Genomic representations using concatenates of Type IIB restriction endonuclease digestion fragments

DNA Computing: Concepts for Medical Applications

The branch of informatics that deals with construction and operation of computers built of DNA, is one of the research directions which investigates issues related to the use of DNA as hardware and software. This concept assumes the use of DNA computers due to their biological origin mainly for intelligent, personalized and targeted diagnostics frequently related to therapy. Important elements of this concept are (1) the retrieval of unique DNA sequences using machine learning methods and, based on the results of this process, (2) the construction/design of smart diagnostic biochip projects. The authors of this paper propose a new concept of designing diagnostic biochips, the key elements of which are machine-learning methods and the concept of biomolecular queue automata. This approach enables the scheduling of computational tasks at the molecular level by sequential events of cutting and ligating DNA molecules. We also summarize current challenges and perspectives of biomolecular computer application and machine-learning approaches using DNA sequence data mining.

Emerging pathogens in the fish farming industry and sequencing-based pathogen discovery

The use of large scale DNA/RNA sequencing has become an integral part of biomedical research. Reduced sequencing costs and the availability of efficient computational resources has led to a revolution in how problems concerning genomics and transcriptomics are addressed. Sequencing-based pathogen discovery represents one example of how genetic data can now be used in ways that were previously considered infeasible. Emerging pathogens affect both human and animal health due to a multitude of factors, including globalization, a shifting environment and an increasing human population. Fish farming represents a relevant, interesting and challenging system to study emerging pathogens. This review summarizes recent progress in pathogen discovery using sequence data, with particular emphasis on viruses in Atlantic salmon (Salmo salar).

The mouse genome displays highly dynamic populations of KRAB-zinc finger protein genes and related genetic units

KRAB-containing poly-zinc finger proteins (KZFPs) constitute the largest family of transcription factors encoded by mammalian genomes, and growing evidence indicates that they fulfill functions critical to both embryonic development and maintenance of adult homeostasis. KZFP genes underwent broad and independent waves of expansion in many higher vertebrates lineages, yet comprehensive studies of members harbored by a given species are scarce. Here we present a thorough analysis of KZFP genes and related units in the murine genome. We first identified about twice as many elements than previously annotated as either KZFP genes or pseudogenes, notably by assigning to this family an entity formerly considered as a large group of Satellite repeats. We then could delineate an organization in clusters distributed throughout the genome, with signs of recombination, translocation, duplication and seeding of new sites by retrotransposition of KZFP genes and related genetic units (KZFP/rGUs). Moreover, we harvested evidence indicating that closely related paralogs had evolved through both drifting and shifting of sequences encoding for zinc finger arrays. Finally, we could demonstrate that the KAP1-SETDB1 repressor complex tames the expression of KZFP/rGUs within clusters, yet that the primary targets of this regulation are not the KZFP/rGUs themselves but enhancers contained in neighboring endogenous retroelements and that, underneath, KZFPs conserve highly individualized patterns of expression.

Serial sequencing of isolength RAD tags for cost-efficient genome-wide profiling of genetic and epigenetic variations

Isolength restriction site-associated DNA (isoRAD) sequencing is a very simple but powerful approach that was originally developed for genome-wide genotyping at minimal labor and cost, and it has recently extended its applicability to allow quantification of DNA methylation levels. The isoRAD method is distinct from other genotyping-by-sequencing (GBS) methods because of its use of special restriction enzymes to produce isolength tags (32-36 bp), and sequencing of these uniform tags can bring many benefits. However, the relatively short tags produced by the original protocol are mostly suited to single-end (SE) sequencing (36-50 bp), and therefore they cannot efficiently match the gradually increased sequencing capacity of next-generation sequencing (NGS) platforms. To address this issue, we describe an advanced protocol that allows the preparation of five concatenated isoRAD tags for Illumina paired-end (PE) sequencing (100-150 bp). The configuration of the five concatenated tags is highly flexible, and can be defined by users to work with a desired combination of samples and/or restriction enzymes to suit specific research purposes. In comparison with the original protocol, the advanced protocol has an additional digestion and ligation step, and library preparation can be completed in ∼8 h.

Whole genome phylogeny for 21 Drosophila species using predicted 2b-RAD fragments

Type IIB restriction endonucleases are site-specific endonucleases that cut both strands of double-stranded DNA upstream and downstream of their recognition sequences. These restriction enzymes have recognition sequences that are generally interrupted and range from 5 to 7 bases long. They produce DNA fragments which are uniformly small, ranging from 21 to 33 base pairs in length (without cohesive ends). The fragments are generated from throughout the entire length of a genomic DNA providing an excellent fractional representation of the genome. In this study we simulated restriction enzyme digestions on 21 sequenced genomes of various Drosophila species using the predicted targets of 16 Type IIB restriction enzymes to effectively produce a large and arbitrary selection of loci from these genomes. The fragments were then used to compare organisms and to calculate the distance between genomes in pair-wise combination by counting the number of shared fragments between the two genomes. Phylogenetic trees were then generated for each enzyme using this distance measure and the consensus was calculated. The consensus tree obtained agrees well with the currently accepted tree for the Drosophila species. We conclude that multi-locus sub-genomic representation combined with next generation sequencing, especially for individuals and species without previous genome characterization, can accelerate studies of comparative genomics and the building of accurate phylogenetic trees.

Reconsideration of in silico siRNA design from a perspective of heterogeneous data integration: problems and solutions

The success of RNA interference (RNAi) depends on the interaction between short interference RNAs (siRNAs) and mRNAs. Design of highly efficient and specific siRNAs has become a challenging issue in applications of RNAi. Here, we present a detailed survey on the state-of-the-art siRNAs design, focusing on several key issues with the current in silico RNAi studies, including: (i) inconsistencies among the proposed guidelines for siRNAs design and the incomplete list of siRNAs features, (ii) improper integration of the heterogeneous cross-platform siRNAs data, (iii) inadequate consideration of the binding specificity of the target mRNAs and (iv) reduction in the 'off-target' effect in siRNAs design. With these considerations, the popular in silico siRNAs design rules are reexamined and several inconsistent viewpoints toward siRNAs feature identifications are clarified. In addition, novel computational models for siRNAs design using state-of-art machine learning techniques are discussed, which focus on heterogeneous data integration, joint feature selection and customized siRNAs screening toward highly specific targets. We believe that addressing such issues in siRNA study will provide new clues for further improved design of more efficient and specific siRNAs in RNAi.

Biome representational in silico karyotyping

Metagenomic characterization of complex biomes remains challenging. Here we describe a modification of digital karyotyping-biome representational in silico karyotyping (BRISK)-as a general technique for analyzing a defined representation of all DNA present in a sample. BRISK utilizes a Type IIB DNA restriction enzyme to create a defined representation of 27-mer DNAs in a sample. Massively parallel sequencing of this representation allows for construction of high-resolution karyotypes and identification of multiple species within a biome. Application to normal human tissue demonstrated linear recovery of tags by chromosome. We apply this technique to the biome of the oral mucosa and find that greater than 25% of recovered DNA is nonhuman. DNA from 41 microbial species could be identified from oral mucosa of two subjects. Of recovered nonhuman sequences, fewer than 30% are currently annotated. We characterized seven prevalent unknown sequences by chromosome walking and find these represent novel microbial sequences including two likely derived from novel phage genomes. Application of BRISK to archival tissue from a nasopharyngeal carcinoma resulted in identification of Epstein-Barr virus infection. These results suggest that BRISK is a powerful technique for the analysis of complex microbiomes and potentially for pathogen discovery.

Characterization of unknown genetic modifications using high throughput sequencing and computational subtraction

BACKGROUND

When generating a genetically modified organism (GMO), the primary goal is to give a target organism one or several novel traits by using biotechnology techniques. A GMO will differ from its parental strain in that its pool of transcripts will be altered. Currently, there are no methods that are reliably able to determine if an organism has been genetically altered if the nature of the modification is unknown.

RESULTS

We show that the concept of computational subtraction can be used to identify transgenic cDNA sequences from genetically modified plants. Our datasets include 454-type sequences from a transgenic line of Arabidopsis thaliana and published EST datasets from commercially relevant species (rice and papaya).

CONCLUSION

We believe that computational subtraction represents a powerful new strategy for determining if an organism has been genetically modified as well as to define the nature of the modification. Fewer assumptions have to be made compared to methods currently in use and this is an advantage particularly when working with unknown GMOs.

Identification of microbial DNA in human cancer

BACKGROUND

Microorganisms have been associated with many types of human diseases; however, a significant number of clinically important microbial pathogens remain to be discovered.

METHODS

We have developed a genome-wide approach, called Digital Karyotyping Microbe Identification (DK-MICROBE), to identify genomic DNA of bacteria and viruses in human disease tissues. This method involves the generation of an experimental DNA tag library through Digital Karyotyping (DK) followed by analysis of the tag sequences for the presence of microbial DNA content using a compiled microbial DNA virtual tag library.

RESULTS

To validate this technology and to identify pathogens that may be associated with human cancer pathogenesis, we used DK-MICROBE to determine the presence of microbial DNA in 58 human tumor samples, including brain, ovarian, and colorectal cancers. We detected DNA from Human herpesvirus 6 (HHV-6) in a DK library of a colorectal cancer liver metastasis and in normal tissue from the same patient.

CONCLUSION

DK-MICROBE can identify previously unknown infectious agents in human tumors, and is now available for further applications for the identification of pathogen DNA in human cancer and other diseases.

Use of short representative sequences for structural and functional genomic studies

Existing approaches to direct genomic studies are costly and time-consuming. To overcome these problems, a series of tag-based methods utilizing short fragments uniquely representing full-length transcripts/genes from which they originate has been developed. This review summarizes basic principles underlying these methods and their numerous modifications designed for studying transcriptome profiles, searching for unidentified expressed loci, characterization of promoter regions, and high-throughput mapping of various genomic sites, such as hypo- and hypermethylated CpGs, and chromatin-binding and DNase I cleavage sites.

Serial analysis of gene expression

Serial analysis of gene expression (SAGE) is a method used to obtain comprehensive, unbiased and quantitative gene-expression profiles. Its major advantage over arrays is that it does not require a priori knowledge of the genes to be analyzed and reflects absolute mRNA levels. Since the original SAGE protocol was developed in a short-tag (10-bp) format, several modifications have been made to produce longer SAGE tags for more precise gene identification and to decrease the amount of starting material necessary. Several SAGE-like methods have also been developed for the genome-wide analysis of DNA copy-number changes and methylation patterns, chromatin structure and transcription factor targets. In this protocol, we describe the 17-bp longSAGE method for transcriptome profiling optimized for a small amount of starting material. The generation of such libraries can be completed in 7-10 d, whereas sequencing and data analysis require an additional 2-3 wk.

Highly parallel genomic assays

Recent developments in highly parallel genome-wide assays are transforming the study of human health and disease. High-resolution whole-genome association studies of complex diseases are finally being undertaken after much hypothesizing about their merit for finding disease loci. The availability of inexpensive high-density SNP-genotyping arrays has made this feasible. Cancer biology will also be transformed by high-resolution genomic and epigenomic analysis. In the future, most cancers might be staged by high-resolution molecular profiling rather than by gross cytological analysis. Here, we describe the key developments that enable highly parallel genomic assays.

SAGE and related approaches for cancer target identification

Comprehensive genetic, epigenetic and transcriptional analyses of normal and cancerous tissues and cells have yielded many candidate diagnostic, predictive, and prognostic markers and therapeutic targets in human cancer. This article provides a brief overview of SAGE and SAGE-like techniques, highlighting their utility and advantages relative to other genomic technologies for the discovery of drug targets. We also summarize the results of recent comprehensive profiling studies that utilize these methods to provide insights into mechanisms of tumor initiation and progression, to improve our molecular understanding of the tumor microenvironment and to reveal new targets and avenues for therapeutic interventions.

CARAT: a novel method for allelic detection of DNA copy number changes using high density oligonucleotide arrays

Background

DNA copy number alterations are one of the main characteristics of the cancer cell karyotype and can contribute to the complex phenotype of these cells. These alterations can lead to gains in cellular oncogenes as well as losses in tumor suppressor genes and can span small intervals as well as involve entire chromosomes. The ability to accurately detect these changes is central to understanding how they impact the biology of the cell.

Results

We describe a novel algorithm called CARAT (Copy Number Analysis with Regression And Tree) that uses probe intensity information to infer copy number in an allele-specific manner from high density DNA oligonuceotide arrays designed to genotype over 100, 000 SNPs. Total and allele-specific copy number estimations using CARAT are independently evaluated for a subset of SNPs using quantitative PCR and allelic TaqMan reactions with several human breast cancer cell lines. The sensitivity and specificity of the algorithm are characterized using DNA samples containing differing numbers of X chromosomes as well as a test set of normal individuals. Results from the algorithm show a high degree of agreement with results from independent verification methods.

Conclusion

Overall, CARAT automatically detects regions with copy number variations and assigns a significance score to each alteration as well as generating allele-specific output. When coupled with SNP genotype calls from the same array, CARAT provides additional detail into the structure of genome wide alterations that can contribute to allelic imbalance.

Somatic alterations in the human cancer genome

Most human malignancies are caused by somatic alterations within the cancer genome, leading to oncogene activation or tumor suppressor gene inactivation. The sequence of the human genome has enabled systematic approaches to identify cancer genome alterations, including point mutations, copy number increases and decreases, loss of allelic heterozygosity, and chromosome translocations. Systematic cancer genome analysis has recently led to the discovery of somatic mutations in the BRAF, PIK3CA, and EGFR genes, among others. With further development of targeted cancer therapies and improvement in genome analysis technology, genome-wide surveys of cancer will likely become tools for diagnosis as well as discovery.