Perspectives of DNA microarray and next-generation DNA sequencing technologies

A Comparative View on Molecular Alterations and Potential Therapeutic Strategies for Canine Oral Melanoma

Canine oral melanoma (COM) is a highly aggressive tumour associated with poor prognosis due to metastasis and resistance to conventional anti-cancer therapies. As with human mucosal melanoma, the mutational landscape is predominated by copy number aberrations and chromosomal structural variants, but differences in study cohorts and/or tumour heterogeneity can lead to discordant results regarding the nature of specific genes affected. This review discusses somatic molecular alterations in COM that result from single nucleotide variations, copy number changes, chromosomal rearrangements, and/or dysregulation of small non-coding RNAs. A cross-species comparison highlights notable recurrent aberrations, and functionally grouping dysregulated proteins reveals unifying biological pathways that may be critical for oncogenesis and metastasis. Finally, potential therapeutic strategies are considered to target these pathways in canine patients, and the benefits of collaboration between science, medical, and veterinary communities are emphasised.

High-throughput roll-to-roll production of polymer biochips for multiplexed DNA detection in point-of-care diagnostics

Roll-to-roll UV nanoimprint lithography has superior advantages for high-throughput manufacturing of micro- or nano-structures on flexible polymer foils with various geometries and configurations. Our pilot line provides large-scale structure imprinting for cost-effective polymer biochips (4500 biochips/hour), enabling rapid and multiplexed detections. A complete high-volume process chain of the technology for producing structures like μ-sized, triangular optical out-couplers or capillary channels (width: from 1 μm to 2 mm, height: from 200 nm up to 100 μm) to obtain biochips (width: 25 mm, length: 75 mm, height: 100 μm to 1.5 mm) was described. The imprinting process was performed with custom-developed resins on polymer foils with resin thicknesses ranging between 125-190 μm. The produced chips were tested in a commercial point-of-care diagnostic system for multiplexed DNA analysis of methicillin resistant Staphylococcus aureus (e.g., mecA, mecC gene detections). Specific target DNA capturing was based on hybridisation between surface bound DNA probes and biotinylated targets from the sample. The immobilised biotinylated targets subsequently bind streptavidin-horseradish peroxidase conjugates, which in turn generate light upon incubation with a chemiluminescent substrate. To enhance the light out-coupling thus to improve the system performance, optical structures were integrated into the design. The limits-of-detection of mecA (25 bp) for chips with and without structures were calculated as 0.06 and 0.07 μM, respectively. Further, foil-based chips with fluidic channels were DNA functionalised in our roll-to-roll micro-array spotter following the imprinting. This straightforward approach of sequential imprinting and multiplexed DNA functionalisation on a single foil was also realised for the first time. The corresponding foil-based chips were able to detect mecA gene DNA sequences down to a 0.25 μM concentration.

Ten Years of Landscape Genomics: Challenges and Opportunities

Landscape genomics is a relatively new discipline that aims to reveal the relationship between adaptive genetic imprints in genomes and environmental heterogeneity among natural populations. Although the interest in landscape genomics has increased since this term was coined, studies on this topic remain scarce. Landscape genomics has become a powerful method to scan and determine the genes responsible for the complex adaptive evolution of species at population (mostly) and individual (more rarely) level. This review outlines the sampling strategies, molecular marker types and research categories in 37 articles published during the first 10 years of this field (i.e., 2007-2016). We also address major challenges and future directions for landscape genomics. This review aims to promote interest in conducting additional studies in landscape genomics.

Detection approaches for multidrug resistance genes of leukemia

Leukemia is a clonal malignant hematopoietic stem cell disease. It is the sixth most lethal cancer and accounts for 4% of all cancers. The main form of treatment for leukemia is chemotherapy. While some cancer types with a higher incidence than leukemia, such as lung and gastric cancer, have shown a sharp decline in mortality rates in recent years, leukemia has not followed this trend. Drug resistance is often regarded as the main clinical obstacle to effective chemotherapy in patients diagnosed with leukemia. Many resistance mechanisms have now been identified, and multidrug resistance (MDR) is considered the most important and prevalent mechanism involved in the failure of chemotherapy in leukemia. In order to reverse MDR and improve leukemia prognosis, effective detection methods are needed to identify drug resistance genes at initial diagnosis. This article provides a comprehensive overview of published approaches for the detection of MDR in leukemia. Identification of relevant MDR genes and methods for early detection of these genes will be needed in order to treat leukemia more effectively.

Transcriptomic analysis of Staphylococcus aureus using microarray and advanced next-generation RNA-seq technologies

The transcriptome has shown tremendous potential for the comprehensive investigation of gene expression profiles and transcriptional levels in comparative biology, the identification of regulatory mechanism of transcriptional regulators, and the evaluation of target gene for developing new chemotherapeutic agents, vaccine, and diagnostic methods. The traditional microarray and advanced next-generation RNA sequencing technologies (RNA-seq) provide powerful and effective tools for the determination of the transcriptome of bacterial cells. In this chapter, we provide a detailed protocol for scientists who want to investigate gene expression profiles by performing microarray and/or RNA-seq analysis, including different RNA purification methods, mRNA enrichment, decontamination, cDNA synthesis, fragmentation, biotin labeling for hybridization using Affymetrix Staphylococcus aureus chips, quantitative real-time reverse transcription PCR, and RNA-seq data analysis.

Transcriptome profilings of female Schistosoma japonicum reveal significant differential expression of genes after pairing

Pairing of Schistosoma japonicum initiates female development, leads to female sexual maturation, and maintains this mature state. To understand the mechanism involved in these processes, we studied parasites isolated from single- and double-sex cercariae-infected mice using deep-sequencing analysis, Solexa, to uncover pair-regulated transcriptional profiles. In this study, we report the results of high-throughput tag-sequencing (Tag-seq) analysis of the transcriptome of female worms 18 and 23 days postsingle- and double-sex infections. We sequenced over 3 million tags, obtained a total of 14,034, 27,251, 22,755, and 22,555 distinct tags corresponding to 5,773, 9,794, 8,885, and 8,870 tag-mapped genes for 23-day-old female schistosomula from double-sex infections (23DSI), 23-day-old female schistosomula from single-sex infections (23SSI), 18-day-old female schistosomula from double-sex infections (18DSI), and 18-day-old female schistosomula from single-sex infections (18SSI), respectively. Analyses of differentially expressed genes revealed similarities in the gene expression profiles between 18SSI and 18DSI as well as rational differential gene expression between 18SSI and 23SSI. However, fewer upregulated genes were found in 23DSI compared with 18DSI. Of the 3,446 differentially expressed genes between 23DSI and 23SSI, 2,913 genes were upregulated in 23SSI, whereas only 533 genes were upregulated in 23DSI. In these upregulated genes in 23DSI, phosphoglycerate mutase, superoxide dismutase, egg antigen, ribosomal proteins, ferritin-1 heavy chain, and eukaryotic translation initiation factor 2 were detected. Detection of these genes suggests that gene expression in 23DSI is specialized for functions such as promotion and maintenance of female sexual maturation and egg production. Quantitative real-time (RT)-PCR analysis confirmed the Solexa results, thereby supporting the reliability of the system. Our results offer new insights into the biological significance of pairing, which directs the expression of genes specific for sexual maturation and egg production.

Engineering Gene Control Circuits with Allosteric Ribozymes in Human Cells as a Medicine of the Future

Systems and synthetic biology promise to develop new approaches for analysis and design of complex gene expression regulatory networks in living cells with many practical applications to the pharmaceutical and biotech industries. In this chapter the development of novel universal strategies for exogenous control of gene expression is discussed. They are based on designer allosteric ribozymes that can function in the cell. The synthetic riboswitches are obtained by a patented computational procedure that provides fast and accurate modular designs with various Boolean logic functions. The riboswitches can be designed to sense in the cell either the presence or the absence of disease indicative RNA(s) or small molecules, and to switch on or off the gene expression of any exogenous protein. In addition, the riboswitches can be engineered to induce RNA interference or microRNA pathways that can conditionally down regulate the expression of key proteins in the cell. That can prevent a disease’s development. Therefore, the presented synthetic riboswitches can be used as truly universal cellular biosensors. Nowadays, disease indicative RNA(s) can be precisely identified by employing next-generation sequencing technologies with high accuracy . The methods can be employed not only for exogenous control of gene expression but also for re-programming the cell fate, anticancer, and antiviral gene therapies. Such approaches may be employed as potent molecular medicines of the future.

FunSys: Software for functional analysis of prokaryotic transcriptome and proteome

The vast amount of data produced by next-generation sequencing (NGS) has necessitated the development of computational tools to assist in understanding the myriad functions performed by the biological macromolecules involved in heredity. In this work, we developed the FunSys programme, a stand-alone tool with an user friendly interface that enables us to evaluate and correlate differential expression patterns from RNA sequencing and proteomics datasets. The FunSys generates charts and reports based on the results of the analysis of differential expression to aid the interpretation of the results.

AVAILABILITY

The database is available for free at https://sourceforge.net/projects/funsysufpa/

Application of RNA-seq to reveal the transcript profile in bacteria

The large number of microbial genomes deposited in databanks has opened the door for in-depth studies of organisms, including post-genomics investigations. Thanks to new generation sequencing technology, these studies have made advances that have lead to extraordinary discoveries in bacterial transcriptomics. In this review, we describe bacterial RNA sequencing studies that use these new techniques. We also examined the advantages and biases of these new generation technologies; advances in bioinformatics make it possible to overcome the biases, providing interesting and surprising results.

Exploring the application of high-throughput genomics technologies in the field of maternal-embryo communication

Deciphering the complex molecular dialogue between the maternal tract and embryo is crucial to increasing our understanding of pregnancy failure, infertility problems and in the modulation of embryo development, which has consequences through adulthood. High-throughput genomic technologies have been applied to look for a holistic view of the molecular interactions occurring during this dialogue. Among these technologies, microarrays have been widely used, being one of the most popular tools in maternal-embryo communication. Today, next generation sequencing technologies are dwarfing the capabilities of microarrays. The application of these new technologies has broadened to almost all areas of genomics research, because of their massive sequencing capacity. We review the current status of high-throughput genomic technologies and their application to maternal-embryo communication research. We also survey next generation technologies and their huge potential in many research areas. Given the diversity of unanswered questions in the field of maternal-embryo communication and the wide range of possibilities that these technologies offer, here we discuss future perspectives on the use of these technologies to enhance maternal-embryo research.

Nutrigenomics: implications for breast and colon cancer prevention

Nutrigenomics refers to the interaction between one's diet and his/her genes. These interactions can markedly influence digestion, absorption, and the elimination of bioactive food components, as well as influence their site of actions/molecular targets. Nutrigenomics comprises nutrigenetics, epigenetics, and transcriptomics, coupled with other "omic," such as proteomics and metabolomics, that apparently account for the wide variability in cancer risk among individuals with similar dietary habits. Multiple food components including essential nutrients, phytochemical, zoochemicals, fungochemical, and bacterochemicals have been implicated in cancer risk and tumor behavior, admittedly with mixed results. Such findings suggest that not all individuals respond identically to a diet. This chapter highlights the influence of single-nucleotide polymorphism, copy number, epigenetic events, and transcriptomic homeostasis as factors influencing the response to food components and ultimately health, including cancer risk. Both breast and colorectal cancers are reviewed as examples about how nutrigenomics may influence the response to dietary intakes. As the concept that "one size fits all" comes to an end and personalized approaches surface, additional research data will be required to identify those who will benefit most from dietary change and any who might be placed at risk because of an adjustment.

Revealing the missing expressed genes beyond the human reference genome by RNA-Seq

BACKGROUND

The complete and accurate human reference genome is important for functional genomics researches. Therefore, the incomplete reference genome and individual specific sequences have significant effects on various studies.

RESULTS

we used two RNA-Seq datasets from human brain tissues and 10 mixed cell lines to investigate the completeness of human reference genome. First, we demonstrated that in previously identified ~5 Mb Asian and ~5 Mb African novel sequences that are absent from the human reference genome of NCBI build 36, ~211 kb and ~201 kb of them could be transcribed, respectively. Our results suggest that many of those transcribed regions are not specific to Asian and African, but also present in Caucasian. Then, we found that the expressions of 104 RefSeq genes that are unalignable to NCBI build 37 in brain and cell lines are higher than 0.1 RPKM. 55 of them are conserved across human, chimpanzee and macaque, suggesting that there are still a significant number of functional human genes absent from the human reference genome. Moreover, we identified hundreds of novel transcript contigs that cannot be aligned to NCBI build 37, RefSeq genes and EST sequences. Some of those novel transcript contigs are also conserved among human, chimpanzee and macaque. By positioning those contigs onto the human genome, we identified several large deletions in the reference genome. Several conserved novel transcript contigs were further validated by RT-PCR.

CONCLUSION

Our findings demonstrate that a significant number of genes are still absent from the incomplete human reference genome, highlighting the importance of further refining the human reference genome and curating those missing genes. Our study also shows the importance of de novo transcriptome assembly. The comparative approach between reference genome and other related human genomes based on the transcriptome provides an alternative way to refine the human reference genome.

Novel sequencing-based strategies for high-throughput discovery of genetic mutations underlying inherited antibody deficiency disorders

Human inherited antibody deficiency disorders are generally caused by mutations in genes involved in the pathways regulating B-cell class switch recombination; DNA damage repair; and B-cell development, differentiation, and survival. Sequencing a large set of candidate genes involved in these pathways appears to be a highly efficient way to identify novel mutations. Herein we review several high-throughput sequencing approaches as well as recent improvements in target gene enrichment technologies. Systematic improvement of enrichment and sequencing methods, along with refinement of the experimental process is necessary to develop a cost-effective high-throughput resequencing assay for a large cohort of patient samples. The Hyper-IgM/CVID chip is one example of a resequencing platform that may be used to identify known or novel mutations in patents with various types of inherited antibody deficiency.

Systems biology and modeling in neuroblastoma: practicalities and perspectives

Neuroblastoma (NB) is a common pediatric malignancy characterized by clinical and biological heterogeneity. A host of prognostic markers are available, contributing to accurate risk stratification and appropriate treatment allocation. Unfortunately, outcome is still poor for many patients, indicating the need for a new approach with enhanced utilization of the available biological data. Systems biology is a holistic approach in which all components of a biological system carry equal importance. Systems biology uses mathematical modeling and simulation to investigate dynamic interactions between system components, as a means of explaining overall system behavior. Systems biology can benefit the biomedical sciences by providing a more complete understanding of human disease, enhancing the development of targeted therapeutics. Systems biology is largely contiguous with current approaches in NB, which already employ an integrative and pseudo-holistic approach to disease management. Systems modeling of NB offers an optimal method for continuing progression in this field, and conferring additional benefit to current risk stratification and management. Likewise, NB provides an opportunity for systems biology to prove its utility in the context of human disease, since the biology of NB is comprehensively characterized and, therefore, suited to modeling. The purpose of this review is to outline the benefits, challenges and fundamental workings of systems modeling in human disease, using a specific example of bottom-up modeling in NB. The intention is to demonstrate practical requirements to begin bridging the gap between biological research and applied mathematical approaches for the mutual gain of both fields, and with additional benefits for clinical management.

Comparing transcription rate and mRNA abundance as parameters for biochemical pathway and network analysis

The cells adapt to extra- and intra-cellular signals by dynamic orchestration of activities of pathways in the biochemical networks. Dynamic control of the gene expression process represents a major mechanism for pathway activity regulation. Gene expression has thus been routinely measured, most frequently at steady-state mRNA abundance level using micro-array technology. The results are widely used in statistical inference of the structures of underlying biochemical networks, with the assumption that functionally related genes exhibit similar dynamic profiles. Steady-state mRNA abundance, however, is a composite of two factors: transcription rate and mRNA degradation rate. The question being asked here is therefore whether steady-state mRNA abundance or any of two factors is a more informative measurement target for studying network dynamics. The yeast S. cerevisiae was used as model organism and transcription rate was chosen out of the two factors in this study, because genome-wide determination of transcription rates has been reported for several physiological processes in this species. Our strategy is to test which one is a better measurement of functional relatedness between genes. The analysis was performed on those S. cerevisiae genes that have bacterial orthologs as identified by reciprocal BLAST analysis, so that functional relatedness of a gene pair can be measured by the frequency at which their bacterial orthologs co-occur in the same operon in the collection of bacterial genomes. It is found that transcription rate data is generally a better parameter for functional relatedness than steady state mRNA abundance, suggesting transcription rate data is more informative to use in deciphering the logics used by the cells in dynamic regulation of biochemical network behaviors. The significance of this finding for network and systems biology, as well as biomedical research in general, is discussed.