Diagnostic applications of high-throughput DNA sequencing

Virus Detection by CRISPR-Cas9-Mediated Strand Displacement in a Lateral Flow Assay

In public health emergencies or in resource-constrained settings, laboratory-based diagnostic methods, such as RT-qPCR, need to be complemented with accurate, rapid, and accessible approaches to increase testing capacity, as this will translate into better outcomes in disease prevention and management. Here, we develop an original nucleic acid detection platform by leveraging CRISPR-Cas9 and lateral flow immunochromatography technologies. In combination with an isothermal amplification that runs with a biotinylated primer, the system exploits the interaction between the CRISPR-Cas9 R-loop formed upon targeting a specific nucleic acid and a fluorescein-labeled probe to generate a visual readout on a lateral flow device. Our method enables rapid, sensitive detection of nucleic acids, achieving a limit of 1-10 copies/μL in 1 h at a low temperature. We validated the efficacy of the method by using clinical samples of patients infected with SARS-CoV-2. Compared with other assays, it operates with more accessible molecular elements and showcases a robust signal-to-noise ratio. Moreover, multiplexed detection was demonstrated using primers labeled with biotin and digoxigenin, achieving the simultaneous identification of target genes on lateral flow devices with two test lines. We successfully detected SARS-CoV-2 and Influenza A (H1N1) in spiked samples, highlighting the potential of the method for multiplexed diagnostics of respiratory viruses. All in all, this represents a versatile and manageable platform for point-of-care testing, thereby supporting better patient outcomes and enhanced pandemic preparedness.

Personalized Nutrition: Tailoring Dietary Recommendations through Genetic Insights

Personalized nutrition (PN) represents a transformative approach in dietary science, where individual genetic profiles guide tailored dietary recommendations, thereby optimizing health outcomes and managing chronic diseases more effectively. This review synthesizes key aspects of PN, emphasizing the genetic basis of dietary responses, contemporary research, and practical applications. We explore how individual genetic differences influence dietary metabolisms, thus underscoring the importance of nutrigenomics in developing personalized dietary guidelines. Current research in PN highlights significant gene-diet interactions that affect various conditions, including obesity and diabetes, suggesting that dietary interventions could be more precise and beneficial if they are customized to genetic profiles. Moreover, we discuss practical implementations of PN, including technological advancements in genetic testing that enable real-time dietary customization. Looking forward, this review identifies the robust integration of bioinformatics and genomics as critical for advancing PN. We advocate for multidisciplinary research to overcome current challenges, such as data privacy and ethical concerns associated with genetic testing. The future of PN lies in broader adoption across health and wellness sectors, promising significant advancements in public health and personalized medicine.

Immune infiltration-related genes regulate the progression of AML by invading the bone marrow microenvironment

In this study, we try to find the pathogenic role of immune-related genes in the bone marrow microenvironment of AML. Through WGCNA, seven modules were obtained, among which the turquoise module containing 1793 genes was highly correlated with the immune infiltration score. By unsupervised clustering, the turquoise module was divided into two clusters: the intersection of clinically significant genes in the TCGA and DEGs to obtain 178 genes for mutation analysis, followed by obtaining 17 genes with high mutation frequency. Subsequently, these 17 genes were subjected to LASSO regression analysis to construct a riskscore model of 8 hub genes. The TIMER database, ImmuCellAI portal website, and ssGSEA elucidate that the hub genes and risk scores are closely related to immune cell infiltration into the bone marrow microenvironment. In addition, we also validated the relative expression levels of hub genes using the TCGA database and GSE114868, and additional expression levels of hub genes in AML cell lines in vitro. Therefore, we constructed an immune infiltration-related gene model that identify 8 hub genes with good risk stratification and predictive prognosis for AML.

Biodiversity, Distribution and Functional Differences of Fungi in Four Species of Corals from the South China Sea, Elucidated by High-Throughput Sequencing Technology

Recent studies have predominantly spotlighted bacterial diversity within coral microbiomes, leaving coral-associated fungi in the shadows of scientific inquiry. This study endeavors to fill this knowledge gap by delving into the biodiversity, distribution and functional differences of fungi associated with soft corals Cladiella krempfi and Sarcophyton tortuosum, gorgonian coral Dichotella gemmacea and stony coral Favia speciosa from the South China Sea. Leveraging high-throughput sequencing of fungal internal transcribed spacer-1 (ITS1) region of the rRNA gene, a total of 431 fungal amplicon sequence variants (ASVs) were identified in this study, which indicated that a large number of fungal communities were harbored in the South China Sea corals. Noteworthy among our findings is that 10 fungal genera are reported for the first time in corals, with Candolleomyces, Exophiala, Fomitopsis, Inaequalispora, Kneiffiella, Paraphaeosphaeria, and Yamadazyma belonging to the Ascomycota, and Cystobasidium, Psathyrella, and Solicoccozyma to the Basidiomycota. Moreover, significant differences (p < 0.05) of fungal communities were observed among the various coral species. In particular, the gorgonian coral D. gemmacea emerged as a veritable haven for fungal diversity, boasting 307 unique ASVs. Contrastingly, soft corals S. tortuosum and C. krempfi exhibited modest fungal diversity, with 36 and 21 unique ASVs, respectively, while the stony coral F. speciosa hosted a comparatively sparse fungal community, with merely 10 unique ASVs in total. These findings not only provide basic data on fungal diversity and function in the South China Sea corals, but also underscore the imperative of nuanced conservation and management strategies for coral reef ecosystems worldwide.

Integrative analysis reveals that SLC38A1 promotes hepatocellular carcinoma development via PI3K/AKT/mTOR signaling via glutamine mediated energy metabolism

Although hepatocellular carcinoma (HCC) is rather frequent, little is known about the molecular pathways underlying its development, progression, and prognosis. In the current study, we comprehensively analyzed the deferentially expressed metabolism-related genes (MRGs) in HCC based on TCGA datasets attempting to discover the potentially prognostic genes in HCC. The up-regulated MRGs were further subjected to analyze their prognostic values and protein expressions. Twenty-seven genes were identified because their high expressions were significant in OS, PFS, DFS, DSS, and HCC tumor samples. They were then used for GO, KEGG, methylation, genetics changes, immune infiltration analyses. Moreover, we established a prognostic model in HCC using univariate assays and LASSO regression based on these MRGs. Additionally, we also found that SLC38A1, an amino acid metabolism closely related transporter, was a potential prognostic gene in HCC, and its function in HCC was further studied using experiments. We found that the knockdown of SLC38A1 notably suppressed the growth and migration of HCC cells. Further studies revealed that SLC38A1 modulated the development of HCC cells by regulating PI3K/AKT/mTOR signaling via glutamine mediated energy metabolism. In conclusion, this study identified the potentially prognostic MRGs in HCC and uncovered that SLC38A1 regulated HCC development and progression by regulating PI3K/AKT/mTOR signaling via glutamine mediated energy metabolism, which might provide a novel marker and potential therapeutic target in HCC.

Integrated Multi-Omics Analysis Model to Identify Biomarkers Associated With Prognosis of Breast Cancer

Background

With the rapid development and wide application of high-throughput sequencing technology, biomedical research has entered the era of large-scale omics data. We aim to identify genes associated with breast cancer prognosis by integrating multi-omics data.

Method

Gene-gene interactions were taken into account, and we applied two differential network methods JDINAC and LGCDG to identify differential genes. The patients were divided into case and control groups according to their survival time. The TCGA and METABRIC database were used as the training and validation set respectively.

Result

In the TCGA dataset, C11orf1, OLA1, RPL31, SPDL1 and IL33 were identified to be associated with prognosis of breast cancer. In the METABRIC database, ZNF273, ZBTB37, TRIM52, TSGA10, ZNF727, TRAF2, TSPAN17, USP28 and ZNF519 were identified as hub genes. In addition, RPL31, TMEM163 and ZNF273 were screened out in both datasets. GO enrichment analysis shows that most of these hub genes were involved in zinc ion binding.

Conclusion

In this study, a total of 15 hub genes associated with long-term survival of breast cancer were identified, which can promote understanding of the molecular mechanism of breast cancer and provide new insight into clinical research and treatment.

Polygenic and Network-Based Studies in Risk Identification and Demystification of cancer

INTRODUCTION

Diseases were initially thought to be the consequence of a single gene mutation. Advances in DNA sequencing tools and our understanding of gene behavior have revealed that complex diseases, such as cancer, are the product of genes cooperating with each other and with their environment in orchestrated communication networks. Seeing that the function of individual genes is still used to analyze cancer, the shift to using functionally interacting groups of genes as a new unit of study holds promise for demystifying cancer.

AREAS COVERED

The literature search focused on three types of cancer, namely breast, lung, and prostate, but arguments from other cancers were also included. The aim was to prove that multigene analyses can accurately predict and prognosticate cancer risk, subtype cancer for more personalized and effective treatments, and discover anti-cancer therapies. Computational intelligence is being harnessed to analyze this type of data and is proving indispensable to scientific progress.

EXPERT OPINION

In the future, comprehensive profiling of all kinds of patient data (e.g., serum molecules, environmental exposures) can be used to build universal networks that should help us elucidate the molecular mechanisms underlying diseases and provide appropriate preventive measures, ensuring lifelong health and longevity.

Diagnosis and prognosis models for hepatocellular carcinoma patient's management based on tumor mutation burden

Introduction

The development and prognosis of HCC involve complex molecular mechanisms, which affect the effectiveness of its treatment strategies. Tumor mutational burden (TMB) is related to the efficacy of immunotherapy, but the prognostic role of TMB-related genes in HCC has not yet been determined clearly.

Objectives

In this study, we identified TMB-specific genes with good prognostic value to build diagnostic and prognostic models and provide guidance for the treatment of HCC patients.

Methods

Weighted gene co-expression network analysis (WGCNA) was applied to identify the TMB-specific genes. And LASSO method and Cox regression were used in establishing the prognostic model.

Results

The prognostic model based on SMG5 and MRPL9 showed patients with higher prognostic risk had a remarkedly poorer survival probability than their counterparts with lower prognostic risk in both a TCGA cohort (P < 0.001, HR = 1.93) and an ICGC cohort (P < 0.001, HR = 3.58). In addition, higher infiltrating fractions of memory B cells, M0 macrophages, neutrophils, activated memory CD4 + T cells, follicular helper T cells and regulatory T cells and higher expression of B7H3, CTLA4, PD1, and TIM3 were present in the high-risk group than in the low-risk group (P < 0.05). Patients with high prognostic risk had higher resistance to some chemotherapy and targeted drugs, such as methotrexate, vinblastine and erlotinib, than those with low prognostic risk (P < 0.05). And a diagnostic model considering two genes was able to accurately distinguish patients with HCC from normal samples and those with dysplastic nodules. In addition, knockdown of SMG5 and MRPL9 was determined to significantly inhibit cell proliferation and migration in HCC.

Conclusion

Our study helps to select patients suitable for chemotherapy, targeted drugs and immunotherapy and provide new ideas for developing treatment strategies to improve disease outcomes in HCC patients.

Cost Effectiveness of Whole Exome Sequencing for Children with Developmental Delay in a Developing Country: A Study from Jordan

This retrospective study aimed to determine the cost effectiveness of whole exome sequencing (WES) in the diagnosis of children with developmental delay in a developing country. In this study of 40 patients, the average cost of traditional investigations and indirect costs related to rehabilitation and medications per child were USD847 and 6,585 per year, respectively. With a current cost for WES of approximately USD1,200, we concluded that performing WES could be cost effective, even in countries with limited resources, as it provides the option for genetic counseling in affected families with an ultimate reduction of overall financial burden to both parents and health care system.

Clinical Implications of the Genetic Architecture of Dilated Cardiomyopathy

PURPOSE OF REVIEW

Dilated cardiomyopathy (DCM) frequently involves an underlying genetic etiology, but the clinical approach for genetic diagnosis and application of results in clinical practice can be complex.

RECENT FINDINGS

International sequence databases described the landscape of genetic variability across populations, which informed guidelines for the interpretation of DCM gene variants. New evidence indicates that loss-of-function mutations in filamin C (FLNC) contribute to DCM and portend high risk of ventricular arrhythmia. A clinical framework aids in referring patients for DCM genetic testing and applying results to patient care. Results of genetic testing can change medical management, particularly in a subset of genes that increase risk for life-threatening ventricular arrhythmias, and can influence decisions for defibrillator therapy. Clinical screening and cascade genetic testing of family members should be diligently pursued to identify those at risk of developing DCM.

The Biological Significance of Multi-copy Regions and Their Impact on Variant Discovery

Identification of genetic variants via high-throughput sequencing (HTS) technologies has been essential for both fundamental and clinical studies. However, to what extent the genome sequence composition affects variant calling remains unclear. In this study, we identified 63,897 multi-copy sequences (MCSs) with a minimum length of 300 bp, each of which occurs at least twice in the human genome. The 151,749 genomic loci (multi-copy regions, or MCRs) harboring these MCSs account for 1.98% of the genome and are distributed unevenly across chromosomes. MCRs containing the same MCS tend to be located on the same chromosome. Gene Ontology (GO) analyses revealed that 3800 genes whose UTRs or exons overlap with MCRs are enriched for Golgi-related cellular component terms and various enzymatic activities in the GO biological function category. MCRs are also enriched for loci that are sensitive to neocarzinostatin-induced double-strand breaks. Moreover, genetic variants discovered by genome-wide association studies and recorded in dbSNP are significantly underrepresented in MCRs. Using simulated HTS datasets, we show that false variant discovery rates are significantly higher in MCRs than in other genomic regions. These results suggest that extra caution must be taken when identifying genetic variants in the MCRs via HTS technologies.

New technologies and applications in infant B cell immunology

The human immune system changes dramatically with age, and early life exposures to pathogens and environmental antigens begin the formation of immune memory which influences subsequent responses later in life. To study infant immunity, sample-sparing experimental methods that extract maximal data from small samples of blood or other tissues are needed; fortunately, recent developments in high-throughput sequencing and multiplexed labeling and measurement of markers on cells are well-suited to these tasks. Here, we review some recent studies of infant immune responses to infectious disease, highlighting similarities and differences between infants and adults, and identifying important questions for future research. Recent clinical trials in food allergy have revealed the critical role of immunological events in the first year of life that determine an individual's risk of developing peanut allergy; these also warrant thorough evaluation using the new immune monitoring tools.

Enabling precision medicine via standard communication of HTS provenance, analysis, and results

A personalized approach based on a patient's or pathogen’s unique genomic sequence is the foundation of precision medicine. Genomic findings must be robust and reproducible, and experimental data capture should adhere to findable, accessible, interoperable, and reusable (FAIR) guiding principles. Moreover, effective precision medicine requires standardized reporting that extends beyond wet-lab procedures to computational methods. The BioCompute framework (https://w3id.org/biocompute/1.3.0) enables standardized reporting of genomic sequence data provenance, including provenance domain, usability domain, execution domain, verification kit, and error domain. This framework facilitates communication and promotes interoperability. Bioinformatics computation instances that employ the BioCompute framework are easily relayed, repeated if needed, and compared by scientists, regulators, test developers, and clinicians. Easing the burden of performing the aforementioned tasks greatly extends the range of practical application. Large clinical trials, precision medicine, and regulatory submissions require a set of agreed upon standards that ensures efficient communication and documentation of genomic analyses. The BioCompute paradigm and the resulting BioCompute Objects (BCOs) offer that standard and are freely accessible as a GitHub organization (https://github.com/biocompute-objects) following the “Open-Stand.org principles for collaborative open standards development.” With high-throughput sequencing (HTS) studies communicated using a BCO, regulatory agencies (e.g., Food and Drug Administration [FDA]), diagnostic test developers, researchers, and clinicians can expand collaboration to drive innovation in precision medicine, potentially decreasing the time and cost associated with next-generation sequencing workflow exchange, reporting, and regulatory reviews.

This Community Page article presents a communication standard for the provenance of high-throughput sequencing data; a BioCompute Object (BCO) can serve as a history of what was computed, be used as part of a validation process, or provide clarity and transparency of an experimental process to collaborators.

Cost of cancer diagnosis using next-generation sequencing targeted gene panels in routine practice: a nationwide French study

It is currently unclear if next-generation sequencing (NGS) technologies can be implemented in the diagnosis setting at an affordable cost. The aim of this study was to measure the total cost of performing NGS in clinical practice in France, in both germline and somatic cancer genetics.The study was performed on 15 French representative cancer molecular genetics laboratories performing NGS panels' tests. The production cost was estimated using a micro-costing method with resources consumed collected in situ in each laboratory from a healthcare provider perspective. In addition, we used a top-down methodology for specific post-sequencing steps including bioinformatics, technical validation, and biological validation. Additional non-specific costs were also included. Costs were detailed per step of the process (from the pre-analytical phase to delivery of results), and per cost driver (consumables, staff, equipment, maintenance, overheads). Sensitivity analyses were performed.The mean total cost of NGS for targeted gene panels was estimated to 607€ (±207) in somatic genetics and 550€ (±140) in germline oncogenetic analysis. Consumables were the highest cost driver of the sequencing process. The sensitivity analysis showed that a 25% reduction of consumables resulted in a 15% decrease in total NGS cost in somatic genetics, and 13% in germline analysis. Additional costs accounted for 30-32% of the total NGS costs.Beyond cost assessment considerations, the diffusion of NGS technologies will raise questions about their efficiency when compared to more targeted approaches, and their added value in a context of routine diagnosis.

Precision monitoring of immunotherapies in solid organ and hematopoietic stem cell transplantation

Pharmacological immunotherapies are a key component of post-transplant therapy in solid-organ and hematopoietic stem cell transplantation. In current clinical practice, immunotherapies largely follow a one-size fits all approach, leaving a large portion of transplant recipients either over- or under-immunosuppressed, and consequently at risk of infections or immune-mediated complications. Our goal here is to review recent and rapid advances in precision and genomic medicine approaches to monitoring of post-transplant immunotherapies. We will discuss recent advances in precision measurements of pharmacological immunosuppression, measurements of the plasma and gut microbiome, strategies to monitor for allograft injury and post-transplant malignancies via circulating cell-free DNA, and comprehensive measurements of the B and T cell immune cell repertoire.

A sensitive DNA capacitive biosensor using interdigitated electrodes

This paper presents a label-free affinity-based capacitive biosensor using interdigitated electrodes. Using an optimized process of DNA probe preparation to minimize the effect of contaminants in commercial thiolated DNA probe, the electrode surface was functionalized with the 24-nucleotide DNA probes based on the West Nile virus sequence (Kunjin strain). The biosensor has the ability to detect complementary DNA fragments with a detection limit down to 20 DNA target molecules (1.5aM range), making it suitable for a practical point-of-care (POC) platform for low target count clinical applications without the need for amplification. The reproducibility of the biosensor detection was improved with efficient covalent immobilization of purified single-stranded DNA probe oligomers on cleaned gold microelectrodes. In addition to the low detection limit, the biosensor showed a dynamic range of detection from 1µL-1 to 105µL-1 target molecules (20 to 2 million targets), making it suitable for sample analysis in a typical clinical application environment. The binding results presented in this paper were validated using fluorescent oligomers.

Gold Nanoparticles for Diagnostics: Advances towards Points of Care

The remarkable physicochemical properties of gold nanoparticles (AuNPs) have prompted developments in the exploration of biomolecular interactions with AuNP-containing systems, in particular for biomedical applications in diagnostics. These systems show great promise in improving sensitivity, ease of operation and portability. Despite this endeavor, most platforms have yet to reach maturity and make their way into clinics or points of care (POC). Here, we present an overview of emerging and available molecular diagnostics using AuNPs for biomedical sensing that are currently being translated to the clinical setting.

Immunohistochemical correlates of TP53 somatic mutations in cancer

Despite controversy on the correlation between p53 accumulation and TP53 mutational status, immunohistochemical (IHC) detection of overexpressed protein has long been used as a surrogate method for mutation analysis. The aim of our study was to characterise the IHC expression features of TP53 somatic mutations and define their occurrence in human cancers. A large-scale database analysis was conducted in the IARC TP53 Database (R17); 7878 mutations with IHC features were retrieved representing 60 distinct tumour sites. The majority of the alterations were immunopositive (p <0.001). Sex was known for 4897 mutations showing a female dominance (57.2%) and females carrying negative mutations were significantly younger. TP53 mutations were divided into three IHC groups according to mutation frequency and IHC positivity. Each group had female dominance. Among the IHC groups, significant correlations were observed with age at diagnosis in breast, bladder, liver, haematopoietic system and head & neck cancers. An increased likelihood of false negative IHC associated with rare nonsense mutations was observed in certain tumour sites. Our study demonstrates that p53 immunopositivity largely correlates with TP53 mutational status but expression is absent in certain mutation types.Besides, describing the complex IHC expression of TP53 somatic mutations, our results reveal some caveats for the diagnostic practice.

Streaming algorithms for identification of pathogens and antibiotic resistance potential from real-time MinION(TM) sequencing

The recently introduced Oxford Nanopore MinION platform generates DNA sequence data in real-time. This has great potential to shorten the sample-to-results time and is likely to have benefits such as rapid diagnosis of bacterial infection and identification of drug resistance. However, there are few tools available for streaming analysis of real-time sequencing data. Here, we present a framework for streaming analysis of MinION real-time sequence data, together with probabilistic streaming algorithms for species typing, strain typing and antibiotic resistance profile identification. Using four culture isolate samples, as well as a mixed-species sample, we demonstrate that bacterial species and strain information can be obtained within 30 min of sequencing and using about 500 reads, initial drug-resistance profiles within two hours, and complete resistance profiles within 10 h. While strain identification with multi-locus sequence typing required more than 15x coverage to generate confident assignments, our novel gene-presence typing could detect the presence of a known strain with 0.5x coverage. We also show that our pipeline can process over 100 times more data than the current throughput of the MinION on a desktop computer.

The healthy human microbiome

Humans are virtually identical in their genetic makeup, yet the small differences in our DNA give rise to tremendous phenotypic diversity across the human population. By contrast, the metagenome of the human microbiome—the total DNA content of microbes inhabiting our bodies—is quite a bit more variable, with only a third of its constituent genes found in a majority of healthy individuals. Understanding this variability in the “healthy microbiome” has thus been a major challenge in microbiome research, dating back at least to the 1960s, continuing through the Human Microbiome Project and beyond. Cataloguing the necessary and sufficient sets of microbiome features that support health, and the normal ranges of these features in healthy populations, is an essential first step to identifying and correcting microbial configurations that are implicated in disease. Toward this goal, several population-scale studies have documented the ranges and diversity of both taxonomic compositions and functional potentials normally observed in the microbiomes of healthy populations, along with possible driving factors such as geography, diet, and lifestyle. Here, we review several definitions of a ‘healthy microbiome’ that have emerged, the current understanding of the ranges of healthy microbial diversity, and gaps such as the characterization of molecular function and the development of ecological therapies to be addressed in the future.

Deep sequencing and human antibody repertoire analysis

In the past decade, high-throughput DNA sequencing (HTS) methods and improved approaches for isolating antigen-specific B cells and their antibody genes have been applied in many areas of human immunology. This work has greatly increased our understanding of human antibody repertoires and the specific clones responsible for protective immunity or immune-mediated pathogenesis. Although the principles underlying selection of individual B cell clones in the intact immune system are still under investigation, the combination of more powerful genetic tracking of antibody lineage development and functional testing of the encoded proteins promises to transform therapeutic antibody discovery and optimization. Here, we highlight recent advances in this fast-moving field.

Pyrosequencing on a glass surface

We demonstrate the use of open-surface microfluidics to sequence DNA by pyrosequencing at the plain hydrophobically coated surface of a microscope glass cover slip. This method offers significant advantages in terms of instrument size, simplicity, disposability, and functional integration, particularly when combined with the broad and flexible capabilities of open-surface microfluidics. The DNA was incubated on superparamagnetic particles and placed on a hydrophobically coated glass substrate. The particles with bound DNA were moved using magnetic force through microliter-sized droplets covered with mineral oil to prevent water evaporation from the droplets. These droplets served as reaction "stations" performing pyrosequencing as well as washing stations. The resequencing protocol with 34-mer single-stranded DNA (ssDNA) was used to determine the reaction performance. The de novo sequencing was performed with 51-mer and 81-mer ssDNA. The method can be integrated with previously shown sample preparation and PCR into a single sample-to-answer system on a plain glass surface.

High-Throughput DNA Sequencing Analysis of Antibody Repertoires

New high-throughput DNA sequencing (HTS) technologies developed in the past decade have begun to be applied to the study of the complex gene rearrangements that encode human antibodies. This article first reviews the genetic features of Ig loci and the HTS technologies that have been applied to human repertoire studies, then discusses key choices for experimental design and data analysis in these experiments and the insights gained in immunological and infectious disease studies with the use of these approaches.

Assessing the Costs and Cost-Effectiveness of Genomic Sequencing

Despite dramatic drops in DNA sequencing costs, concerns are great that the integration of genomic sequencing into clinical settings will drastically increase health care expenditures. This commentary presents an overview of what is known about the costs and cost-effectiveness of genomic sequencing. We discuss the cost of germline genomic sequencing, addressing factors that have facilitated the decrease in sequencing costs to date and anticipating the factors that will drive sequencing costs in the future. We then address the cost-effectiveness of diagnostic and pharmacogenomic applications of genomic sequencing, with an emphasis on the implications for secondary findings disclosure and the integration of genomic sequencing into general patient care. Throughout, we ground the discussion by describing efforts in the MedSeq Project, an ongoing randomized controlled clinical trial, to understand the costs and cost-effectiveness of integrating whole genome sequencing into cardiology and primary care settings.

The long tail and rare disease research: the impact of next-generation sequencing for rare Mendelian disorders

There are an estimated 6000-8000 rare Mendelian diseases that collectively affect 30 million individuals in the United States. The low incidence and prevalence of these diseases present significant challenges to improving diagnostics and treatments. Next-generation sequencing (NGS) technologies have revolutionized research of rare diseases. This article will first comment on the effectiveness of NGS through the lens of long-tailed economics. We then provide an overview of recent developments and challenges of NGS-based research on rare diseases. As the quality of NGS studies improve and the cost of sequencing decreases, NGS will continue to make a significant impact on the study of rare diseases moving forward.

High-Throughput Genetic Testing for Thrombotic Microangiopathies and C3 Glomerulopathies

The thrombotic microangiopathies (TMAs) and C3 glomerulopathies (C3Gs) include a spectrum of rare diseases such as atypical hemolytic uremic syndrome, thrombotic thrombocytopenic purpura, C3GN, and dense deposit disease, which share phenotypic similarities and underlying genetic commonalities. Variants in several genes contribute to the pathogenesis of these diseases, and identification of these variants may inform the diagnosis and treatment of affected patients. We have developed and validated a comprehensive genetic panel that screens all exons of all genes implicated in TMA and C3G. The closely integrated pipeline implemented includes targeted genomic enrichment, massively parallel sequencing, bioinformatic analysis, and a multidisciplinary conference to analyze identified variants in the context of each patient's specific phenotype. Herein, we present our 1-year experience with this panel, during which time we studied 193 patients. We identified 17 novel and 74 rare variants, which we classified as pathogenic (11), likely pathogenic (12), and of uncertain significance (68). Compared with controls, patients with C3G had a higher frequency of rare and novel variants in C3 convertase (C3 and CFB) and complement regulator (CFH, CFI, CFHR5, and CD46) genes (P<0.05). In contrast, patients with TMA had an increase in rare and novel variants only in complement regulator genes (P<0.01), a distinction consistent with differing sites of complement dysregulation in these two diseases. In summary, we were able to provide a positive genetic diagnosis in 43% and 41% of patients carrying the clinical diagnosis of C3G and TMA, respectively.

Defining "mutation" and "polymorphism" in the era of personal genomics

BACKGROUND

The growing advances in DNA sequencing tools have made analyzing the human genome cheaper and faster. While such analyses are intended to identify complex variants, related to disease susceptibility and efficacy of drug responses, they have blurred the definitions of mutation and polymorphism.

DISCUSSION

In the era of personal genomics, it is critical to establish clear guidelines regarding the use of a reference genome. Nowadays DNA variants are called as differences in comparison to a reference. In a sequencing project Single Nucleotide Polymorphisms (SNPs) and DNA mutations are defined as DNA variants detectable in >1 % or <1 % of the population, respectively. The alternative use of the two terms mutation or polymorphism for the same event (a difference as compared with a reference) can lead to problems of classification. These problems can impact the accuracy of the interpretation and the functional relationship between a disease state and a genomic sequence. We propose to solve this nomenclature dilemma by defining mutations as DNA variants obtained in a paired sequencing project including the germline DNA of the same individual as a reference. Moreover, the term mutation should be accompanied by a qualifying prefix indicating whether the mutation occurs only in somatic cells (somatic mutation) or also in the germline (germline mutation). We believe this distinction in definition will help avoid confusion among researchers and support the practice of sequencing the germline and somatic tissues in parallel to classify the DNA variants thus defined as mutations.

Genomics in the clinic: ethical and policy challenges in clinical next-generation sequencing programs at early adopter USA institutions

Next-generation sequencing (NGS) technologies are poised to revolutionize clinical diagnosis and treatment, but raise significant ethical and policy challenges. This review examines NGS program challenges through a synthesis of published literature, website and conference presentation content, and interviews at early-adopting institutions in the USA. Institutions are proactively addressing policy challenges related to the management and technical aspects of program development. However, ethical challenges related to patient-related aspects have not been fully addressed. These complex challenges present opportunities to develop comprehensive and standardized regulations across programs. Understanding the strengths, weaknesses and current practices of evolving NGS program approaches are important considerations for institutions developing NGS services, policymakers regulating or funding NGS programs and physicians and patients considering NGS services.

Characterizing immune repertoires by high throughput sequencing: strategies and applications

As the key cellular effectors of adaptive immunity, T and B lymphocytes utilize specialized receptors to recognize, respond to, and neutralize a diverse array of extrinsic threats. These receptors (immunoglobulins in B lymphocytes, T cell receptors in T lymphocytes) are incredibly variable, the products of specialized genetic diversification mechanisms that generate complex lymphocyte repertoires with extensive collections of antigen specificities. Recent advances in high throughput sequencing (HTS) technologies have transformed our ability to examine antigen receptor repertoires at single nucleotide, and more recently, single cell, resolution. Here we review current approaches to examining antigen receptor repertoires by HTS, and discuss inherent biological and technical challenges. We further describe emerging applications of this powerful methodology for exploring the adaptive immune system.

Performance of amplicon-based next generation DNA sequencing for diagnostic gene mutation profiling in oncopathology

PURPOSE

Next generation DNA sequencing (NGS) holds promise for diagnostic applications, yet implementation in routine molecular pathology practice requires performance evaluation on DNA derived from routine formalin-fixed paraffin-embedded (FFPE) tissue specimens. The current study presents a comprehensive analysis of TruSeq Amplicon Cancer Panel-based NGS using a MiSeq Personal sequencer (TSACP-MiSeq-NGS) for somatic mutation profiling.

METHODS

TSACP-MiSeq-NGS (testing 212 hotspot mutation amplicons of 48 genes) and a data analysis pipeline were evaluated in a retrospective learning/test set approach (n = 58/n = 45 FFPE-tumor DNA samples) against 'gold standard' high-resolution-melting (HRM)-sequencing for the genes KRAS, EGFR, BRAF and PIK3CA. Next, the performance of the validated test algorithm was assessed in an independent, prospective cohort of FFPE-tumor DNA samples (n = 75).

RESULTS

In the learning set, a number of minimum parameter settings was defined to decide whether a FFPE-DNA sample is qualified for TSACP-MiSeq-NGS and for calling mutations. The resulting test algorithm revealed 82% (37/45) compliance to the quality criteria and 95% (35/37) concordant assay findings for KRAS, EGFR, BRAF and PIK3CA with HRM-sequencing (kappa = 0.92; 95% CI = 0.81-1.03) in the test set. Subsequent application of the validated test algorithm to the prospective cohort yielded a success rate of 84% (63/75), and a high concordance with HRM-sequencing (95% (60/63); kappa = 0.92; 95% CI = 0.84-1.01). TSACP-MiSeq-NGS detected 77 mutations in 29 additional genes.

CONCLUSION

TSACP-MiSeq-NGS is suitable for diagnostic gene mutation profiling in oncopathology.

A Balanced Look at the Implications of Genomic (and Other "Omics") Testing for Disease Diagnosis and Clinical Care

The tremendous increase in DNA sequencing capacity arising from the commercialization of "next generation" instruments has opened the door to innumerable routes of investigation in basic and translational medical science. It enables very large data sets to be gathered, whose interpretation and conversion into useful knowledge is only beginning. A challenge for modern healthcare systems and academic medical centers is to apply these new methods for the diagnosis of disease and the management of patient care without unnecessary delay, but also with appropriate evaluation of the quality of data and interpretation, as well as the clinical value of the insights gained. Most critically, the standards applied for evaluating these new laboratory data and ensuring that the results and their significance are clearly communicated to patients and their caregivers should be at least as rigorous as those applied to other kinds of medical tests. Here, we present an overview of conceptual and practical issues to be considered in planning for the integration of genomic methods or, in principle, any other type of "omics" testing into clinical care.

Uncovering the molecular networks in periodontitis

Periodontitis is a complex immune-inflammatory disease that results from a preestablished infection in gingiva, mainly due to Gram-negative bacteria that colonize deeper in gingival sulcus and latter periodontal pocket. Host inflammatory and immune responses have both protective and destructive roles. Although cytokines, prostaglandins, and proteases struggle against microbial burden, these molecules promote connective tissue loss and alveolar bone resorption, leading to several histopathological changes, namely destruction of periodontal ligament, deepening of periodontal pocket, and bone loss, which can converge to attain tooth loss. Despite the efforts of genomics, transcriptomics, proteomics/peptidomics, and metabolomics, there is no available biomarker for periodontitis diagnosis, prognosis, and treatment evaluation, which could assist on the established clinical evaluation. Nevertheless, some genes, transcripts, proteins and metabolites have already shown a different expression in healthy subjects and in patients. Though, so far, 'omics approaches only disclosed the host inflammatory response as a consequence of microbial invasion in periodontitis and the diagnosis in periodontitis still relies on clinical parameters, thus a molecular tool for assessing periodontitis lacks in current dental medicine paradigm. Saliva and gingival crevicular fluid have been attracting researchers due to their diagnostic potential, ease, and noninvasive nature of collection. Each one of these fluids has some advantages and disadvantages that are discussed in this review.

Unifying immunology with informatics and multiscale biology

The immune system is a highly complex and dynamic system. Historically, the most common scientific and clinical practice has been to evaluate its individual components. This kind of approach cannot always expose the interconnecting pathways that control immune-system responses and does not reveal how the immune system works across multiple biological systems and scales. High-throughput technologies can be used to measure thousands of parameters of the immune system at a genome-wide scale. These system-wide surveys yield massive amounts of quantitative data that provide a means to monitor and probe immune-system function. New integrative analyses can help synthesize and transform these data into valuable biological insight. Here we review some of the computational analysis tools for high-dimensional data and how they can be applied to immunology.

A novel high-throughput irradiator for in vitro radiation sensitivity bioassays

This paper describes the development and characterization of a fully automated in vitro cell irradiator using an electronic brachytherapy source to perform radiation sensitivity bioassays. This novel irradiator allows complex variable dose and dose rate schemes to be delivered to multiple wells of 96-well culture plates used in standard biological assays. The Xoft Axxent® eBx™ was chosen as the x-ray source due to its ability to vary tube current up to 300 µA for a 50 kVp spectrum using clinical surface applicators. Translation of the multiwell plate across the fixed radiation field is achieved using a precision motor driven computer controlled positioning system. A series of measurements was performed to characterize dosimetric performance of the system. Measurements have shown that the radiation output measured with an end window ionization chamber is stable between operating currents of 50-300 µA. In addition, radiochromic film was used to characterize the field flatness and symmetry. The average field flatness in the in-plane and cross-plane direction was 2.9 ± 1.0% and 4.0 ± 1.7%, respectively. The average symmetry in the in-plane and cross-plane direction was 1.8 ± 0.9% and 1.6 ± 0.5%, respectively. The optimal focal spot resolution at the cellular plane was determined by measuring sequential irradiations on radiochromic film for three different well spacing schemes. It was determined that the current system can irradiate every other well with negligible impact on the radiation field characteristics. Finally, a performance comparison between this system and a common cabinet irradiator is presented.

Genomic medicine: a decade of successes, challenges, and opportunities

Genomic medicine--an aspirational term 10 years ago--is gaining momentum across the entire clinical continuum from risk assessment in healthy individuals to genome-guided treatment in patients with complex diseases. We review the latest achievements in genome research and their impact on medicine, primarily in the past decade. In most cases, genomic medicine tools remain in the realm of research, but some tools are crossing over into clinical application, where they have the potential to markedly alter the clinical care of patients. In this State of the Art Review, we highlight notable examples including the use of next-generation sequencing in cancer pharmacogenomics, in the diagnosis of rare disorders, and in the tracking of infectious disease outbreaks. We also discuss progress in dissecting the molecular basis of common diseases, the role of the host microbiome, the identification of drug response biomarkers, and the repurposing of drugs. The significant challenges of implementing genomic medicine are examined, along with the innovative solutions being sought. These challenges include the difficulty in establishing clinical validity and utility of tests, how to increase awareness and promote their uptake by clinicians, a changing regulatory and coverage landscape, the need for education, and addressing the ethical aspects of genomics for patients and society. Finally, we consider the future of genomics in medicine and offer a glimpse of the forces shaping genomic medicine, such as fundamental shifts in how we define disease, how medicine is delivered to patients, and how consumers are managing their own health and affecting change.

Improved coverage and accuracy with strand-conserving sequence enrichment

Targeted next-generation sequencing is becoming a common tool in the molecular diagnostic laboratory. However, currently available methods to enrich for regions of interest in the DNA sequence suffer from drawbacks such as high cost, complex protocols, lack of clinical-level accuracy and uneven target coverage. A target-enrichment approach using complementary long padlock probes described in a recent article significantly improves on previous methods in most of these areas.

See related Research: http://genomemedicine.com/content/5/5/50

Mutascope: sensitive detection of somatic mutations from deep amplicon sequencing

Summary: We present Mutascope, a sequencing analysis pipeline specifically developed for the identification of somatic variants present at low-allelic fraction from high-throughput sequencing of amplicons from matched tumor-normal specimen. Using datasets reproducing tumor genetic heterogeneity, we demonstrate that Mutascope has a higher sensitivity and generates fewer false-positive calls than tools designed for shotgun sequencing or diploid genomes.

Availability: Freely available on the web at http://sourceforge.net/projects/mutascope/.

Contact:oharismendy@ucsd.edu

Supplementary information:Supplementary data are available at Bioinformatics online.