Identifying CpG islands by different computational techniques

Hypermethylation of a New Distal Sodium/Iodide Symporter (NIS) enhancer (NDE) is associated with reduced NIS expression in thyroid tumors

CONTEXT

In thyroid tumors, reduced radioiodine uptake is associated with worse patient outcome concomitantly with low sodium/iodide symporter (NIS) mRNA expression. Previous studies showed that CpG-island methylation in the NIS proximal promoter does not correlate with mRNA expression.

OBJECTIVES

The aim of the study was to identify new CpG-islands within the NIS 5'region and investigate the involvement of their methylation in NIS expression.

DESIGN

DNA was obtained from 30 pairs of thyroid samples: tumor (T) and surrounding nontumor (NT) samples. All T samples had reduced NIS mRNA expression compared to NT samples.

MAIN OUTCOME MEASURES

Methylation degree was quantified by bisulfite sequencing, and NIS expression by real-time PCR and Western blot. Reporter gene assays were performed to determine CpG-island functionality. Tumor cell cultures were treated with 5-Aza demethylating agent to determine NIS expression, methylation status, and (125)I uptake.

RESULTS

We identified a new CpG-island2 with 14 CpG sites, located -2152/-1887 relative to ATG site. CpG-island2 was hypermethylated in T compared to NT samples, in both benign and malignant tumor groups. There was a significant inverse correlation between NIS mRNA expression and degree of CpG-island2 methylation in NT and T samples. This sequence increased the expression of a reporter gene; thus, it was considered a new enhancer. Cell culture treatments with 5-Aza reduced CpG-island2 methylation levels concomitantly with restoration of NIS mRNA and protein expression and (125)I uptake.

CONCLUSIONS

We identified a new distal enhancer, NIS distal enhancer, that regulates gene expression through DNA methylation. This enhancer is hypermethylated in T compared to NT samples and is associated with decreased NIS expression in tumors. This epigenetic deregulation may be an early event in tumorigenesis.

Identification of Candidate Vaccine Antigens In Silico

The identification of immunogenic whole-protein antigens is fundamental to the successful discovery of candidate subunit vaccines and their rapid, effective, and efficient transformation into clinically useful, commercially successful vaccine formulations. In the wider context of the experimental discovery of vaccine antigens, with particular reference to reverse vaccinology, this chapter adumbrates the principal computational approaches currently deployed in the hunt for novel antigens: genome-level prediction of antigens, antigen identification through the use of protein sequence alignment-based approaches, antigen detection through the use of subcellular location prediction, and the use of alignment-independent approaches to antigen discovery. Reference is also made to the recent emergence of various expert systems for protein antigen identification.

Computational studies of imprinted genes

Computational studies on imprinted genes can have very different purposes: one major aim of these studies is the identification of DNA elements that distinguish imprinted genes from biallelically expressed genes. Comparative studies may help to identify imprinting regulatory elements and to understand common mechanisms of imprinted gene regulation in mammalian species. To date, the continuously growing number of genomic and epigenetic data sets makes detailed, genome-wide analyses on imprinted genes feasible. However, imprinted genes are characterized by genomic features that can influence statistics and can make such studies difficult. Hence, comparative computational studies can get very complex and require a tight interaction between bioinformaticians and biologists. Furthermore, analyses of raw data that are generated by micro-array hybridization and high-throughput sequencing technologies require computational approaches that have been designed especially for the epigenetic field. This chapter gives an overview about databases and software that is suitable for analyses of imprinted genes. Furthermore, possible difficulties that are typical for computational and statistical analyses of imprinted genes are described.

Imprinted genes show unique patterns of sequence conservation

BACKGROUND

Genomic imprinting is an evolutionary conserved mechanism of epigenetic gene regulation in placental mammals that results in silencing of one of the parental alleles. In order to decipher interactions between allele-specific DNA methylation of imprinted genes and evolutionary conservation, we performed a genome-wide comparative investigation of genomic sequences and highly conserved elements of imprinted genes in human and mouse.

RESULTS

Evolutionarily conserved elements in imprinted regions differ from those associated with autosomal genes in various ways. Whereas for maternally expressed genes strong divergence of protein-encoding sequences is most prominent, paternally expressed genes exhibit substantial conservation of coding and noncoding sequences. Conserved elements in imprinted regions are marked by enrichment of CpG dinucleotides and low (TpG+CpA)/(2·CpG) ratios indicate reduced CpG deamination. Interestingly, paternally and maternally expressed genes can be distinguished by differences in G+C and CpG contents that might be associated with unusual epigenetic features. Especially noncoding conserved elements of paternally expressed genes are exceptionally G+C and CpG rich. In addition, we confirmed a frequent occurrence of intronic CpG islands and observed a decelerated degeneration of ancient LINE-1 repeats. We also found a moderate enrichment of YY1 and CTCF binding sites in imprinted regions and identified several short sequence motifs in highly conserved elements that might act as additional regulatory elements.

CONCLUSIONS

We discovered several novel conserved DNA features that might be related to allele-specific DNA methylation. Our results hint at reduced CpG deamination rates in imprinted regions, which affects mostly noncoding conserved elements of paternally expressed genes. Pronounced differences between maternally and paternally expressed genes imply specific modes of evolution as a result of differences in epigenetic features and a special response to selective pressure. In addition, our data support the potential role of intronic CpG islands as epigenetic key regulatory elements and suggest that evolutionary conserved LINE-1 elements fulfill regulatory functions in imprinted regions.

Computer aided selection of candidate vaccine antigens

Immunoinformatics is an emergent branch of informatics science that long ago pullulated from the tree of knowledge that is bioinformatics. It is a discipline which applies informatic techniques to problems of the immune system. To a great extent, immunoinformatics is typified by epitope prediction methods. It has found disappointingly limited use in the design and discovery of new vaccines, which is an area where proper computational support is generally lacking. Most extant vaccines are not based around isolated epitopes but rather correspond to chemically-treated or attenuated whole pathogens or correspond to individual proteins extract from whole pathogens or correspond to complex carbohydrate. In this chapter we attempt to review what progress there has been in an as-yet-underexplored area of immunoinformatics: the computational discovery of whole protein antigens. The effective development of antigen prediction methods would significantly reduce the laboratory resource required to identify pathogenic proteins as candidate subunit vaccines. We begin our review by placing antigen prediction firmly into context, exploring the role of reverse vaccinology in the design and discovery of vaccines. We also highlight several competing yet ultimately complementary methodological approaches: sub-cellular location prediction, identifying antigens using sequence similarity, and the use of sophisticated statistical approaches for predicting the probability of antigen characteristics. We end by exploring how a systems immunomics approach to the prediction of immunogenicity would prove helpful in the prediction of antigens.

CpG_MI: a novel approach for identifying functional CpG islands in mammalian genomes

CpG islands (CGIs) are CpG-rich regions compared to CpG-depleted bulk DNA of mammalian genomes and are generally regarded as the epigenetic regulatory regions in association with unmethylation, promoter activity and histone modifications. Accurate identification of CpG islands with epigenetic regulatory function in bulk genomes is of wide interest. Here, the common features of functional CGIs are identified using an average mutual information method to differentiate functional CGIs from the remaining CGIs. A new approach (CpG mutual information, CpG_MI) was further explored to identify functional CGIs based on the cumulative mutual information of physical distances between two neighboring CpGs. Compared to current approaches, CpG_MI achieved the highest prediction accuracy. This approach also identified new functional CGIs overlapping with gene promoter regions which were missed by other algorithms. Nearly all CGIs identified by CpG_MI overlapped with histone modification marks. CpG_MI could also be used to identify potential functional CGIs in other mammalian genomes, as the CpG dinucleotide contents and cumulative mutual information distributions are almost the same among six mammalian genomes in our analysis. It is a reliable quantitative tool for the identification of functional CGIs from bulk genomes and helps in understanding the relationships between genomic functional elements and epigenomic modifications.