Targeted and complete genomic sequencing of the major histocompatibility complex in haplotypic form of individual heterozygous samples.

The human major histocompatibility complex (MHC) is a ∼4 Mb genomic segment on Chromosome 6 that plays a pivotal role in the immune response. Despite its importance in various traits and diseases, its complex nature makes it challenging to accurately characterize on a routine basis. We present a novel approach allowing targeted sequencing and de novo haplotypic assembly of the MHC region in heterozygous samples, using long-read sequencing technologies. Our approach is validated using two reference samples, two family trios, and an African-American sample. We achieved excellent coverage (96.6%-99.9% with at least 30× depth) and high accuracy (99.89%-99.99%) for the different haplotypes. This methodology offers a reliable and cost-effective method for sequencing and fully characterizing the MHC without the need for whole-genome sequencing, facilitating broader studies on this important genomic segment and having significant implications in immunology, genetics, and medicine.

Genetic variant pathogenicity prediction trained using disease-specific clinical sequencing data sets.

Recent advances in DNA sequencing have expanded our understanding of the molecular basis of genetic disorders and increased the utilization of clinical genomic tests. Given the paucity of evidence to accurately classify each variant and the difficulty of experimentally evaluating its clinical significance, a large number of variants generated by clinical tests are reported as variants of unknown clinical significance. Population-scale variant databases can improve clinical interpretation. Specifically, pathogenicity prediction for novel missense variants can use features describing regional variant constraint. Constrained genomic regions are those that have an unusually low variant count in the general population. Computational methods have been introduced to capture these regions and incorporate them into pathogenicity classifiers, but these methods have yet to be compared on an independent clinical variant data set. Here, we introduce one variant data set derived from clinical sequencing panels and use it to compare the ability of different genomic constraint metrics to determine missense variant pathogenicity. This data set is compiled from 17,071 patients surveyed with clinical genomic sequencing for cardiomyopathy, epilepsy, or RASopathies. We further use this data set to demonstrate the necessity of disease-specific classifiers and to train PathoPredictor, a disease-specific ensemble classifier of pathogenicity based on regional constraint and variant-level features. PathoPredictor achieves an average precision >90% for variants from all 99 tested disease genes while approaching 100% accuracy for some genes. The accumulation of larger clinical variant training data sets can significantly enhance their performance in a disease- and gene-specific manner.

Evaluating the impact of in silico predictors on clinical variant classification.

PURPOSE: According to the American College of Medical Genetics and Genomics/Association of Medical Pathology (ACMG/AMP) guidelines, in silico evidence is applied at the supporting strength level for pathogenic (PP3) and benign (BP4) evidence. Although PP3 is commonly used, less is known about the effect of these criteria on variant classification outcomes. METHODS: A total of 727 missense variants curated by Clinical Genome Resource expert groups were analyzed to determine how often PP3 and BP4 were applied and their impact on variant classification. The ACMG/AMP categorical system of variant classification was compared with a quantitative point-based system. The pathogenicity likelihood ratios of REVEL, VEST, FATHMM, and MPC were calibrated using a gold standard set of 237 pathogenic and benign variants (classified independent of the PP3/BP4 criteria). RESULTS: The PP3 and BP4 criteria were applied by Variant Curation Expert Panels to 55% of missense variants. Application of those criteria changed the classification of 15% of missense variants for which either criterion was applied. The point-based system resolved borderline classifications. REVEL and VEST performed best at a strength level consistent with moderate evidence. CONCLUSION: We show that in silico criteria are commonly applied and often affect the final variant classifications. When appropriate thresholds for in silico predictors are established, our results show that PP3 and BP4 can be used at a moderate strength.

AnthOligo: automating the design of oligonucleotides for capture/enrichment technologies.

SUMMARY: A number of methods have been devised to address the need for targeted genomic resequencing. One of these methods, region-specific extraction (RSE) is characterized by the capture of long DNA fragments (15-20 kb) by magnetic beads, after enzymatic extension of oligonucleotides hybridized to selected genomic regions. Facilitating the selection of the most appropriate capture oligos for targeting a region of interest, satisfying the properties of temperature (Tm) and entropy (ΔG), while minimizing the formation of primer-dimers in a pooled experiment, is therefore necessary. Manual design and selection of oligos becomes very challenging, complicated by factors such as length of the target region and number of targeted regions. Here we describe, AnthOligo, a web-based application developed to optimally automate the process of generation of oligo sequences used to target and capture the continuum of large and complex genomic regions. Apart from generating oligos for RSE, this program may have wider applications in the design of customizable internal oligos to be used as baits for gene panel analysis or even probes for large-scale comparative genomic hybridization array processes. AnthOligo was tested by capturing the Major Histocompatibility Complex (MHC) of a random sample.The application provides users with a simple interface to upload an input file in BED format and customize parameters for each task. The task of probe design in AnthOligo commences when a user uploads an input file and concludes with the generation of a result-set containing an optimal set of region-specific oligos. AnthOligo is currently available as a public web application with URL: http://antholigo.chop.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Diagnosing Cornelia de Lange syndrome and related neurodevelopmental disorders using RNA sequencing.

PURPOSE: Neurodevelopmental disorders represent a frequent indication for clinical exome sequencing. Fifty percent of cases, however, remain undiagnosed even upon exome reanalysis. Here we show RNA sequencing (RNA-seq) on human B-lymphoblastoid cell lines (LCL) is highly suitable for neurodevelopmental Mendelian gene testing and demonstrate the utility of this approach in suspected cases of Cornelia de Lange syndrome (CdLS). METHODS: Genotype-Tissue Expression project transcriptome data for LCL, blood, and brain were assessed for neurodevelopmental Mendelian gene expression. Detection of abnormal splicing and pathogenic variants in these genes was performed with a novel RNA-seq diagnostic pipeline and using a validation CdLS-LCL cohort (n = 10) and test cohort of patients who carry a clinical diagnosis of CdLS but negative genetic testing (n = 5). RESULTS: LCLs share isoform diversity of brain tissue for a large subset of neurodevelopmental genes and express 1.8-fold more of these genes compared with blood (LCL, n = 1706; whole blood, n = 917). This enables testing of more than 1000 genetic syndromes. The RNA-seq pipeline had 90% sensitivity for detecting pathogenic events and revealed novel diagnoses such as abnormal splice products in NIPBL and pathogenic coding variants in BRD4 and ANKRD11. CONCLUSION: The LCL transcriptome enables robust frontline and/or reflexive diagnostic testing for neurodevelopmental disorders.

Using Machine Learning to Identify True Somatic Variants from Next-Generation Sequencing.

BACKGROUND: Molecular profiling has become essential for tumor risk stratification and treatment selection. However, cancer genome complexity and technical artifacts make identification of real variants a challenge. Currently, clinical laboratories rely on manual screening, which is costly, subjective, and not scalable. We present a machine learning-based method to distinguish artifacts from bona fide single-nucleotide variants (SNVs) detected by next-generation sequencing from nonformalin-fixed paraffin-embedded tumor specimens. METHODS: A cohort of 11278 SNVs identified through clinical sequencing of tumor specimens was collected and divided into training, validation, and test sets. Each SNV was manually inspected and labeled as either real or artifact as part of clinical laboratory workflow. A 3-class (real, artifact, and uncertain) model was developed on the training set, fine-tuned with the validation set, and then evaluated on the test set. Prediction intervals reflecting the certainty of the classifications were derived during the process to label "uncertain" variants. RESULTS: The optimized classifier demonstrated 100% specificity and 97% sensitivity over 5587 SNVs of the test set. Overall, 1252 of 1341 true-positive variants were identified as real, 4143 of 4246 false-positive calls were deemed artifacts, whereas only 192 (3.4%) SNVs were labeled as "uncertain," with zero misclassification between the true positives and artifacts in the test set. CONCLUSIONS: We presented a computational classifier to identify variant artifacts detected from tumor sequencing. Overall, 96.6% of the SNVs received definitive labels and thus were exempt from manual review. This framework could improve quality and efficiency of the variant review process in clinical laboratories.

A mutation update for the PCDH19 gene causing early-onset epilepsy in females with an unusual expression pattern.

The PCDH19 gene consists of six exons encoding a 1,148 amino acid transmembrane protein, Protocadherin 19, which is involved in brain development. Heterozygous pathogenic variants in this gene are inherited in an unusual X-linked dominant pattern in which heterozygous females are affected, while hemizygous males are typically unaffected, although they pass on the pathogenic variant to each affected daughter. PCDH19-related disorder is known to cause early-onset epilepsy in females characterized by seizure clusters exacerbated by fever and in most cases, onset is within the first year of life. This condition was initially described in 1971 and in 2008 PCDH19 was identified as the underlying genetic etiology. This condition is the result of pathogenic loss-of-function variants that may be de novo or inherited from an affected mother or unaffected father and cellular interference has been hypothesized to be the culprit. Heterozygous females are symptomatic because of the presence of both wild-type and mutant cells that interfere with one another due to the production of different surface proteins, whereas nonmosaic hemizygous males produce a homogenous population of cells. Here, we review novel pathogenic variants in the PCDH19 gene since 2012 to date, and summarize any genotype-phenotype correlations.

AUDIOME: a tiered exome sequencing-based comprehensive gene panel for the diagnosis of heterogeneous nonsyndromic sensorineural hearing loss.

PURPOSE: Hereditary hearing loss is highly heterogeneous. To keep up with rapidly emerging disease-causing genes, we developed the AUDIOME test for nonsyndromic hearing loss (NSHL) using an exome sequencing (ES) platform and targeted analysis for the curated genes. METHODS: A tiered strategy was implemented for this test. Tier 1 includes combined Sanger and targeted deletion analyses of the two most common NSHL genes and two mitochondrial genes. Nondiagnostic tier 1 cases are subjected to ES and array followed by targeted analysis of the remaining AUDIOME genes. RESULTS: ES resulted in good coverage of the selected genes with 98.24% of targeted bases at >15 ×. A fill-in strategy was developed for the poorly covered regions, which generally fell within GC-rich or highly homologous regions. Prospective testing of 33 patients with NSHL revealed a diagnosis in 11 (33%) and a possible diagnosis in 8 cases (24.2%). Among those, 10 individuals had variants in tier 1 genes. The ES data in the remaining nondiagnostic cases are readily available for further analysis. CONCLUSION: The tiered and ES-based test provides an efficient and cost-effective diagnostic strategy for NSHL, with the potential to reflex to full exome to identify causal changes outside of the AUDIOME test.

Correction: Novel findings with reassessment of exome data: implications for validation testing and interpretation of genomic data.

In the published version of this article, the degree of author Bo Zhang was incorrectly listed as PhD. The correct degree is BS.

Novel findings with reassessment of exome data: implications for validation testing and interpretation of genomic data.

PurposeThe objective of this study was to assess the ability of our laboratory's exome-sequencing test to detect known and novel sequence variants and identify the critical factors influencing the interpretation of a clinical exome test.MethodsWe developed a two-tiered validation strategy: (i) a method-based approach that assessed the ability of our exome test to detect known variants using a reference HapMap sample, and (ii) an interpretation-based approach that assessed our relative ability to identify and interpret disease-causing variants, by analyzing and comparing the results of 19 randomly selected patients previously tested by external laboratories.ResultsWe demonstrate that this approach is reproducible with >99% analytical sensitivity and specificity for single-nucleotide variants and indels <10 bp. Our findings were concordant with the reference laboratories in 84% of cases. A new molecular diagnosis was applied to three cases, including discovery of two novel candidate genes.ConclusionWe provide an assessment of critical areas that influence interpretation of an exome test, including comprehensive phenotype capture, assessment of clinical overlap, availability of parental data, and the addressing of limitations in database updates. These results can be used to inform improvements in phenotype-driven interpretation of medical exomes in clinical and research settings.

Correction: Novel findings with reassessment of exome data: implications for validation testing and interpretation of genomic data.

In the published version of this article, the name of the 18th author was misspelled as Minjie Lou. The correct name is Minjie Luo. The authors regret the error.

Utility and limitations of exome sequencing as a genetic diagnostic tool for children with hearing loss.

PURPOSE: Hearing loss (HL) is the most common sensory disorder in children. Prompt molecular diagnosis may guide screening and management, especially in syndromic cases when HL is the single presenting feature. Exome sequencing (ES) is an appealing diagnostic tool for HL as the genetic causes are highly heterogeneous. METHODS: ES was performed on a prospective cohort of 43 probands with HL. Sequence data were analyzed for primary and secondary findings. Capture and coverage analysis was performed for genes and variants associated with HL. RESULTS: The diagnostic rate using ES was 37.2%, compared with 15.8% for the clinical HL panel. Secondary findings were discovered in three patients. For 247 genes associated with HL, 94.7% of the exons were targeted for capture and 81.7% of these exons were covered at 20× or greater. Further analysis of 454 randomly selected HL-associated variants showed that 89% were targeted for capture and 75% were covered at a read depth of at least 20×. CONCLUSION: ES has an improved yield compared with clinical testing and may capture diagnoses not initially considered due to subtle clinical phenotypes. Technical challenges were identified, including inadequate capture and coverage of HL genes. Additional considerations of ES include secondary findings, cost, and turnaround time.

Characterizing reduced coverage regions through comparison of exome and genome sequencing data across 10 centers.

PURPOSE: As massively parallel sequencing is increasingly being used for clinical decision making, it has become critical to understand parameters that affect sequencing quality and to establish methods for measuring and reporting clinical sequencing standards. In this report, we propose a definition for reduced coverage regions and describe a set of standards for variant calling in clinical sequencing applications. METHODS: To enable sequencing centers to assess the regions of poor sequencing quality in their own data, we optimized and used a tool (ExCID) to identify reduced coverage loci within genes or regions of particular interest. We used this framework to examine sequencing data from 500 patients generated in 10 projects at sequencing centers in the National Human Genome Research Institute/National Cancer Institute Clinical Sequencing Exploratory Research Consortium. RESULTS: This approach identified reduced coverage regions in clinically relevant genes, including known clinically relevant loci that were uniquely missed at individual centers, in multiple centers, and in all centers. CONCLUSION: This report provides a process road map for clinical sequencing centers looking to perform similar analyses on their data.

Using large sequencing data sets to refine intragenic disease regions and prioritize clinical variant interpretation.

PURPOSE: Classification of novel variants is a major challenge facing the widespread adoption of comprehensive clinical genomic sequencing and the field of personalized medicine in general. This is largely because most novel variants do not have functional, genetic, or population data to support their clinical classification. METHODS: To improve variant interpretation, we leveraged the Exome Aggregation Consortium (ExAC) data set (N = ~60,000) as well as 7,000 clinically curated variants in 132 genes identified in more than 11,000 probands clinically tested for cardiomyopathies, rasopathies, hearing loss, or connective tissue disorders to perform a systematic evaluation of domain level disease associations. RESULTS: We statistically identify regions that are most sensitive to functional variation in the general population and also most commonly impacted in symptomatic individuals. Our data show that a significant number of exons and domains in genes strongly associated with disease can be defined as disease-sensitive or disease-tolerant, leading to potential reclassification of at least 26% (450 out of 1,742) of variants of uncertain clinical significance in the 132 genes. CONCLUSION: This approach leverages domain functional annotation and associated disease in each gene to prioritize candidate disease variants, increasing the sensitivity and specificity of novel variant assessment within these genes.Genet Med advance online publication 22 September 2016.

Exome sequencing analysis reveals variants in primary immunodeficiency genes in patients with very early onset inflammatory bowel disease.

BACKGROUND & AIMS: Very early onset inflammatory bowel disease (VEO-IBD), IBD diagnosed at 5 years of age or younger, frequently presents with a different and more severe phenotype than older-onset IBD. We investigated whether patients with VEO-IBD carry rare or novel variants in genes associated with immunodeficiencies that might contribute to disease development. METHODS: Patients with VEO-IBD and parents (when available) were recruited from the Children's Hospital of Philadelphia from March 2013 through July 2014. We analyzed DNA from 125 patients with VEO-IBD (age, 3 wk to 4 y) and 19 parents, 4 of whom also had IBD. Exome capture was performed by Agilent SureSelect V4, and sequencing was performed using the Illumina HiSeq platform. Alignment to human genome GRCh37 was achieved followed by postprocessing and variant calling. After functional annotation, candidate variants were analyzed for change in protein function, minor allele frequency less than 0.1%, and scaled combined annotation-dependent depletion scores of 10 or less. We focused on genes associated with primary immunodeficiencies and related pathways. An additional 210 exome samples from patients with pediatric IBD (n = 45) or adult-onset Crohn's disease (n = 20) and healthy individuals (controls, n = 145) were obtained from the University of Kiel, Germany, and used as control groups. RESULTS: Four hundred genes and regions associated with primary immunodeficiency, covering approximately 6500 coding exons totaling more than 1 Mbp of coding sequence, were selected from the whole-exome data. Our analysis showed novel and rare variants within these genes that could contribute to the development of VEO-IBD, including rare heterozygous missense variants in IL10RA and previously unidentified variants in MSH5 and CD19. CONCLUSIONS: In an exome sequence analysis of patients with VEO-IBD and their parents, we identified variants in genes that regulate B- and T-cell functions and could contribute to pathogenesis. Our analysis could lead to the identification of previously unidentified IBD-associated variants.

Utility and limitations of exome sequencing as a genetic diagnostic tool for conditions associated with pediatric sudden cardiac arrest/sudden cardiac death.

BACKGROUND: Conditions associated with sudden cardiac arrest/death (SCA/D) in youth often have a genetic etiology. While SCA/D is uncommon, a pro-active family screening approach may identify these inherited structural and electrical abnormalities prior to symptomatic events and allow appropriate surveillance and treatment. This study investigated the diagnostic utility of exome sequencing (ES) by evaluating the capture and coverage of genes related to SCA/D. METHODS: Samples from 102 individuals (13 with known molecular etiologies for SCA/D, 30 individuals without known molecular etiologies for SCA/D and 59 with other conditions) were analyzed following exome capture and sequencing at an average read depth of 100X. Reads were mapped to human genome GRCh37 using Novoalign, and post-processing and analysis was done using Picard and GATK. A total of 103 genes (2,190 exons) related to SCA/D were used as a primary filter. An additional 100 random variants within the targeted genes associated with SCA/D were also selected and evaluated for depth of sequencing and coverage. Although the primary objective was to evaluate the adequacy of depth of sequencing and coverage of targeted SCA/D genes and not for primary diagnosis, all patients who had SCA/D (known or unknown molecular etiologies) were evaluated with the project's variant analysis pipeline to determine if the molecular etiologies could be successfully identified. RESULTS: The majority of exons (97.6 %) were captured and fully covered on average at minimum of 20x sequencing depth. The proportion of unique genomic positions reported within poorly covered exons remained small (4 %). Exonic regions with less coverage reflect the need to enrich these areas to improve coverage. Despite limitations in coverage, we identified 100 % of cases with a prior known molecular etiology for SCA/D, and analysis of an additional 30 individuals with SCA/D but no known molecular etiology revealed a diagnostic answer in 5/30 (17 %). We also demonstrated 95 % of 100 randomly selected reported variants within our targeted genes would have been picked up on ES based on our coverage analysis. CONCLUSIONS: ES is a helpful clinical diagnostic tool for SCA/D given its potential to successfully identify a molecular diagnosis, but clinicians should be aware of limitations of available platforms from technical and diagnostic perspectives.

Exome sequencing expands the mechanism of SOX5-associated intellectual disability: A case presentation with review of sox-related disorders.

The SOX5 haploinsufficiency syndrome is characterized by global developmental delay, intellectual disability, language and motor impairment, and distinct facial features. The smallest deletion encompassed only one gene, SOX5 (OMIM 604975), indicating that haploinsufficiency of SOX5 contributes to neuro developmental delay. Although multiple deletions of the SOX5 gene have been reported in patients, none are strictly intragenic point mutations. Here, we report the identification of a de novo loss of function variant in SOX5 identified through whole exome sequencing. The proband presented with moderate developmental delay, bilateral optic atrophy, mildly dysmorphic features, and scoliosis, which correlates with the previously-described SOX5-associated phenotype. These results broaden the diagnostic spectrum of SOX5-related intellectual disability. Furthermore it highlights the utility of exome sequencing in establishing an etiological basis in clinically and genetically heterogeneous conditions such as intellectual disability.

The Impact of Patterns in Linkage Disequilibrium and Sequencing Quality on the Imprint of Balancing Selection.

Regions under balancing selection are characterized by dense polymorphisms and multiple persistent haplotypes, along with other sequence complexities. Successful identification of these patterns depends on both the statistical approach and the quality of sequencing. To address this challenge, at first, a new statistical method called LD-ABF was developed, employing efficient Bayesian techniques to effectively test for balancing selection. LD-ABF demonstrated the most robust detection of selection in a variety of simulation scenarios, compared against a range of existing tests/tools (Tajima's D, HKA, Dng, BetaScan, and BalLerMix). Furthermore, the impact of the quality of sequencing on detection of balancing selection was explored, as well, using: (i) SNP genotyping and exome data, (ii) targeted high-resolution HLA genotyping (IHIW), and (iii) whole-genome long-read sequencing data (Pangenome). In the analysis of SNP genotyping and exome data, we identified known targets and 38 new selection signatures in genes not previously linked to balancing selection. To further investigate the impact of sequencing quality on detection of balancing selection, a detailed investigation of the MHC was performed with high-resolution HLA typing data. Higher quality sequencing revealed the HLA-DQ genes consistently demonstrated strong selection signatures otherwise not observed from the sparser SNP array and exome data. The HLA-DQ selection signature was also replicated in the Pangenome samples using considerably less samples but, with high-quality long-read sequence data. The improved statistical method, coupled with higher quality sequencing, leads to more consistent identification of selection and enhanced localization of variants under selection, particularly in complex regions.

Efficient digest of high-throughput sequencing data in a reproducible report.

BACKGROUND: High-throughput sequencing (HTS) technologies are spearheading the accelerated development of biomedical research. Processing and summarizing the large amount of data generated by HTS presents a non-trivial challenge to bioinformatics. A commonly adopted standard is to store sequencing reads aligned to a reference genome in SAM (Sequence Alignment/Map) or BAM (Binary Alignment/Map) files. Quality control of SAM/BAM files is a critical checkpoint before downstream analysis. The goal of the current project is to facilitate and standardize this process. RESULTS: We developed bamchop, a robust program to efficiently summarize key statistical metrics of HTS data stored in BAM files, and to visually present the results in a formatted report. The report documents information about various aspects of HTS data, such as sequencing quality, mapping to a reference genome, sequencing coverage, and base frequency. Bamchop uses the R language and Bioconductor packages to calculate statistical matrices and the Sweave utility and associated LaTeX markup for documentation. Bamchop's efficiency and robustness were tested on BAM files generated by local sequencing facilities and the 1000 Genomes Project. Source code, instruction and example reports of bamchop are freely available from https://github.com/CBMi-BiG/bamchop. CONCLUSIONS: Bamchop enables biomedical researchers to quickly and rigorously evaluate HTS data by providing a convenient synopsis and user-friendly reports.

Molecular Diagnostic Outcomes from 700 Cases: What Can We Learn from a Retrospective Analysis of Clinical Exome Sequencing?

Clinical exome sequencing (CES) aids in the diagnosis of rare genetic disorders. Herein, we report the molecular diagnostic yield and spectrum of genetic alterations contributing to disease in 700 pediatric cases analyzed at the Children's Hospital of Philadelphia. The overall diagnostic yield was 23%, with three cases having more than one molecular diagnosis and 2.6% having secondary/additional findings. A candidate gene finding was reported in another 8.4% of cases. The clinical indications with the highest diagnostic yield were neurodevelopmental disorders (including seizures), whereas immune- and oncology-related indications were negatively associated with molecular diagnosis. The rapid expansion of knowledge regarding the genome's role in human disease necessitates reanalysis of CES samples. To capture these new discoveries, a subset of cases (n = 240) underwent reanalysis, with an increase in diagnostic yield. We describe our experience reporting CES results in a pediatric setting, including reporting of secondary findings, reporting newly discovered genetic conditions, and revisiting negative test results. Finally, we highlight the challenges associated with implementing critical updates to the CES workflow. Although these updates are necessary, they demand an investment of time and resources from the laboratory. In summary, these data demonstrate the clinical utility of exome sequencing and reanalysis, while highlighting the critical considerations for continuous improvement of a CES test in a clinical laboratory.