Targeted Next‐Generation Sequencing can Replace Sanger Sequencing in Clinical Diagnostics

Mutation detection through exome sequencing allows simultaneous analysis of all coding sequences of genes. However, it cannot yet replace Sanger sequencing (SS) in diagnostics because of incomplete representation and coverage of exons leading to missing clinically relevant mutations. Targeted next‐generation sequencing (NGS), in which a selected fraction of genes is sequenced, may circumvent these shortcomings. We aimed to determine whether the sensitivity and specificity of targeted NGS is equal to those of SS. We constructed a targeted enrichment kit that includes 48 genes associated with hereditary cardiomyopathies. In total, 84 individuals with cardiomyopathies were sequenced using 151 bp paired‐end reads on an Illumina MiSeq sequencer. The reproducibility was tested by repeating the entire procedure for five patients. The coverage of ≥30 reads per nucleotide, our major quality criterion, was 99% and in total ～21,000 variants were identified. Confirmation with SS was performed for 168 variants (155 substitutions, 13 indels). All were confirmed, including a deletion of 18 bp and an insertion of 6 bp. The reproducibility was nearly 100%. We demonstrate that targeted NGS of a disease‐specific subset of genes is equal to the quality of SS and it can therefore be reliably implemented as a stand‐alone diagnostic test.     

Next‐generation sequencing: ready for the clinics?

Next-generation sequencing (NGS) has transformed genomic research by decreasing the cost of sequencing and increasing the throughput. Now, the focus is on using NGS technology for diagnostics and therapeutics. In this review, we discuss the possible clinical applications of NGS and the potential of some of the current systems to transition to the clinic. Clinical use of NGS technologies will enable the identification of causative mutations for rare genetic disorders through whole-genome or targeted genome resequencing, rapid pathogen screening and cancer diagnosis along with the identification of appropriate therapy. Routine clinical use of NGS technologies is appealing, but mandates high accuracy, simple assays, small inexpensive instruments, flexible throughput, short run times and most importantly, easy data analysis as well as interpretation. A number of NGS systems launched recently have least some of these characteristics, namely, small instruments, flexible throughput and short run time, but still face a few challenges. Moreover, simplified data analysis tools will need to be developed to minimize the requirement of sophisticated bioinformatics support in clinics. In summary, for successful transition of NGS to clinic, a sustained collaboration between research labs, clinical practitioners and vendors offering sequencing based genetic tests is required.     

Integrating next‐generation sequencing into the diagnostic testing of inherited cancer predisposition

The clinical application of next‐generation sequencing (NGS) as a diagnostic tool has become increasingly evident. The coupling of NGS technologies with new genomic sequence enrichment methods has made the sequencing of panels of target genes technically feasible, at the same time as making such an approach cost‐effective for diagnostic applications. In this article, we discuss recent studies that have applied NGS in the diagnostic setting in relation to hereditary cancer.     

GEnomes Management Application (GEM.app): A New Software Tool for Large‐Scale Collaborative Genome Analysis

Novel genes are now identified at a rapid pace for many Mendelian disorders, and increasingly, for genetically complex phenotypes. However, new challenges have also become evident: (1) effectively managing larger exome and/or genome datasets, especially for smaller labs; (2) direct hands‐on analysis and contextual interpretation of variant data in large genomic datasets; and (3) many small and medium‐sized clinical and research‐based investigative teams around the world are generating data that, if combined and shared, will significantly increase the opportunities for the entire community to identify new genes. To address these challenges, we have developed GEnomes Management Application (GEM.app), a software tool to annotate, manage, visualize, and analyze large genomic datasets ( https://genomics.med.miami.edu/">https://genomics.med.miami.edu/">https://genomics.med.miami.edu/ ). GEM.app currently contains ～1,600 whole exomes from 50 different phenotypes studied by 40 principal investigators from 15 different countries. The focus of GEM.app is on user‐friendly analysis for nonbioinformaticians to make next‐generation sequencing data directly accessible. Yet, GEM.app provides powerful and flexible filter options, including single family filtering, across family/phenotype queries, nested filtering, and evaluation of segregation in families. In addition, the system is fast, obtaining results within 4 sec across ～1,200 exomes. We believe that this system will further enhance identification of genetic causes of human disease.     

Plasma nucleic acid analysis by massively parallel sequencing: pathological insights and diagnostic implications

Over the past 15 years there has been increasing interest in the biology and diagnostic applications of circulating DNA in the plasma of human subjects. In particular, DNA from a fetus, a tumour, a transplanted organ and injured tissues has been found in the plasma of pregnant women, cancer patients, transplant recipients and patients suffering from multiple pathologies, respectively. The advent of massively parallel sequencing has given us a quantitative and powerful tool for studying circulating DNA on a genome-wide level. Using this approach, fetal chromosomal aneuploidies can be robustly detected using maternal plasma. Furthermore, a genome-wide genetic map of a fetus can also be constructed using this approach. This method has also allowed one to identify tumour-associated chromosomal translocations, which can then be detected in plasma. The direct application of massively parallel sequencing to the serum of cancer patients has also allowed quantitative aberrations that are associated with malignancy to be detected in serum. The use of massively parallel sequencing on the plasma of transplantation recipients has opened up an approach for detecting rejection. The application of circulating DNA sequencing has also opened up a new method for elucidating the quantitative aberration of circulating DNA in many pathological conditions. Such developments would provide new modalities for molecular diagnostics and would improve our understanding of the biology of circulating nucleic acids.     

Is gene panel sequencing more efficient than clinical‐based gene sequencing to diagnose autoinflammatory diseases? A randomized study

The aim of this study was to compare the effectiveness of the gene‐panel next‐generation sequencing (NGS) strategy versus the clinical‐based gene Sanger sequencing for the genetic diagnosis of autoinflammatory diseases (AIDs). Secondary goals were to describe the gene and mutation distribution in AID patients and to evaluate the impact of the genetic report on the patient’s medical care and treatment. Patients with AID symptoms were enrolled prospectively and randomized to two arms, NGS (n = 99) (32–55 genes) and Sanger sequencing (n = 197) (one to four genes). Genotypes were classified as ‘consistent/confirmatory’, ‘uncertain significance’ or ‘non‐contributory’. The proportion of patients with pathogenic genotypes concordant with the AID phenotype (consistent/confirmatory) was significantly higher with NGS than Sanger sequencing [10 of 99 (10·1%) versus eight of 197 (4·1%)]. MEFV, ADA2 and MVK were the most represented genes with a consistent/confirmed genotype, whereas MEFV, NLRP3, NOD2 and TNFRSF1A were found in the ‘uncertain significance’ genotypes. Six months after the genetic report was sent, 54 of 128 (42·2%) patients had received effective treatment for their symptoms; 13 of 128 (10·2%) had started treatment after the genetic study. For 59 of 128 (46%) patients, the results had an impact on their overall care, independent of sequencing group and diagnostic conclusion. Targeted NGS improved the diagnosis and global care of patients with AIDs.     

Clinical Applications of Next‐Generation Sequencing: The 2013 Human Genome Variation Society Scientific Meeting

Next‐generation sequencing (NGS) has significantly contributed to the transformation of genomic research by providing access to the genome for analysis, by significantly decreasing the sequencing costs and increasing the throughput. The next goal is to exploit this powerful technology in the clinic, namely for diagnostics and therapeutics. The 2013 annual meeting of the Human Genome Variation Society, held in Paris, France, provided a forum to discuss possible clinical applications of NGS, the potential of some of the current NGS systems to transition to the clinic, the identification of causative mutations for rare genetic disorders through whole‐genome or targeted genome resequencing, the application of NGS for family genomics, and NGS data analysis tools.     

NEUROINFORMATICS IN MODEL ORGANISMS

Since its first availability in 2009, the next-generation sequencing (NGS) has been proved to be a powerful tool in identifying disease-associated variants in many neurological diseases, such as spinocerebellar ataxias, Charcot–Marie–Tooth disease, hereditary spastic paraplegia, and amyotrophic lateral sclerosis. Whole exome sequencing and whole genome sequencing are efficient for identifying variants in novel or unexpected genes responsible for inherited diseases, whereas targeted sequencing is useful in detecting variants in previously known disease-associated genes. The trove of genetic data yielded by NGS has made a significant impact on the clinical diagnoses while contributing hugely on the discovery of molecular pathomechanisms underlying these diseases. Nonetheless, elucidation of the pathogenic roles of the variants identified by NGS is challenging. Establishment of consensus guidelines and development of public genomic/phenotypic databases are thus vital to facilitate data sharing and validation.