De novo DNA methylation at the CpG island of the zebrafish no tail gene

The zebrafish no tail gene (ntl) is indispensable for the formation of the notochord and the tail structure. Here we showed that de novo DNA methylation occurred at the CpG island of ntl. The methylation started at the segmentation stage and continued after the larval stage. However, it occurred predominantly between 14 and 48 h postfertilization, which overlaps the period in which ntl expression disappears in the notochord and the tailbud. This inverse correlation, together with the methylation-associated formation of an inaccessible chromatin structure at the ntl CpG island region, suggested the involvement of the de novo methylation in ntl repression. Since no changes in methylation patterns were observed at the CpG islands of four other zebrafish genes, there must be a mechanism in zebrafish for specific methylation of the ntl CpG island.     

Genome-wide methylation analysis identifies differentially methylated CpG loci associated with severe obesity in childhood

Childhood obesity is a major public health issue. Here we investigated whether differential DNA methylation was associated with childhood obesity. We studied DNA methylation profiles in whole blood from 78 obese children (mean BMI Z-score: 2.6) and 71 age- and sex-matched controls (mean BMI Z-score: 0.1). DNA samples from obese and control groups were pooled and analyzed using the Infinium HumanMethylation450 BeadChip array. Comparison of the methylation profiles between obese and control subjects revealed 129 differentially methylated CpG (DMCpG) loci associated with 80 unique genes that had a greater than 10% difference in methylation (P-value < 0.05). The top pathways enriched among the DMCpGs included developmental processes, immune system regulation, regulation of cell signaling, and small GTPase-mediated signal transduction. The associations between the methylation of selected DMCpGs with childhood obesity were validated using sodium bisulfite pyrosequencing across loci within the FYN, PIWIL4, and TAOK3 genes in individual subjects. Three CpG loci within FYN were hypermethylated in obese individuals (all P < 0.01), while obesity was associated with lower methylation of CpG loci within PIWIL4 (P = 0.003) and TAOK3 (P = 0.001). After building logistic regression models, we determined that a 1% increase in methylation in TAOK3, multiplicatively decreased the odds of being obese by 0.91 (95% CI: 0.86 – 0.97), and an increase of 1% methylation in FYN CpG3, multiplicatively increased the odds of being obese by 1.03 (95% CI: 0.99 – 1.07). In conclusion, these findings provide evidence that childhood obesity is associated with specific DNA methylation changes in whole blood, which may have utility as biomarkers of obesity risk.     

Global, comparative analysis of tissue-specific promoter CpG methylation

Understanding cell-type-specific epigenetic codes on a global level is a major challenge after the sequencing of the human genome has been completed. Here we applied methyl-CpG immunoprecipitation (MCIp) to obtain comparative methylation profiles of coding and noncoding genes in three human tissues, testis, brain, and monocytes. Forty-four mainly testis-specific promoters were independently validated using bisulfite sequencing or single-gene MCIp, confirming the results obtained by the MCIp microarray approach. We demonstrate the previously unknown somatic hypermethylation at many CpG-rich, testis-specific gene promoters, in particular in ampliconic areas of the Y chromosome. We also identify a number of miRNA genes showing tissue-specific methylation patterns. The comparison of the obtained tissue methylation profiles with corresponding gene expression data indicates a significant association between tissue-specific promoter methylation and gene expression, not only in CpG-rich promoters. In summary, our study highlights the exceptional epigenetic status of germ-line cells in testis and provides a global insight into tissue-specific DNA methylation patterns.     

Evaluation of single CpG sites as proxies of CpG island methylation states at the genome scale

Methylation of a CpG island is a faithful marker of silencing of its associated gene. Different approaches report the methylation status of a CpG island based on the determination of one or a few CpG sites by assuming the homogeneity of methylation along the element. This strategy is frequently applied in both locus-specific and genome-wide studies, but often without a validation of the representativeness of the interrogated CpG site compared with the whole element. We have evaluated the predictive informativeness of the HpaII sites located in CpG islands using data from high-resolution methylome maps, which offer the possibility to assess the methylation homogeneity of each CpG island and to determine the reporter accuracy of single sites as surrogate markers. An excellent correlation was observed between the HpaII and CpG island methylation levels (r > 0.93). At the qualitative level, the predictive sensitivity of HpaII was >95% with >92% specificity for methylated CpG islands and >90% sensitivity with >95% specificity for unmethylated CpG islands. This analysis provides a global validation framework for strategies based on the use of the methylation-sensitive HpaII restriction enzyme.     

DNA motifs associated with aberrant CpG island methylation

Epigenetic silencing involving the aberrant methylation of promoter region CpG islands is widely recognized as a tumor suppressor silencing mechanism in cancer. However, the molecular pathways underlying aberrant DNA methylation remain elusive. Recently we showed that, on a genome-wide level, CpG island loci differ in their intrinsic susceptibility to aberrant methylation and that this susceptibility can be predicted based on underlying sequence context. These data suggest that there are sequence/structural features that contribute to the protection from or susceptibility to aberrant methylation. Here we use motif elicitation coupled with classification techniques to identify DNA sequence motifs that selectively define methylation-prone or methylation-resistant CpG islands. Motifs common to 28 methylation-prone or 47 methylation-resistant CpG island-containing genomic fragments were determined using the MEME and MAST algorithms (). The five most discriminatory motifs derived from methylation-prone sequences were found to be associated with CpG islands in general and were nonrandomly distributed throughout the genome. In contrast, the eight most discriminatory motifs derived from the methylation-resistant CpG islands were randomly distributed throughout the genome. Interestingly, this latter group tended to associate with Alu and other repetitive sequences. Used together, the frequency of occurrence of these motifs successfully discriminated methylation-prone and methylation-resistant CpG island groups with an accuracy of 87% after 10-fold cross-validation. The motifs identified here are candidate methylation-targeting or methylation-protection DNA sequences.     

CpG island methylation in precursors of gastrointestinal malignancies

Gastrointestinal malignancies account for about 20% of all cancers worldwide. It is widely accepted that cancer evolves through several stepwise morphological stages such as the adenoma-carcinoma and hyperplastic polyp-serrated adenoma-carcinoma sequences in colorectal cancers, and the metaplasia-dysplasia-carcinoma sequences in esophageal and gastric cancers. The morphological progression is associated with the accumulation of multiple genetic and epigenetic events. It is now recognized that epigenetic silencing of gene expression by CpG island methylation is an important alternative mechanism of inactivating tumor suppressor genes. Inflammatory conditions of the gastrointestinal and pancreaticobiliary tracts and liver such as Barrett esophagus, Helicobacter pylori gastritis, inflammatory bowel disease and viral hepatitis, are associated with increased frequency of malignancies and CpG methylation. In addition, CpG methylation is present in aberrant crypt foci and pancreatic intraepithelial neoplasia that are considered putative precursors of colon and pancreatic carcinomas, respectively. Understanding of these early genetic and epigenetic changes allows for the discoveries of potential screening, monitoring and therapeutic strategies. Targeting of the epigenetic changes that occur before the development of frank malignancy offers a potential chemopreventive strategy.     

CpG methylation modulates tissue-specific expression of a transgene in chickens

The use of genetically modified germ cells is an ideal system to induce transgenesis in birds; the primordial germ cell (PGC) is the most promising candidate for this system. In the present study, we confirmed the practical application of this system using lentivirus-transduced chicken gonadal PGCs (gPGCs). Embryonic gonads were collected from 5.5-d old Korean Oge chickens (black feathers). The gPGC population was enriched (magnetic-activated cell sorting technique) and then they were transduced with a lentiviral vector expressing enhanced green fluorescent protein (eGFP), under the control of the Rous sarcoma virus (RSV) promoter. Subsequently, the eGFP-transduced PGCs were transplanted into blood vessels of 2.5-d-old embryonic White Leghorn (white feathers). Among 21 germline chimeric chickens, one male produced transgenic offspring (G₁ generation), as demonstrated by testcross and genetic analysis. A homozygous line was produced and maintained through the G₃ generation. Based on serum biochemistry, there were no significant physiological differences between G₃ homozygotes and non-transgenic chickens. However, since eGFP transgene expression in G₃ chickens varied among tissues, it was further characterized by Western blotting and ELISA. Furthermore, there were indications that DNA methylation may have affected tissue-specific expression of transgenes in chickens. In conclusion, the PGC-mediated approach used may be an efficient tool for avian transgenesis, and transgenic chickens could provide a useful model for investigating regulation of gene expression.     

CpG island methylation pattern in different human tissues and its correlation with gene expression

The study on DNA methylation pattern in different human tissues attracts increasing interest nowadays, but a systematic analysis of CpG island methylation pattern between both somatic tissues and gametocyte is still lacking. In this work, we analyzed the CpG island methylation data of sperm and other 11 somatic tissues from Human Epigenome Project, and found that the CpG island methylation profiles are highly correlated between somatic tissues, while the methylation profile in sperm is quite distinct. Furthermore, we observed that in the six tissues investigated, there is no obvious correlation between the methylation level of promoter CpG islands and corresponding gene expression across different tissues.     

山羊克隆胎儿不同组织中H19基因CpG岛甲基化模式及表达量检测

表观重编程异常是核移植胚胎发育异常的重要原因。为了研究克隆山羊胎儿不同组织中H19基因CpG岛甲基化水平和相对表达量,本实验运用亚硫酸盐法和荧光实时定量PCR法分别检测了死亡克隆山羊胎儿和同期普通山羊胎儿(对照组)肝脏、胎盘、肾脏、肺脏和心脏组织中H19基因CpG岛甲基化水平和mRNA的相对表达量。结果表明,克隆山羊胎儿胎盘组织中H19基因第5个CpG岛的甲基化水平显著高于对照组(70%vs49.41%,P0.05),H19基因相对表达量显著低于对照组(883.3vs1264.5,P0.05);肺脏组织甲基化水平显著低于对照组(63.53%vs88.24%,P0.05),相对表达量显著高于对照组(1003.4vs515.5,P0.05);其他各组差异不显著(P0.05)。结果说明,H19基因在克隆山羊胎儿部分组织中DNA甲基化重编程异常,而且这种异常影响H19基因的正常表达,这也可能是导致克隆动物死亡的重要因素之一。     

Smchd1-dependent and -independent pathways determine developmental dynamics of CpG island methylation on the inactive x chromosome

X chromosome inactivation involves multiple levels of chromatin modification, established progressively and in a stepwise manner during early development. The chromosomal protein Smchd1 was recently shown to play an important role in DNA methylation of CpG islands (CGIs), a late step in the X inactivation?pathway that is required for long-term maintenance of gene silencing. Here we show that inactive X chromosome (Xi) CGI methylation can occur via either Smchd1-dependent or -independent pathways. Smchd1-dependent CGI methylation, the primary pathway, is acquired gradually over an extended period, whereas Smchd1-independent CGI methylation occurs rapidly after the onset of X inactivation. The de novo methyltransferase Dnmt3b is required for methylation of both classes of CGI, whereas Dnmt3a and Dnmt3L are dispensable. Xi CGIs methylated by these distinct pathways differ with respect to their sequence characteristics and immediate chromosomal environment. We discuss the implications of these results for understanding CGI methylation during development.     

Tissue-specific methylation of a CpG island in transgenic mice.

Clustering of CpG dinucleotides in CpG-rich islands is a characteristic feature of mammalian genomes. Such CpG islands are frequently associated with genes and usually hypomethylated, regardless of the gene activity. This is the case for the CpG island of the murine Thy-1 gene. A transgenic line containing multiple copies of a truncated, concatemeric CpG island from the Thy-1.1 allele (Thy-1.2 background) showed that a stable fraction (approx. 0.20) became fully methylated in somatic tissues of homozygous mice with respect to testable restriction sites, while the remaining copies were methylation-free, i.e., this methylation appears to be an 'all-or-none' phenomenon. DNA from extraembryonic tissues (placenta and yolk sac) and epididymal sperm showed, however, an even higher degree of methylation in two distinct patterns. In the extraembryonic tissue, partial methylation of each copy was seen, whereas in sperm a high degree of 'all-or-none' methylation (greater than 0.35) was observed.     

A human CpG island randomly inserted into a plant genome is protected from methylation

In vertebrate genomes the dinucleotide CpG is heavily methylated, except in CpG islands, which are normally unmethylated. It is not clear why the CpG islands are such poor substrates for DNA methyltransferase. Plant genomes display methylation, but otherwise the genomes of plants and animals represent two very divergent evolutionary lines. To gain a further understanding of the resistance of CpG islands to methylation, we introduced a human CpG island from the proteasome-like subunit I gene into the genome of the plant Arabidopsis thaliana. Our results show that prevention of methylation is an intrinsic property of CpG islands, recognized even if a human CpG island is transferred to a plant genome. Two different parts of the human CpG island – the promoter region/ first exon and exon2–4 – both displayed resistance against methylation, but the promoter/ exon1 construct seemed to be most resistant. In contrast, certain sites in a plant CpG-rich region used as a control transgene were always methylated. The frequency of silencing of the adjacent nptII (Km^R) gene in the human CpG constructs was lower than observed for the plant CpG-rich region. These results have implications for understanding DNA methylation, and for construction of vectors that will reduce transgene silencing.     

MMASS: an optimized array-based method for assessing CpG island methylation

We describe an optimized microarray method for identifying genome-wide CpG island methylation called microarray-based methylation assessment of single samples (MMASS) which directly compares methylated to unmethylated sequences within a single sample. To improve previous methods we used bioinformatic analysis to predict an optimized combination of methylation-sensitive enzymes that had the highest utility for CpG-island probes and different methods to produce unmethylated representations of test DNA for more sensitive detection of differential methylation by hybridization. Subtraction or methylation-dependent digestion with McrBC was used with optimized (MMASS-v2) or previously described (MMASS-v1, MMASS-sub) methylation-sensitive enzyme combinations and compared with a published McrBC method. Comparison was performed using DNA from the cell line HCT116. We show that the distribution of methylation microarray data is inherently skewed and requires exogenous spiked controls for normalization and that analysis of digestion of methylated and unmethylated control sequences together with linear fit models of replicate data showed superior statistical power for the MMASS-v2 method. Comparison with previous methylation data for HCT116 and validation of CpG islands from PXMP4, SFRP2, DCC, RARB and TSEN2 confirmed the accuracy of MMASS-v2 results. The MMASS-v2 method offers improved sensitivity and statistical power for high-throughput microarray identification of differential methylation.