The complete genome of an individual by massively parallel DNA sequencing

Molecular diagnostic experience of whole-exome sequencing in adult patients

PURPOSE

Whole-exome sequencing (WES) is increasingly used as a diagnostic tool in medicine, but prior reports focus on predominantly pediatric cohorts with neurologic or developmental disorders. We describe the diagnostic yield and characteristics of WES in adults.

METHODS

We performed a retrospective analysis of consecutive WES reports for adults from a diagnostic laboratory. Phenotype composition was determined using Human Phenotype Ontology terms.

RESULTS

Molecular diagnoses were reported for 17.5% (85/486) of adults, which is lower than that for a primarily pediatric population (25.2%; P = 0.0003); the diagnostic rate was higher (23.9%) for those 18-30 years of age compared to patients older than 30 years (10.4%; P = 0.0001). Dual Mendelian diagnoses contributed to 7% of diagnoses, revealing blended phenotypes. Diagnoses were more frequent among individuals with abnormalities of the nervous system, skeletal system, head/neck, and growth. Diagnostic rate was independent of family history information, and de novo mutations contributed to 61.4% of autosomal dominant diagnoses.

CONCLUSION

Early WES experience in adults demonstrates molecular diagnoses in a substantial proportion of patients, informing clinical management, recurrence risk, and recommendations for relatives. A positive family history was not predictive, consistent with molecular diagnoses often revealed by de novo events, informing the Mendelian basis of genetic disease in adults.Genet Med 18 7, 678-685.

Next generation sequencing technology and genomewide data analysis: Perspectives for retinal research

The advent of high throughput next generation sequencing (NGS) has accelerated the pace of discovery of disease-associated genetic variants and genomewide profiling of expressed sequences and epigenetic marks, thereby permitting systems-based analyses of ocular development and disease. Rapid evolution of NGS and associated methodologies presents significant challenges in acquisition, management, and analysis of large data sets and for extracting biologically or clinically relevant information. Here we illustrate the basic design of commonly used NGS-based methods, specifically whole exome sequencing, transcriptome, and epigenome profiling, and provide recommendations for data analyses. We briefly discuss systems biology approaches for integrating multiple data sets to elucidate gene regulatory or disease networks. While we provide examples from the retina, the NGS guidelines reviewed here are applicable to other tissues/cell types as well.

Suppression Subtractive Hybridization Versus Next-Generation Sequencing in Plant Genetic Engineering: Challenges and Perspectives

Suppression subtractive hybridization (SSH) is an effective method to identify different genes with different expression levels involved in a variety of biological processes. This method has often been used to study molecular mechanisms of plants in complex relationships with different pathogens and a variety of biotic stresses. Compared to other techniques used in gene expression profiling, SSH needs relatively smaller amounts of the initial materials, with lower costs, and fewer false positives present within the results. Extraction of total RNA from plant species rich in phenolic compounds, carbohydrates, and polysaccharides that easily bind to nucleic acids through cellular mechanisms is difficult and needs to be considered. Remarkable advancement has been achieved in the next-generation sequencing (NGS) field. As a result of progress within fields related to molecular chemistry and biology as well as specialized engineering, parallelization in the sequencing reaction has exceptionally enhanced the overall read number of generated sequences per run. Currently available sequencing platforms support an earlier unparalleled view directly into complex mixes associated with RNA in addition to DNA samples. NGS technology has demonstrated the ability to sequence DNA with remarkable swiftness, therefore allowing previously unthinkable scientific accomplishments along with novel biological purposes. However, the massive amounts of data generated by NGS impose a substantial challenge with regard to data safe-keeping and analysis. This review examines some simple but vital points involved in preparing the initial material for SSH and introduces this method as well as its associated applications to detect different novel genes from different plant species. This review evaluates general concepts, basic applications, plus the probable results of NGS technology in genomics, with unique mention of feasible potential tools as well as bioinformatics.

Recommendations on e-infrastructures for next-generation sequencing

With ever-increasing amounts of data being produced by next-generation sequencing (NGS) experiments, the requirements placed on supporting e-infrastructures have grown. In this work, we provide recommendations based on the collective experiences from participants in the EU COST Action SeqAhead for the tasks of data preprocessing, upstream processing, data delivery, and downstream analysis, as well as long-term storage and archiving. We cover demands on computational and storage resources, networks, software stacks, automation of analysis, education, and also discuss emerging trends in the field. E-infrastructures for NGS require substantial effort to set up and maintain over time, and with sequencing technologies and best practices for data analysis evolving rapidly it is important to prioritize both processing capacity and e-infrastructure flexibility when making strategic decisions to support the data analysis demands of tomorrow. Due to increasingly demanding technical requirements we recommend that e-infrastructure development and maintenance be handled by a professional service unit, be it internal or external to the organization, and emphasis should be placed on collaboration between researchers and IT professionals.

Draft Genome Sequence of Bacillus cereus 905, a Plant Growth-Promoting Rhizobacterium of Wheat

Bacillus cereus 905 is a plant growth-promoting rhizobacterium, isolated from wheat rhizosphere. The draft genome sequence of this strain is 5.39 Mb and harbors 5,412 coding sequences.

Clinical genomics: from a truly personal genome viewpoint

The path to Clinical Genomics is punctuated by our understanding of what types of DNA structural and sequence variation contribute to disease, the many technical challenges to detect such variation genome-wide, and the initial struggles to interpret personal genome variation in the context of disease. This review describes one perspective of the development of clinical genomics; whereas the experimental challenges, and hurdles to overcoming them, might be deemed readily apparent, the non-technical issues for clinical implementation may be less obvious. Some of these latter challenges, including: (1) informed consent, (2) privacy, (3) what constitutes potentially pathogenic variation contributing to disease, (4) disease penetrance in populations, and (5) the genetic architecture of disease, and the struggles sometimes faced for solutions, are highlighted using illustrative examples.

The A, C, G, and T of Genome Assembly

Genome assembly in its two decades of history has produced significant research, in terms of both biotechnology and computational biology. This contribution delineates sequencing platforms and their characteristics, examines key steps involved in filtering and processing raw data, explains assembly frameworks, and discusses quality statistics for the assessment of the assembled sequence. Furthermore, the paper explores recent Ubuntu-based software environments oriented towards genome assembly as well as some avenues for future research.

SLC15A2 genomic variation is associated with the extraordinary response of sorafenib treatment: whole-genome analysis in patients with hepatocellular carcinoma

Reliable biomarkers are required to predict the response to sorafenib. We investigated genomic variations associated with responsiveness to sorafenib for patients with unresectable hepatocellular carcinoma (HCC). Blood samples from 2 extreme, 2 strong and 3 poor responders to sorafenib were subjected to whole-genome analysis. Then, we validated candidate genomic variations with another 174 HCC patients, and performed in vitro functional analysis and in silico analyses. Genomic data of >96 gigabases/sample was generated at average of ~34X sequencing depth. In total, 1813 genomic variations were matched to sorafenib responses in clinical data; 708 were located within regions for sorafenib-target genes or drug absorption, distribution, metabolism, and excretion (ADME)-related genes. From them, 36 variants were within the coding regions and 6 identified as non-synonymous single-nucleotide variants from 4 ADME-related genes (ABCB1, FMO3, MUSK, and SLC15A2). Validation genotyping confirmed sequencing results and revealed patients genotype for rs2257212 in SLC15A2 showed longer progression-free survival (HR = 2.18). In vitro study displayed different response to sorafenib depending on the genotype of SLC15A2. Structural prediction analysis revealed changes of the phosphorylation levels in protein, potentially affecting sorafenib-associated enzymatic activity. Our finding using extreme responder seems to generate robust biomarker to predict the response of sorafenib treatment for HCC.

Challenges, Solutions, and Quality Metrics of Personal Genome Assembly in Advancing Precision Medicine

Even though each of us shares more than 99% of the DNA sequences in our genome, there are millions of sequence codes or structure in small regions that differ between individuals, giving us different characteristics of appearance or responsiveness to medical treatments. Currently, genetic variants in diseased tissues, such as tumors, are uncovered by exploring the differences between the reference genome and the sequences detected in the diseased tissue. However, the public reference genome was derived with the DNA from multiple individuals. As a result of this, the reference genome is incomplete and may misrepresent the sequence variants of the general population. The more reliable solution is to compare sequences of diseased tissue with its own genome sequence derived from tissue in a normal state. As the price to sequence the human genome has dropped dramatically to around $1000, it shows a promising future of documenting the personal genome for every individual. However, de novo assembly of individual genomes at an affordable cost is still challenging. Thus, till now, only a few human genomes have been fully assembled. In this review, we introduce the history of human genome sequencing and the evolution of sequencing platforms, from Sanger sequencing to emerging "third generation sequencing" technologies. We present the currently available de novo assembly and post-assembly software packages for human genome assembly and their requirements for computational infrastructures. We recommend that a combined hybrid assembly with long and short reads would be a promising way to generate good quality human genome assemblies and specify parameters for the quality assessment of assembly outcomes. We provide a perspective view of the benefit of using personal genomes as references and suggestions for obtaining a quality personal genome. Finally, we discuss the usage of the personal genome in aiding vaccine design and development, monitoring host immune-response, tailoring drug therapy and detecting tumors. We believe the precision medicine would largely benefit from bioinformatics solutions, particularly for personal genome assembly.

A uniform survey of allele-specific binding and expression over 1000-Genomes-Project individuals

Large-scale sequencing in the 1000 Genomes Project has revealed multitudes of single nucleotide variants (SNVs). Here, we provide insights into the functional effect of these variants using allele-specific behaviour. This can be assessed for an individual by mapping ChIP-seq and RNA-seq reads to a personal genome, and then measuring 'allelic imbalances' between the numbers of reads mapped to the paternal and maternal chromosomes. We annotate variants associated with allele-specific binding and expression in 382 individuals by uniformly processing 1,263 functional genomics data sets, developing approaches to reduce the heterogeneity between data sets due to overdispersion and mapping bias. Since many allelic variants are rare, aggregation across multiple individuals is necessary to identify broadly applicable 'allelic elements'. We also found SNVs for which we can anticipate allelic imbalance from the disruption of a binding motif. Our results serve as an allele-specific annotation for the 1000 Genomes variant catalogue and are distributed as an online resource (alleledb.gersteinlab.org).

An NGS Workflow Blueprint for DNA Sequencing Data and Its Application in Individualized Molecular Oncology

Next-generation sequencing (NGS) technologies that have advanced rapidly in the past few years possess the potential to classify diseases, decipher the molecular code of related cell processes, identify targets for decision-making on targeted therapy or prevention strategies, and predict clinical treatment response. Thus, NGS is on its way to revolutionize oncology. With the help of NGS, we can draw a finer map for the genetic basis of diseases and can improve our understanding of diagnostic and prognostic applications and therapeutic methods. Despite these advantages and its potential, NGS is facing several critical challenges, including reduction of sequencing cost, enhancement of sequencing quality, improvement of technical simplicity and reliability, and development of semiautomated and integrated analysis workflow. In order to address these challenges, we conducted a literature research and summarized a four-stage NGS workflow for providing a systematic review on NGS-based analysis, explaining the strength and weakness of diverse NGS-based software tools, and elucidating its potential connection to individualized medicine. By presenting this four-stage NGS workflow, we try to provide a minimal structural layout required for NGS data storage and reproducibility.

Personal Genome Sequencing in Ostensibly Healthy Individuals and the PeopleSeq Consortium

Thousands of ostensibly healthy individuals have had their exome or genome sequenced, but a much smaller number of these individuals have received any personal genomic results from that sequencing. We term those projects in which ostensibly healthy participants can receive sequencing-derived genetic findings and may also have access to their genomic data as participatory predispositional personal genome sequencing (PPGS). Here we are focused on genome sequencing applied in a pre-symptomatic context and so define PPGS to exclude diagnostic genome sequencing intended to identify the molecular cause of suspected or diagnosed genetic disease. In this report we describe the design of completed and underway PPGS projects, briefly summarize the results reported to date and introduce the PeopleSeq Consortium, a newly formed collaboration of PPGS projects designed to collect much-needed longitudinal outcome data.

Whole-genome re-sequencing for the identification of high contribution susceptibility gene variants in patients with type 2 diabetes

There is increasing evidence that several genes are associated with an increased risk of type 2 diabetes (T2D); genome-wide association investigations and whole-genome re-sequencing investigations offer a useful approach for the identification of genes involved in common human diseases. To further investigate which polymorphisms confer susceptibility to T2D, the present study screened for high-contribution susceptibility gene variants Chinese patients with T2D using whole-genome re-sequencing with DNA pooling. In total, 100 Chinese individuals with T2D and 100 healthy Chinese individuals were analyzed using whole-genome re-sequencing using DNA pooling. To minimize the likelihood of systematic bias in sampling, paired-end libraries with an insert size of 500 bp were prepared for in T2D in all samples, which were then subjected to whole-genome sequencing. Each library contained four lanes. The average sequencing depth was 35.70. In the present study, 1.36 GB of clean sequence data were generated, and the resulting calculated T2D genome consensus sequence covered 99.88% of the hg19 sequence. A total of 3,974,307 single nucleotide polymorphisms were identified, of which 99.88% were in the dbSNP database. The present study also found 642,189 insertions and deletions, 5,590 structure variants (SVs), 4,713 copy number variants (CNVs) and 13,049 single nucleotide variants. A total of 1,884 somatic CNVs and 74 somatic SVs were significantly different between the cases and controls. Therefore, the present study provided validation of whole-genome re-sequencing using the DNA pooling approach. It also generated a whole-genome re-sequencing genotype database for future investigations of T2D.

From Mutational Mechanisms in Single Cells to Mutational Patterns in Cancer Genomes

Analysis of mutations in thousands of cancer genomes has revealed many characteristic patterns of mutagenesis. The search for the molecular mechanisms underlying these mutational patterns has not only generated novel biological insight but also led to the development of new experimental strategies to study cell-to-cell variation and genome evolution. In this essay, we discuss recent progress in the study of mutational mechanisms with a particular emphasis on the analysis of mutagenesis at the single-cell level.

Comparison of whole-exome sequencing of matched fresh and formalin fixed paraffin embedded melanoma tumours: implications for clinical decision making

The identification of recurrent driver mutations by whole-exome sequencing (WES) of fresh-frozen human cancers and the subsequent development of novel targeted therapies have recently transformed the treatment of many cancers including melanoma. In routine clinical practice, fresh-frozen tissue is rarely available and mutation testing usually needs to be carried out on archival formalin fixed, paraffin embedded (FFPE) tissue, from which DNA is typically fragmented, cross-linked and of lower quality. In this study we aimed to determine whether WES data generated from genomic DNA (gDNA) extracted from FFPE tissues can be produced reliably and of clinically-actionable standard. In this study of ten melanoma patients, we compared WES data produced from analysis of gDNA isolated from FFPE tumour tissue with that isolated from fresh-frozen tumour tissue from the same specimen. FFPE samples were sequenced using both Illumina's Nextera and NimbleGen SeqCap exome capture kits. To examine mutations between the two tissue sources and platforms, somatic mutations in the FFPE exomes were called using the matched fresh tissue sequence as a reference. Of the 10 FFPE DNA samples, seven Nextera and four SeqCap samples passed library preparation. On average, there were 5341 and 2246 variants lost in FFPE compared to matched fresh tissue utilising Nextera and SeqCap kits, respectively. In order to explore the feasibility of future clinical implementation of WES, FFPE variants in 27 genes of important clinical relevance in melanoma were assessed. The average concordance rate was 43.2% over a total of 1299 calls for the chosen genes in the FFPE DNA. For the current clinically most important melanoma mutations, 0/3 BRAF and 6/8 (75%) NRAS FFPE calls were concordant with the fresh tissue result, which was confirmed using a Sequenom OncoCarta Panel. The poor performance of FFPE WES indicates that specialised library construction to account for low quality DNA and further refinements will be necessary before this approach could be used for routine clinical decision making over currently preferred techniques.

APLICACIONES DE LA BIOINFORMÁTICA EN LA MEDICINA: EL GENOMA HUMANO. ¿CÓMO PODEMOS VER TANTO DETALLE?

<p lang="es-ES" align="JUSTIFY">La bioinformática es un campo novedoso que soporta parte de la investigación biológica dirigida a la identificación de variantes génicas que pueden ser descubiertas desde los estudios de genomas completos. Basados en esta motivación se presenta el panorama general de los aportes principales de la bioinformática en el desarrollo del secuenciamiento del primer genoma humano. Adicionalmente se resumen los principales avances en cómputo desarrollados para responder a las demandas requeridas por los métodos de secuenciamiento de última generación para lograr re-secuenciar un genoma humano. Finalmente se introducen algunos de los nuevos retos que deben asumirse para aplicar la genómica personalizada en el desarrollo de la medicina. </p><p lang="es-ES" align="JUSTIFY"> </p><p lang="es-ES" align="JUSTIFY">Abstract</p><p lang="es-ES" align="JUSTIFY">Bioinformatics is a new field that supports part of the biological research aimed at identifying gene variants that can be discovered from studies of whole genomes. Based on this motivation the overview of the main contributions of bioinformatics in the development of sequencing the first human genome is presented. Additionally it is summarized the main advances in computing developed to meet the demands to re-sequence a human genome by using the next generation sequencing technologies. Finally some new challenges that must be faced to apply the personalized genomics into the medicine development are introduced.</p>

Advances in genetics and genomics: use and limitations in achieving malaria elimination goals

Success of the global research agenda towards eradication of malaria will depend on the development of new tools, including drugs, vaccines, insecticides and diagnostics. Genetic and genomic information now available for the malaria parasites, their mosquito vectors and human host, can be harnessed to both develop these tools and monitor their effectiveness. Here we review and provide specific examples of current technological advances and how these genetic and genomic tools have increased our knowledge of host, parasite and vector biology in relation to malaria elimination and in turn enhanced the potential to reach that goal. We then discuss limitations of these tools and future prospects for the successful achievement of global malaria elimination goals.

Targeted Next Generation Sequencing as a Reliable Diagnostic Assay for the Detection of Somatic Mutations in Tumours Using Minimal DNA Amounts from Formalin Fixed Paraffin Embedded Material

Background

Targeted Next Generation Sequencing (NGS) offers a way to implement testing of multiple genetic aberrations in diagnostic pathology practice, which is necessary for personalized cancer treatment. However, no standards regarding input material have been defined. This study therefore aimed to determine the effect of the type of input material (e.g. formalin fixed paraffin embedded (FFPE) versus fresh frozen (FF) tissue) on NGS derived results. Moreover, this study aimed to explore a standardized analysis pipeline to support consistent clinical decision-making.

Method

We used the Ion Torrent PGM sequencing platform in combination with the Ion AmpliSeq Cancer Hotspot Panel v2 to sequence frequently mutated regions in 50 cancer related genes, and validated the NGS detected variants in 250 FFPE samples using standard diagnostic assays. Next, 386 tumour samples were sequenced to explore the effect of input material on variant detection variables. For variant calling, Ion Torrent analysis software was supplemented with additional variant annotation and filtering.

Results

Both FFPE and FF tissue could be sequenced reliably with a sensitivity of 99.1%. Validation showed a 98.5% concordance between NGS and conventional sequencing techniques, where NGS provided both the advantage of low input DNA concentration and the detection of low-frequency variants. The reliability of mutation analysis could be further improved with manual inspection of sequence data.

Conclusion

Targeted NGS can be reliably implemented in cancer diagnostics using both FFPE and FF tissue when using appropriate analysis settings, even with low input DNA.

UMD-Predictor: A High-Throughput Sequencing Compliant System for Pathogenicity Prediction of any Human cDNA Substitution

Whole‐exome sequencing (WES) is increasingly applied to research and clinical diagnosis of human diseases. It typically results in large amounts of genetic variations. Depending on the mode of inheritance, only one or two correspond to pathogenic mutations responsible for the disease and present in affected individuals. Therefore, it is crucial to filter out nonpathogenic variants and limit downstream analysis to a handful of candidate mutations. We have developed a new computational combinatorial system UMD‐Predictor (http://umd‐predictor.eu) to efficiently annotate cDNA substitutions of all human transcripts for their potential pathogenicity. It combines biochemical properties, impact on splicing signals, localization in protein domains, variation frequency in the global population, and conservation through the BLOSUM62 global substitution matrix and a protein‐specific conservation among 100 species. We compared its accuracy with the seven most used and reliable prediction tools, using the largest reference variation datasets including more than 140,000 annotated variations. This system consistently demonstrated a better accuracy, specificity, Matthews correlation coefficient, diagnostic odds ratio, speed, and provided the shortest list of candidate mutations for WES. Webservices allow its implementation in any bioinformatics pipeline for next‐generation sequencing analysis. It could benefit to a wide range of users and applications varying from gene discovery to clinical diagnosis.

Sub-7-second genotyping of single-nucleotide polymorphism by high-resolution melting curve analysis on a thermal digital microfluidic device

We developed a thermal digital microfluidic (T-DMF) device enabling ultrafast DNA melting curve analysis (MCA). Within 7 seconds, the T-DMF device succeeded in differentiating a melting point difference down to 1.6 °C with a variation of 0.3 °C in a tiny droplet sample (1.2 μL), which was 300 times faster and with 20 times less sample spending than the standard MCA (35 minutes, 25 μL) run in a commercial qPCR machine. Such a performance makes it possible for a rapid discrimination of single-nucleotide mutation relevant to prompt clinical decision-making. Also, aided by electronic intelligent control, the T-DMF device facilitates sample handling and pipelining in an automatic serial manner. An optimized oval-shaped thermal electrode is introduced to achieve high thermal uniformity. A device-sealing technique averts sample contamination and permits uninterrupted chemical/biological reactions. Simple fabrication using a single chromium layer fulfills both the thermal and typical transport electrode requirements. Capable of thermally modulating DNA samples with ultrafast MCA, this T-DMF device has the potential for a wide variety of life science analyses, especially for disease diagnosis and prognosis.

Using high-throughput sequencing transcriptome data for INDEL detection: challenges for cancer drug discovery

INTRODUCTION

A cancer cell is a mosaic of genomic and epigenomic alterations. Distinct cancer molecular signatures can be observed depending on tumor type or patient genetic background. One type of genomic alteration is the insertion and/or deletion (INDEL) of nucleotides in the DNA sequence, which may vary in length, and may change the encoded protein or modify protein domains. INDELs are associated to a large number of diseases and their detection is done based on low-throughput techniques. However, high-throughput sequencing has also started to be used for detection of novel disease-causing INDELs. This search may identify novel drug targets.

AREAS COVERED

This review presents examples of using high-throughput sequencing (DNA-Seq and RNA-Seq) to investigate the incidence of INDELs in coding regions of human genes. Some of these examples successfully utilized RNA-Seq to identify INDELs associated to diseases. In addition, other studies have described small INDELs related to chemo-resistance or poor outcome of patients, while structural variants were associated with a better clinical outcome.

EXPERT OPINION

On average, there is twice as much RNA-Seq data available at the most used repositories for such data compared to DNA-Seq. Therefore, using RNA-Seq data is a promising strategy for studying cancer samples with unknown mechanisms of drug resistance, aiming at the discovery of proteins with potential as novel drug targets.

Growing Embossed Nanostructures of Polymer Brushes on Wet-Etched Silicon Templated via Block Copolymers

Block copolymer nanolithography has attracted enormous interest in chip technologies, such as integrated silicon chips and biochips, due to its large-scale and mass production of uniform patterns. We further modified this technology to grow embossed nanodots, nanorods, and nanofingerprints of polymer brushes on silicon from their corresponding wet-etched nanostructures covered with pendent SiHx (X = 1–3) species. Atomic force microscopy (AFM) was used to image the topomorphologies, and multiple transmission-reflection infrared spectroscopy (MTR-IR) was used to monitor the surface molecular films in each step for the sequential stepwise reactions. In addition, two layers of polymethacrylic acid (PMAA) brush nanodots were observed, which were attributed to the circumferential convergence growth and the diffusion-limited growth of the polymer brushes. The pH response of PMAA nanodots in the same region was investigated by AFM from pH 3.0 to 9.0.

Decoding DNA, RNA and peptides with quantum tunnelling

Drugs and treatments could be precisely tailored to an individual patient by extracting their cellular- and molecular-level information. For this approach to be feasible on a global scale, however, information on complete genomes (DNA), transcriptomes (RNA) and proteomes (all proteins) needs to be obtained quickly and at low cost. Quantum mechanical phenomena could potentially be of value here, because the biological information needs to be decoded at an atomic level and quantum tunnelling has recently been shown to be able to differentiate single nucleobases and amino acids in short sequences. Here, we review the different approaches to using quantum tunnelling for sequencing, highlighting the theoretical background to the method and the experimental capabilities demonstrated to date. We also explore the potential advantages of the approach and the technical challenges that must be addressed to deliver practical quantum sequencing devices.

Clinical applications of molecular genetic discoveries

Genome-wide association studies of complex traits have mapped >15,000 common single nucleotide variants (SNVs). Likewise, applications of massively parallel nucleic acid sequencing technologies often referred to as next-generation sequencing to molecular genetic studies of complex traits have catalogued a large number of rare variants (population frequency of <0.01) in cases with complex traits. Moreover, high-throughput nucleic acid sequencing, variant burden analysis, and linkage studies are illuminating the presence of large number of SNVs in cases and families with single-gene disorders. The plethora of the genetic variants has exposed the formidable challenge of identifying the causal and pathogenic variants from the enormous number of innocuous common and rare variants that exist in the population and in an individual genome. The arduous task of identifying the causal and pathogenic variants is further compounded by the pleiotropic effects of the variants, complexity of cis and trans interactions in the genome, variability in phenotypic expression of the disease, as well as phenotypic plasticity, and the multifarious determinants of the phenotype. Population genetic studies offer the initial roadmaps and have the potential to elucidate novel pathways involved in the pathogenesis of the disease. However, the genome of an individual is unique, rendering unambiguous identification of the causal or pathogenic variant in a single individual exceedingly challenging. Yet, the focus of the practice of medicine is on the individual, as Sir William Osler elegantly expressed in his insightful quotation: "The good physician treats the disease; the great physician treats the patient who has the disease." The daunting task facing physicians, patients, and researchers alike is to apply the modern genetic discoveries to care of the individual with or at risk of the disease.

The Phylogeny of Bacillus cereus sensu lato

The three main species of the Bacillus cereus sensu lato , B. cereus , B. thuringiensis , and B. anthracis , were recognized and established by the early 1900s because they each exhibited distinct phenotypic traits. B. thuringiensis isolates and their parasporal crystal proteins have long been established as a natural pesticide and insect pathogen. B. anthracis , the etiological agent for anthrax, was used by Robert Koch in the 19th century as a model to develop the germ theory of disease, and B. cereus , a common soil organism, is also an occasional opportunistic pathogen of humans. In addition to these three historical species designations, are three less-recognized and -understood species: B. mycoides , B. weihenstephanensis , and B. pseudomycoides . All of these “species” combined comprise the Bacillus cereus sensu lato group. Despite these apparently clear phenotypic definitions, early molecular approaches to separate the first three by various DNA hybridization and 16S/23S ribosomal sequence analyses led to some “confusion” because there were limited differences to differentiate between these species. These and other results have led to frequent suggestions that a taxonomic change was warranted to reclassify this group to a single species. But the pathogenic properties of B. anthracis and the biopesticide applications of B. thuringiensis appear to “have outweighed pure taxonomic considerations” and the separate species categories are still being maintained. B. cereus sensu lato represents a classic example of a now common bacterial species taxonomic quandary.

Genome-wide association studies in pharmacogenomics of antidepressants

Major depressive disorder (MDD) is one of the most common psychiatric disorders worldwide. Doctors must prescribe antidepressants based on educated guesses due to the fact that it is unmanageable to predict the effectiveness of any particular antidepressant in an individual patient. With the recent advent of scientific research, the genome-wide association study (GWAS) is extensively employed to analyze hundreds of thousands of single nucleotide polymorphisms by high-throughput genotyping technologies. In addition to the candidate-gene approach, the GWAS approach has recently been utilized to investigate the determinants of antidepressant response to therapy. In this study, we reviewed GWAS studies, their limitations and future directions with respect to the pharmacogenomics of antidepressants in MDD.

Different Facets of Copy Number Changes: Permanent, Transient, and Adaptive

Chromosomal copy number changes are frequently associated with harmful consequences and are thought of as an underlying mechanism for the development of diseases. However, changes in copy number are observed during development and occur during normal biological processes. In this review, we highlight the causes and consequences of copy number changes in normal physiologic processes as well as cover their associations with cancer and acquired drug resistance. We discuss the permanent and transient nature of copy number gains and relate these observations to a new mechanism driving transient site-specific copy gains (TSSGs). Finally, we discuss implications of TSSGs in generating intratumoral heterogeneity and tumor evolution and how TSSGs can influence the therapeutic response in cancer.

A novel method of microsatellite genotyping-by-sequencing using individual combinatorial barcoding

This study examines the potential of next-generation sequencing based 'genotyping-by-sequencing' (GBS) of microsatellite loci for rapid and cost-effective genotyping in large-scale population genetic studies. The recovery of individual genotypes from large sequence pools was achieved by PCR-incorporated combinatorial barcoding using universal primers. Three experimental conditions were employed to explore the possibility of using this approach with existing and novel multiplex marker panels and weighted amplicon mixture. The GBS approach was validated against microsatellite data generated by capillary electrophoresis. GBS allows access to the underlying nucleotide sequences that can reveal homoplasy, even in large datasets and facilitates cross laboratory transfer. GBS of microsatellites, using individual combinatorial barcoding, is potentially faster and cheaper than current microsatellite approaches and offers better and more data.

Optical fingerprints and electron transport properties of DNA bases adsorbed on monolayer MoS2

Electronic, optical and transport properties of DNA nucleobase adsorbed on monolayer MoS₂ has been investigated using density functional theory.

The sequence of sequencers: The history of sequencing DNA

Determining the order of nucleic acid residues in biological samples is an integral component of a wide variety of research applications. Over the last fifty years large numbers of researchers have applied themselves to the production of techniques and technologies to facilitate this feat, sequencing DNA and RNA molecules. This time-scale has witnessed tremendous changes, moving from sequencing short oligonucleotides to millions of bases, from struggling towards the deduction of the coding sequence of a single gene to rapid and widely available whole genome sequencing. This article traverses those years, iterating through the different generations of sequencing technology, highlighting some of the key discoveries, researchers, and sequences along the way.

Single-Nucleotide Polymorphism to Associate Cancer Risk

Genetic heterogeneity explains variation in predisposition for cancer. Whole-genome analysis allows risk to be quantified, giving better targeted screening and quantification of the personalized risk posed by environmental factors. Array-based approaches to whole-genome analysis are rapidly being overtaken by next-generation sequencing (NGS). In this review the different platforms currently available for NGS are compared and the opportunities and risks of this approach are discussed: including the informatics packages required and the ethical issues. Methods applicable to the personal genome machine (PGM) are given as an example of workflows.

RAD Capture (Rapture): Flexible and Efficient Sequence-Based Genotyping

Massively parallel sequencing has revolutionized many areas of biology, but sequencing large amounts of DNA in many individuals is cost-prohibitive and unnecessary for many studies. Genomic complexity reduction techniques such as sequence capture and restriction enzyme-based methods enable the analysis of many more individuals per unit cost. Despite their utility, current complexity reduction methods have limitations, especially when large numbers of individuals are analyzed. Here we develop a much improved restriction site-associated DNA (RAD) sequencing protocol and a new method called Rapture ( R: AD c APTURE: ). The new RAD protocol improves versatility by separating RAD tag isolation and sequencing library preparation into two distinct steps. This protocol also recovers more unique (nonclonal) RAD fragments, which improves both standard RAD and Rapture analysis. Rapture then uses an in-solution capture of chosen RAD tags to target sequencing reads to desired loci. Rapture combines the benefits of both RAD and sequence capture, i.e., very inexpensive and rapid library preparation for many individuals as well as high specificity in the number and location of genomic loci analyzed. Our results demonstrate that Rapture is a rapid and flexible technology capable of analyzing a very large number of individuals with minimal sequencing and library preparation cost. The methods presented here should improve the efficiency of genetic analysis for many aspects of agricultural, environmental, and biomedical science.

Theoretical assessment of feasibility to sequence DNA through interlayer electronic tunneling transport at aligned nanopores in bilayer graphene

Fast, cost effective, single-shot DNA sequencing could be the prelude of a new era in genetics. As DNA encodes the information for the production of proteins in all known living beings on Earth, determining the nucleobase sequences is the first and necessary step in that direction. Graphene-based nanopore devices hold great promise for next-generation DNA sequencing. In this work, we develop a novel approach for sequencing DNA using bilayer graphene to read the interlayer conductance through the layers in the presence of target nucleobases. Classical molecular dynamics simulations of DNA translocation through the pore were performed to trace the nucleobase trajectories and evaluate the interaction between the nucleobases and the nanopore. This interaction stabilizes the bases in different orientations, resulting in smaller fluctuations of the nucleobases inside the pore. We assessed the performance of a bilayer graphene nanopore setup for the purpose of DNA sequencing by employing density functional theory and non-equilibrium Green’s function method to investigate the interlayer conductance of nucleobases coupling simultaneously to the top and bottom graphene layers. The obtained conductance is significantly affected by the presence of DNA in the bilayer graphene nanopore, allowing us to analyze DNA sequences.

Virtual Pharmacist: A Platform for Pharmacogenomics

We present Virtual Pharmacist, a web-based platform that takes common types of high-throughput data, namely microarray SNP genotyping data, FASTQ and Variant Call Format (VCF) files as inputs, and reports potential drug responses in terms of efficacy, dosage and toxicity at one glance. Batch submission facilitates multivariate analysis or data mining of targeted groups. Individual analysis consists of a report that is readily comprehensible to patients and practioners who have basic knowledge in pharmacology, a table that summarizes variants and potential affected drug response according to the US Food and Drug Administration pharmacogenomic biomarker labeled drug list and PharmGKB, and visualization of a gene-drug-target network. Group analysis provides the distribution of the variants and potential affected drug response of a target group, a sample-gene variant count table, and a sample-drug count table. Our analysis of genomes from the 1000 Genome Project underlines the potentially differential drug responses among different human populations. Even within the same population, the findings from Watson's genome highlight the importance of personalized medicine. Virtual Pharmacist can be accessed freely at http://www.sustc-genome.org.cn/vp or installed as a local web server. The codes and documentation are available at the GitHub repository (https://github.com/VirtualPharmacist/vp). Administrators can download the source codes to customize access settings for further development.

Interpreting functional effects of coding variants: challenges in proteome-scale prediction, annotation and assessment

Accurate assessment of genetic variation in human DNA sequencing studies remains a nontrivial challenge in clinical genomics and genome informatics. Ascribing functional roles and/or clinical significances to single nucleotide variants identified from a next-generation sequencing study is an important step in genome interpretation. Experimental characterization of all the observed functional variants is yet impractical; thus, the prediction of functional and/or regulatory impacts of the various mutations using in silico approaches is an important step toward the identification of functionally significant or clinically actionable variants. The relationships between genotypes and the expressed phenotypes are multilayered and biologically complex; such relationships present numerous challenges and at the same time offer various opportunities for the design of in silico variant assessment strategies. Over the past decade, many bioinformatics algorithms have been developed to predict functional consequences of single nucleotide variants in the protein coding regions. In this review, we provide an overview of the bioinformatics resources for the prediction, annotation and visualization of coding single nucleotide variants. We discuss the currently available approaches and major challenges from the perspective of protein sequence, structure, function and interactions that require consideration when interpreting the impact of putatively functional variants. We also discuss the relevance of incorporating integrated workflows for predicting the biomedical impact of the functionally important variations encoded in a genome, exome or transcriptome. Finally, we propose a framework to classify variant assessment approaches and strategies for incorporation of variant assessment within electronic health records.

Analytical applications for pore-forming proteins

Proteinaceous nanometer-scale pores are ubiquitous in biology. The canonical ionic channels (e.g., those that transport Na(+), K(+), Ca(2+), and Cl(-) across cell membranes) play key roles in many cellular processes, including nerve and muscle activity. Another class of channels includes bacterial pore-forming toxins, which disrupt cell function, and can lead to cell death. We describe here the recent development of these toxins for a wide range of biological sensing applications. This article is part of a Special Issue entitled: Pore-Forming Toxins edited by Mauro Dalla Serra and Franco Gambale.

Identification of novel hereditary cancer genes by whole exome sequencing

Whole exome sequencing (WES) provides a powerful tool for medical genetic research. Several dozens of WES studies involving patients with hereditary cancer syndromes have already been reported. WES led to breakthrough in understanding of the genetic basis of some exceptionally rare syndromes; for example, identification of germ-line SMARCA4 mutations in patients with ovarian hypercalcemic small cell carcinomas indeed explains a noticeable share of familial aggregation of this disease. However, studies on common cancer types turned out to be more difficult. In particular, there is almost a dozen of reports describing WES analysis of breast cancer patients, but none of them yet succeeded to reveal a gene responsible for the significant share of missing heritability. Virtually all components of WES studies require substantial improvement, e.g. technical performance of WES, interpretation of WES results, mode of patient selection, etc. Most of contemporary investigations focus on genes with autosomal dominant mechanism of inheritance; however, recessive and oligogenic models of transmission of cancer susceptibility also need to be considered. It is expected that the list of medically relevant tumor-predisposing genes will be rapidly expanding in the next few years.

Next-Generation Sequencing Approaches in Cancer: Where Have They Brought Us and Where Will They Take Us?

Next-generation sequencing (NGS) technologies and data have revolutionized cancer research and are increasingly being deployed to guide clinicians in treatment decision-making. NGS technologies have allowed us to take an “omics” approach to cancer in order to reveal genomic, transcriptomic, and epigenomic landscapes of individual malignancies. Integrative multi-platform analyses are increasingly used in large-scale projects that aim to fully characterize individual tumours as well as general cancer types and subtypes. In this review, we examine how NGS technologies in particular have contributed to “omics” approaches in cancer research, allowing for large-scale integrative analyses that consider hundreds of tumour samples. These types of studies have provided us with an unprecedented wealth of information, providing the background knowledge needed to make small-scale (including “N of 1”) studies informative and relevant. We also take a look at emerging opportunities provided by NGS and state-of-the-art third-generation sequencing technologies, particularly in the context of translational research. Cancer research and care are currently poised to experience significant progress catalyzed by accessible sequencing technologies that will benefit both clinical- and research-based efforts.

Metagenomics for the development of new biocatalysts to advance lignocellulose saccharification for bioeconomic development

The world economy is moving toward the use of renewable and nonedible lignocellulosic biomasses as substitutes for fossil sources in order to decrease the environmental impact of manufacturing processes and overcome the conflict with food production. Enzymatic hydrolysis of the feedstock is a key technology for bio-based chemical production, and the identification of novel, less expensive and more efficient biocatalysts is one of the main challenges. As the genomic era has shown that only a few microorganisms can be cultured under standard laboratory conditions, the extraction and analysis of genetic material directly from environmental samples, termed metagenomics, is a promising way to overcome this bottleneck. Two screening methodologies can be used on metagenomic material: the function-driven approach of expression libraries and sequence-driven analysis based on gene homology. Both techniques have been shown to be useful for the discovery of novel biocatalysts for lignocellulose conversion, and they enabled identification of several (hemi)cellulases and accessory enzymes involved in (hemi)cellulose hydrolysis. This review summarizes the latest progress in metagenomics aimed at discovering new enzymes for lignocellulose saccharification.

DNA-Encoded Solid-Phase Synthesis: Encoding Language Design and Complex Oligomer Library Synthesis

The promise of exploiting combinatorial synthesis for small molecule discovery remains unfulfilled due primarily to the “structure elucidation problem”: the back-end mass spectrometric analysis that significantly restricts one-bead-one-compound (OBOC) library complexity. The very molecular features that confer binding potency and specificity, such as stereochemistry, regiochemistry, and scaffold rigidity, are conspicuously absent from most libraries because isomerism introduces mass redundancy and diverse scaffolds yield uninterpretable MS fragmentation. Here we present DNA-encoded solid-phase synthesis (DESPS), comprising parallel compound synthesis in organic solvent and aqueous enzymatic ligation of unprotected encoding dsDNA oligonucleotides. Computational encoding language design yielded 148 thermodynamically optimized sequences with Hamming string distance ≥ 3 and total read length <100 bases for facile sequencing. Ligation is efficient (70% yield), specific, and directional over 6 encoding positions. A series of isomers served as a testbed for DESPS’s utility in split-and-pool diversification. Single-bead quantitative PCR detected 9 × 10⁴ molecules/bead and sequencing allowed for elucidation of each compound’s synthetic history. We applied DESPS to the combinatorial synthesis of a 75 645-member OBOC library containing scaffold, stereochemical and regiochemical diversity using mixed-scale resin (160-μm quality control beads and 10-μm screening beads). Tandem DNA sequencing/MALDI-TOF MS analysis of 19 quality control beads showed excellent agreement (<1 ppt) between DNA sequence-predicted mass and the observed mass. DESPS synergistically unites the advantages of solid-phase synthesis and DNA encoding, enabling single-bead structural elucidation of complex compounds and synthesis using reactions normally considered incompatible with unprotected DNA. The widespread availability of inexpensive oligonucleotide synthesis, enzymes, DNA sequencing, and PCR make implementation of DESPS straightforward, and may prompt the chemistry community to revisit the synthesis of more complex and diverse libraries.

OncDRS: An integrative clinical and genomic data platform for enabling translational research and precision medicine

We live in the genomic era of medicine, where a patient's genomic/molecular data is becoming increasingly important for disease diagnosis, identification of targeted therapy, and risk assessment for adverse reactions. However, decoding the genomic test results and integrating it with clinical data for retrospective studies and cohort identification for prospective clinical trials is still a challenging task. In order to overcome these barriers, we developed an overarching enterprise informatics framework for translational research and personalized medicine called Synergistic Patient and Research Knowledge Systems (SPARKS) and a suite of tools called Oncology Data Retrieval Systems (OncDRS). OncDRS enables seamless data integration, secure and self-navigated query and extraction of clinical and genomic data from heterogeneous sources. Within a year of release, the system has facilitated more than 1500 research queries and has delivered data for more than 50 research studies.