Developmental features of DNA methylation in CpG islands of human gametes and preimplantation embryos

Abstract Somatic cell nuclear transfer technique (SCNT) has proved to be an outstanding method of multiplication of elite animals but accompanied with low efficiency and live birth rate of cloned animals. Epigenetic alterations of DNA has been one of the culprits behind this issue. Cloned embryos are found to deviate slightly from regular pattern of demethylation and re-methylation at the time of nuclear reprogramming and embryonic development when compared with embryos produced by in vitro fertilization (IVF). Thus, the present study was aimed at evaluating global DNA methylation profiles of cloned embryos at 2-cell, 8-cell and blastocyst stages and compare it with corresponding stages of embryos produced by IVF by using MeDIP-Sequencing on Illumina-based platform. We found out that cloned embryos exhibited significantly different DNA methylation pattern as compared to IVF embryos with respect to distribution of differentially methylated regions in different components of genome, CpG islands distribution and methylation status, gene ontological profiles and pathways affected throughout the developmental stages. The data generated from MeDIP-Seq was validated at blastocyst stage cloned and IVF embryos by bisulfite-sequencing PCR on five randomly selected gene regions.

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Conservation of DNA Methylation Programming Between Mouse and Human Gametes and Preimplantation Embryos

Biology of Reproduction ◽

10.1095/biolreprod.116.140319 ◽

2016 ◽

Vol 95 (3) ◽

pp. 61-61 ◽

Cited By ~ 11

Author(s):

C. R. White ◽

W. A. MacDonald ◽

M. R. W. Mann

Keyword(s):

Dna Methylation ◽

Preimplantation Embryos ◽

Human Gametes

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Data Mining Technique Applied To DNA Sequencing

International Research Journal of Management IT and Social Sciences ◽

10.21744/irjmis.v2i7.70 ◽

2015 ◽

Vol 2 (7) ◽

pp. 18

Author(s):

R. Jamuna

Keyword(s):

Data Mining ◽

Dna Methylation ◽

Markov Chain ◽

Human Genome ◽

Transition Probabilities ◽

Markov Chain Model ◽

Effective Means ◽

Cpg Islands ◽

Chain Model ◽

The Given

CpG islands (CGIs) play a vital role in genome analysis as genomic markers. Identification of the CpG pair has contributed not only to the prediction of promoters but also to the understanding of the epigenetic causes of cancer. In the human genome [1] wherever the dinucleotides CG occurs the C nucleotide (cytosine) undergoes chemical modifications. There is a relatively high probability of this modification that mutates C into a T. For biologically important reasons the mutation modification process is suppressed in short stretches of the genome, such as ‘start’ regions. In these regions [2] predominant CpG dinucleotides are found than elsewhere. Such regions are called CpG islands. DNA methylation is an effective means by which gene expression is silenced. In normal cells, DNA methylation functions to prevent the expression of imprinted and inactive X chromosome genes. In cancerous cells, DNA methylation inactivates tumor-suppressor genes, as well as DNA repair genes, can disrupt cell-cycle regulation. The most current methods for identifying CGIs suffered from various limitations and involved a lot of human interventions. This paper gives an easy searching technique with data mining of Markov Chain in genes. Markov chain model has been applied to study the probability of occurrence of C-G pair in the given gene sequence. Maximum Likelihood estimators for the transition probabilities for each model and analgously for the model has been developed and log odds ratio that is calculated estimates the presence or absence of CpG is lands in the given gene which brings in many facts for the cancer detection in human genome.

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Two competing mechanisms of DNMT3A recruitment regulate the dynamics of de novo DNA methylation at PRC1-targeted CpG islands

Nature Genetics ◽

10.1038/s41588-021-00856-5 ◽

2021 ◽

Author(s):

Daniel N. Weinberg ◽

Phillip Rosenbaum ◽

Xiao Chen ◽

Douglas Barrows ◽

Cynthia Horth ◽

...

Keyword(s):

Dna Methylation ◽

De Novo ◽

Cpg Islands

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DNA Methylation of Human Choline Kinase Alpha Promoter-Associated CpG Islands in MCF-7 Cells

Genes ◽

10.3390/genes12060853 ◽

2021 ◽

Vol 12 (6) ◽

pp. 853

Author(s):

Siti Aisyah Faten Mohamed Sa’dom ◽

Sweta Raikundalia ◽

Shaharum Shamsuddin ◽

Wei Cun See Too ◽

Ling Ling Few

Keyword(s):

Dna Methylation ◽

Transcription Factor ◽

Binding Site ◽

Promoter Activity ◽

Cytosine Methylation ◽

Cpg Island ◽

Cpg Islands ◽

Site Directed Mutagenesis ◽

Choline Kinase ◽

Mcf 7

Choline kinase (CK) is the enzyme catalyzing the first reaction in CDP-choline pathway for the biosynthesis of phosphatidylcholine. Higher expression of the α isozyme of CK has been implicated in carcinogenesis, and inhibition or downregulation of CKα (CHKA) is a promising anticancer approach. This study aimed to investigate the regulation of CKα expression by DNA methylation of the CpG islands found on the promoter of this gene in MCF-7 cells. Four CpG islands have been predicted in the 2000 bp promoter region of ckα (chka) gene. Six CpG island deletion mutants were constructed using PCR site-directed mutagenesis method and cloned into pGL4.10 vectors for promoter activity assays. Deletion of CpG4C region located between –225 and –56 significantly increased the promoter activity by 4-fold, indicating the presence of important repressive transcription factor binding site. The promoter activity of methylated full-length promoter was significantly lower than the methylated CpG4C deletion mutant by 16-fold. The results show that DNA methylation of CpG4C promotes the binding of the transcription factor that suppresses the promoter activity. Electrophoretic mobility shift assay analysis showed that cytosine methylation at MZF1 binding site in CpG4C increased the binding of putative MZF1 in nuclear extract. In conclusion, the results suggest that DNA methylation decreased the promoter activity by promoting the binding of putative MZF1 transcription factor at CpG4C region of the ckα gene promoter.

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PGC7 suppresses TET3 for protecting DNA methylation

Nucleic Acids Research ◽

10.1093/nar/gkt1261 ◽

2013 ◽

Vol 42 (5) ◽

pp. 2893-2905 ◽

Cited By ~ 39

Author(s):

Chunjing Bian ◽

Xiaochun Yu

Keyword(s):

Dna Methylation ◽

Molecular Mechanism ◽

Biological Process ◽

Cpg Islands ◽

Binding Motifs ◽

Genome Wide Analysis ◽

Dna Motif ◽

Genome Wide

Abstract Ten-eleven translocation (TET) family enzymes convert 5-methylcytosine to 5-hydroxylmethylcytosine. However, the molecular mechanism that regulates this biological process is not clear. Here, we show the evidence that PGC7 (also known as Dppa3 or Stella) interacts with TET2 and TET3 both in vitro and in vivo to suppress the enzymatic activity of TET2 and TET3. Moreover, lacking PGC7 induces the loss of DNA methylation at imprinting loci. Genome-wide analysis of PGC7 reveals a consensus DNA motif that is recognized by PGC7. The CpG islands surrounding the PGC7-binding motifs are hypermethylated. Taken together, our study demonstrates a molecular mechanism by which PGC7 protects DNA methylation from TET family enzyme-dependent oxidation.

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Pilot study of DNA methylation in the pathogenesis of chronic rhinosinusitis with nasal polyps

Rhinology Journal ◽

10.4193/rhino14.086 ◽

2015 ◽

Vol 53 (4) ◽

pp. 345-352

Author(s):

Y.B. Zheng ◽

Y. Zhao ◽

L.Y. Yue ◽

P. Lin ◽

Y.F. Liu ◽

...

Keyword(s):

Dna Methylation ◽

Polymerase Chain Reaction ◽

Chronic Rhinosinusitis ◽

Nasal Polyps ◽

Cpg Islands ◽

Inferior Turbinate ◽

Control Group ◽

Chain Reaction ◽

Bisulphite Sequencing ◽

Polymerase Chain

Background: DNA methylation has been implicated in the pathogenesis of allergy and atopy. This study aimed to identify whether DNA methylation also plays an important role in the pathogenesis of nasal polyps (NP). Methodology: NP tissues were obtained from 32 patients with chronic rhinosinusitis with bilateral NP. Biopsies of inferior turbinate mucosa (ITM) were taken from 18 patients who underwent rhinoseptoplasty (control group). The methylated genes, which were detected by DNA methylation microarray, were validated by methylation-specific polymerase chain reaction, bisulphite sequencing, real-time polymerase chain reaction and immunohistochemistry. Results: DNA methylation microarray identified 8,008 CpG islands in 2,848 genes. One hundred and ninety-eight genes were found to have a methylated signal in the promoter region in NP samples compared with ITM samples. The four top genes that changed, COL18A1, EP300, GNAS and SMURF1, were selected for further study. The methylation frequency of COL18A1 was significantly higher in NP samples than in ITM samples. Conclusions: DNA methylation might play an important role in the pathogenesis of NP. Promoter methylation of COL18A1 was found to be significantly increased in NP tissues, further studies are necessary to confirm the significance of these epigenetic factors in the mechanisms underlying the development or persistence of NP.

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Epigenetic analysis of Paget’s disease of bone identifies differentially methylated loci that predict disease status

10.1101/2021.01.04.425216 ◽

2021 ◽

Author(s):

Ilhame Diboun ◽

Sachin Wani ◽

Stuart H Ralston ◽

Omar M E Albagha

Keyword(s):

Dna Methylation ◽

Meta Analysis ◽

Cpg Islands ◽

Osteoclast Differentiation ◽

Paget’S Disease ◽

Disease Status ◽

Paget's Disease ◽

Paget’S Disease Of Bone ◽

Paget's Disease Of Bone ◽

Body Regions

AbstractPaget’s Disease of Bone (PDB) is characterized by focal increases in disorganized bone remodeling. This study aims to characterize PDB associated changes in DNA methylation profiles in patients’ blood. Meta-analysis of data from the discovery and replication set, comprising of 116 PDB cases and 130 controls, revealed significant differences in DNA methylation at 14 CpG sites, 4 CpG islands, and 6 gene-body regions. These loci, including two characterized as functional through eQTM analysis, were associated with functions related to osteoclast differentiation, mechanical loading, immune function, and viral infection. A multivariate classifier based on discovery samples was found to discriminate PDB cases and controls from the replication with a sensitivity of 0.84, specificity of 0.81, and an area under curve of 92.8%. In conclusion, this study has shown for the first time that epigenetic factors contribute to the pathogenesis of PDB and may offer diagnostic markers for prediction of the disease.

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