Segregation of partly melted DNA molecules

Segregation of partly melted DNA molecules is a convenient and efficient method to isolate DNA fragments associated with CpG islands. The method stands on the observation that the electrophoretic mobility of partly melted DNA fragments in a denaturing gradient gel is low and that they persist in the gel so long as the remaining helical part is sufficiently resistant to strand dissociation and dissociates slowly. Such features are observed in DNA fragments derived from CpG islands. These DNA fragments are preferentially retained in a denaturing gradient gel after prolonged electric field exposure, permitting the enrichment of DNA fragments derived from CpG islands. The principle and practical application of this method are reviewed.     

Segregation of Partly Melted DNA Molecules

Segregation of partly melted DNA molecules is a convenient and efficient method to isolate DNA fragments associated with CpG islands. The method stands on the observation that the electrophoretic mobility of partly melted DNA fragments in a denaturing gradient gel is low and that they persist in the gel so long as the remaining helical part is sufficiently resistant to strand dissociation and dissociates slowly. Such features are observed in DNA fragments derived from CpG islands. These DNA fragments are preferentially retained in a denaturing gradient gel after prolonged electric field exposure, permitting the enrichment of DNA fragments derived from CpG islands. The principle and practical application of this method are reviewed.     

The isolation of CpG islands from human chromosomal regions 11q13 and Xp22 by segregation of partlymelted molecules.

We isolated fragments containing parts of CpG islands from human chromosomal regions chosen for expected differences in gene density by segregation of partly melted molecules. Restriction fragments of P1 bacteriophage clones covering a region of 11q13 and those of cosmid clones derived from Xp22 were recovered from bands in denaturing gradient gels that were retained following prolonged exposure to electric field. Forty-five independent fragments derived from 11q13 and five from Xp22 were isolated. Nucleotide sequence analysis revealed that 11 of the 45 fragments from 11q13 contained CpG islands including four derived from known genes in 11q13. None of the five fragments derived from Xp22 resembled CpG islands. The number of CpG island fragments obtained was consistent with the expectation based on the number of Not I restriction endonuclease sites present at these regions. Adjustment of parameters in our quasi-theoretical approach to the rate of fragment dissociation improves the discrimination between retention and non-retention. The results support probable identification of CpG island fragments by their reduced rate of strand dissociation when retarded in a denaturing gradient gel.     

Quick Identification and Localization of CpG Islands in Large Genomic Fragments by Partial Digestion with Hpa II and Hha I

More than 50% of mammalian genes are associated with CpG islandsand thus they serve as a good gene marker. We have devised asimple method to scan large pieces of native or cloned genomicDNA for CpG islands. The method is based on the presence ofmultiple Hpa II and Hha I sites in CpG islands, at a frequency30 times higher than in the rest of the genome. The steps includecomplete digestion of DNA with a rare-cutting restriction endonuclease(to produce large fragments with defined ends), partial digestionwith Hpa II and Hha I, and subsequent Southern hybridizationwith an end probe. This identifies a CpG island as a clusterof sub-bands and, based on their electrophoretic mobility, onecan immediately locate the island relative to the ends. Formany vectors, universal probes flanking the cloning site areavailable, enabling the simultaneous analysis of a large numberof samples. We demonstrated the usefulness of the method byanalyzing known CpG islands in native genomic DNA and lambda,cosmid and P1 clones, and by isolating two novel transcribedislands from anonymous cosmid clones. Our method is quick, inexpensive,and can detect CpG islands with few or even no rare-cutter sites.     

Reduced representation bisulfite sequencing design for assessing the methylation of human CpG islands in large samples

The reduced representation bisulfite sequencing (RRBS) method has been developed for the high-throughput analysis of DNA methylation based on the sequencing of genomic libraries treated with sodium bisulfite by next-generation approaches. In contrast to whole-genome sequencing, the RRBS approach elaborates specific endonucleases to prepare libraries in order to produce pools of CpG-rich DNA fragments. The original RRBS technology based on the use of the MspI libraries allows one to increase the relative number of CpG islands in the pools of genomic fragments compared to whole-genome bisulfite sequencing. Nevertheless, this technology is rarely used due to the high cost compared with bisulfite methylation analysis with hybridization microarrays and significant residual amount of data represented by the sequences of genomic repeats that complicates the alignment and is not of particular interest for developing DNA methylation markers, which is often the main goal of biomedical research. We have developed an algorithm for estimating the likelihood that recognition sites of restriction endonucleases will be represented in CpG islands and present a method of reducing the effective size of the RRBS library without a significant loss of the CpG islands based on the use of the XmaI endonuclease for library preparation. In silico analysis demonstrates that the optimum range of the XmaI-RRBS fragment lengths is 110–200 base pairs. The sequencing of this library allows one to assess the methylation status of over 125000 CpG dinucleotides, of which over 90000 belong to CpG islands.

     

Restriction landmark genome scanning

Restriction landmark genome scanning (RLGS) is a quantitative approach that is uniquely suited for simultaneously assessing the methylation status of thousands of CpG islands. RLGS separates radiolabeled NotI fragments (or other CpG-containing restriction enzyme fragments) in two dimensions and allows distinction of single-copy CpG islands from multicopy CpG-rich sequences. The methylation sensitivity of the endonuclease activity of NotI provides the basis for differential methylation analysis, and NotI sites occur primarily in CpG islands and genes. RLGS has been used to identify novel imprinted genes, novel targets of DNA amplification and methylation in human cancer, and to identify deletion, methylation, and gene amplification in a mouse model of tumorigenesis. Such massively parallel analyses are critical for pattern recognition within and between tumor types, and for estimating the overall influence of CpG island methylation on the cancer cell genome. RLGS is also a useful method for integrating methylation analyses with high-resolution gene copy number analyses.     

A Hybrid Approach for CpG Island Detection in the Human Genome

Background

CpG islands have been demonstrated to influence local chromatin structures and simplify the regulation of gene activity. However, the accurate and rapid determination of CpG islands for whole DNA sequences remains experimentally and computationally challenging.

Methodology/Principal Findings

A novel procedure is proposed to detect CpG islands by combining clustering technology with the sliding-window method (PSO-based). Clustering technology is used to detect the locations of all possible CpG islands and process the data, thus effectively obviating the need for the extensive and unnecessary processing of DNA fragments, and thus improving the efficiency of sliding-window based particle swarm optimization (PSO) search. This proposed approach, named ClusterPSO, provides versatile and highly-sensitive detection of CpG islands in the human genome. In addition, the detection efficiency of ClusterPSO is compared with eight CpG island detection methods in the human genome. Comparison of the detection efficiency for the CpG islands in human genome, including sensitivity, specificity, accuracy, performance coefficient (PC), and correlation coefficient (CC), ClusterPSO revealed superior detection ability among all of the test methods. Moreover, the combination of clustering technology and PSO method can successfully overcome their respective drawbacks while maintaining their advantages. Thus, clustering technology could be hybridized with the optimization algorithm method to optimize CpG island detection.

Conclusion/Significance

The prediction accuracy of ClusterPSO was quite high, indicating the combination of CpGcluster and PSO has several advantages over CpGcluster and PSO alone. In addition, ClusterPSO significantly reduced implementation time.     

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.     

一种快速高效的全基因组甲基化CpG岛富集方法的建立

高甲基化的CpG岛所致基因表观遗传学转录失活已经成为肿瘤表观基因组学研究的重要内容。现在已有很多检测CpG岛甲基化的方法,但由于各自的局限,还没有建立一种能快速在全基因组水平上进行甲基化CpG岛的富集方法。本研究利用甲基化结合蛋白MBD2b具有特异性结合甲基化DNA的特性, 建立了一种基于DNA免疫共沉淀技术的全基因组甲基化CpG岛的富集方法。在大肠杆菌中表达重组的GST-MBD2b蛋白,通过Glutathione Sepharose 4B对重组蛋白进行纯化,制备成亲和层析柱,利用在不同的盐离子强度下甲基化DNA和非甲基化DNA的结合能力不同,对甲基化DNA进行富集。用甲基化酶SssI处理过的DNA片段与非甲基化DNA片段进行富集效率的检测,发现0.5M KCl的浓度是甲基化DNA片段和非甲基化DNA片段得以分开的临界条件。样品的富集效率用Real Time PCR进行检测。结果表明,这种方法能够实现对全基因组甲基化DNA的有效富集且最高的富集倍数可达到100多倍。富集到的甲基化DNA可以进行后续的定量PCR, DNA测序和全基因组芯片的分析等工作,为大规模分析全基因组CpG 岛甲基化的改变奠定了基础。     

CpG island methylation in human lymphocytes is highly correlated with DNA sequence, repeats, and predicted DNA structure

CpG island methylation plays an important role in epigenetic gene control during mammalian development and is frequently altered in disease situations such as cancer. The majority of CpG islands is normally unmethylated, but a sizeable fraction is prone to become methylated in various cell types and pathological situations. The goal of this study is to show that a computational epigenetics approach can discriminate between CpG islands that are prone to methylation from those that remain unmethylated. We develop a bioinformatics scoring and prediction method on the basis of a set of 1,184 DNA attributes, which refer to sequence, repeats, predicted structure, CpG islands, genes, predicted binding sites, conservation, and single nucleotide polymorphisms. These attributes are scored on 132 CpG islands across the entire human Chromosome 21, whose methylation status was previously established for normal human lymphocytes. Our results show that three groups of DNA attributes, namely certain sequence patterns, specific DNA repeats, and a particular DNA structure, are each highly correlated with CpG island methylation (correlation coefficients of 0.64, 0.66, and 0.49, respectively). We predicted, and subsequently experimentally examined 12 CpG islands from human Chromosome 21 with unknown methylation patterns and found more than 90% of our predictions to be correct. In addition, we applied our prediction method to analyzing Human Epigenome Project methylation data on human Chromosome 6 and again observed high prediction accuracy. In summary, our results suggest that DNA composition of CpG islands (sequence, repeats, and structure) plays a significant role in predisposing CpG islands for DNA methylation. This finding may have a strong impact on our understanding of changes in CpG island methylation in development and disease.     

CpG islands: features and distribution in the genomes of vertebrates

We have investigated the distribution of unmethylated CpG islands in vertebrate genomes fractionated according to their base composition. Genomes from warm-blooded vertebrates (man, mouse and chicken) are characterized by abundant CpG islands, whose frequency increases in DNA fractions of increasing % of guanine + cytosine; % G + C (GC), in parallel with the distribution of genes and CpG doublets. Small, yet significant, differences in the distribution of CpG islands were found in the three genomes. In contrast, genomes from cold-blooded vertebrates (two reptiles, one amphibian, and two fishes) were characterized by an extreme scarcity or absence of CpG islands (detected in these experiments as HpaII tiny fragments or HTF). CpG islands associated with homologous genes from cold- and warm-blooded vertebrates were then compared by analyzing CpG frequencies, GC levels, HpaII sites, rare-cutter sites and G/C boxes (GGGGCGGGGC and closely related motifs) in sequences available in gene banks. Small, yet significant, differences were again detected among the CpG islands associated with homologous genes from warm-blooded vertebrates, in that CpG islands associated with mouse or rat genes often showed low CpG and/or GC levels, as well as low numbers of HpaII sites, rare-cutter sites and G/C boxes, compared to homologous human genes; more rarely, CpG islands were just absent. As far as cold-blooded vertebrates were concerned, a number of genes showed CpG islands, which exhibited a much lower frequency of CpG doublets than that found in CpG islands of warm-blooded vertebrates, but still approached the statistically expected frequency; none of the other features of CpG islands associated with genes from warm-blooded vertebrates were present. Other genes did not show any associated CpG islands, unlike their homologues from warm-blooded vertebrates.     

Primate CpG islands are maintained by heterogeneous evolutionary regimes involving minimal selection

Mammalian CpG islands are key epigenomic elements that were first characterized experimentally as genomic fractions with low levels of DNA methylation. Currently, CpG islands are defined based on their genomic sequences alone. Here, we develop evolutionary models to show that several distinct evolutionary processes generate and maintain CpG islands. One central evolutionary regime resulting in enriched CpG content is driven by low levels of DNA methylation and consequentially low rates of CpG deamination. Another major force forming CpG islands is biased gene conversion that stabilizes constitutively methylated CpG islands by balancing rapid deamination with CpG fixation. Importantly, evolutionary analysis and population genetics data suggest that selection for high CpG content is not?a significant factor contributing to conservation of CpGs in differentially methylated regions. The heterogeneous, but not selective, origins of CpG islands have direct implications for the understanding of DNA methylation patterns in healthy and diseased cells.     

Histone methylation marks play important roles in predicting the methylation status of CpG islands

The methylation status of CpG islands is highly correlated with gene expression. Current methods for computational prediction of DNA methylation only utilize DNA sequence features. In this study, besides 35 DNA sequence features, we added four histone methylation marks to predict the methylation status of CpG islands, and improved the accuracy to 89.94%. Also we applied our model to predict the methylation pattern of all the CpG islands in the human genome, and the results are consistent with the previous reports. Our results imply the important roles of histone methylation marks in affecting the methylation status of CpG islands. H3K4me enriched in the methylation-resistant CpG islands could disrupt the contacts between nucleosomes, unravel chromatin and make DNA sequences accessible. And the established open environment may be a prerequisite for or a consequence of the function implementation of zinc finger proteins that could protect CpG islands from DNA methylation.