Eugene J. H., Sakandar Rauf, Muhammad J. A. Shiddiky, Alexander Dobrovic, and Matt Trau. "DNA Ligase-Based Strategy for Quantifying Heterogeneous DNA Methylation without Sequencing." Clinical Chemistry 61, no. 1 (January 1, 2015): 163–71. http://dx.doi.org/10.1373/clinchem.2014.227546.

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Abstract BACKGROUND DNA methylation is a potential source of disease biomarkers. Typically, methylation levels are measured at individual cytosine/guanine (CpG) sites or over a short region of interest. However, regions of interest often show heterogeneous methylation comprising multiple patterns of methylation (epialleles) on individual DNA strands. Heterogeneous methylation is largely ignored because digital methods are required to deconvolute these usually complex patterns of epialleles. Currently, only single-molecule approaches, such as next generation sequencing (NGS), can provide detailed epiallele information. Because NGS is not yet feasible for routine practice, we developed a single-molecule–like approach, named for epiallele quantification (EpiQ). METHODS EpiQ uses DNA ligases and the enhanced thermal instability of short (≤19 bases) mismatched DNA probes for the relative quantification of epialleles. The assay was developed using fluorescent detection on a gel and then adapted for electrochemical detection on a microfabricated device. NGS was used to validate the analytical accuracy of EpiQ. RESULTS In this proof of principle study, EpiQ detected with 90%–95% specificity each of the 8 possible epialleles for a 3-CpG cluster at the promoter region of the CDKN2B (p15) tumor suppressor gene. EpiQ successfully profiled heterogeneous methylation patterns in clinically derived samples, and the results were cross-validated with NGS. CONCLUSIONS EpiQ is a potential alternative tool for characterizing heterogeneous methylation, thus facilitating its use as a biomarker. EpiQ was developed on a gel-based assay but can also easily be adapted for miniaturized chip-based platforms.

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Yu, Huichuan, Liangliang Bai, Guannan Tang, Xiaolin Wang, Meijin Huang, Guangwen Cao, Jianping Wang, and Yanxin Luo. "Novel Assay for Quantitative Analysis of DNA Methylation at Single-Base Resolution." Clinical Chemistry 65, no. 5 (May 1, 2019): 664–73. http://dx.doi.org/10.1373/clinchem.2018.298570.

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Abstract BACKGROUND The DNA methylation profile provides valuable biological information with potential clinical utility. Several methods, such as quantitative methylation-specific PCR (qMSP), have been developed to examine methylation of specific CpG sites. Existing qMSP-based techniques fail to examine the genomic methylation at a single-base resolution, particularly for loci in gene bodies or extensive CpG open seas lacking flanking CpGs. Therefore, we established a novel assay for quantitative analysis of single-base methylation. METHODS To achieve a robust single-base specificity, we developed a PCR-based method using paired probes following bisulfite treatment. The 6-carboxyfluorescein- and 2′-chloro-7′phenyl-1,4-dichloro-6-carboxy-fluorescein-labeled probes conjugated with minor groove binder were designed to specifically bind to the methylated and unmethylated allele of targeted single CpGs at their 3′ half regions, respectively. The methylation percentage was calculated by values of methylation / (methylation + unmethylation). RESULTS In the detection of single CpGs within promoters or bodies of 4 human genes, the quantitative analysis of the single-base methylation assay showed a detection capability in the 1 to 1:10000 dilution experiments with linearity over 4 orders of magnitude (R2 = 0.989–0.994; all P < 0.001). In a cohort of 10 colorectal cancer samples, the assay showed a comparable detection performance with bisulfite pyrosequencing (R2 = 0.875–0.990; all P < 0.001), which was better than conventional qMSP methods normalized by input control reaction (R2 = 0.841 vs 0.769; P = 0.002 vs 0.009). CONCLUSIONS This assay is highly specific and sensitive for determining single-base methylation and, thus, is potentially useful for methylation-based panels in diagnostic and prognostic applications.

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Ahuja, Nita, Ruby Kwak, Brian Keeley, Alejandro Stark, Angela Anna Guzzetta, Christopher Lee Wolfgang, James Gordon Herman, Christine A. Iacobuzio-Donahue, and Tza Huei Wang. "Blood-based screening for methylation changes in colorectal cancer patients using novel nanotechnologies." Journal of Clinical Oncology 31, no. 4_suppl (February 1, 2013): 384. http://dx.doi.org/10.1200/jco.2013.31.4_suppl.384.

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384 Background: Identification of blood-based biomarkers for cancer screening is essential in order to develop novel and minimally invasive methods for colorectal cancer screening. Our lab has successfully applied a novel nanotechnology that allows us to detect and amplify a single tumor DNA fragment in a plasma sample. This DNA is tested for methylation of several genes including TFPI2 which has shown to be highly sensitive and specific for the detection colorectal cancer in stool. Methods: Whole blood was obtained from 18 colorectal cancer patients and plasma was isolated. Plasma was processed using Methylation On Beads nanotechnology (MOB) and bisulfate treated. Methylation status was determined via quantitative PCR method. Results: Two genes, TFPI2 and IGFBP3, were detected with a high sensitivity. TFPI2, demonstrated a methylation frequency of 94.4%, which is concordant with the TFPI2 methylation frequency of 99% in primary colorectal cancer tissues. IGFBP3 showed the methylation frequency of 61.1%, which corresponds with the methylation frequency of 52% in retrospective colorectal cancer tissues in previous studies. Quantification using standard curves indicated a single copy level of DNA found in plasma. Conclusions: Blood-based screening is challenging due to extremely low quantities of circulating DNA in blood. Utilizing a novel nanotechnology that detects DNA at a single copy level, the methylation changes in colorectal cancer were successfully detected in plasmas at similar frequencies as in tissue samples. This study has demonstrated the feasablility and applicability to blood-based screening. Future studies will focus on improving the sensitivity and determining the specificity of this method.

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von Kanel, Thomas, Dominik Gerber, André Schaller, Alessandra Baumer, Eva Wey, Christopher B. Jackson, Franziska M. Gisler, Karl Heinimann, and Sabina Gallati. "Quantitative 1-Step DNA Methylation Analysis with Native Genomic DNA as Template." Clinical Chemistry 56, no. 7 (July 1, 2010): 1098–106. http://dx.doi.org/10.1373/clinchem.2009.142828.

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Abstract Background: DNA methylation analysis currently requires complex multistep procedures based on bisulfite conversion of unmethylated cytosines or on methylation-sensitive endonucleases. To facilitate DNA methylation analysis, we have developed a quantitative 1-step assay for DNA methylation analysis. Methods: The assay is based on combining methylation-sensitive FastDigest® endonuclease digestion and quantitative real-time PCR (qPCR) in a single reaction. The first step consists of DNA digestion, followed by endonuclease inactivation and qPCR. The degree of DNA methylation is evaluated by comparing the quantification cycles of a reaction containing a methylation-sensitive endonuclease with the reaction of a sham mixture containing no endonuclease. Control reactions interrogating an unmethylated locus allow the detection and correction of artifacts caused by endonuclease inhibitors, while simultaneously permitting copy number assessment of the locus of interest. Results: With our novel approach, we correctly diagnosed the imprinting disorders Prader–Willi syndrome and Angelman syndrome in 35 individuals by measuring methylation levels and copy numbers for the SNRPN (small nuclear ribonucleoprotein polypeptide N) promoter. We also demonstrated that the proposed correction model significantly (P < 0.05) increases the assay’s accuracy with low-quality DNA, allowing analysis of DNA samples with decreased digestibility, as is often the case in retrospective studies. Conclusions: Our novel DNA methylation assay reduces both the hands-on time and errors caused by handling and pipetting and allows methylation analyses to be completed within 90 min after DNA extraction. Combined with its precision and reliability, these features make the assay well suited for diagnostic procedures as well as high-throughput analyses.

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Prabhu, Jyothi S., Aruna Korlimarla, Arindam Banerjee, Shivangi Wani, K. Payal, and Rashmita Sahoo. "Gene-Specific Methylation: Potential Markers for Colorectal Cancer." International Journal of Biological Markers 24, no. 1 (January 2009): 57–62. http://dx.doi.org/10.1177/172460080902400109.

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Purpose Aberrant methylation of the promoter region is associated with silencing of many genes in neoplasia. CpG island methylation is an epigenetic mechanism for transcriptional silencing that occurs at various stages of colon tumorigenesis. In this study, we tested the promoter methylation and expression of seven genes from various pathways of DNA repair, apoptosis and inflammation, i.e., sFRP1, MLH1, RASSF1A, CDA, v-fgr, LYN-B, and TNFR10d. Method The genes were analyzed by quantitative polymerase chain reaction for the level of gene expression. The promoter methylation status of the genes was studied by methylation-specific polymerase chain reaction. Result The correlation of promoter methylation status with suppressed gene expression patterns suggested a potential role for the silencing these genes in colon cancer progression. Conclusion Promoter methylations of the studied genes could be explored as promising biomarkers for new diagnostic, prognostic and therapeutic targets of colorectal cancer.

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Karbalaie Niya, Mohammad Hadi, Naeimeh Roshan-zamir, and Elham Mortazavi. "DNA Methylation Tools and Strategies: Methods in a Review." Asian Pacific Journal of Cancer Biology 4, no. 3 (September 8, 2019): 51–57. http://dx.doi.org/10.31557/apjcb.2019.4.3.51-57.

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DNA methylation is known as an important epigenetic change in plants and vertebrates genome. In this process, the methyl group transferred by DNA methyl transferase enzymes to cytosine at carbon residue 5 often in the CpG dinucleotide context. DNA methylation plays an important role in the natural development of the organism, genome stability maintenance and processes such as genomic imprinting and chromosome X inactivation in mammals. In addition, changes in DNA methylation pattern have seen in many diseases, including cancer. Analysis of DNA methylation has been useful for rapid disease diagnosis and progression. In recent decades, a revolution has taken place in the methods of DNA methylation analysis, and it is possible to study the pattern of gene methylation at a widespread, short and high resolution level. These methods can be divided into three general categories: (1) cut-based methods by methylation-sensitive enzymes; (2) sodium bisulfide based methods; (3) antibody based methods. Since the existence of different methods makes it difficult to select the appropriate approach, in this review, a number of common methods for examining the methylation pattern with the advantages and disadvantages will be discussed.

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Stoccoro, Andrea, Pierpaola Tannorella, Lucia Migliore, and Fabio Coppedè. "Polymorphisms of genes required for methionine synthesis and DNA methylation influence mitochondrial DNA methylation." Epigenomics 12, no. 12 (June 2020): 1003–12. http://dx.doi.org/10.2217/epi-2020-0041.

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Aim: Impaired methylation of the mitochondrial DNA and particularly in the regulatory displacement loop (D-loop) region, is increasingly observed in patients with neurodegenerative disorders. The present study aims to investigate if common polymorphisms of genes required for one-carbon metabolism ( MTHFR, MTRR, MTR and RFC-1) and DNA methylation reactions ( DNMT1, DNMT3A and DNMT3B) influence D-loop methylation levels. Materials & methods: D-loop methylation data were available from 133 late-onset Alzheimer’s disease patients and 130 matched controls. Genotyping was performed with PCR-RFLP or high resolution melting techniques. Results: Both MTRR 66A > G and DNMT3A -448A > G polymorphisms were significantly associated with D-loop methylation levels. Conclusion: This exploratory study suggests that MTRR and DNMT3A polymorphisms influence mitochondrial DNA methylation; further research is required to better address this issue.

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