CpG islands in genes showing tissue-specific expression

Patterns of DNA methylation at CpG dinucleotides and their relations with gene expression are complex. Methylation-free CpG clusters, so-called HTF islands, are most often associated with the promoter regions of housekeeping genes, whereas genes expressed in a single-cell type are usually deficient in these sequences. However, in the human carbonic anhydrase (CA) gene family, both the ubiquitously expressed CAII and the muscle specific CAIII appear to have such CpG islands although erythrocyte-specific CAI does not. The CAII island is quantitatively more CpG rich than that of CAIII, with a CpG:GpC ratio of 0.94 compared with 0.82 for CAIII. Estimation of CpG:GpC ratios in the proximal-promoter regions of 44 vertebrate genes suggest that 40% of genes with tissue-specific or limited tissue distribution may show methylation-free CpG clusters in their promoter regions. In many cases the CpG:GpC ratio is less than that found in housekeeping genes and this may reflect variation in the interaction of CpG clusters with regulatory factors that define different patterns of tissue expression.     

Long-range autocorrelations of CpG islands in the human genome

In this paper, we use a statistical estimator developed in astrophysics to study the distribution and organization of features of the human genome. Using the human reference sequence we quantify the global distribution of CpG islands (CGI) in each chromosome and demonstrate that the organization of the CGI across a chromosome is non-random, exhibits surprisingly long range correlations (10 Mb) and varies significantly among chromosomes. These correlations of CGI summarize functional properties of the genome that are not captured when considering variation in any particular separate (and local) feature. The demonstration of the proposed methods to quantify the organization of CGI in the human genome forms the basis of future studies. The most illuminating of these will assess the potential impact on phenotypic variation of inter-individual variation in the organization of the functional features of the genome within and among chromosomes, and among individuals for particular chromosomes.     

Evolution of CpG islands within the myc gene family

CpG islands are discrete regions of DNA with significantly greater frequencies of CpG doublets than bulk genomic DNA. They are most frequently associated with the 5'-ends of housekeeping genes and are involved in the regulation of their expression. In this study, the structure and evolution of CpG islands within genes of the myc family were evaluated with the protein-coding sequences of animals and their transducing viruses. These evaluations relied on a gene tree for the entire myc family to test the origins of CpG islands within their two protein-coding exons. Overall, CG-very rich and CG-rich islands are associated with exon 2 of the different myc genes of warm-blooded vertebrates and with exon 3 of the N-myc and s-myc sequences of mammals, but not birds. These overall distributions of well-developed islands can be related to the major transitions of the CG-rich genomes of warm-blooded vertebrates from the CG-poor ones of other animals. In turn, the greater variability of well-developed islands within exon 3 of the N-myc gene and among the different retrogenes of the myc family can be attributed to their reduced functional constraints, as evidenced by their limited and very restricted patterns of expression, respectively.     

Identifying hypermethylated CpG islands using a quantile regression model

Background  

DNA methylation has been shown to play an important role in the silencing of tumor suppressor genes in various tumor types. In order to have a system-wide understanding of the methylation changes that occur in tumors, we have developed a differential methylation hybridization (DMH) protocol that can simultaneously assay the methylation status of all known CpG islands (CGIs) using microarray technologies. A large percentage of signals obtained from microarrays can be attributed to various measurable and unmeasurable confounding factors unrelated to the biological question at hand. In order to correct the bias due to noise, we first implemented a quantile regression model, with a quantile level equal to 75%, to identify hypermethylated CGIs in an earlier work. As a proof of concept, we applied this model to methylation microarray data generated from breast cancer cell lines. However, we were unsure whether 75% was the best quantile level for identifying hypermethylated CGIs. In this paper, we attempt to determine which quantile level should be used to identify hypermethylated CGIs and their associated genes.     

CpG islands: Algorithms and applications in methylation studies

Methylation occurs frequently at 5’-cytosine of the CpG dinucleotides in vertebrate genomes; however, this epigenetic feature is rarely observed in CpG islands (CGIs) or CpG clusters in the promoter regions of genes. Aberrant methylation of the promoter-associated CGIs might influence gene expression and cause carcinogenesis. Because of the functional importance, multiple algorithms have been available for identifying CGIs in a genome or a sequence. They can be categorized into the traditional algorithms (e.g., Gardiner-Garden and Frommer (1987), Takai and Jones (2002), and CpGPRoD (2002)) or statistical property based algorithms (CpGcluster (2006) and CG cluster (2007)). We reviewed the features of these algorithms and evaluated their performance on identifying functional CGIs using genome-wide methylation data. Moreover, identification of CGIs is an initial step in many recent studies for predicting methylation status as well as in the design of methylation detection platforms. We reviewed the benchmarks and features used in these studies.     

Factors to preserve CpG-rich sequences in methylated CpG islands

Background

Mammalian CpG islands (CGIs) normally escape DNA methylation in all adult tissues and developmental stages. However, in our previous study we unexpectedly identified many methylated CGIs in human peripheral blood leukocytes. Methylated CpG dinucleotides convert to TpG dinucleotides through deaminization of their cytosine bases more frequently than hypomethylated CpG dinucleotides. Therefore, we wondered how methylated CGIs in germline or non-germline cells maintain their CpG-rich sequences. It is known that events such as germline hypomethylation, CpG selection, biased gene conversion (BGC), and frequent CpG fixation can contribute to the maintenance of CpG-rich sequences in methylated CGIs in germline or non-germline cells. However, it has not been investigated which of the processes maintain CpG-rich sequences of methylated CGIs in each genomic position.

Results

In this study, we comprehensively examined the contribution of the processes described above to the maintenance of CpG-rich sequences in methylated CGIs in germline and non-germline cells which were classified by genomic positions. Approximately 60–80% of CGIs with high methylation in H1 cell line (H1-HM) in all the genomic positions showed a low average CpG → TpG/CpA substitution rate. In contrast, fewer than half the numbers of CGIs with H1-HM in all the genomic positions showed a low average CpG → TpG/CpA substitution rate and low levels of methylation in sperm cells (SPM-LM). Furthermore, a small fraction of CGIs with a low average CpG → TpG/CpA substitution rate and high levels of methylation in sperm cells (SPM-HM) showed CpG selection.On the other hand, independent of the positions in genes, most CGIs with SPM-HM showed a slightly higher average TpG/CpA → CpG substitution rate compared with those with SPM-LM.

Conclusions

Relatively high numbers (approximately 60–80%) of CGIs with H1-HM in all the genomic positions preserve their CpG-rich sequences by a low CpG → TpG/CpA substitution rate caused mainly by their SPM-LM, and for those with SPM-HM partly by CpG selection and TpG/CpA → CpG fixation. BGC has little contribution to the maintenance of CpG-rich sequences of CGIs with SPM-HM which were classified by genomic positions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1286-x) contains supplementary material, which is available to authorized users.     

CpG islands of the X chromosome are gene associated.

Unmethylated CpG rich islands are a feature of vertebrate DNA: they are associated with housekeeping and many tissue specific genes. CpG islands on the active X chromosome of mammals are also unmethylated. However, islands on the inactive X chromosome are heavily methylated. We have identified a CpG island in the 5' region of the G6PD gene, and two islands forty Kb 3' from the G6PD gene, on the human X chromosome. Expression of the G6PD gene is associated with concordant demethylation of all three CpG islands. We have shown that one of the two islands is in the promoter region of a housekeeping gene, GdX. In this paper we show that the second CpG island is also associated with a gene, P3. The P3 gene has no homology to previously described genes. It is a single copy, 4 kb gene, conserved in evolution, and it has the features of a housekeeping two genes is within the CpG island and that sequences in the islands have promoter function.     

WT1 CpG islands methylation in human lung cancer: A pilot study

Background

CpG island hypermethylation of gene promoters and regulatory regions is a well-known mechanism of epigenetic silencing of tumor suppressors and is directly linked to carcinogenesis. Wilm’s tumor gene (WT1) is a tumor suppressor protein involved in the regulation of human cell growth and differentiation and a modulator of oncogenic K Ras signaling in lung cancer. Changes in the pattern of methylation of the WT1 gene have not yet been studied in detail in human lung cancer. In this study we compared the methylation profile of WT1 gene in samples of neoplastic and non-neoplastic lung tissue taken from the same patients.

Methods

DNA was extracted from neoplastic and normal lung tissue obtained from 16 patients with non small cell lung cancer (NSCLC). The methylation status of 29 CpG islands in the 5′ region of WT1 was determined by pyrosequencing. Statistical analysis was carried out by T test and Mann Whitney test.

Results

The mean percentage of methylation, considering all CpG islands of WT1 in the neoplastic tissues of the 16 NSCLC patients, was 16.2 ± 3.4, whereas in the normal lung tissue from the same patients it was 5.6 ± 1.7 (p < 0.001). Adenocarcinomas presented higher methylation levels than squamous cell carcinomas (p < 0,001).

Conclusions

Methylation of WT1 gene is significantly increased in NSCLC. Both histotype and exposure to cigarette smoke heavily influence the pattern of CpG islands which undergo hypermethylation.     

CpGIF: an algorithm for the identification of CpG islands

CpG islands (CGIs) play a fundamental role in genome analysis and annotation, and contribute to improving the accuracy of promoter prediction. Besides, CGIs in promoter regions are abnormally methylated in cancer cells and thus can be used as tumor markers. However, current methods for identifying CGIs suffer from various drawbacks. We present a new algorithm for detecting CGIs, called CpG Island Finder (CpGIF), which combines the best features in the most commonly used algorithms and avoids their disadvantages as much as possible. Five public tools for CpG island searching are used to compare with CpGIF for the assessment of accuracy and computational efficiency. The results reveal that CpGIF has higher performance coefficient and correlation coefficient than these previous methods, which indicates that CpGIF is able to provide high sensitivity and specificity at the same time. CpGIF is also faster than those methods with comparable prediction accuracy.