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.     

Particle swarm optimization with reinforcement learning for the prediction of CpG islands in the human genome

Background

Regions with abundant GC nucleotides, a high CpG number, and a length greater than 200 bp in a genome are often referred to as CpG islands. These islands are usually located in the 5′ end of genes. Recently, several algorithms for the prediction of CpG islands have been proposed.

Methodology/Principal Findings

We propose here a new method called CPSORL to predict CpG islands, which consists of a complement particle swarm optimization algorithm combined with reinforcement learning to predict CpG islands more reliably. Several CpG island prediction tools equipped with the sliding window technique have been developed previously. However, the quality of the results seems to rely too much on the choices that are made for the window sizes, and thus these methods leave room for improvement.

Conclusions/Significance

Experimental results indicate that CPSORL provides results of a higher sensitivity and a higher correlation coefficient in all selected experimental contigs than the other methods it was compared to (CpGIS, CpGcluster, CpGProd and CpGPlot). A higher number of CpG islands were identified in chromosomes 21 and 22 of the human genome than with the other methods from the literature. CPSORL also achieved the highest coverage rate (3.4%). CPSORL is an application for identifying promoter and TSS regions associated with CpG islands in entire human genomic. When compared to CpGcluster, the islands predicted by CPSORL covered a larger region in the TSS (12.2%) and promoter (26.1%) region. If Alu sequences are considered, the islands predicted by CPSORL (Alu) covered a larger TSS (40.5%) and promoter (67.8%) region than CpGIS. Furthermore, CPSORL was used to verify that the average methylation density was 5.33% for CpG islands in the entire human genome.     

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.     

Sequence-specific and methylation-dependent and -independent binding of rice nuclear proteins to a rice tungro bacilliform virus vascular bundle expression element

Nuclear proteins from rice (Oryza sativa) were identified that bind specifically to a rice tungro bacilliform virus promoter region containing a vascular bundle expression element (VBE). One set of proteins of 29, 33, and 37 kDa, present in shoot and cell suspension extracts but hardly detectable in root extracts, bound to a site containing the sequence AGAAGGACCAGA within the VBE, which also contains two CpG and one CpNpG potential methylation motifs. Binding by these proteins was determined to be cytosine methylation-independent. However, a novel protein present in all analyzed extracts bound specifically to the methylated VBE. A region of at least 49 nucleotides overlapping the VBE and complete cytosine methylation of the three Cp(Np)G motifs was required for efficient binding of this methylated VBE-binding protein (MVBP).     

Highly immunostimulatory CpG-free oligodeoxynucleotides for activation of human leukocytes

Synthetic oligodeoxynucleotides (ODNs) bearing CpG dinucleotides can mimic the immunostimulatory effects of bacterial DNA in vertebrates. Besides the known CpG motifs, no other sequence motif has been shown to have independent immunostimulatory effects. Several past investigators have demonstrated that the nucleotide content or the phosphorothioate (PS) backbone may have effects independently of the sequence. However, the effect of both nucleotide content and PS backbone to stimulate human leukocytes is not well understood. We investigated the immunostimulatory activity of 34 PS-ODNs with different nucleotide contents, lengths, and methylation status on human leukocytes. The thymidine content showed strong CpG-independent contribution to immunostimulation. In contrast, ODNs rich in other nucleotides (guanosine, cytosine, or adenosine) induced no or much lower levels of immunostimulation. The observed effects were highly dependent on the PS backbone chemistry. In addition to the base content and the backbone chemistry, the length of the PS-ODN was directly related to the magnitude of its stimulatory effects, especially on B cells. In addition, methylation of CpG dinucleotides did not always cause an abrogation of the immunostimulation. Immunostimulatory effects could be observed with methylated CpG ODNs, specifically as the ODN length was increased from 18 to 24 or more nucleotides (nt). In contrast, PS-ODNs with inverted CpG dinucleotides showed some but only weak immunostimulation. Our results demonstrate that non-CpG ODNs rich in thymidine or ODNs with methylated CpG motifs have length-dependent immunostimulatory effects. Such ODNs can induce effects similar to those seen with CpG ODNs but are much less efficient in stimulating human immune cells.     

Human epigenome data reveal increased CpG methylation in alternatively spliced sites and putative exonic splicing enhancers

The role of gene body methylation, which represents a major part of methylation in DNA, remains mostly unknown. Evidence based on the CpG distribution associates its presence with nucleosome positioning and alternative splicing. Recently, it was also shown that cytosine methylation influences splicing. However, to date, there is no methylation-based data on the association of methylation with alternative splicing and the distribution in exonic splicing enhancers (ESEs). We presently report that, based on the computational analysis of the Human Epigenome Project data, CpG hypermethylation (>80%) is frequent in alternatively spliced sites (particularly in noncanonical) but not in alternate promoters. The methylation frequency increases in sequences containing multiple putative ESEs. However, significant differences in the extent of methylation are observed among different ESEs. Specifically, moderate levels of methylation, ranging from 20% to 80%, are frequent in SRp55-binding elements, which are associated with response to extracellular conditions, but not in SF2/ASF, primarily responsible for alternative splicing, or in CpG islands. Finally, methylation is more frequent in the presence of AT repeats and CpGs separated by 10 nucleotides and lower in adjacent CpGs, probably indicating its dependence on helical formations and on the presence of nucleosome positioning-related sequences. In conclusion, our results show the regulation of methylation in ESEs and support its involvement in alternative splicing.