Expanding the Boundaries of RNA Sequencing as a Diagnostic Tool for Rare Mendelian Disease.

Gene-panel and whole-exome analyses are now standard methodologies for mutation detection in Mendelian disease. However, the diagnostic yield achieved is at best 50%, leaving the genetic basis for disease unsolved in many individuals. New approaches are thus needed to narrow the diagnostic gap. Whole-genome sequencing is one potential strategy, but it currently has variant-interpretation challenges, particularly for non-coding changes. In this study we focus on transcriptome analysis, specifically total RNA sequencing (RNA-seq), by using monogenetic neuromuscular disorders as proof of principle. We examined a cohort of 25 exome and/or panel "negative" cases and provided genetic resolution in 36% (9/25). Causative mutations were identified in coding and non-coding exons, as well as in intronic regions, and the mutational pathomechanisms included transcriptional repression, exon skipping, and intron inclusion. We address a key barrier of transcriptome-based diagnostics: the need for source material with disease-representative expression patterns. We establish that blood-based RNA-seq is not adequate for neuromuscular diagnostics, whereas myotubes generated by transdifferentiation from an individual's fibroblasts accurately reflect the muscle transcriptome and faithfully reveal disease-causing mutations. Our work confirms that RNA-seq can greatly improve diagnostic yield in genetically unresolved cases of Mendelian disease, defines strengths and challenges of the technology, and demonstrates the suitability of cell models for RNA-based diagnostics. Our data set the stage for development of RNA-seq as a powerful clinical diagnostic tool that can be applied to the large population of individuals with undiagnosed, rare diseases and provide a framework for establishing minimally invasive strategies for doing so.

Targeted exome analysis identifies the genetic basis of disease in over 50% of patients with a wide range of ataxia-related phenotypes.

PURPOSE: To examine the impact of a targeted exome approach for the molecular diagnosis of patients nationwide with a wide range of ataxia-related phenotypes. METHODS: One hundred and seventy patients with ataxia of unknown etiology referred from clinics throughout the United States and Canada were studied using a targeted exome approach. Patients ranged in age from 2 to 88 years. Analysis was focused on 441 curated genes associated with ataxia and ataxia-like conditions. RESULTS: Pathogenic and suspected diagnostic variants were identified in 88 of the 170 patients, providing a positive molecular diagnostic rate of 52%. Forty-six different genes were implicated, with the six most commonly mutated genes being SPG7, SYNE1, ADCK3, CACNA1A, ATP1A3, and SPTBN2, which accounted for >40% of the positive cases. In many cases a diagnosis was provided for conditions that were not suspected and resulted in the broadening of the clinical spectrum of several conditions. CONCLUSION: Exome sequencing with targeted analysis provides a high-yield approach for the genetic diagnosis of ataxia-related conditions. This is the largest targeted exome study performed to date in patients with ataxia and ataxia-like conditions and represents patients with a wide range of ataxia phenotypes typically encountered in neurology and genetics clinics.

Congenital hyperinsulinism as the presenting feature of Kabuki syndrome: clinical and molecular characterization of 9 affected individuals.

PURPOSE: Describe the clinical and molecular findings of patients with Kabuki syndrome (KS) who present with hypoglycemia due to congenital hyperinsulinism (HI), and assess the incidence of KS in patients with HI. METHODS: We documented the clinical features and molecular diagnoses of 9 infants with persistent HI and KS via a combination of sequencing and copy-number profiling methodologies. Subsequently, we retrospectively evaluated 100 infants with HI lacking a genetic diagnosis, for causative variants in KS genes. RESULTS: Molecular diagnoses of KS were established by identification of pathogenic variants in KMT2D (n = 5) and KDM6A (n = 4). Among the 100 infants with HI of unknown genetic etiology, a KS diagnosis was uncovered in one patient. CONCLUSIONS: The incidence of HI among patients with KS may be higher than previously reported, and KS may account for as much as 1% of patients diagnosed with HI. As the recognition of dysmorphic features associated with KS is challenging in the neonatal period, we propose KS should be considered in the differential diagnosis of HI. Since HI in patients with KS is well managed medically, a timely recognition of hyperinsulinemic episodes will improve outcomes, and prevent aggravation of the preexisting mild to moderate intellectual disability in KS.

Correction: "Congenital hyperinsulinism as the presenting feature of Kabuki syndrome: clinical and molecular characterization of 10 affected individuals".

The author Diva D. De Leon was incorrectly listed as instead of Diva D. De Leó-Critchlow in the original version of this paper.

Supercomputing for the parallelization of whole genome analysis.

MOTIVATION: The declining cost of generating DNA sequence is promoting an increase in whole genome sequencing, especially as applied to the human genome. Whole genome analysis requires the alignment and comparison of raw sequence data, and results in a computational bottleneck because of limited ability to analyze multiple genomes simultaneously. RESULTS: We now adapted a Cray XE6 supercomputer to achieve the parallelization required for concurrent multiple genome analysis. This approach not only markedly speeds computational time but also results in increased usable sequence per genome. Relying on publically available software, the Cray XE6 has the capacity to align and call variants on 240 whole genomes in ∼50 h. Multisample variant calling is also accelerated. AVAILABILITY AND IMPLEMENTATION: The MegaSeq workflow is designed to harness the size and memory of the Cray XE6, housed at Argonne National Laboratory, for whole genome analysis in a platform designed to better match current and emerging sequencing volume.

Developing OCHROdb, a comprehensive quality checked database of open chromatin regions from sequencing data.

International consortia, including ENCODE, Roadmap Epigenomics, Genomics of Gene Regulation and Blueprint Epigenome have made large-scale datasets of open chromatin regions publicly available. While these datasets are extremely useful for studying mechanisms of gene regulation in disease and cell development, they only identify open chromatin regions in individual samples. A uniform comparison of accessibility of the same regulatory sites across multiple samples is necessary to correlate open chromatin accessibility and expression of target genes across matched cell types. Additionally, although replicate samples are available for majority of cell types, a comprehensive replication-based quality checking of individual regulatory sites is still lacking. We have integrated 828 DNase-I hypersensitive sequencing samples, which we have uniformly processed and then clustered their regulatory regions across all samples. We checked the quality of open-chromatin regions using our replication test. This has resulted in a comprehensive, quality-checked database of Open CHROmatin (OCHROdb) regions for 194 unique human cell types and cell lines which can serve as a reference for gene regulatory studies involving open chromatin. We have made this resource publicly available: users can download the whole database, or query it for their genomic regions of interest and visualize the results in an interactive genome browser.

A computational genomics pipeline for prokaryotic sequencing projects.

MOTIVATION: New sequencing technologies have accelerated research on prokaryotic genomes and have made genome sequencing operations outside major genome sequencing centers routine. However, no off-the-shelf solution exists for the combined assembly, gene prediction, genome annotation and data presentation necessary to interpret sequencing data. The resulting requirement to invest significant resources into custom informatics support for genome sequencing projects remains a major impediment to the accessibility of high-throughput sequence data. RESULTS: We present a self-contained, automated high-throughput open source genome sequencing and computational genomics pipeline suitable for prokaryotic sequencing projects. The pipeline has been used at the Georgia Institute of Technology and the Centers for Disease Control and Prevention for the analysis of Neisseria meningitidis and Bordetella bronchiseptica genomes. The pipeline is capable of enhanced or manually assisted reference-based assembly using multiple assemblers and modes; gene predictor combining; and functional annotation of genes and gene products. Because every component of the pipeline is executed on a local machine with no need to access resources over the Internet, the pipeline is suitable for projects of a sensitive nature. Annotation of virulence-related features makes the pipeline particularly useful for projects working with pathogenic prokaryotes. AVAILABILITY AND IMPLEMENTATION: The pipeline is licensed under the open-source GNU General Public License and available at the Georgia Tech Neisseria Base (http://nbase.biology.gatech.edu/). The pipeline is implemented with a combination of Perl, Bourne Shell and MySQL and is compatible with Linux and other Unix systems.

Frequency of Germline Mutations in Cancer Susceptibility Genes in Malignant Mesothelioma.

PURPOSE: The aim of the current study was to determine the prevalence and clinical predictors of germline cancer susceptibility mutations in patients with malignant mesothelioma (MM). METHODS: We performed targeted capture and next-generation sequencing of 85 cancer susceptibility genes on germline DNA from 198 patients with pleural, peritoneal, and tunica vaginalis MM. RESULTS: Twenty-four germline mutations were identified in 13 genes in 23 (12%) of 198 patients. BAP1 mutations were the most common (n = 6; 25%). The remaining were in genes involved in DNA damage sensing and repair (n = 14), oxygen sensing (n = 2), endosome trafficking (n = 1), and cell growth (n = 1). Pleural site (odds ratio [OR], 0.23; 95% CI, 0.10 to 0.58; P < .01), asbestos exposure (OR, 0.28; 95% CI, 0.11 to 0.72; P < .01), and older age (OR, 0.95; 95% CI, 0.92 to 0.99; P = .01) were associated with decreased odds of carrying a germline mutation, whereas having a second cancer diagnosis (OR, 3.33; 95% CI, 1.22 to 9.07; P = .02) significantly increased the odds. The odds of carrying a mutation in BAP1 (OR, 1,658; 95% CI, 199 to 76,224; P < .001), BRCA2 (OR, 5; 95% CI, 1.0 to 14.7; P = .03), CDKN2A (OR, 53; 95% CI, 6 to 249; P < .001), TMEM127 (OR, 88; 95% CI, 1.7 to 1,105; P = .01), VHL (OR, 51; 95% CI, 1.1 to 453; P = .02), and WT1 (OR, 20; 95% CI, 0.5 to 135; P = .049) were significantly higher in MM cases than in a noncancer control population. Tumor sequencing identified mutations in a homologous recombination pathway gene in 52% (n = 29 of 54). CONCLUSION: A significant proportion of patients with MM carry germline mutations in cancer susceptibility genes, especially those with peritoneal MM, minimal asbestos exposure, young age, and a second cancer diagnosis. These data support clinical germline genetic testing for patients with MM and provide a rationale for additional investigation of the homologous recombination pathway in MM.

Targeted analysis of whole genome sequence data to diagnose genetic cardiomyopathy.

BACKGROUND: Cardiomyopathy is highly heritable but genetically diverse. At present, genetic testing for cardiomyopathy uses targeted sequencing to simultaneously assess the coding regions of >50 genes. New genes are routinely added to panels to improve the diagnostic yield. With the anticipated $1000 genome, it is expected that genetic testing will shift toward comprehensive genome sequencing accompanied by targeted gene analysis. Therefore, we assessed the reliability of whole genome sequencing and targeted analysis to identify cardiomyopathy variants in 11 subjects with cardiomyopathy. METHODS AND RESULTS: Whole genome sequencing with an average of 37× coverage was combined with targeted analysis focused on 204 genes linked to cardiomyopathy. Genetic variants were scored using multiple prediction algorithms combined with frequency data from public databases. This pipeline yielded 1 to 14 potentially pathogenic variants per individual. Variants were further analyzed using clinical criteria and segregation analysis, where available. Three of 3 previously identified primary mutations were detected by this analysis. In 6 subjects for whom the primary mutation was previously unknown, we identified mutations that segregated with disease, had clinical correlates, and had additional pathological correlation to provide evidence for causality. For 2 subjects with previously known primary mutations, we identified additional variants that may act as modifiers of disease severity. In total, we identified the likely pathological mutation in 9 of 11 (82%) subjects. CONCLUSIONS: These pilot data demonstrate that ≈30 to 40× coverage whole genome sequencing combined with targeted analysis is feasible and sensitive to identify rare variants in cardiomyopathy-associated genes.

Neisseria Base: a comparative genomics database for Neisseria meningitidis.

Neisseria meningitidis is an important pathogen, causing life-threatening diseases including meningitis, septicemia and in some cases pneumonia. Genomic studies hold great promise for N. meningitidis research, but substantial database resources are needed to deal with the wealth of information that comes with completely sequenced and annotated genomes. To address this need, we developed Neisseria Base (NBase), a comparative genomics database and genome browser that houses and displays publicly available N. meningitidis genomes. In addition to existing N. meningitidis genome sequences, we sequenced and annotated 19 new genomes using 454 pyrosequencing and the CG-Pipeline genome analysis tool. In total, NBase hosts 27 complete N. meningitidis genome sequences along with their associated annotations. The NBase platform is designed to be scalable, via the underlying database schema and modular code architecture, such that it can readily incorporate new genomes and their associated annotations. The front page of NBase provides user access to these genomes through searching, browsing and downloading. NBase search utility includes BLAST-based sequence similarity searches along with a variety of semantic search options. All genomes can be browsed using a modified version of the GBrowse platform, and a plethora of information on each gene can be viewed using a customized details page. NBase also has a whole-genome comparison tool that yields single-nucleotide polymorphism differences between two user-defined groups of genomes. Using the virulent ST-11 lineage as an example, we demonstrate how this comparative genomics utility can be used to identify novel genomic markers for molecular profiling of N. meningitidis.