Next generation sequencing for clinical diagnostics: Five year experience of an academic laboratory.

Clinical laboratories have adopted next generation sequencing (NGS) as a gold standard for the diagnosis of hereditary disorders because of its analytic accuracy, high throughput, and potential for cost-effectiveness. We describe the implementation of a single broad-based NGS sequencing assay to meet the genetic testing needs at the University of Minnesota. A single hybrid capture library preparation was used for each test ordered, data was informatically blinded to clinically-ordered genes, and identified variants were reviewed and classified by genetic counselors and molecular pathologists. We performed 2509 sequencing tests from August 2012 till December 2017. The diagnostic yield has remained steady at 25%, but the number of variants of uncertain significance (VUS) included in a patient report decreased over time with 50% of the patient reports including at least one VUS in 2012 and only 22% of the patient reports reporting a VUS in 2017 (p = .002). Among the various clinical specialties, the diagnostic yield was highest in dermatology (60% diagnostic yield) and ophthalmology (42% diagnostic yield) while the diagnostic yield was lowest in gastrointestinal diseases and pulmonary diseases (10% detection yield in both specialties). Deletion/duplication analysis was also implemented in a subset of panels ordered, with 9% of samples having a diagnostic finding using the deletion/duplication analysis. We have demonstrated the feasibility of this broad-based NGS platform to meet the needs of our academic institution by aggregating a sufficient sample volume from many individually rare tests and providing a flexible ordering for custom, patient-specific panels.

Comprehensive Functional Analysis of the Enterococcus faecalis Core Genome Using an Ordered, Sequence-Defined Collection of Insertional Mutations in Strain OG1RF.

Enterococcus faecalis is a common commensal bacterium in animal gastrointestinal (GI) tracts and a leading cause of opportunistic infections of humans in the modern health care setting. E. faecalis OG1RF is a plasmid-free strain that contains few mobile elements yet retains the robust survival characteristics, intrinsic antibiotic resistance, and virulence traits characteristic of most E. faecalis genotypes. To facilitate interrogation of the core enterococcal genetic determinants for competitive fitness in the GI tract, biofilm formation, intrinsic antimicrobial resistance, and survival in the environment, we generated an arrayed, sequence-defined set of chromosomal transposon insertions in OG1RF. We used an orthogonal pooling strategy in conjunction with Illumina sequencing to identify a set of mutants with unique, single Himar-based transposon insertions. The mutants contained insertions in 1,926 of 2,651 (72.6%) annotated open reading frames and in the majority of hypothetical protein-encoding genes and intergenic regions greater than 100 bp in length, which could encode small RNAs. As proof of principle of the usefulness of this arrayed transposon library, we created a minimal input pool containing 6,829 mutants chosen for maximal genomic coverage and used an approach that we term SMarT (sequence-defined mariner technology) transposon sequencing (TnSeq) to identify numerous genetic determinants of bile resistance in E. faecalis OG1RF. These included several genes previously associated with bile acid resistance as well as new loci. Our arrayed library allows functional screening of a large percentage of the genome with a relatively small number of mutants, reducing potential effects of bottlenecking, and enables immediate recovery of mutants following competitions. IMPORTANCE The robust ability of Enterococcus faecalis to survive outside the host and to spread via oral-fecal transmission and its high degree of intrinsic and acquired antimicrobial resistance all complicate the treatment of hospital-acquired enterococcal infections. The conserved E. faecalis core genome serves as an important genetic scaffold for evolution of this bacterium in the modern health care setting and also provides interesting vaccine and drug targets. We used an innovative pooling/sequencing strategy to map a large collection of arrayed transposon insertions in E. faecalis OG1RF and generated an arrayed library of defined mutants covering approximately 70% of the OG1RF genome. Then, we performed high-throughput transposon sequencing experiments using this library to determine core genomic determinants of bile resistance in OG1RF. This collection is a valuable resource for comprehensive, functional enterococcal genomics using both traditional and high-throughput approaches and enables immediate recovery of mutants of interest.

Systematic improvement of amplicon marker gene methods for increased accuracy in microbiome studies.

Amplicon-based marker gene surveys form the basis of most microbiome and other microbial community studies. Such PCR-based methods have multiple steps, each of which is susceptible to error and bias. Variance in results has also arisen through the use of multiple methods of next-generation sequencing (NGS) amplicon library preparation. Here we formally characterized errors and biases by comparing different methods of amplicon-based NGS library preparation. Using mock community standards, we analyzed the amplification process to reveal insights into sources of experimental error and bias in amplicon-based microbial community and microbiome experiments. We present a method that improves on the current best practices and enables the detection of taxonomic groups that often go undetected with existing methods.

Clinical validation of targeted next-generation sequencing for inherited disorders.

CONTEXT: Although next-generation sequencing (NGS) can revolutionize molecular diagnostics, several hurdles remain in the implementation of this technology in clinical laboratories. OBJECTIVES: To validate and implement an NGS panel for genetic diagnosis of more than 100 inherited diseases, such as neurologic conditions, congenital hearing loss and eye disorders, developmental disorders, nonmalignant diseases treated by hematopoietic cell transplantation, familial cancers, connective tissue disorders, metabolic disorders, disorders of sexual development, and cardiac disorders. The diagnostic gene panels ranged from 1 to 54 genes with most of panels containing 10 genes or fewer. DESIGN: We used a liquid hybridization-based, target-enrichment strategy to enrich 10 067 exons in 568 genes, followed by NGS with a HiSeq 2000 sequencing system (Illumina, San Diego, California). RESULTS: We successfully sequenced 97.6% (9825 of 10 067) of the targeted exons to obtain a minimum coverage of 20× at all bases. We demonstrated 100% concordance in detecting 19 pathogenic single-nucleotide variations and 11 pathogenic insertion-deletion mutations ranging in size from 1 to 18 base pairs across 18 samples that were previously characterized by Sanger sequencing. Using 4 pairs of blinded, duplicate samples, we demonstrated a high degree of concordance (>99%) among the blinded, duplicate pairs. CONCLUSIONS: We have successfully demonstrated the feasibility of using the NGS platform to multiplex genetic tests for several rare diseases and the use of cloud computing for bioinformatics analysis as a relatively low-cost solution for implementing NGS in clinical laboratories.

Implementation of Cloud based next generation sequencing data analysis in a clinical laboratory.

BACKGROUND: The introduction of next generation sequencing (NGS) has revolutionized molecular diagnostics, though several challenges remain limiting the widespread adoption of NGS testing into clinical practice. One such difficulty includes the development of a robust bioinformatics pipeline that can handle the volume of data generated by high-throughput sequencing in a cost-effective manner. Analysis of sequencing data typically requires a substantial level of computing power that is often cost-prohibitive to most clinical diagnostics laboratories. FINDINGS: To address this challenge, our institution has developed a Galaxy-based data analysis pipeline which relies on a web-based, cloud-computing infrastructure to process NGS data and identify genetic variants. It provides additional flexibility, needed to control storage costs, resulting in a pipeline that is cost-effective on a per-sample basis. It does not require the usage of EBS disk to run a sample. CONCLUSIONS: We demonstrate the validation and feasibility of implementing this bioinformatics pipeline in a molecular diagnostics laboratory. Four samples were analyzed in duplicate pairs and showed 100% concordance in mutations identified. This pipeline is currently being used in the clinic and all identified pathogenic variants confirmed using Sanger sequencing further validating the software.