CpG Island Sequences Research Articles

Hyper-methylation of ABCG1 as an epigenetics biomarker in non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is the most prevalent histological type of lung cancer and the leading cause of death globally. Patients with NSCLC have a poor prognosis for various factors, and a late diagnosis is one of them. The DNA methylation of CpG island sequences found in the promoter regions of tumor suppressor genes has recently received attention as a potential biomarker of human cancer. In this study, we report DNA methylation changes of the adenosine triphosphate (ATP)-binding cassette transporter G1 (ABCG1), which belongs to the ATP cassette transporter family in NSCLC patients. Our results demonstrate that ABCG1 is hyper-methylation in NSCLC samples, and these changes are negatively correlated to gene and protein expression. Furthermore, the expression of the ABCG1 gene is significantly associated with the survival time of lung adenocarcinoma (LUAD) patients; however, it did not show a correlation to overall survival (OS) of lung squamous cell carcinoma (LUSC) patients. Notably, we found ABCG1 methylation status at locus cg20214535 is strongly associated with the survival time and consistently observed hyper-methylation in LUAD samples. This novel finding suggests ABCG1 is a potential candidate for targeted therapy in lung cancer via this specific probe. In addition, we illustrate the protein-protein interaction (PPI) of ABCG1 with other proteins and the strong communication of ABCG1 with immune cells.

CMIC: predicting DNA methylation inheritance of CpG islands with embedding vectors of variable-length k-mers

BackgroundEpigenetic modifications established in mammalian gametes are largely reprogrammed during early development, however, are partly inherited by the embryo to support its development. In this study, we examine CpG island (CGI) sequences to predict whether a mouse blastocyst CGI inherits oocyte-derived DNA methylation from the maternal genome. Recurrent neural networks (RNNs), including that based on gated recurrent units (GRUs), have recently been employed for variable-length inputs in classification and regression analyses. One advantage of this strategy is the ability of RNNs to automatically learn latent features embedded in inputs by learning their model parameters. However, the available CGI dataset applied for the prediction of oocyte-derived DNA methylation inheritance are not large enough to train the neural networks.ResultsWe propose a GRU-based model called CMIC (CGI Methylation Inheritance Classifier) to augment CGI sequence by converting it into variable-length k-mers, where the length k is randomly selected from the range k_{min } to k_{max }, N times, which were then used as neural network input. N was set to 1000 in the default setting. In addition, we proposed a new embedding vector generator for k-mers called splitDNA2vec. The randomness of this procedure was higher than the previous work, dna2vec.ConclusionsWe found that CMIC can predict the inheritance of oocyte-derived DNA methylation at CGIs in the maternal genome of blastocysts with a high F-measure (0.93). We also show that the F-measure can be improved by increasing the parameter N, that is, the number of sequences of variable-length k-mers derived from a single CGI sequence. This implies the effectiveness of augmenting input data by converting a DNA sequence to N sequences of variable-length k-mers. This approach can be applied to different DNA sequence classification and regression analyses, particularly those involving a small amount of data.

Ranked k-Spectrum Kernel for Comparative and Evolutionary Comparison of Exons, Introns, and CpG Islands.

Existing k-mer based string kernel methods have been successfully used for sequence comparison. However, existing kernel methods have limitations for comparative and evolutionary comparisons of genomes due to the sensitiveness to over-represented k-mers and variable sequence lengths. In this study, we propose a novel ranked k-spectrum string (RKSS) kernel. 1) RKSS kernel utilizes common k-mer sets across species, named landmarks, that can be used for comparing multiple genomes. 2) Based on the landmarks, we can use ranks of k-mers, rather than frequencies, that can produce more robust distances between genomes. To show the power of RKSS kernel, we conducted two experiments using 10 mammalian species with exon, intron, and CpG island sequences. RKSS kernel reconstructed more consistent evolutionary trees than the k-spectrum string kernel. In the subsequent experiment, for each sequence, kernel distance was calculated from 30 landmarks representing exon, intron, and CpG island sequences of 10 genomes. Based on kernel distances, concordance tests were performed and the result suggested that more information is conserved in CpG islands across species than in introns. In conclusion, our analysis suggests that the relational order, exon CpG island intron, in terms of evolutionary information contents.

Genome Sequencing Technology used to Explore the 6mA Methylation Level of Silent Alpha-Thalassemia in Postmenopausal Women.

Based on whole-genome sequencing technology our aim is to explore the expression of the alpha-thalassemia trait during menopause period at the 6mA methylation site and evaluate the significance in clinical diagnosis. In this study, we collected peripheral blood from the women in the postmenopausal period in our hospital and used the method of (ChIP-seq) immunoprecipitation assay combined with next genome sequencing technology to select the 6mA site and differentially expressed genes and KEGG pathways and thereby investigate the clinical significance of the 6mA methylation site in women with thalassemia. A total of 38,879 methylation sites were selected, covering a wide range of CpG island and reference sequence genes. Methylation sites are located in different regions of the gene. PKA, PIK3C, CREB1, HSP90A, ITPR1, HSPA, and SOS were significantly enriched at the 6mA radicalization site and KEGG pathways, p < 0.01. The 6mA methylation site of alpha-thalassemia trait in menopause was less distributed than that of healthy controls and mainly distributed in introns. Estrogen signaling pathways may affect alpha-thalassemia in menopause through the 6mA methylation of differentially expressed genes.

Expression and differential regulation of human TERRA at several chromosome ends.

The telomeric long noncoding RNA TERRA has been implicated in regulating telomere maintenance by telomerase and homologous recombination, and in influencing telomeric protein composition during the cell cycle and the telomeric DNA damage response. TERRA transcription starts at subtelomeric regions resembling the CpG islands of eukaryotic genes extending toward chromosome ends. TERRA contains chromosome-specific subtelomeric sequences at its 5′ end and long tracts of UUAGGG-repeats toward the 3′ end. Conflicting studies have been published as to whether TERRA is expressed from one or several chromosome ends. Here, we quantify TERRA species by RT-qPCR in normal and several cancerous human cell lines. By using chromosome-specific subtelomeric DNA primers, we demonstrate that TERRA is expressed from a large number of telomeres. Deficiency in DNA methyltransferases leads to TERRA up-regulation only at the subset of chromosome ends that contain CpG-island sequences, revealing differential regulation of TERRA promoters by DNA methylation. However, independently of the differences in TERRA expression, short telomeres were uniformly present in a DNA methyltransferase deficient cell line, indicating that telomere length was not dictated by TERRA expression in cis. Bioinformatic analyses indicated the presence of a large number of putative transcription factors binding sites at TERRA promoters, and we identified a subset of them that repress TERRA expression. Altogether, our study confirms that TERRA corresponds to a large gene family transcribed from multiple chromosome ends where we identified two types of TERRA promoters, only one of which is regulated by DNA methylation.

Lineage-associated underrepresented permutations (LAUPs) of mammalian genomic sequences based on a Jellyfish-based LAUPs analysis application (JBLA).

This study addresses several important questions related to naturally underrepresented sequences: (i) are there permutations of real genomic DNA sequences in a defined length (k-mer) and a given lineage that do not actually exist or underrepresented? (ii) If there are such sequences, what are their characteristics in terms of k-mer length and base composition? (iii) Are they related to CpG or TpA underrepresentation known for human sequences? We propose that the answers to these questions are of great significance for the study of sequence-associated regulatory mechanisms, such cytosine methylation and chromosomal structures in physiological or pathological conditions such as cancer. We empirically defined sequences that were not included in any well-known public databases as lineage-associated underrepresented permutations (LAUPs). Then, we developed a Jellyfish-based LAUPs analysis application (JBLA) to investigate LAUPs for 24 representative species. The present discoveries include: (i) lengths for the shortest LAUPs, ranging from 10 to 14, which collectively constitute a low proportion of the genome. (ii) Common LAUPs showing higher CG content over the analysed mammalian genome and possessing distinct CG*CG motifs. (iii) Neither CpG-containing LAUPs nor CpG island sequences are randomly structured and distributed over the genomes; some LAUPs and most CpG-containing sequences exhibit an opposite trend within the same k and n variants. In addition, we demonstrate that the JBLA algorithm is more efficient than the original Jellyfish for computing LAUPs. We developed a Jellyfish-based LAUP analysis (JBLA) application by integrating Jellyfish (Marçais and Kingsford, 2011), MEME (Bailey, et al., 2009) and the NCBI genome database (Pruitt, et al., 2007) applications, which are listed as Supplementary Material. Supplementary data are available at Bioinformatics online.

Spectrum structures and biological functions of 8-mers in the human genome

The spectra of k-mer frequencies can reveal the structures and evolution of genome sequences. We confirmed that the trimodal spectrum of 8-mers in human genome sequences is distinguished only by CG2, CG1 and CG0 8-mer sets, containing 2,1 or 0 CpG, respectively. This phenomenon is called independent selection law. The three types of CG 8-mers were considered as different functional elements. We conjectured that (1) nucleosome binding motifs are mainly characterized by CG1 8-mers and (2) the core structural units of CpG island sequences are predominantly characterized by CG2 8-mers. To validate our conjectures, nucleosome occupied sequences and CGI sequences were extracted, then the sequence parameters were constructed through the information of the three CG 8-mer sets respectively. ROC analysis showed that CG1 8-mers are more preference in nucleosome occupied segments (AUC > 0.7) and CG2 8-mers are more preference in CGI sequences (AUC > 0.99). This validates our conjecture in principle.

Corrigendum: CpG island erosion, polycomb occupancy and sequence motif enrichment at bivalent promoters in mammalian embryonic stem cells.

Scientific Reports 5: Article number: 16791; published online: 19 November 2015; updated: 23 May 2016. This Article contained errors. In Figure 5c, the labels of the last two panels were inverted, where ‘H3K27me3’ and H3K4me3’ were incorrectly given as ‘H3K4me3’ and ‘H3K27me3’ respectively. The correct Figure 5 appears below as Fig.

CpG island erosion, polycomb occupancy and sequence motif enrichment at bivalent promoters in mammalian embryonic stem cells.

In embryonic stem (ES) cells, developmental regulators have a characteristic bivalent chromatin signature marked by simultaneous presence of both activation (H3K4me3) and repression (H3K27me3) signals and are thought to be in a ‘poised’ state for subsequent activation or silencing during differentiation. We collected eleven pairs (H3K4me3 and H3K27me3) of ChIP sequencing datasets in human ES cells and eight pairs in murine ES cells, and predicted high-confidence (HC) bivalent promoters. Over 85% of H3K27me3 marked promoters were bivalent in human and mouse ES cells. We found that (i) HC bivalent promoters were enriched for developmental factors and were highly likely to be differentially expressed upon transcription factor perturbation; (ii) murine HC bivalent promoters were occupied by both polycomb repressive component classes (PRC1 and PRC2) and grouped into four distinct clusters with different biological functions; (iii) HC bivalent and active promoters were CpG rich while H3K27me3-only promoters lacked CpG islands. Binding enrichment of distinct sets of regulators distinguished bivalent from active promoters. Moreover, a ‘TCCCC’ sequence motif was specifically enriched in bivalent promoters. Finally, this analysis will serve as a resource for future studies to further understand transcriptional regulation during embryonic development.

CpG island erosion, Polycomb occupancy, and sequence motif enrichment at bivalent promoters in mammalian embryonic stem cells

In embryonic stem (ES) cells, developmental regulators have a characteristic bivalent chromatin signature marked by simultaneous presence of both activation (H3K4me3) and repression (H3K27me3) signals and are thought to be in a 'poised' state for subsequent activation or silencing during differentiation. We collected eleven pairs (H3K4me3 and H3K27me3) of ChIP sequencing datasets in human ES cells and eight pairs in murine ES cells, and predicted high-confidence (HC) bivalent promoters. Over 85% of H3K27me3 marked promoters were bivalent in human and mouse ES cells. We found that (i) HC bivalent promoters were enriched for developmental factors and were highly likely to be differentially expressed upon transcription factor perturbation; (ii) murine HC bivalent promoters were occupied by both polycomb repressive component classes (PRC1 and PRC2) and grouped into four distinct clusters with different biological functions; (iii) HC bivalent and active promoters were CpG rich while H3K27me3-only promoters lacked CpG islands. Binding enrichment of distinct sets of regulators distinguished bivalent from active promoters. Moreover, a 'TCCCC' sequence motif was specifically enriched in bivalent promoters. Finally, this analysis will serve as a resource for future studies to further understand transcriptional regulation during embryonic development.

Methylation pattern of ALX4 gene promoter as a potential biomarker for blood-based early detection of colorectal cancer.

Background:To develop a non-invasive screening method for colorectal cancer, we evaluated the methylation of ALX4 gene promoter in serum samples from patients with colorectal cancer (CRC) and equal number of healthy individuals.Materials and Methods:In serum samples from 25 patients with colorectal cancer and 25 healthy control subjects, isolated serum free-floating DNA was treated with sodium bisulfite and analyzed by methylation-specific polymerase chain reaction (MSP) with primers specific for methylated or unmethylated promoter CpG island sequences of the ALX4 gene.Results:Methylation of the ALX4 gene promoter was present in the serum DNA of patients with adenoma and colorectal cancer. A sensitivity of 68% and specificity of 88% were achieved in the detection of promoter methylation in colorectal neoplasia samples. The difference in methylation status of the ALX4 promoter between the patients with colorectal neoplasia and the control group was statistically highly significant (P < 0.001).Conclusions:The results indicate that this serum free DNA test of methylation of the ALX4 gene promoter is a sensitive and specific method. Therefore in combination with other useful markers it seems ALX4 has the potential of a clinically useful test for the early detection of colorectal cancer.

Direct observation of preferential processing of clustered abasic DNA damages with APE1 in TATA box and CpG island by reaction kinetics and fluorescence dynamics

Sequences like the core element of TATA box and CpG island are frequently encountered in the genome and related to transcription. The fate of repair of clustered abasic sites in such sequences of genomic importance is largely unknown. This prompted us to investigate the sequence dependence of cleavage efficiency of APE1 enzyme at abasic sites within the core sequences of TATA box and CpG island using fluorescence dynamics and reaction kinetics. Simultaneous molecular dynamics study through steady state and time resolved fluorescence spectroscopy using unique ethidium bromide dye release assay confirmed an elevated amount of abasic site cleavage of the TATA box sequence as compared to the core CpG island. Reaction kinetics showed that catalytic efficiency of APE1 for abasic site cleavage of core CpG island sequence was ∼4 times lower as compared to that of the TATA box. Higher value of Km was obtained from the core CpG island sequence than the TATA box sequence. This suggests a greater binding effect of APE1 enzyme on TATA sequence that signifies a prominent role of the sequence context of the DNA substrate. Evidently, a faster response from APE1 was obtained for clustered abasic damage repair of TATA box core sequences than CpG island consensus sequences. The neighboring bases of the abasic sites in the complementary DNA strand were found to have significant contribution in addition to the flanking bases in modulating APE1 activity. The repair refractivity of the bistranded clustered abasic sites arise from the slow processing of the second abasic site, consequently resulting in decreased overall production of potentially lethal double strand breaks.

Comparative analysis using K-mer and K-flank patterns provides evidence for CpG island sequence evolution in mammalian genomes

CpG islands are GC-rich regions often located in the 5′ end of genes and normally protected from cytosine methylation in mammals. The important role of CpG islands in gene transcription strongly suggests evolutionary conservation in the mammalian genome. However, as CpG dinucleotides are over-represented in CpG islands, comparative CpG island analysis using conventional sequence analysis techniques remains a major challenge in the epigenetics field. In this study, we conducted a comparative analysis of all CpG island sequences in 10 mammalian genomes. As sequence similarity methods and character composition techniques such as information theory are particularly difficult to conduct, we used exact patterns in CpG island sequences and single character discrepancies to identify differences in CpG island sequences. First, by calculating genome distance based on rank correlation tests, we show that k-mer and k-flank patterns around CpG sites can be used to correctly reconstruct the phylogeny of 10 mammalian genomes. Further, we used various machine learning algorithms to demonstrate that CpG islands sequences can be characterized using k-mers. In addition, by testing a human model on the nine different mammalian genomes, we provide the first evidence that k-mer signatures are consistent with evolutionary history.

A novel k-mer mixture logistic regression for methylation susceptibility modeling of CpG dinucleotides in human gene promoters

BackgroundDNA methylation is essential for normal development and differentiation and plays a crucial role in the development of nearly all types of cancer. Aberrant DNA methylation patterns, including genome-wide hypomethylation and region-specific hypermethylation, are frequently observed and contribute to the malignant phenotype. A number of studies have recently identified distinct features of genomic sequences that can be used for modeling specific DNA sequences that may be susceptible to aberrant CpG methylation in both cancer and normal cells. Although it is now possible, using next generation sequencing technologies, to assess human methylomes at base resolution, no reports currently exist on modeling cell type-specific DNA methylation susceptibility. Thus, we conducted a comprehensive modeling study of cell type-specific DNA methylation susceptibility at three different resolutions: CpG dinucleotides, CpG segments, and individual gene promoter regions.ResultsUsing a k-mer mixture logistic regression model, we effectively modeled DNA methylation susceptibility across five different cell types. Further, at the segment level, we achieved up to 0.75 in AUC prediction accuracy in a 10-fold cross validation study using a mixture of k-mers.ConclusionsThe significance of these results is three fold: 1) this is the first report to indicate that CpG methylation susceptible "segments" exist; 2) our model demonstrates the significance of certain k-mers for the mixture model, potentially highlighting DNA sequence features (k-mers) of differentially methylated, promoter CpG island sequences across different tissue types; 3) as only 3 or 4 bp patterns had previously been used for modeling DNA methylation susceptibility, ours is the first demonstration that 6-mer modeling can be performed without loss of accuracy.

Humanizing π-Class Glutathione S-Transferase Regulation in a Mouse Model Alters Liver Toxicity in Response to Acetaminophen Overdose

BackgroundGlutathione S-transferases (GSTs) metabolize drugs and xenobiotics. Yet despite high protein sequence homology, expression of π-class GSTs, the most abundant of the enzymes, varies significantly between species. In mouse liver, hepatocytes exhibit high mGstp expression, while in human liver, hepatocytes contain little or no hGSTP1 mRNA or hGSTP1 protein. π-class GSTs are known to be critical determinants of liver responses to drugs and toxins: when treated with high doses of acetaminophen, mGstp1/2+/+ mice suffer marked liver damage, while mGstp1/2−/− mice escape liver injury.Methodology/Principal FindingsTo more faithfully model the contribution of π-class GSTs to human liver toxicology, we introduced hGSTP1, with its exons, introns, and flanking sequences, into the germline of mice carrying disrupted mGstp genes. In the resultant hGSTP1+mGstp1/2−/− strain, π-class GSTs were regulated differently than in wild-type mice. In the liver, enzyme expression was restricted to bile duct cells, Kupffer cells, macrophages, and endothelial cells, reminiscent of human liver, while in the prostate, enzyme production was limited to basal epithelial cells, reminiscent of human prostate. The human patterns of hGSTP1 transgene regulation were accompanied by human patterns of DNA methylation, with bisulfite genomic sequencing revealing establishment of an unmethylated CpG island sequence encompassing the gene promoter. Unlike wild-type or mGstp1/2−/− mice, when hGSTP1+mGstp1/2−/− mice were overdosed with acetaminophen, liver tissues showed limited centrilobular necrosis, suggesting that π-class GSTs may be critical determinants of toxin-induced hepatocyte injury even when not expressed by hepatocytes.ConclusionsBy recapitulating human π-class GST expression, hGSTP1+mGstp1/2−/− mice may better model human drug and xenobiotic toxicology.

Epigenetic Regulation of MicroRNA Genes and the Role of miR-34b in Cell Invasion and Motility in Human Melanoma

Invasive melanoma is the most lethal form of skin cancer. The treatment of melanoma-derived cell lines with 5-aza-2′-deoxycytidine (5-Aza-dC) markedly increases the expression of several miRNAs, suggesting that the miRNA-encoding genes might be epigenetically regulated, either directly or indirectly, by DNA methylation. We have identified a group of epigenetically regulated miRNA genes in melanoma cells, and have confirmed that the upstream CpG island sequences of several such miRNA genes are hypermethylated in cell lines derived from different stages of melanoma, but not in melanocytes and keratinocytes. We used direct DNA bisulfite and immunoprecipitated DNA (Methyl-DIP) to identify changes in CpG island methylation in distinct melanoma patient samples classified as primary in situ, regional metastatic, and distant metastatic. Two melanoma cell lines (WM1552C and A375 derived from stage 3 and stage 4 human melanoma, respectively) were engineered to ectopically express one of the epigenetically modified miRNA: miR-34b. Expression of miR-34b reduced cell invasion and motility rates of both WM1552C and A375, suggesting that the enhanced cell invasiveness and motility observed in metastatic melanoma cells may be related to their reduced expression of miR-34b. Total RNA isolated from control or miR-34b-expressing WM1552C cells was subjected to deep sequencing to identify gene networks around miR-34b. We identified network modules that are potentially regulated by miR-34b, and which suggest a mechanism for the role of miR-34b in regulating normal cell motility and cytokinesis.

Epigenetic Mechanisms of Promigratory Chemokine CXCL14 Regulation in Human Prostate Cancer Cells

Chemokines play the key role in initiating immune responses by regulating the attraction and homing of immune cells to the lymphoid and nonlymphoid tissues. CXCL14 is a chemokine that in tumors may act as chemoattractant for monocytes and dendritic cells (DC), which may modulate antitumor immune responses in certain cancers. In this study, we investigated the mechanisms of loss of CXCL14 in prostate cancer cells. Cell treatment with the demethylating agent 5-aza-2-deoxycytidine resulted in the recovery of CXCL14 mRNA and protein expression. Hypermethylated CpG island sequences encompassing the CXCL14 gene promoter were identified. The restoration of CXCL14 by 5-aza-2-deoxycytidine treatment had functional impact, based on the DC chemoattractant activity of conditioned medium from drug-treated cells. Conversely, CXCL14 removal from conditioned media by affinity chromatography abolished its chemotactic properties, confirming that functionally active CXCL14 was generated in prostate cancer cells by relieving its transcriptional silencing with 5-aza-2-deoxycytidine. Our findings offer the first direct evidence for epigenetic regulation of chemokine expression in tumor cells.

Ectopic Production of Parathyroid Hormone in a Patient with Sporadic Medullary Thyroid Cancer

Elevation of serum parathyroid hormone (PTH) in patients with medullary thyroid cancer (MTC) is usually found in multiple endocrine neoplasia type 2A (MEN2A). However, ectopic production of PTH is rare and its molecular etiology remains largely uninvestigated. We report a case of ectopic production of PTH by a sporadic MTC. The etiology of ectopic PTH gene expression was examined, focusing on GCM2 which has a crucial role in developing parathyroid glands. We observed ectopic expression of the PTH and GCM2 genes in tissues from the tumor and metastatic lymph nodes. However, GCM2 gene expression was also detected in adjacent thyroid tissue and lymphoblasts, in which PTH gene expression was absent. Hypomethylation of the PTH promoter, which is reportedly associated with ectopic production of PTH, was not seen in either the tumor tissue or metastatic lymph nodes. Meanwhile, DNA hypomethylation was seen in a CpG island identified in the GCM2 promoter region, regardless of whether or not the GCM2 gene was expressed. We showed that transcriptional activity of the CpG island sequences cloned into a reporter plasmid was dependent upon DNA methylation. Finally, we present the first report of a PTH-producing MTC. There was no apparent association between ectopic PTH and GCM2 gene expression, despite co-expression of the two genes. Neither genomic rearrangement nor DNA hypomethylation in the PTH gene appeared responsible for ectopic production of PTH. Although DNA hypomethylation may be necessary for the GCM2 gene expression, ectopic expression of GCM2 won't be possible by DNA hypomethylation alone.

A new class of tissue‐specifically methylated regions involving entire CpG islands in the mouse

CpG islands, which have higher GC content and CpG frequencies compared to the genome as a whole, are generally believed to be unmethylated in tissues except at promoters of genes undergoing X chromosome inactivation or genomic imprinting. Recent studies, however, have shown that CpG islands at promoters of a number of genes contain tissue-dependent, differentially methylated regions (T-DMRs). In general, the tissue-specific methylation is restricted to a part of the promoter CpG island, with hypomethylation of the remaining sequence. In the current study, using comparison between Restriction Landmark Genomic Scanning (RLGS) and in silico RLGS, we identified ten sperm-specific unmethylated NotI sites, T-DMRs located in CpG islands that were hypomethylated in sperm but near-completely methylated in the kidney and brain. Unusually, these T-DMRs involve the whole CpG island at each of these loci. We characterized one of these genes, adenine nucleotide translocator 4 (Ant4), which is expressed in germ cells. Using a promoter assay, we demonstrated that expression of Ant4 gene is controlled by DNA methylation at the CpG island sequences within the promoter region. Ant4 and other sperm-specific hypomethylated loci represent a new class of CpG islands that become completely methylated in different cell lineages. T-DMRs at CpG islands are functionally important gene regulatory elements that may now be categorized into two classes: T-DMRs involving a subregion of the CpG island and those that occupy the whole CpG island.

Relational Analysis of CpG Islands Methylation and Gene Expression in Human Lymphomas Using Possibilistic C-Means Clustering and Modified Cluster Fuzzy Density

Heterogeneous genetic and epigenetic alterations are commonly found in human non-Hodgkin's lymphomas (NHL). One such epigenetic alteration is aberrant methylation of gene promoter-related CpG islands, where hypermethylation frequently results in transcriptional inactivation of target genes, while a decrease or loss of promoter methylation (hypomethylation) is frequently associated with transcriptional activation. Discovering genes with these relationships in NHL or other types of cancers could lead to a better understanding of the pathobiology of these diseases. The simultaneous analysis of promoter methylation using Differential Methylation Hybridization (DMH) and its associated gene expression using Expressed CpG Island Sequence Tag (ECIST) microarrays generates a large volume of methylation-expression relational data. To analyze this data, we propose a set of algorithms based on fuzzy sets theory, in particular Possibilistic c-Means (PCM) and cluster fuzzy density. For each gene, these algorithms calculate measures of confidence of various methylation-expression relationships in each NHL subclass. Thus, these tools can be used as a means of high volume data exploration to better guide biological confirmation using independent molecular biology methods.