Coming of age: ten years of next-generation sequencing technologies

Multidimensional Integrative Genomics Approaches to Dissecting Cardiovascular Disease

Elucidating the mechanisms of complex diseases such as cardiovascular disease (CVD) remains a significant challenge due to multidimensional alterations at molecular, cellular, tissue, and organ levels. To better understand CVD and offer insights into the underlying mechanisms and potential therapeutic strategies, data from multiple omics types (genomics, epigenomics, transcriptomics, metabolomics, proteomics, microbiomics) from both humans and model organisms have become available. However, individual omics data types capture only a fraction of the molecular mechanisms. To address this challenge, there have been numerous efforts to develop integrative genomics methods that can leverage multidimensional information from diverse data types to derive comprehensive molecular insights. In this review, we summarize recent methodological advances in multidimensional omics integration, exemplify their applications in cardiovascular research, and pinpoint challenges and future directions in this incipient field.

Two novel mutations in the PPIB gene cause a rare pedigree of osteogenesis imperfecta type IX

BACKGROUND

Osteogenesis imperfecta (OI) is a rare genetic skeletal disorder characterized by increased bone fragility and vulnerability to fractures. PPIB is identified as a candidate gene for OI-IX, here we detect two pathogenic mutations in PPIB and analyze the genotype-phenotype correlation in a Chinese family with OI.

METHODS

Next-generation sequencing (NGS) was used to screen the whole exome of the parents of proband. Screening of variation frequency, evolutionary conservation comparisons, pathogenicity evaluation, and protein structure prediction were conducted to assess the pathogenicity of the novel mutations. Sanger sequencing was used to confirm the candidate variants. RTQ-PCR was used to analyze the PPIB gene expression.

RESULTS

All mutant genes screened out by NGS were excluded except PPIB. Two novel heterozygous PPIB mutations (father, c.25A>G; mother, c.509G>A) were identified in relation to osteogenesis imperfecta type IX. Both mutations were predicted to be pathogenic by bioinformatics analysis and RTQ-PCR analysis revealed downregulated PPIB expression in the two carriers.

CONCLUSION

We report a rare pedigree with an autosomal recessive osteogenesis imperfecta type IX (OI-IX) caused by two novel PPIB mutations identified for the first time in China. The current study expands our knowledge of PPIB mutations and their associated phenotypes, and provides new information on the genetic defects associated with this disease for clinical diagnosis.

Advances in the application of high-throughput sequencing in invertebrate virology

Over the last decade, advances in high-throughput sequencing technologies have revolutionised biological research, making it possible for DNA/RNA sequencing of any organism of interest to be undertaken. Sequencing approaches are now routinely used in the detection and characterisation of (novel) viruses, investigation of host-pathogen interactions, and effective development of disease treatment strategies. For the sequencing and identification of viruses of interest, metagenomics approaches using infected host tissue are frequently used, as it is not always possible to culture and isolate these pathogens. High-throughput sequencing can also be used to investigate host-pathogen interactions by investigating (temporal) transcriptomic responses of both the host and virus, potentially leading to the discovery of novel opportunities for treatment and drug targets. In addition, viruses in environmental samples (e.g. water or soil samples) can be identified using eDNA/metagenomics approaches. The promise that recent developments in sequencing brings to the field of invertebrate virology are not devoid of technical challenges, including the need for better laboratory and bioinformatics strategies to sequence and assemble virus genomes within complex tissue or environmental samples, and the difficulties associated with the annotation of the large number of novel viruses being discovered.

Screening the Molecular Framework Underlying Local Dendritic mRNA Translation

In the last decade, bioinformatic analyses of high-throughput proteomics and transcriptomics data have enabled researchers to gain insight into the molecular networks that may underlie lasting changes in synaptic efficacy. Development and utilization of these techniques have advanced the field of learning and memory significantly. It is now possible to move from the study of activity-dependent changes of a single protein to modeling entire network changes that require local protein synthesis. This data revolution has necessitated the development of alternative computational and statistical techniques to analyze and understand the patterns contained within. Thus, the focus of this review is to provide a synopsis of the journey and evolution toward big data techniques to address still unanswered questions regarding how synapses are modified to strengthen neuronal circuits. We first review the seminal studies that demonstrated the pivotal role played by local mRNA translation as the mechanism underlying the enhancement of enduring synaptic activity. In the interest of those who are new to the field, we provide a brief overview of molecular biology and biochemical techniques utilized for sample preparation to identify locally translated proteins using RNA sequencing and proteomics, as well as the computational approaches used to analyze these data. While many mRNAs have been identified, few have been shown to be locally synthesized. To this end, we review techniques currently being utilized to visualize new protein synthesis, a task that has proven to be the most difficult aspect of the field. Finally, we provide examples of future applications to test the physiological relevance of locally synthesized proteins identified by big data approaches.

Fluorescence in situ hybridization in surgical pathology: principles and applications

Identification of recurrent tumour‐specific chromosomal translocations and novel fusion oncogenes has important diagnostic, therapeutic and prognostic implications. Over the past decade, fluorescence in situ hybridization (FISH) analysis of tumour samples has been one of the most rapidly growing areas in genomic medicine and surgical pathology practice. Unlike traditional cytogenetics, FISH affords a rapid analysis of formalin‐fixed, paraffin‐embedded cells within a routine pathology practice workflow. As more diagnostic and treatment decisions are based on results of FISH, demand for the technology will become more widespread. Common FISH‐detected alterations are chromosome deletions, gains, translocations, amplifications and polysomy. These chromosome alterations may have diagnostic and therapeutic implications for many tumour types. Integrating genomic testing into cancer treatment decisions poses many technical challenges, but rapid progress is being made to overcome these challenges in precision medicine. FISH assessment of chromosomal changes relevant to differential diagnosis and cancer treatment decisions has become an important tool for the surgical pathologist. The aim of this review is to provide a theoretical and practical survey of FISH detected translocations with a focus on strategies for clinical application in surgical pathology practice.

Resolving host-pathogen interactions by dual RNA-seq

The transcriptome is a powerful proxy for the physiological state of a cell, healthy or diseased. As a result, transcriptome analysis has become a key tool in understanding the molecular changes that accompany bacterial infections of eukaryotic cells. Until recently, such transcriptomic studies have been technically limited to analyzing mRNA expression changes in either the bacterial pathogen or the infected eukaryotic host cell. However, the increasing sensitivity of high-throughput RNA sequencing now enables "dual RNA-seq" studies, simultaneously capturing all classes of coding and noncoding transcripts in both the pathogen and the host. In the five years since the concept of dual RNA-seq was introduced, the technique has been applied to a range of infection models. This has not only led to a better understanding of the physiological changes in pathogen and host during the course of an infection but has also revealed hidden molecular phenotypes of virulence-associated small noncoding RNAs that were not visible in standard infection assays. Here, we use the knowledge gained from these recent studies to suggest experimental and computational guidelines for the design of future dual RNA-seq studies. We conclude this review by discussing prospective applications of the technique.

Opportunities and challenges of whole-genome and -exome sequencing

Recent advances in the development of sequencing technologies provide researchers with unprecedented possibilities for genetic analyses. In this review, we will discuss the history of genetic studies and the progress driven by next-generation sequencing (NGS), using complex inflammatory bowel diseases as an example. We focus on the opportunities, but also challenges that researchers are facing when working with NGS data to unravel the genetic causes underlying diseases.

Optical DNA mapping in nanofluidic devices: principles and applications

Optical DNA mapping has over the last decade emerged as a very powerful tool for obtaining long range sequence information from single DNA molecules. In optical DNA mapping, intact large single DNA molecules are labeled, stretched out, and imaged using a fluorescence microscope. This means that sequence information ranging over hundreds of kilobasepairs (kbp) can be obtained in one single image. Nanochannels offer homogeneous and efficient stretching of DNA that is crucial to maximize the information that can be obtained from optical DNA maps. In this review, we highlight progress in the field of optical DNA mapping in nanochannels. We discuss the different protocols for sequence specific labeling and divide them into two main categories, enzymatic labeling and affinity-based labeling. Examples are highlighted where optical DNA mapping is used to gain information on length scales that would be inaccessible with traditional techniques. Enzymatic labeling has been commercialized and is mainly used in human genetics and assembly of complex genomes, while the affinity-based methods have primarily been applied in bacteriology, for example for rapid analysis of plasmids encoding antibiotic resistance. Next, we highlight how the design of nanofluidic channels can been altered in order to obtain the desired information and discuss how recent advances in the field make it possible to retrieve information beyond DNA sequence. In the outlook section, we discuss future directions of optical DNA mapping, such as fully integrated devices and portable microscopes.

Solid-phase PCR for rapid multiplex detection of Salmonella spp. at the subspecies level, with amplification efficiency comparable to conventional PCR

Solid-phase PCR (SP-PCR) has attracted considerable interest in different research fields since it allows parallel DNA amplification on the surface of a solid substrate. However, the applications of SP-PCR have been hampered by the low efficiency of the solid-phase amplification. In order to increase the yield of the solid-phase amplification, we studied various parameters including the length, the density, as well as the annealing position of the solid support primer. A dramatic increase in the signal-to-noise (S/N) ratio was observed when increasing the length of solid support primers from 45 to 80 bp. The density of the primer on the surface was found to be important for the S/N ratio of the SP-PCR, and the optimal S/N was obtained with a density of 1.49 × 10¹¹ molecules/mm². In addition, the use of solid support primers with a short overhang at the 5' end would help improve the S/N ratio of the SP-PCR. With optimized conditions, SP-PCR can achieve amplification efficiency comparable to conventional PCR, with a limit of detection of 1.5 copies/μl (37.5 copies/reaction). These improvements will pave the way for wider applications of SP-PCR in various fields such as clinical diagnosis, high-throughput DNA sequencing, and single-nucleotide polymorphism analysis. Graphical abstract Schematic representation of solid-phase PCR.

Multi-OMICS: a critical technical perspective on integrative lipidomics approaches

During the past decades, high-throughput approaches for analyzing different molecular classes such as nucleic acids, proteins, metabolites, and lipids have grown rapidly. These approaches became powerful tools for getting a fundamental understanding of biological systems. Considering each approach and its results separately, relations and causal connections between these classes have no chance to be revealed, since only separate molecular snapshots are provided. Only a combined approach, not fully established yet, with the integration of the corresponding data, might yield a comprehensive and complete understanding of biological processes, such as crosstalk and interactions in signaling pathways. Taking two or more omics-methods into consideration for analysis is referred to as a multi-omics approach, which is gradually evolving. In this critical note, we briefly discuss the relevance, challenges, current state, and potential of data integration from multi-omics approaches, with a special focus on lipidomics analysis, listing the advantages and gaps in this field. This article is part of a Special Issue entitled: BBALIP_Lipidomics Opinion Articles edited by Sepp Kohlwein.

The first validated criteria for effective screening and a new simplified method for α-globin gene sequencing for diagnosis of uncommon α-globin mutations

No well-defined phenotypes that distinguish between unknown α- and β-globin mutations have been reported to date. Direct DNA sequencing of α-globin genes can be technically challenging, as α1- and α2-globin genes are nearly indistinguishable. To detect hemoglobin variants (HbXs) on Hb analysis, the entire β- and α-globin genes were directly sequenced using a newly developed sequencing protocol for α-globin genes. An algorithm to distinguish between α- and β-HbXs was constructed and subsequently validated in the independent validation group. Distinctive characteristics that can distinguish 39 α-HbXs from 24 β-HbXs were the presence of unidentifiable variants of HbA₂ and/or HbX of <37% on isoelectric focusing and <31% on high-performance liquid chromatography. Another set of 67 HbXs was employed to validate our algorithm. This accurately predicted 33 α-HbXs with 100% sensitivity and 97.1% specificity. Our sequencing protocol for α-globin genes was able to identify 11 rare mutations among all exons of both α-globin genes from 72 subjects. Six of these variants were first discovered in Thais. This is the first well-characterized algorithm for distinguishing unknown Hb variants in a large cohort. Our validated criteria and DNA sequencing procedure are highly efficient for molecular characterization of rare Hb mutations.

Molecular approaches for HPV genotyping and HPV-DNA physical status

Persistent infection with high-risk human papillomavirus (HPV) genotypes is the leading cause of cervical cancer development. To this end several studies have focused on designing molecular assays for HPV genotyping, which are considered as the gold standard for the early diagnosis of HPV infection. Moreover, the tendency of HPV DNA to be integrated into the host chromosome is a determining event for cervical oncogenesis. Thus, the establishment of molecular techniques was promoted in order to investigate the physical status of the HPV DNA and the locus of viral insertion into the host chromosome. The molecular approaches that have been developed recently facilitate the collection of a wide spectrum of valuable information specific to each individual patient and therefore can significantly contribute to the establishment of a personalised prognosis, diagnosis and treatment of HPV-positive patients. The present review focuses on state of the art molecular assays for HPV detection and genotyping for intra-lesion analyses, it examines molecular approaches for the determination of HPV-DNA physical status and it discusses the criteria for selecting the most appropriate regions of viral DNA to be incorporated in HPV genotyping and in the determination of HPV-DNA physical status.

Next-Generation Sequencing in Oncology: Genetic Diagnosis, Risk Prediction and Cancer Classification

Next-generation sequencing (NGS) technology has expanded in the last decades with significant improvements in the reliability, sequencing chemistry, pipeline analyses, data interpretation and costs. Such advances make the use of NGS feasible in clinical practice today. This review describes the recent technological developments in NGS applied to the field of oncology. A number of clinical applications are reviewed, i.e., mutation detection in inherited cancer syndromes based on DNA-sequencing, detection of spliceogenic variants based on RNA-sequencing, DNA-sequencing to identify risk modifiers and application for pre-implantation genetic diagnosis, cancer somatic mutation analysis, pharmacogenetics and liquid biopsy. Conclusive remarks, clinical limitations, implications and ethical considerations that relate to the different applications are provided.

Detection and Enumeration of Spore-Forming Bacteria in Powdered Dairy Products

With the abolition of milk quotas in the European Union in 2015, several member states including Ireland, Luxembourg, and Belgium have seen year on year bi-monthly milk deliveries to dairies increase by up to 35%. Milk production has also increased outside of Europe in the past number of years. Unsurprisingly, there has been a corresponding increased focus on the production of dried milk products for improved shelf life. These powders are used in a wide variety of products, including confectionery, infant formula, sports dietary supplements and supplements for health recovery. To ensure quality and safety standards in the dairy sector, strict controls are in place with respect to the acceptable quantity and species of microorganisms present in these products. A particular emphasis on spore-forming bacteria is necessary due to their inherent ability to survive extreme processing conditions. Traditional microbiological detection methods used in industry have limitations in terms of time, efficiency, accuracy, and sensitivity. The following review will explore the common spore-forming bacterial contaminants of milk powders, will review the guidelines with respect to the acceptable limits of these microorganisms and will provide an insight into recent advances in methods for detecting these microbes. The various advantages and limitations with respect to the application of these diagnostics approaches for dairy food will be provided. It is anticipated that the optimization and application of these methods in appropriate ways can ensure that the enhanced pressures associated with increased production will not result in any lessening of safety and quality standards.

Deep Assessment of Genomic Diversity in Cassava for Herbicide Tolerance and Starch Biosynthesis

Cassava is one of the most important food security crops in tropical countries, and a competitive resource for the starch, food, feed and ethanol industries. However, genomics research in this crop is much less developed compared to other economically important crops such as rice or maize. The International Center for Tropical Agriculture (CIAT) maintains the largest cassava germplasm collection in the world. Unfortunately, the genetic potential of this diversity for breeding programs remains underexploited due to the difficulties in phenotypic screening and lack of deep genomic information about the different accessions. A chromosome-level assembly of the cassava reference genome was released this year and only a handful of studies have been made, mainly to find quantitative trait loci (QTL) on breeding populations with limited variability. This work presents the results of pooled targeted resequencing of more than 1500 cassava accessions from the CIAT germplasm collection to obtain a dataset of more than 2000 variants within genes related to starch functional properties and herbicide tolerance. Results of twelve bioinformatic pipelines for variant detection in pooled samples were compared to ensure the quality of the variant calling process. Predictions of functional impact were performed using two separate methods to prioritize interesting variation for genotyping and cultivar selection. Targeted resequencing, either by pooled samples or by similar approaches such as Ecotilling or capture, emerges as a cost effective alternative to whole genome sequencing to identify interesting alleles of genes related to relevant traits within large germplasm collections.

Gastric Cancer Genomics: Advances and Future Directions

Advancement in the field of cancer genomics is revolutionizing the molecular characterization of a wide variety of different cancers. Recent application of large-scale, next-generation sequencing technology to gastric cancer, which remains a major source of morbidity and mortality throughout the world, has helped better define the complex genomic landscape of this cancer. These studies also have led to the development of novel genomically based molecular classification systems for gastric cancer, reinforced the importance of classic driver mutations in gastric cancer pathogenesis, and led to the discovery of new driver gene mutations that previously were not known to be associated with gastric cancer. This wealth of genomic data has significant potential to impact the future management of this disease, and the challenge remains to effectively translate this genomic data into better treatment paradigms for gastric cancer.

Population and clinical genetics of human transposable elements in the (post) genomic era

Recent technological developments-in genomics, bioinformatics and high-throughput experimental techniques-are providing opportunities to study ongoing human transposable element (TE) activity at an unprecedented level of detail. It is now possible to characterize genome-wide collections of TE insertion sites for multiple human individuals, within and between populations, and for a variety of tissue types. Comparison of TE insertion site profiles between individuals captures the germline activity of TEs and reveals insertion site variants that segregate as polymorphisms among human populations, whereas comparison among tissue types ascertains somatic TE activity that generates cellular heterogeneity. In this review, we provide an overview of these new technologies and explore their implications for population and clinical genetic studies of human TEs. We cover both recent published results on human TE insertion activity as well as the prospects for future TE studies related to human evolution and health.

Molecular Analysis of Gene Rearrangements and Mutations in Acute Leukemias and Myeloid Neoplasms

A subset of acute leukemias and other myeloid neoplasms contains specific genetic alterations, many of which are associated with unique clinical and pathologic features. These alterations include chromosomal rearrangements leading to oncogenic fusion proteins or alteration of gene expression by juxtaposing oncogenes to enhancer elements, as well as mutations leading to aberrant activation of a variety of proteins critical to hematopoietic progenitor cell proliferation and differentiation. Molecular analysis is central to diagnosis and clinical management of leukemias, permitting genetic confirmation of a clinical and histologic impression, providing prognostic and predictive information, and facilitating detection of minimal residual disease. This unit will outline approaches to the molecular diagnosis of the most frequent and clinically relevant genetic alterations in acute leukemias and myeloid neoplasms. © 2017 by John Wiley & Sons, Inc.

From isolate to answer: how whole genome sequencing is helping us rapidly characterise nosocomial bacterial outbreaks

The occurrence of highly resistant bacterial pathogens has risen in recent years, causing immense strain on the healthcare industry. Hospital-acquired infections are arguably of most concern, as bacterial outbreaks in clinical settings provide an ideal environment for proliferation among vulnerable populations. Understanding these outbreaks beyond what can be determined with traditional clinical diagnostics and implementing these new techniques routinely in the hospital environment has now become a major focus. This brief review will discuss the three main whole genome sequence techniques available today, and how they are being used to further discriminate bacterial outbreaks in nosocomial settings.

The Case for Laboratory Developed Procedures: Quality and Positive Impact on Patient Care

An explosion of knowledge and technology is revolutionizing medicine and patient care. Novel testing must be brought to the clinic with safety and accuracy, but also in a timely and cost-effective manner, so that patients can benefit and laboratories can offer testing consistent with current guidelines. Under the oversight provided by the Clinical Laboratory Improvement Amendments, laboratories have been able to develop and optimize laboratory procedures for use in-house. Quality improvement programs, interlaboratory comparisons, and the ability of laboratories to adjust assays as needed to improve results, utilize new sample types, or incorporate new mutations, information, or technologies are positive aspects of Clinical Laboratory Improvement Amendments oversight of laboratory-developed procedures. Laboratories have a long history of successful service to patients operating under Clinical Laboratory Improvement Amendments. A series of detailed clinical examples illustrating the quality and positive impact of laboratory-developed procedures on patient care is provided. These examples also demonstrate how Clinical Laboratory Improvement Amendments oversight ensures accurate, reliable, and reproducible testing in clinical laboratories.

Genome-Wide Association Studies In Plant Pathosystems: Toward an Ecological Genomics Approach

The emergence and re-emergence of plant pathogenic microorganisms are processes that imply perturbations in both host and pathogen ecological niches. Global change is largely assumed to drive the emergence of new etiological agents by altering the equilibrium of the ecological habitats which in turn places hosts more in contact with pathogen reservoirs. In this context, the number of epidemics is expected to increase dramatically in the next coming decades both in wild and crop plants. Under these considerations, the identification of the genetic variants underlying natural variation of resistance is a pre-requisite to estimate the adaptive potential of wild plant populations and to develop new breeding resistant cultivars. On the other hand, the prediction of pathogen's genetic determinants underlying disease emergence can help to identify plant resistance alleles. In the genomic era, whole genome sequencing combined with the development of statistical methods led to the emergence of Genome Wide Association (GWA) mapping, a powerful tool for detecting genomic regions associated with natural variation of disease resistance in both wild and cultivated plants. However, GWA mapping has been less employed for the detection of genetic variants associated with pathogenicity in microbes. Here, we reviewed GWA studies performed either in plants or in pathogenic microorganisms (bacteria, fungi and oomycetes). In addition, we highlighted the benefits and caveats of the emerging joint GWA mapping approach that allows for the simultaneous identification of genes interacting between genomes of both partners. Finally, based on co-evolutionary processes in wild populations, we highlighted a phenotyping-free joint GWA mapping approach as a promising tool for describing the molecular landscape underlying plant - microbe interactions.

Genetic linkage analysis using DNA markers in sweetpotato

Sweetpotato is one of the most important food crop species in the world, with more than 104,000,000 tons produced each year, and the breeding of superior cultivars with agronomically important traits, such as improved disease resistance, yield, and nutrient richness, is necessary, especially in developing countries. However, as a result of the crop's complex genomic architecture, which results from its hexaploidy (2n = 6× = 90), high heterozygosity, huge genome, and outcrossing nature, the analysis of genetic linkage in sweetpotato has been challenging. In addition, the lack of whole genome sequences or gene annotations for cultivated hexaploids has interrupted the validation of mapped QTL regions and gene cloning. In spite of these technical difficulties, linkage map construction and QTL mapping analysis have been reported. This review summarizes the results of these linkage analyses, which used SSR, AFLP, and retrotransposon-based molecular markers, and describes future directions for the genetic analysis and marker-assisted breeding of this important but genetically complex crop species.

Erythrogene: a database for in-depth analysis of the extensive variation in 36 blood group systems in the 1000 Genomes Project

Blood group genotyping has recently developed into a clinical tool to improve compatibility of blood transfusions and management of pregnancies. Next-generation sequencing (NGS) is rapidly moving toward routine practice for patient and donor typing and has the potential to remedy some of the limitations of currently used platforms. However, a large-scale investigation into the blood group genotypes obtained by NGS in a multiethnic cohort is lacking. The 1000 Genomes Project provides information on genome variation among 2504 individuals representing 26 populations worldwide. We extracted their NGS data for all 36 blood group systems to a custom-designed database. In total, 210 412 alleles from 43 blood group-related genes were imported and curated. Matching algorithms were developed to compare them to blood group variants identified to date. Of the 1241 non-synonymous variants identified in the coding regions, 241 are known blood group polymorphisms. Interestingly, 357 of the remaining 1000 variants are predicted to occur on extracellular portions of 31 different blood group-carrying proteins and some may represent undiscovered antigens. Of the alleles analyzed, 1504 were not previously described. The ABO/GBGT1/FUT2/FUT3 and GYPB/GYPC genes showed the highest degree of variation per kilobase coding sequence, and ACKR1 variants had the most skewed distribution across 5 continental superpopulations in the dataset. Results were exported to an online search engine, www.erythrogene.com, which presents data according to the allele nomenclature developed for clinical reporting by the International Society of Blood Transfusion. The established database deepens our knowledge on blood group polymorphism globally and provides a long-sought platform for future research.

The contribution of genome mining strategies to the understanding of active principles of PGPR strains

Pathogenic microorganisms and insects affecting plant health are a major and chronic threat to food production and the ecosystem worldwide. As agricultural production has intensified over the years, the use of agrochemicals has in turn increased. However, this extensive usage has had several detrimental effects, with a pervasive environmental impact and the emergence of pathogen resistance. In addition, there is an increasing tendency among consumers to give preference to pesticide-free food products. Biological control, through the employment of plant growth-promoting rhizobacteria (PGPR), is therefore considered a possible route to the reduction, even the elimination, of the use of agrochemicals. PGPR exert their beneficial influence by a multitude of mechanisms, often involving antibiotics and proteins, to defend the host plant against pathogens. To date, these key metabolites have been uncovered only by systematic investigation or by serendipity; their discovery has nevertheless been propelled by the genomic revolution of recent years, as increasing numbers of genomic studies have been integrated into this field, facilitating a holistic view of this topic and the rapid identification of ecologically important metabolites. This review surveys the highlights and advances of genome-driven compound and protein discovery in the field of bacterial PGPR strains, and aims to advocate for the benefits of this strategy.

Mechanical Trapping of DNA in a Double-Nanopore System

Nanopores have become ubiquitous components of systems for single-molecule manipulation and detection, in particular DNA sequencing where electric field driven translocation of DNA through a nanopore is used to read out the DNA molecule. Here, we present a double-pore system where two nanopores are drilled in parallel through the same solid-state membrane, which offers new opportunities for DNA manipulation. Our experiments and molecular dynamics simulations show that simultaneous electrophoretic capture of a DNA molecule by the two nanopores mechanically traps the molecule, increasing its residence time within the nanopores by orders of magnitude. Remarkably, by using two unequal-sized nanopores, the pore of DNA entry and exit can be discerned from the ionic current blockades, and the translocation direction can be precisely controlled by small differences in the effective force applied to DNA. The mechanical arrest of DNA translocation using a double-pore system can be straightforwardly integrated into any solid-state nanopore platform, including those using optical or transverse-current readouts.

Topological methods for genomics: present and future directions

Topological methods are emerging as a new set of tools for the analysis of large genomic datasets. They are mathematically grounded methods that extract information from the geometric structure of data. In the last few years, applications to evolutionary biology, cancer genomics, and the analysis of complex diseases have uncovered significant biological results, highlighting their utility for fulfilling some of the current analytic needs of genomics. In this review, the state of the art in the application of topological methods to genomics is summarized, and some of the present limitations and possible future developments are reviewed.

A Survey of Computational Tools to Analyze and Interpret Whole Exome Sequencing Data

Whole Exome Sequencing (WES) is the application of the next-generation technology to determine the variations in the exome and is becoming a standard approach in studying genetic variants in diseases. Understanding the exomes of individuals at single base resolution allows the identification of actionable mutations for disease treatment and management. WES technologies have shifted the bottleneck in experimental data production to computationally intensive informatics-based data analysis. Novel computational tools and methods have been developed to analyze and interpret WES data. Here, we review some of the current tools that are being used to analyze WES data. These tools range from the alignment of raw sequencing reads all the way to linking variants to actionable therapeutics. Strengths and weaknesses of each tool are discussed for the purpose of helping researchers make more informative decisions on selecting the best tools to analyze their WES data.

The application of genome-wide 5-hydroxymethylcytosine studies in cancer research

Early detection and characterization of molecular events associated with tumorgenesis remain high priorities. Genome-wide epigenetic assays are promising diagnostic tools, as aberrant epigenetic events are frequent and often cancer specific. The deposition and analysis of multiple patient-derived cancer epigenomic profiles contributes to our appreciation of the underlying biology; aiding the detection of novel identifiers for cancer subtypes. Modifying enzymes and co-factors regulating these epigenetic marks are frequently mutated in cancers, and as epigenetic modifications themselves are reversible, this makes their study very attractive with respect to pharmaceutical intervention. Here we focus on the novel modified base, 5-hydoxymethylcytosine, and discuss how genome-wide 5-hydoxymethylcytosine profiling expedites our molecular understanding of cancer, serves as a lineage tracer, classifies the mode of action of potentially carcinogenic agents and clarifies the roles of potential novel cancer drug targets; thus assisting the development of new diagnostic/prognostic tools.

Mate-pair editing: a perspective to double mate-pair sequencing coverage

In this report, I am proposing a hypothetical approach that can enable sequencing of four short reads from the same insert using Illumina next-generation sequencing. The methodology is similar to that used in mate-pair sequencing except that it involves two circularization steps and the sequencing slide should have four different oligonucleotides.

PRECISION MEDICINE - The Golden Gate for Detection, Treatment and Prevention of Alzheimer's Disease

During this decade, breakthrough conceptual shifts have commenced to emerge in the field of Alzheimer's disease (AD) recognizing risk factors and the non-linear dynamic continuum of complex pathophysiologies amongst a wide dimensional spectrum of multi-factorial brain proteinopathies/neurodegenerative diseases. As is the case in most fields of medicine, substantial advancements in detecting, treating and preventing AD will likely evolve from the generation and implementation of a systematic precision medicine strategy. This approach will likely be based on the success found from more advanced research fields, such as oncology. Precision medicine will require integration and transfertilization across fragmented specialities of medicine and direct reintegration of Neuroscience, Neurology and Psychiatry into a continuum of medical sciences away from the silo approach. Precision medicine is biomarker-guided medicine on systems-levels that takes into account methodological advancements and discoveries of the comprehensive pathophysiological profiles of complex multi-factorial neurodegenerative diseases, such as late-onset sporadic AD. This will allow identifying and characterizing the disease processes at the asymptomatic preclinical stage, where pathophysiological and topographical abnormalities precede overt clinical symptoms by many years to decades. In this respect, the uncharted territory of the AD preclinical stage has become a major research challenge as the field postulates that early biomarker guided customized interventions may offer the best chance of therapeutic success. Clarification and practical operationalization is needed for comprehensive dissection and classification of interacting and converging disease mechanisms, description of genomic and epigenetic drivers, natural history trajectories through space and time, surrogate biomarkers and indicators of risk and progression, as well as considerations about the regulatory, ethical, political and societal consequences of early detection at asymptomatic stages. In this scenario, the integrated roles of genome sequencing, investigations of comprehensive fluid-based biomarkers and multimodal neuroimaging will be of key importance for the identification of distinct molecular mechanisms and signaling pathways in subsets of asymptomatic people at greatest risk for progression to clinical milestones due to those specific pathways. The precision medicine strategy facilitates a paradigm shift in Neuroscience and AD research and development away from the classical "one-size-fits-all" approach in drug discovery towards biomarker guided "molecularly" tailored therapy for truly effective treatment and prevention options. After the long and winding decade of failed therapy trials progress towards the holistic systems-based strategy of precision medicine may finally turn into the new age of scientific and medical success curbing the global AD epidemic.

Microreact: visualizing and sharing data for genomic epidemiology and phylogeography

Visualization is frequently used to aid our interpretation of complex datasets. Within microbial genomics, visualizing the relationships between multiple genomes as a tree provides a framework onto which associated data (geographical, temporal, phenotypic and epidemiological) are added to generate hypotheses and to explore the dynamics of the system under investigation. Selected static images are then used within publications to highlight the key findings to a wider audience. However, these images are a very inadequate way of exploring and interpreting the richness of the data. There is, therefore, a need for flexible, interactive software that presents the population genomic outputs and associated data in a user-friendly manner for a wide range of end users, from trained bioinformaticians to front-line epidemiologists and health workers. Here, we present Microreact, a web application for the easy visualization of datasets consisting of any combination of trees, geographical, temporal and associated metadata. Data files can be uploaded to Microreact directly via the web browser or by linking to their location (e.g. from Google Drive/Dropbox or via API), and an integrated visualization via trees, maps, timelines and tables provides interactive querying of the data. The visualization can be shared as a permanent web link among collaborators, or embedded within publications to enable readers to explore and download the data. Microreact can act as an end point for any tool or bioinformatic pipeline that ultimately generates a tree, and provides a simple, yet powerful, visualization method that will aid research and discovery and the open sharing of datasets.

Primer Sets Developed for Functional Genes Reveal Shifts in Functionality of Fungal Community in Soils

Phylogenetic diversity of soil microbes is a hot topic at the moment. However, the molecular tools for the assessment of functional diversity in the fungal community are less developed than tools based on genes encoding the ribosomal operon. Here 20 sets of primers targeting genes involved mainly in carbon cycling were designed and/or validated and the functioning of soil fungal communities along a chronosequence of land abandonment from agriculture was evaluated using them. We hypothesized that changes in fungal community structure during secondary succession would lead to difference in the types of genes present in soils and that these changes would be directional. We expected an increase in genes involved in degradation of recalcitrant organic matter in time since agriculture. Out of the investigated genes, the richness of the genes related to carbon cycling was significantly higher in fields abandoned for longer time. The composition of six of the genes analyzed revealed significant differences between fields abandoned for shorter and longer time. However, all genes revealed significant variance over the fields studied, and this could be related to other parameters than the time since agriculture such as pH, organic matter, and the amount of available nitrogen. Contrary to our initial hypothesis, the genes significantly different between fields were not related to the decomposition of more recalcitrant matter but rather involved in degradation of cellulose and hemicellulose.

New insights into the generation and role of de novo mutations in health and disease

Aside from inheriting half of the genome of each of our parents, we are born with a small number of novel mutations that occurred during gametogenesis and postzygotically. Recent genome and exome sequencing studies of parent-offspring trios have provided the first insights into the number and distribution of these de novo mutations in health and disease, pointing to risk factors that increase their number in the offspring. De novo mutations have been shown to be a major cause of severe early-onset genetic disorders such as intellectual disability, autism spectrum disorder, and other developmental diseases. In fact, the occurrence of novel mutations in each generation explains why these reproductively lethal disorders continue to occur in our population. Recent studies have also shown that de novo mutations are predominantly of paternal origin and that their number increases with advanced paternal age. Here, we review the recent literature on de novo mutations, covering their detection, biological characterization, and medical impact.

MathIOmica: An Integrative Platform for Dynamic Omics

Multiple omics data are rapidly becoming available, necessitating the use of new methods to integrate different technologies and interpret the results arising from multimodal assaying. The MathIOmica package for Mathematica provides one of the first extensive introductions to the use of the Wolfram Language to tackle such problems in bioinformatics. The package particularly addresses the necessity to integrate multiple omics information arising from dynamic profiling in a personalized medicine approach. It provides multiple tools to facilitate bioinformatics analysis, including importing data, annotating datasets, tracking missing values, normalizing data, clustering and visualizing the classification of data, carrying out annotation and enumeration of ontology memberships and pathway analysis. We anticipate MathIOmica to not only help in the creation of new bioinformatics tools, but also in promoting interdisciplinary investigations, particularly from researchers in mathematical, physical science and engineering fields transitioning into genomics, bioinformatics and omics data integration.

Understanding the complex evolution of rapidly mutating viruses with deep sequencing: Beyond the analysis of viral diversity

With the advent of affordable deep sequencing technologies, detection of low frequency variants within genetically diverse viral populations can now be achieved with unprecedented depth and efficiency. The high-resolution data provided by next generation sequencing technologies is currently recognised as the gold standard in estimation of viral diversity. In the analysis of rapidly mutating viruses, longitudinal deep sequencing datasets from viral genomes during individual infection episodes, as well as at the epidemiological level during outbreaks, now allow for more sophisticated analyses such as statistical estimates of the impact of complex mutation patterns on the evolution of the viral populations both within and between hosts. These analyses are revealing more accurate descriptions of the evolutionary dynamics that underpin the rapid adaptation of these viruses to the host response, and to drug therapies. This review assesses recent developments in methods and provide informative research examples using deep sequencing data generated from rapidly mutating viruses infecting humans, particularly hepatitis C virus (HCV), human immunodeficiency virus (HIV), Ebola virus and influenza virus, to understand the evolution of viral genomes and to explore the relationship between viral mutations and the host adaptive immune response. Finally, we discuss limitations in current technologies, and future directions that take advantage of publically available large deep sequencing datasets.

Advances in analyzing RNA diversity in eukaryotic transcriptomes: peering through the Omics lens

Alternative splicing, polyadenylation, and chemical modifications of RNA generate astonishing complexity within eukaryotic transcriptomes. The last decade has brought numerous advances in sequencing technologies that allow biologists to investigate these phenomena with greater depth and accuracy while reducing time and cost. A commensurate development in biochemical techniques for the enrichment and analysis of different RNA variants has accompanied the advancement of global sequencing analysis platforms. Here, we present a detailed overview of the latest biochemical methods, along with bioinformatics pipelines that have aided in identifying different RNA variants. We also highlight the ongoing developments and challenges associated with RNA variant detection and quantification, including sample heterogeneity and isolation, as well as 'Omics' big data handling.

Metagenomics: Probing pollutant fate in natural and engineered ecosystems

Polluted environments are a reservoir of microbial species able to degrade or to convert pollutants to harmless compounds. The proper management of microbial resources requires a comprehensive characterization of their genetic pool to assess the fate of contaminants and increase the efficiency of bioremediation processes. Metagenomics offers appropriate tools to describe microbial communities in their whole complexity without lab-based cultivation of individual strains. After a decade of use of metagenomics to study microbiomes, the scientific community has made significant progress in this field. In this review, we survey the main steps of metagenomics applied to environments contaminated with organic compounds or heavy metals. We emphasize technical solutions proposed to overcome encountered obstacles. We then compare two metagenomic approaches, i.e. library-based targeted metagenomics and direct sequencing of metagenomes. In the former, environmental DNA is cloned inside a host, and then clones of interest are selected based on (i) their expression of biodegradative functions or (ii) sequence homology with probes and primers designed from relevant, already known sequences. The highest score for the discovery of novel genes and degradation pathways has been achieved so far by functional screening of large clone libraries. On the other hand, direct sequencing of metagenomes without a cloning step has been more often applied to polluted environments for characterization of the taxonomic and functional composition of microbial communities and their dynamics. In this case, the analysis has focused on 16S rRNA genes and marker genes of biodegradation. Advances in next generation sequencing and in bioinformatic analysis of sequencing data have opened up new opportunities for assessing the potential of biodegradation by microbes, but annotation of collected genes is still hampered by a limited number of available reference sequences in databases. Although metagenomics is still facing technical and computational challenges, our review of the recent literature highlights its value as an aid to efficiently monitor the clean-up of contaminated environments and develop successful strategies to mitigate the impact of pollutants on ecosystems.