Clinical exome performance for reporting secondary genetic findings

A multi-omics dataset of human transcriptome and proteome stable reference

The development of high-throughput omics technology has greatly promoted the development of biomedicine. However, the poor reproducibility of omics techniques limits their application. It is necessary to use standard reference materials of complex RNAs or proteins to test and calibrate the accuracy and reproducibility of omics workflows. The transcriptome and proteome of most cell lines shift during culturing, which limits their applicability as standard samples. In this study, we demonstrated that the human hepatocellular cell line MHCC97H has a very stable transcriptome (r = 0.983~0.997) and proteome (r = 0.966~0.988 for data-dependent acquisition, r = 0.970~0.994 for data-independent acquisition) after 9 subculturing generations, which allows this steady standard sample to be consistently produced on an industrial scale in long term. Moreover, this stability was maintained across labs and platforms. In sum, our study provides omics standard reference material and reference datasets for transcriptomic and proteomics research. This helps to further standardize the workflow and data quality of omics techniques and thus promotes the application of omics technology in precision medicine.

Towards an accurate and robust analysis pipeline for somatic mutation calling

Accurate and robust somatic mutation detection is essential for cancer treatment, diagnostics and research. Various analysis pipelines give different results and thus should be systematically evaluated. In this study, we benchmarked 5 commonly-used somatic mutation calling pipelines (VarScan, VarDictJava, Mutect2, Strelka2 and FANSe) for their precision, recall and speed, using standard benchmarking datasets based on a series of real-world whole-exome sequencing datasets. All the 5 pipelines showed very high precision in all cases, and high recall rate in mutation rates higher than 10%. However, for the low frequency mutations, these pipelines showed large difference. FANSe showed the highest accuracy (especially the sensitivity) in all cases, and VarScan and VarDictJava outperformed Mutect2 and Strelka2 in low frequency mutations at all sequencing depths. The flaws in filter was the major cause of the low sensitivity of the four pipelines other than FANSe. Concerning the speed, FANSe pipeline was 8.8∼19x faster than the other pipelines. Our benchmarking results demonstrated performance of the somatic calling pipelines and provided a reference for a proper choice of such pipelines in cancer applications.

A multi-laboratory assessment of clinical exome sequencing for detection of hereditary disease variants: 4441 ClinVar variants for clinical genomic test development and validation

BACKGROUND AND AIMS

Whole-exome sequencing (WES) technology has become an essential tool in the clinical diagnostic for rare genetic disorders, however, the issues that reduce testing precision, sensitivity, and concordance are not clear under routine testing conditions. The study is to systematically evaluate the comparability of clinical WES testing results in laboratories under routine conditions.

METHODS

We designed a multi-laboratory study across 24 participating laboratories in China. We assessed sequencing quality across capture methods and sequencing platforms, benchmarked the impact of coverage and callable regions on detecting single nucleotide variants (SNVs), small insertions and deletions (Indels) under the same computational approaches, and compared the sensitivity, precision and reproducibility on detecting mutations across laboratories.

RESULTS

High inter-laboratory variability on variants detection were found across participating laboratories. Sample DNA concentration and sequencing evenness are two major variables that lead to the coverage variation. The difference in bioinformatics tools and computational settings affect the sensitivity and precision of the final output. Besides, copy-number variants (CNVs) identification is less reproducible than SNVs and Indels in the WES testing. We also compiled a list of 4441 low coverage ClinVar variants of 1176 genes from this study, which can be used as a source for creating in silico and synthetic DNA reference materials for clinical genetic disorder detection.

CONCLUSIONS

The considerable inter-laboratory variability seen in both sequencing coverage evenness and variants detection highlights the urgent need to improve the precision, sensitivity and comparability of the results generated across different laboratories. The list of low coverage variants can have important implications for the development and validation of clinical genetic disorder tests by laboratories. This study also serves to best practice inform guidelines for detecting clinical genetic disorders by exome sequencing.

The evolving role of diagnostic genomics in kidney transplantation

Monogenic forms of heritable kidney disease account for a significant proportion of chronic kidney disease (CKD) across both pediatric and adult patient populations and up to 11% of patients under 40 years reaching end-stage kidney failure (KF) and awaiting kidney transplant. Diagnostic genomics in the field of nephrology is ever evolving and now plays an important role in assessment and management of kidney transplant recipients and their related donor pairs. Genomic testing can help identify the cause of KF in kidney transplant recipients and assist in prognostication around graft survival and rate of recurrence of primary kidney disease. If a gene variant has been identified in the recipient, at-risk related donors can be assessed for the same and excluded if affected. This paper aims to address the indications for genomic testing in the context for kidney transplantation, the technologies available for testing, the conditions and groups in which testing should be most often considered, and the role for the renal genetics multidisciplinary team in this process.

Analytical Performance of NGS-Based Molecular Genetic Tests Used in the Diagnostic Workflow of Pheochromocytoma/Paraganglioma

Next Generation Sequencing (NGS)-based methods are high-throughput and cost-effective molecular genetic diagnostic tools. Targeted gene panel and whole exome sequencing (WES) are applied in clinical practice for assessing mutations of pheochromocytoma/paraganglioma (PPGL) associated genes, but the best strategy is debated. Germline mutations of at the least 18 PPGL genes are present in approximately 20-40% of patients, thus molecular genetic testing is recommended in all cases. We aimed to evaluate the analytical and clinical performances of NGS methods for mutation detection of PPGL-associated genes. WES (three different library preparation and bioinformatics workflows) and an in-house, hybridization based gene panel (endocrine-onco-gene-panel- ENDOGENE) was evaluated on 37 (20 WES and 17 ENDOGENE) samples with known variants. After optimization of the bioinformatic workflow, 61 additional samples were tested prospectively. All clinically relevant variants were validated with Sanger sequencing. Target capture of PPGL genes differed markedly between WES platforms and genes tested. All known variants were correctly identified by all methods, but methods of library preparations, sequencing platforms and bioinformatical settings significantly affected the diagnostic accuracy. The ENDOGENE panel identified several pathogenic mutations and unusual genotype-phenotype associations suggesting that the whole panel should be used for identification of genetic susceptibility of PPGL.

The Ultrafast and Accurate Mapping Algorithm FANSe3: Mapping a Human Whole-Genome Sequencing Dataset Within 30 Minutes

Aligning billions of reads generated by the next-generation sequencing (NGS) to reference sequences, termed "mapping", is the time-consuming and computationally-intensive process in most NGS applications. A Fast, accurate and robust mapping algorithm is highly needed. Therefore, we developed the FANSe3 mapping algorithm, which can map a 30 × human whole-genome sequencing (WGS) dataset within 30 min, a 50 × human whole exome sequencing (WES) dataset within 30 s, and a typical mRNA-seq dataset within seconds in a single-server node without the need for any hardware acceleration feature. Like its predecessor FANSe2, the error rate of FANSe3 can be kept as low as 10^-9 in most cases, this is more robust than the Burrows-Wheeler transform-based algorithms. Error allowance hardly affected the identification of a driver somatic mutation in clinically relevant WGS data and provided robust gene expression profiles regardless of the parameter settings and sequencer used. The novel algorithm, designed for high-performance cloud-computing after infrastructures, will break the bottleneck of speed and accuracy in NGS data analysis and promote NGS applications in various fields. The FANSe3 algorithm can be downloaded from the website: http://www.chi-biotech.com/fanse3/.

Clinical Genetic Screening in Adult Patients with Kidney Disease

Expanded accessibility of genetic sequencing technologies, such as chromosomal microarray and massively parallel sequencing approaches, is changing the management of hereditary kidney diseases. Genetic causes account for a substantial proportion of pediatric kidney disease cases, and with increased utilization of diagnostic genetic testing in nephrology, they are now also detected at appreciable frequencies in adult populations. Establishing a molecular diagnosis can have many potential benefits for patient care, such as guiding treatment, familial testing, and providing deeper insights on the molecular pathogenesis of kidney diseases. Today, with wider clinical use of genetic testing as part of the diagnostic evaluation, nephrologists have the challenging task of selecting the most suitable genetic test for each patient, and then applying the results into the appropriate clinical contexts. This review is intended to familiarize nephrologists with the various technical, logistical, and ethical considerations accompanying the increasing utilization of genetic testing in nephrology care.

Clinical Exome Studies Have Inconsistent Coverage

BACKGROUND

Exome sequencing has become a commonly used clinical diagnostic test. Multiple studies have examined the diagnostic utility and individual laboratory performance of exome testing; however, no previous study has surveyed and compared the data quality from multiple clinical laboratories.

METHODS

We examined sequencing data from 36 clinical exome tests from 3 clinical laboratories. Exome data were compared in terms of overall characteristics and coverage of specific genes and nucleotide positions. The sets of genes examined included genes in Consensus Coding Sequence (CCDS) (n = 17723), a subset of genes clinically relevant to epilepsy (n = 108), and genes that are recommended for reporting of secondary findings (n = 57; excludes X-linked genes).

RESULTS

The average exome nucleotide coverage (≥20×) of each laboratory varied at 96.49% (CV = 3%), 96.54% (CV = 1%), and 91.68% (CV = 4%), for laboratories A, B, and C, respectively. For CCDS genes, the average number of completely covered genes varied at 12184 (CV = 29%), 11687 (CV = 13%), and 5989 (CV = 37%), for laboratories A, B, and C, respectively. With smaller subsets of genes related to epilepsy and secondary findings, the CV revealed low consistency, with a maximum CV seen in laboratory C for both epilepsy genes (CV = 60%) and secondary findings genes (CV = 71%).

CONCLUSIONS

Poor consistency in complete gene coverage was seen in the clinical exome laboratories surveyed. The degree of consistency varied widely between the laboratories.

Considerations for whole exome sequencing unique to prenatal care

Whole exome sequencing (WES) is increasingly being used in the prenatal setting. The emerging data support the clinical utility of prenatal WES based on its diagnostic yield, which can be as high as 80% for certain ultrasound findings. However, detailed practice and laboratory guidelines, addressing the indications for prenatal WES and the surrounding technical, interpretation, ethical, and counseling issues, are still lacking. Herein, we review the literature and summarize the most recent findings and applications of prenatal WES. This review offers specialists and clinical genetic laboratorians a body of evidence and expert opinions that can serve as a resource to assist in their practice. Finally, we highlight the emerging technologies that promise a future of prenatal WES without the risks associated with invasive testing.

Genomic testing in pediatric epilepsy

Genomic testing has become routine in the diagnosis and management of pediatric patients with epilepsy. In a single test, hundreds to thousands of genes are examined for DNA changes that may not only explain the etiology of the patient's condition but may also inform management and seizure control. Clinical genomic testing has been in clinical practice for less than a decade, and because of this short period of time, the appropriate clinical use and interpretation of genomic testing is still evolving. Compared to the previous era of single-gene testing in epilepsy, which yielded a diagnosis in <5% of cases, many clinical genomic studies of epilepsy have demonstrated a clinically significant diagnosis in 30% or more of patients tested. This review will examine key studies of the past decade and indicate the clinical scenarios in which genomic testing should be considered standard of care.

A suite of automated sequence analyses reduces the number of candidate deleterious variants and reveals a difference between probands and unaffected siblings

PURPOSE

Develop an automated exome analysis workflow that can produce a very small number of candidate variants yet still detect different numbers of deleterious variants between probands and unaffected siblings.

METHODS

Ninety-seven outbred nuclear families from the Undiagnosed Diseases Program/Network included single probands and the corresponding unaffected sibling(s). Single-nucleotide polymorphism (SNP) chip and exome analyses were performed on all, with proband and unaffected sibling considered independently as the target. The total burden of candidate genetic variants was summed for probands and siblings over all considered disease models.

RESULTS

Exome analysis workflow include automated programs for ethnicity-matched genotype calling, salvage pathway for Mendelian inconsistency, compound heterozygous recessive detection, BAM file regional curation, population frequency filtering, pedigree-aware BAM file noise evaluation, and exon deletion filtration. This workflow relied heavily on BAM file analysis. A greater average pathogenic variant number was found compared with unaffected siblings. This was significant (p < 0.05) when using published recommended thresholds, and implies that causal variants are retained in many probands' lists.

CONCLUSION

Using Mendelian and non-Mendelian models, this agnostic exome analysis shows a difference between a small group of probands and their unaffected siblings. This workflow produces candidate lists small enough to pursue with laboratory validation.

Genomic medicine for kidney disease

Technologies such as next-generation sequencing and chromosomal microarray have advanced the understanding of the molecular pathogenesis of a variety of renal disorders. Genetic findings are increasingly used to inform the clinical management of many nephropathies, enabling targeted disease surveillance, choice of therapy, and family counselling. Genetic analysis has excellent diagnostic utility in paediatric nephrology, as illustrated by sequencing studies of patients with congenital anomalies of the kidney and urinary tract and steroid-resistant nephrotic syndrome. Although additional investigation is needed, pilot studies suggest that genetic testing can also provide similar diagnostic insight among adult patients. Reaching a genetic diagnosis first involves choosing the appropriate testing modality, as guided by the clinical presentation of the patient and the number of potential genes associated with the suspected nephropathy. Genome-wide sequencing increases diagnostic sensitivity relative to targeted panels, but holds the challenges of identifying causal variants in the vast amount of data generated and interpreting secondary findings. In order to realize the promise of genomic medicine for kidney disease, many technical, logistical, and ethical questions that accompany the implementation of genetic testing in nephrology must be addressed. The creation of evidence-based guidelines for the utilization and implementation of genetic testing in nephrology will help to translate genetic knowledge into improved clinical outcomes for patients with kidney disease.

Evaluation of whole exome sequencing by targeted gene sequencing and Sanger sequencing

BACKGROUND

Targeted gene sequencing (TGS) and whole exome sequencing (WES) are being used in clinical testing in laboratories. We compared the performances of TGS and WES using the same DNA samples.

METHODS

DNA was extracted from 10 endometrial tumor tissue specimens. Sequencing were performed with an Illumina HiSeq 2000. We randomly selected variants to confirm through Sanger sequencing or mutant-enriched PCR with Sanger sequencing.

RESULTS

We found that the variants identified in both TGS and WES were true positives (47/47), regardless of the sequencing depth. Most variants found in TGS only were true positives (34/40), and most of the variants found by WES only were false positives (8/18). From these results, we suggest that the sequencing depth may not play important role in the accuracy of NGS-based methods. After analysis, we found that WES had a sensitivity of 72.70%, specificity of 96.27%, precision of 99.44%, and accuracy of 75.03%.

CONCLUSIONS

The results of NGS-based methods must currently be validated, especially for important reported variants regardless of the methods used, and for the use of WES in cancers a higher false negative rate must be considered. More sensitive methods should be used to confirm the NGS results in uneven cancer tissues.

Exome sequencing establishes a gelsolin mutation as the cause of inherited bulbar-onset neuropathy

INTRODUCTION

Progressive bulbar motor neuropathy is primarily caused by bulbar-onset ALS. Hereditary amyloidosis type IV also presents with a bulbar neuropathy that mimics motor neuron disease. The disease is prevalent in Finland only and is not commonly included in the differential diagnosis of ALS.

METHODS

We studied 18 members of a family in which some had bulbar motor neuropathy, and we performed exome sequencing.

RESULTS

Five affected family members were found to have a D187Y substitution in the GSN gene known to cause hereditary amyloidosis type IV.

CONCLUSIONS

This American family presented with progressive bulbar neuropathy due to a gelsolin mutation not found in Finland. Hereditary amyloidosis type IV presents with bulbar motor neuropathy and not with peripheral neuropathy as occurs with common forms of amyloidosis. This report demonstrates the power of exome sequencing to determine the cause of rare hereditary diseases with incomplete or atypical phenotypes. Muscle Nerve 56: 1001-1005, 2017.

Identification of novel mutations in endometrial cancer patients by whole-exome sequencing

The aim of the present study was to identify genomic alterations in Taiwanese endometrial cancer patients. This information is vitally important in Taiwan, where endometrial cancer is the second most common gynecological cancer. We performed whole-exome sequencing on DNA from 14 tumor tissue samples from Taiwanese endometrial cancer patients. We used the Genome Analysis Tool kit software package for data analysis, and the dbSNP, Catalogue of Somatic Mutations in Cancer (COSMIC) and The Cancer Genome Atlas (TCGA) databases for comparisons. Variants were validated via Sanger sequencing. We identified 143 non-synonymous mutations in 756 canonical cancer-related genes and 1,271 non-synonymous mutations in non-canonical cancer-related genes in 14 endometrial samples. PTEN, KRAS and PIK3R1 were the most frequently mutated canonical cancer-related genes. Our results revealed nine potential driver genes (MAPT, IL24, MCM6, TSC1, BIRC2, CIITA, DST, CASP8 and NOTCH2) and 21 potential passenger genes (ARMCX4, IGSF10, VPS13C, DCT, DNAH14, TLN1, ZNF605, ZSCAN29, MOCOS, CMYA5, PCDH17, UGT1A8, CYFIP2, MACF1, NUDT5, JAKMIP1, PCDHGB4, FAM178A, SNX6, IMP4 and PCMTD1). The detected molecular aberrations led to putative activation of the mTOR, Wnt, MAPK, VEGF and ErbB pathways, as well as aberrant DNA repair, cell cycle control and apoptosis pathways. We characterized the mutational landscape and genetic alterations in multiple cellular pathways of endometrial cancer in the Taiwanese population.

Exome sequencing covers >98% of mutations identified on targeted next generation sequencing panels

Background

With the expanded availability of next generation sequencing (NGS)-based clinical genetic tests, clinicians seeking to test patients with Mendelian diseases must weigh the superior coverage of targeted gene panels with the greater number of genes included in whole exome sequencing (WES) when considering their first-tier testing approach. Here, we use an in silico analysis to predict the analytic sensitivity of WES using pathogenic variants identified on targeted NGS panels as a reference.

Methods

Corresponding nucleotide positions for 1533 different alterations classified as pathogenic or likely pathogenic identified on targeted NGS multi-gene panel tests in our laboratory were interrogated in data from 100 randomly-selected clinical WES samples to quantify the sequence coverage at each position. Pathogenic variants represented 91 genes implicated in hereditary cancer, X-linked intellectual disability, primary ciliary dyskinesia, Marfan syndrome/aortic aneurysms, cardiomyopathies and arrhythmias.

Results

When assessing coverage among 100 individual WES samples for each pathogenic variant (153,300 individual assessments), 99.7% (n = 152,798) would likely have been detected on WES. All pathogenic variants had at least some coverage on exome sequencing, with a total of 97.3% (n = 1491) detectable across all 100 individuals. For the remaining 42 pathogenic variants, the number of WES samples with adequate coverage ranged from 35 to 99. Factors such as location in GC-rich, repetitive, or homologous regions likely explain why some of these alterations were not detected across all samples. To validate study findings, a similar analysis was performed against coverage data from 60,706 exomes available through the Exome Aggregation Consortium (ExAC). Results from this validation confirmed that 98.6% (91,743,296/93,062,298) of pathogenic variants demonstrated adequate depth for detection.

Conclusions

Results from this in silico analysis suggest that exome sequencing may achieve a diagnostic yield similar to panel-based testing for Mendelian diseases.

Neurology Individualized Medicine: When to Use Next-Generation Sequencing Panels

Next-generation sequencing (NGS) is increasingly being applied to clinical testing. This practice is predicted to grow especially in neurology clinics because many of their patients have monogenetic causes for their "diagnostic odyssey." The cost of sequencing has been steadily decreasing, but the cost of DNA sequencing is a minor part of the total cost. Downstream data analysis, storage, and interpretation account for most of the total expense. In patients with nonspecific neurologic disorders in which an extensive number of genetic differential diagnoses exist, whole-genome sequencing (WGS) or whole-exome sequencing (WES) has shown promise in the identification of genetic causes. However, both WGS and WES have incomplete coverage and produce a large number of rare variants of unknown importance. In addition, ethical dilemmas are often created by unexpected findings in genes unrelated to the initial sequencing indication. Targeted-panel NGS starts with the capture of a set of disease-focused genes, followed by massive parallel sequencing. For many genetically heterogeneous neurologic disorders, a genetic panel that is disease focused yet inclusive of a large genetic differential diagnosis can be defined to reduce cost, increase turnaround time, and optimize performance. Targeted-panel NGS is currently the preferred first-tier approach because it provides a reliable clinical application while eliminating unexpected ethical dilemmas. Targeted-panel NGS is leading to a paradigm shift in the diagnosis of many neurologic disorders, enabling individualized precision medicine. In this review, we provide an overview of WGS, WES, and targeted-panel NGS in consideration of their utility in clinical testing for neurologic diseases.

Actionable Genes, Core Databases, and Locus-Specific Databases

Adoption of next-generation sequencing (NGS) in a diagnostic context raises numerous questions with regard to identification and reports of secondary variants (SVs) in actionable genes. To better understand the whys and wherefores of these questioning, it is necessary to understand how they are selected during the filtering process and how their proportion can be estimated. It is likely that SVs are underestimated and that our capacity to label all true SVs can be improved. In this context, Locus-specific databases (LSDBs) can be key by providing a wealth of information and enabling classifying variants. We illustrate this issue by analyzing 318 SVs in 23 actionable genes involved in cancer susceptibility syndromes identified through sequencing of 572 participants selected for a range of atherosclerosis phenotypes. Among these 318 SVs, only 43.4% are reported in Human Gene Mutation Database (HGMD) Professional versus 71.4% in LSDB. In addition, 23.9% of HGMD Professional variants are reported as pathogenic versus 4.8% for LSDB. These data underline the benefits of LSDBs to annotate SVs and minimize overinterpretation of mutations thanks to their efficient curation process and collection of unpublished data.

A new eIF4E1 allele characterized by RNAseq data mining is associated with resistance to potato virus Y in tomato albeit with a low durability

Allele mining on susceptibility factors offers opportunities to find new sources of resistance among crop wild relatives for breeding purposes. As a proof of concept, we used available RNAseq data to investigate polymorphisms among the four tomato genes encoding translation initiation factors [eIF4E1 and eIF4E2, eIFiso4E and the related gene new cap-binding protein(nCBP)] to look for new potential resistance alleles to potyviruses. By analysing polymorphism among RNAseq data obtained for 20 tomato accessions, 10 belonging to the cultivated type Solanum lycopersicum and 10 belonging to the closest related wild species Solanum pimpinellifolium, we isolated one new eIF4E1 allele, in the S. pimpinellifolium LA0411 accession, which encodes a potential new resistance allele, mainly due to a polymorphism associated with an amino acid change within eIF4E1 region II. We confirmed that this new allele, pot12, is indeed associated with resistance to potato virus Y, although with a restricted resistance spectrum and a very low durability potential. This suggests that mutations occurring in eIF4E region II only may not be sufficient to provide efficient and durable resistance in plants. However, our study emphasizes the opportunity brought by RNAseq data to mine for new resistance alleles. Moreover, this approach could be extended to seek for putative new resistance alleles by screening for variant forms of susceptibility genes encoding plant host proteins known to interact with viral proteins.

Explorations to improve the completeness of exome sequencing

BACKGROUND

Exome sequencing has advanced to clinical practice and proven useful for obtaining molecular diagnoses in rare diseases. In approximately 75 % of cases, however, a clinical exome study does not produce a definitive molecular diagnosis. These residual cases comprise a new diagnostic challenge for the genetics community. The Undiagnosed Diseases Program of the National Institutes of Health routinely utilizes exome sequencing for refractory clinical cases. Our preliminary data suggest that disease-causing variants may be missed by current standard-of-care clinical exome analysis. Such false negatives reflect limitations in experimental design, technical performance, and data analysis.

RESULTS

We present examples from our datasets to quantify the analytical performance associated with current practices, and explore strategies to improve the completeness of data analysis. In particular, we focus on patient ascertainment, exome capture, inclusion of intronic variants, and evaluation of medium-sized structural variants.

CONCLUSIONS

The strategies we present may recover previously-missed, disease causing variants in second-pass exome analysis. Understanding the limitations of the current clinical exome search space provides a rational basis to improve methods for disease variant detection using genome-scale sequencing techniques.

Phenotypic H-Antigen Typing by Mass Spectrometry Combined with Genetic Typing of H Antigens, O Antigens, and Toxins by Whole-Genome Sequencing Enhances Identification of Escherichia coli Isolates

Mass spectrometry-based phenotypic H-antigen typing (MS-H) combined with whole-genome-sequencing-based genetic identification of H antigens, O antigens, and toxins (WGS-HOT) was used to type 60 clinical Escherichia coli isolates, 43 of which were previously identified as nonmotile, H type undetermined, or O rough by serotyping or having shown discordant MS-H and serotyping results. Whole-genome sequencing confirmed that MS-H was able to provide more accurate data regarding H antigen expression than serotyping. Further, enhanced and more confident O antigen identification resulted from gene cluster based typing in combination with conventional typing based on the gene pair comprising wzx and wzy and that comprising wzm and wzt The O antigen was identified in 94.6% of the isolates when the two genetic O typing approaches (gene pair and gene cluster) were used in conjunction, in comparison to 78.6% when the gene pair database was used alone. In addition, 98.2% of the isolates showed the existence of genes for various toxins and/or virulence factors, among which verotoxins (Shiga toxin 1 and/or Shiga toxin 2) were 100% concordant with conventional PCR based testing results. With more applications of mass spectrometry and whole-genome sequencing in clinical microbiology laboratories, this combined phenotypic and genetic typing platform (MS-H plus WGS-HOT) should be ideal for pathogenic E. coli typing.

Precision Medicine in Gastrointestinal Pathology

Context.—Precision medicine is the promise of individualized therapy and management of patients based on their personal biology. There are now multiple global initiatives to perform whole-genome sequencing on millions of individuals. In the United States, an early program was the Million Veteran Program, and a more recent proposal in 2015 by the president of the United States is the Precision Medicine Initiative. To implement precision medicine in routine oncology care, genetic variants present in tumors need to be matched with effective clinical therapeutics. When we focus on the current state of precision medicine for gastrointestinal malignancies, it becomes apparent that there is a mixed history of success and failure.

Objective.—To present the current state of precision medicine using gastrointestinal oncology as a model. We will present currently available targeted therapeutics, promising new findings in clinical genomic oncology, remaining quality issues in genomic testing, and emerging oncology clinical trial designs.

Data Sources.—Review of the literature including clinical genomic studies on gastrointestinal malignancies, clinical oncology trials on therapeutics targeted to molecular alterations, and emerging clinical oncology study designs.

Conclusions.—Translating our ability to sequence thousands of genes into meaningful improvements in patient survival will be the challenge for the next decade.

Newborn screening and the era of medical genomics

Across the span of the last 75+ years, technological and conceptual advances in genetics have found rapid implementation at the beginning of human life. From karyotype testing, to molecular cytogenetics, to gene panel testing, and now to whole exome and whole genome sequencing, each iterative expansion of our capability to acquire genetic data on the next generation has been implemented quickly in the clinical setting. In tandem, our continuously expanding ability to acquire large volumes of genetic data has generated its own challenges in terms of interpretation, clinical utility of the information, and concerns over privacy and discrimination; for the first time, we are faced with the possibility of having complete access to our genetic data from birth, if not shortly after conception. Here, we discuss the evolution of the field toward this new reality and we consider the potentially far-reaching consequences and, at present, an unclear path toward developing best practices for implementation.

Utility of whole-genome sequencing for detection of newborn screening disorders in a population cohort of 1,696 neonates

PURPOSE

To assess the potential of whole-genome sequencing (WGS) to replicate and augment results from conventional blood-based newborn screening (NBS).

METHODS

Research-generated WGS data from an ancestrally diverse cohort of 1,696 infants and both parents of each infant were analyzed for variants in 163 genes involved in disorders included or under discussion for inclusion in US NBS programs. WGS results were compared with results from state NBS and related follow-up testing.

RESULTS

NBS genes are generally well covered by WGS. There is a median of one (range: 0-6) database-annotated pathogenic variant in the NBS genes per infant. Results of WGS and NBS in detecting 28 state-screened disorders and four hemoglobin traits were concordant for 88.6% of true positives (n = 35) and 98.9% of true negatives (n = 45,757). Of the five infants affected with a state-screened disorder, WGS identified two whereas NBS detected four. WGS yielded fewer false positives than NBS (0.037 vs. 0.17%) but more results of uncertain significance (0.90 vs. 0.013%).

CONCLUSION

WGS may help rule in and rule out NBS disorders, pinpoint molecular diagnoses, and detect conditions not amenable to current NBS assays.

Incidental Findings with Genomic Testing: Implications for Genetic Counseling Practice

This paper summarizes the current controversies surrounding the identification and disclosure of "incidental" or "secondary" findings from genomic sequencing and the implications for genetic counseling practice. The rapid expansion of clinical sequencing has influenced the ascertainment and return of incidental findings, while empiric data to inform best practices are still being generated. Using the North Carolina Clinical Genomic Evaluation by Next Generation Exome Sequencing (NCGENES) research project as an example, we discuss the implications of different models of consent and their impact on patient decisions.

Achieving high-sensitivity for clinical applications using augmented exome sequencing

Background

Whole exome sequencing is increasingly used for the clinical evaluation of genetic disease, yet the variation of coverage and sensitivity over medically relevant parts of the genome remains poorly understood. Several sequencing-based assays continue to provide coverage that is inadequate for clinical assessment.

Methods

Using sequence data obtained from the NA12878 reference sample and pre-defined lists of medically-relevant protein-coding and noncoding sequences, we compared the breadth and depth of coverage obtained among four commercial exome capture platforms and whole genome sequencing. In addition, we evaluated the performance of an augmented exome strategy, ACE, that extends coverage in medically relevant regions and enhances coverage in areas that are challenging to sequence. Leveraging reference call-sets, we also examined the effects of improved coverage on variant detection sensitivity.

Results

We observed coverage shortfalls with each of the conventional exome-capture and whole-genome platforms across several medically interpretable genes. These gaps included areas of the genome required for reporting recently established secondary findings (ACMG) and known disease-associated loci. The augmented exome strategy recovered many of these gaps, resulting in improved coverage in these areas. At clinically-relevant coverage levels (100 % bases covered at ≥20×), ACE improved coverage among genes in the medically interpretable genome (>90 % covered relative to 10-78 % with other platforms), the set of ACMG secondary finding genes (91 % covered relative to 4-75 % with other platforms) and a subset of variants known to be associated with human disease (99 % covered relative to 52-95 % with other platforms). Improved coverage translated into improvements in sensitivity, with ACE variant detection sensitivities (>97.5 % SNVs, >92.5 % InDels) exceeding that observed with conventional whole-exome and whole-genome platforms.

Conclusions

Clinicians should consider analytical performance when making clinical assessments, given that even a few missed variants can lead to reporting false negative results. An augmented exome strategy provides a level of coverage not achievable with other platforms, thus addressing concerns regarding the lack of sensitivity in clinically important regions. In clinical applications where comprehensive coverage of medically interpretable areas of the genome requires higher localized sequencing depth, an augmented exome approach offers both cost and performance advantages over other sequencing-based tests.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-015-0197-4) contains supplementary material, which is available to authorized users.

Genetics and genotype-phenotype correlations in Finnish patients with dilated cardiomyopathy

Genetic analysis among patients with dilated cardiomyopathy (DCM) is becoming an important part of clinical assessment, as it is in hypertrophic cardiomyopathy (HCM). The genetics of DCM is complex and therefore next-generation sequencing strategies are essential when providing genetic diagnostics. To achieve maximum yield, the diagnostic approach should include comprehensive clinical phenotyping combined with high-quality, high-coverage deep sequencing of DCM-associated genes and clinical variant classification as a basis for defining true yield in genetic testing. Our study has combined a novel sequencing strategy and clinical interpretation to analyse the yield and genotype–phenotype correlations among well-phenotyped Finnish DCM patients.

Aims

Despite our increased understanding of the genetic basis of dilated cardiomyopathy (DCM), the clinical utility and yield of clinically meaningful findings of comprehensive next-generation sequencing (NGS)-based genetic diagnostics in DCM has been poorly described. We utilized a high-quality oligonucleotide-selective sequencing (OS-Seq)-based targeted sequencing panel to investigate the genetic landscape of DCM in Finnish population and to evaluate the utility of OS-Seq technology as a novel comprehensive diagnostic tool.

Methods and results

Using OS-Seq, we targeted and sequenced the coding regions and splice junctions of 101 genes associated with cardiomyopathies in 145 unrelated Finnish patients with DCM. We developed effective bioinformatic variant filtering strategy and implemented strict variant classification scheme to reveal diagnostic yield and genotype–phenotype correlations. Implemented OS-Seq technology provided high coverage of the target region (median coverage 410× and 99.42% of the nucleotides were sequenced at least 15× read depth). Diagnostic yield was 35.2% (familial 47.6% and sporadic 25.6%, P = 0.004) when both pathogenic and likely pathogenic variants are considered as disease causing. Of these, 20 (53%) were titin (TTN) truncations (non-sense and frameshift) affecting all TTN transcripts. TTN truncations accounted for 20.6% and 14.6% of the familial and sporadic DCM cases, respectively.

Conclusion

Panel-based, high-quality NGS enables high diagnostic yield especially in the familial form of DCM, and bioinformatic variant filtering is a reliable step in the process of interpretation of genomic data in a clinical setting.

The SickKids Genome Clinic: developing and evaluating a pediatric model for individualized genomic medicine

Our increasing knowledge of how genomic variants affect human health and the falling costs of whole-genome sequencing are driving the development of individualized genomic medicine. This new clinical paradigm uses knowledge of an individual's genomic variants to anticipate, diagnose and manage disease. While individualized genetic medicine offers the promise of transformative change in health care, it forces us to reconsider existing ethical, scientific and clinical paradigms. The potential benefits of pre-symptomatic identification of at-risk individuals, improved diagnostics, individualized therapy, accurate prognosis and avoidance of adverse drug reactions coexist with the potential risks of uninterpretable results, psychological harm, outmoded counseling models and increased health care costs. Here we review the challenges, opportunities and limits of integrating genomic analysis into pediatric clinical practice and describe a model for implementing individualized genomic medicine. Our multidisciplinary team of bioinformaticians, health economists, health services and policy researchers, ethicists, geneticists, genetic counselors and clinicians has designed a 'Genome Clinic' research project that addresses multiple challenges in pediatric genomic medicine--ranging from development of bioinformatics tools for the clinical assessment of genomic variants and the discovery of disease genes to health policy inquiries, assessment of clinical care models, patient preference and the ethics of consent.