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Virtually all genome sequencing efforts in national biobanks, complex and Mendelian disease programs, and medical genetic initiatives are reliant upon short-read whole-genome sequencing (srWGS), which presents challenges for the detection of structural variants (SVs) relative to emerging long-read WGS (lrWGS) technologies. Given this ubiquity of srWGS in large-scale genomics initiatives, we sought to establish expectations for routine SV detection from this data type by comparison with lrWGS assembly, as well as to quantify the genomic properties and added value of SVs uniquely accessible to each technology. Analyses from the Human Genome Structural Variation Consortium (HGSVC) of three families captured ~11,000 SVs per genome from srWGS and ~25,000 SVs per genome from lrWGS assembly. Detection power and precision for SV discovery varied dramatically by genomic context and variant class: 9.7% of the current GRCh38 reference is defined by segmental duplication (SD) and simple repeat (SR), yet 91.4% of deletions that were specifically discovered by lrWGS localized to these regions. Across the remaining 90.3% of reference sequence, we observed extremely high (93.8%) concordance between technologies for deletions in these datasets. In contrast, lrWGS was superior for detection of insertions across all genomic contexts. Given that non-SD/SR sequences encompass 95.9% of currently annotated disease-associated exons, improved sensitivity from lrWGS to discover novel pathogenic deletions in these currently interpretable genomic regions is likely to be incremental. However, these analyses highlight the considerable added value of assembly-based lrWGS to create new catalogs of insertions and transposable elements, as well as disease-associated repeat expansions in genomic sequences that were previously recalcitrant to routine assessment.

JAG2 encodes the Notch ligand Jagged2. The conserved Notch signaling pathway contributes to the development and homeostasis of multiple tissues, including skeletal muscle. We studied an international cohort of 23 individuals with genetically unsolved muscular dystrophy from 13 unrelated families. Whole-exome sequencing identified rare homozygous or compound heterozygous JAG2 variants in all 13 families. The identified bi-allelic variants include 10 missense variants that disrupt highly conserved amino acids, a nonsense variant, two frameshift variants, an in-frame deletion, and a microdeletion encompassing JAG2. Onset of muscle weakness occurred from infancy to young adulthood. Serum creatine kinase (CK) levels were normal or mildly elevated. Muscle histology was primarily dystrophic. MRI of the lower extremities revealed a distinct, slightly asymmetric pattern of muscle involvement with cores of preserved and affected muscles in quadriceps and tibialis anterior, in some cases resembling patterns seen in POGLUT1-associated muscular dystrophy. Transcriptome analysis of muscle tissue from two participants suggested misregulation of genes involved in myogenesis, including PAX7. In complementary studies, Jag2 downregulation in murine myoblasts led to downregulation of multiple components of the Notch pathway, including Megf10. Investigations in Drosophila suggested an interaction between Serrate and Drpr, the fly orthologs of JAG1/JAG2 and MEGF10, respectively. In silico analysis predicted that many Jagged2 missense variants are associated with structural changes and protein misfolding. In summary, we describe a muscular dystrophy associated with pathogenic variants in JAG2 and evidence suggests a disease mechanism related to Notch pathway dysfunction.

Cerebellar ataxia, neuropathy and vestibular areflexia syndrome (CANVAS) is a progressive late-onset, neurological disease. Recently, a pentanucleotide expansion in intron 2 of RFC1 was identified as the genetic cause of CANVAS. We screened an Asian-Pacific cohort for CANVAS and identified a novel RFC1 repeat expansion motif, (ACAGG)exp, in three affected individuals. This motif was associated with additional clinical features including fasciculations and elevated serum creatine kinase. These features have not previously been described in individuals with genetically-confirmed CANVAS. Haplotype analysis showed our patients shared the same core haplotype as previously published, supporting the possibility of a single origin of the RFC1 disease allele. We analysed data from >26 000 genetically diverse individuals in gnomAD to show enrichment of (ACAGG) in non-European populations.

Exome and genome sequencing have become the tools of choice for rare disease diagnosis, leading to large amounts of data available for analyses. To identify causal variants in these datasets, powerful filtering and decision support tools that can be efficiently used by clinicians and researchers are required. To address this need, we developed seqr - an open source, web-based tool for family-based monogenic disease analysis that allows researchers to work collaboratively to search and annotate genomic callsets. To date, seqr is being used in several research pipelines and one clinical diagnostic lab. In our own experience through the Broad Institute Center for Mendelian Genomics, seqr has enabled analyses of over 10,000 families, supporting the diagnosis of more than 3,800 individuals with rare disease and discovery of over 300 novel disease genes. Here, we describe a framework for genomic analysis in rare disease that leverages seqr’s capabilities for variant filtration, annotation, and causal variant identification, as well as support for research collaboration and data sharing. The seqr platform is available as open-source software, allowing low-cost participation in rare disease research, and a community effort to support diagnosis and gene discovery in rare disease.

Background Expansions of short tandem repeats are the cause of many neurogenetic disorders including familial amyotrophic lateral sclerosis, Huntington disease, and many others. Multiple methods have been recently developed that can identify repeat expansions in whole genome or exome sequencing data. Despite the widely recognized need for visual assessment of variant calls in clinical settings, current computational tools lack the ability to produce such visualizations for repeat expansions. Expanded repeats are difficult to visualize because they correspond to large insertions relative to the reference genome and involve many misaligning and ambiguously aligning reads. Results We implemented REViewer, a computational method for visualization of sequencing data in genomic regions containing long repeat expansions and FlipBook, a companion image viewer designed for manual curation of large collections of REViewer images. To generate a read pileup, REViewer reconstructs local haplotype sequences and distributes reads to these haplotypes in a way that is most consistent with the fragment lengths and evenness of read coverage. To create appropriate training materials for onboarding new users, we performed a concordance study involving 12 scientists involved in short tandem repeat research. We used the results of this study to create a user guide that describes the basic principles of using REViewer as well as a guide to the typical features of read pileups that correspond to low confidence repeat genotype calls. Additionally, we demonstrated that REViewer can be used to annotate clinically relevant repeat interruptions by comparing visual assessment results of 44 FMR1 repeat alleles with the results of triplet repeat primed PCR. For 38 of these alleles, the results of visual assessment were consistent with triplet repeat primed PCR. Conclusions Read pileup plots generated by REViewer offer an intuitive way to visualize sequencing data in regions containing long repeat expansions. Laboratories can use REViewer and FlipBook to assess the quality of repeat genotype calls as well as to visually detect interruptions or other imperfections in the repeat sequence and the surrounding flanking regions. REViewer and FlipBook are available under open-source licenses at https://github.com/illumina/REViewer and https://github.com/broadinstitute/flipbook respectively.

Hundreds of thousands of genetic variants have been reported to cause severe monogenic diseases, but the probability that a variant carrier develops the disease (termed penetrance) is unknown for virtually all of them. Additionally, the clinical utility of common polygenetic variation remains uncertain. Using exome sequencing from 77,184 adult individuals (38,618 multi-ancestral individuals from a type 2 diabetes case-control study and 38,566 participants from the UK Biobank, for whom genotype array data were also available), we apply clinical standard-of-care gene variant curation for eight monogenic metabolic conditions. Rare variants causing monogenic diabetes and dyslipidemias display effect sizes significantly larger than the top 1% of the corresponding polygenic scores. Nevertheless, penetrance estimates for monogenic variant carriers average 60% or lower for most conditions. We assess epidemiologic and genetic factors contributing to risk prediction in monogenic variant carriers, demonstrating that inclusion of polygenic variation significantly improves biomarker estimation for two monogenic dyslipidemias., Penetrance of variants in monogenic disease and clinical utility of common polygenic variation has not been well explored on a large-scale. Here, the authors use exome sequencing data from 77,184 individuals to generate penetrance estimates and assess the utility of polygenic variation in risk prediction of monogenic variants.

Hundreds of thousands of genetic variants have been reported to cause severe monogenic diseases, but the probability that a variant carrier will develop the disease (termed penetrance) is unknown for virtually all of them. Additionally, the clinical utility of common polygenetic variation remains uncertain. Using exome sequencing from 77,184 adult individuals (38,618 multi-ancestral individuals from a type 2 diabetes case-control study and 38,566 participants from the UK Biobank, for whom genotype array data were also available), we applied clinical standard-of-care gene variant curation for eight monogenic metabolic conditions. Rare variants causing monogenic diabetes and dyslipidemias displayed effect sizes significantly larger than the top 1% of the corresponding polygenic scores. Nevertheless, penetrance estimates for monogenic variant carriers averaged below 60% in both studies for all conditions except monogenic diabetes. We assessed additional epidemiologic and genetic factors contributing to risk prediction, demonstrating that inclusion of common polygenic variation significantly improved biomarker estimation for two monogenic dyslipidemias.

Worldwide, hundreds of thousands of humans have had their genomes or exomes sequenced, and access to the resulting data sets can provide valuable information for variant interpretation and understanding gene function. Here, we present a lightweight, flexible browser framework to display large population datasets of genetic variation. We demonstrate its use for exome sequence data from 60 706 individuals in the Exome Aggregation Consortium (ExAC). The ExAC browser provides gene- and transcript-centric displays of variation, a critical view for clinical applications. Additionally, we provide a variant display, which includes population frequency and functional annotation data as well as short read support for the called variant. This browser is open-source, freely available at http://exac.broadinstitute.org, and has already been used extensively by clinical laboratories worldwide.

ObjectiveTo describe the diagnostic utility of whole-genome sequencing and RNA studies in boys with suspected dystrophinopathy, for whom multiplex ligation-dependent probe amplification and exomic parallel sequencing failed to yield a genetic diagnosis, and to use remnant normal DMD splicing in 3 families to define critical levels of wild-type dystrophin bridging clinical spectrums of Duchenne to myalgia.MethodsExome, genome, and/or muscle RNA sequencing was performed for 7 males with elevated creatine kinase. PCR of muscle-derived complementary DNA (cDNA) studied consequences for DMD premessenger RNA (pre-mRNA) splicing. Quantitative Western blot was used to determine levels of dystrophin, relative to control muscle.ResultsSplice-altering intronic single nucleotide variants or structural rearrangements in DMD were identified in all 7 families. Four individuals, with abnormal splicing causing a premature stop codon and nonsense-mediated decay, expressed remnant levels of normally spliced DMD mRNA. Quantitative Western blot enabled correlation of wild-type dystrophin and clinical severity, with 0%–5% dystrophin conferring a Duchenne phenotype, 10% ± 2% a Becker phenotype, and 15% ± 2% dystrophin associated with myalgia without manifesting weakness.ConclusionsWhole-genome sequencing relied heavily on RNA studies to identify DMD splice-altering variants. Short-read RNA sequencing was regularly confounded by the effectiveness of nonsense-mediated mRNA decay and low read depth of the giant DMD mRNA. PCR of muscle cDNA provided a simple, yet informative approach. Highly relevant to genetic therapies for dystrophinopathies, our data align strongly with previous studies of mutant dystrophin in Becker muscular dystrophy, with the collective conclusion that a fractional increase in levels of normal dystrophin between 5% and 20% is clinically significant.

As part of a broader collaborative network of exome sequencing studies, we developed a jointly called data set of 5,685 Ashkenazi Jewish exomes. We make publicly available a resource of site and allele frequencies, which should serve as a reference for medical genetics in the Ashkenazim (hosted in part at https://ibd.broadinstitute.org, also available in gnomAD at http://gnomad.broadinstitute.org). We estimate that 34% of protein-coding alleles present in the Ashkenazi Jewish population at frequencies greater than 0.2% are significantly more frequent (mean 15-fold) than their maximum frequency observed in other reference populations. Arising via a well-described founder effect approximately 30 generations ago, this catalog of enriched alleles can contribute to differences in genetic risk and overall prevalence of diseases between populations. As validation we document 148 AJ enriched protein-altering alleles that overlap with "pathogenic" ClinVar alleles (table available at https://github.com/macarthur-lab/clinvar/blob/master/output/clinvar.tsv), including those that account for 10–100 fold differences in prevalence between AJ and non-AJ populations of some rare diseases, especially recessive conditions, including Gaucher disease (GBA, p.Asn409Ser, 8-fold enrichment); Canavan disease (ASPA, p.Glu285Ala, 12-fold enrichment); and Tay-Sachs disease (HEXA, c.1421+1G>C, 27-fold enrichment; p.Tyr427IlefsTer5, 12-fold enrichment). We next sought to use this catalog, of well-established relevance to Mendelian disease, to explore Crohn's disease, a common disease with an estimated two to four-fold excess prevalence in AJ. We specifically attempt to evaluate whether strong acting rare alleles, particularly protein-truncating or otherwise large effect-size alleles, enriched by the same founder-effect, contribute excess genetic risk to Crohn's disease in AJ, and find that ten rare genetic risk factors in NOD2 and LRRK2 are enriched in AJ (p < 0.005), including several novel contributing alleles, show evidence of association to CD. Independently, we find that genomewide common variant risk defined by GWAS shows a strong difference between AJ and non-AJ European control population samples (0.97 s.d. higher, p, Author summary The Ashkenazim are a people with ancestry in northern-European Jewish groups. A founder effect caused a bottleneck in this population approximately one thousand years ago, resulting in a group of enriched alleles in their genetic makeup. A higher documented prevalence of Crohn’s Disease in the Ashkenazim indicates that some enriched alleles may confer risk of having this disease. By studying which genes are enriched, and which of these contribute to Crohn’s Disease risk, we are better able to understand the genetic architecture of the affected population, and of the disease itself. Further, we are able to develop a resource containing tables of significantly enriched alleles that are known or suspected to contribute to other disease.

The interpretation of genetic variants identified during clinical sequencing has come to rely heavily on reference population databases such as the Exome Aggregation Consortium (ExAC). Genuinely pathogenic variants, particularly in genes associated with severe autosomal dominant conditions, are assumed to be absent or extremely rare in these databases. Clinical exome sequencing of a six-year-old female patient with seizures, global developmental delay, dysmorphic features and failure to thrive identified an ASXL1 variant that was previously reported as causative of Bohring-Opitz syndrome (BOS). Surprisingly, the variant was observed seven times in the ExAC database, presumably in individuals without BOS. Although the BOS phenotype matched the presentation of the patient, the presence of the variant in reference population databases introduced ambiguity in result interpretation. Interrogation of the literature revealed that acquired somatic mosaicism of ASXL1 variants (including known pathogenic variants) during hematopoietic clonal expansion may be concomitant with aging in healthy individuals. We examined all high quality ASXL1 predicted truncating variant calls in the ExAC database and determined the majority could be attributed to this phenomenon. Failure to consider somatic mosaicism may lead to the inaccurate assumption that conditions like Bohring-Opitz syndrome have reduced penetrance, or the misclassification of potentially pathogenic variants.

SummaryLarge-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) sequence data for 60,706 individuals of diverse ethnicities generated as part of the Exome Aggregation Consortium (ExAC). The resulting catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We show that this catalogue can be used to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; we identify 3,230 genes with near-complete depletion of truncating variants, 72% of which have no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human “knockout” variants in protein-coding genes.

As part of a broader collaborative network of exome sequencing studies, we developed a jointly called data set of 5,685 Ashkenazi Jewish exomes. We make publicly available a resource of site and allele frequencies, which should serve as a reference for medical genetics in the Ashkenazim. We estimate that 30% of protein-coding alleles present in the Ashkenazi Jewish population at frequencies greater than 0.2% are significantly more frequent (mean 7.6-fold) than their maximum frequency observed in other reference populations. Arising via a well-described founder effect, this catalog of enriched alleles can contribute to differences in genetic risk and overall prevalence of diseases between populations. As validation we document 151 AJ enriched protein-altering alleles that overlap with “pathogenic” ClinVar alleles, including those that account for 10-100 fold differences in prevalence between AJ and non-AJ populations of some rare diseases including Gaucher disease (GBA, p.Asn409Ser, 8-fold enrichment); Canavan disease (ASPA, p.Glu285Ala, 12-fold enrichment); and Tay-Sachs disease (HEXA, c.1421+1G>C, 27-fold enrichment; p.Tyr427IlefsTer5, 12-fold enrichment). We next sought to use this catalog, of well-established relevance to Mendelian disease, to explore Crohn’s disease, a common disease with an estimated two to four-fold excess prevalence in AJ. We specifically evaluate whether strong acting rare alleles, enriched by the same founder-effect, contribute excess genetic risk to Crohn’s disease in AJ, and find that ten rare genetic risk factors in NOD2 and LRRK2 are strongly enriched in AJ, including several novel contributing alleles, show evidence of association to CD. Independently, we find that genomewide common variant risk defined by GWAS shows a strong difference between AJ and non-AJ European control population samples (0.97 s.d. higher, p−16). Taken together, the results suggest coordinated selection in AJ population for higher CD risk alleles in general. The results and approach illustrate the value of exome sequencing data in case-control studies along with reference data sets like ExAC to pinpoint genetic variation that contributes to variable disease predisposition across populations.

The human cytomegalovirus (HCMV) genome was sequenced 20 years ago. However, like those of other complex viruses, our understanding of its protein coding potential is far from complete. We used ribosome profiling and transcript analysis to experimentally define the HCMV translation products and follow their temporal expression. We identified hundreds of previously unidentified open reading frames and confirmed a fraction by means of mass spectrometry. We found that regulated use of alternative transcript start sites plays a broad role in enabling tight temporal control of HCMV protein expression and allowing multiple distinct polypeptides to be generated from a single genomic locus. Our results reveal an unanticipated complexity to the HCMV coding capacity and illustrate the role of regulated changes in transcript start sites in generating this complexity.

Productive herpesvirus infection requires a profound, time-controlled remodeling of the viral transcriptome and proteome. To gain insights into the genomic architecture and gene expression control in Kaposi's sarcoma-associated herpesvirus (KSHV), we performed a systematic genome-wide survey of viral transcriptional and translational activity throughout the lytic cycle. Using mRNA-sequencing and ribosome profiling, we found that transcripts encoding lytic genes are promptly bound by ribosomes upon lytic reactivation, suggesting their regulation is mainly transcriptional. Our approach also uncovered new genomic features such as ribosome occupancy of viral non-coding RNAs, numerous upstream and small open reading frames (ORFs), and unusual strategies to expand the virus coding repertoire that include alternative splicing, dynamic viral mRNA editing, and the use of alternative translation initiation codons. Furthermore, we provide a refined and expanded annotation of transcription start sites, polyadenylation sites, splice junctions, and initiation/termination codons of known and new viral features in the KSHV genomic space which we have termed KSHV 2.0. Our results represent a comprehensive genome-scale image of gene regulation during lytic KSHV infection that substantially expands our understanding of the genomic architecture and coding capacity of the virus., Author Summary Kaposi's sarcoma-associated herpesvirus (KSHV) is a cancer-causing agent in immunocompromised patients that establishes long-lasting infections in its hosts. Initially described in 1994 and extensively studied ever since, KSHV molecular biology is understood in broad outline, but many detailed questions are still to be resolved. After almost two decades, specific aspects pertaining to the organization of the KSHV genome as well as the fate of the viral transcripts during the productive stages of infection remain unexplored. Here we use a systematic genome-wide approach to investigate changes in gene and protein expression during the productive stage of infection known as the lytic cycle. We found that the viral genome has a large coding capacity, capable of generating at least 45% more products than initially anticipated by bioinformatic analyses alone, and that it uses multiple strategies to expand its coding capacity well beyond what is determined solely by the DNA sequence of its genome. We also provide an expanded and highly detailed annotation of known and new genomic features in KSHV. We have termed this new architectural and functional annotation KSHV 2.0. Our results indicate that viral genomes are more complex than anticipated, and that they are subject to tight mechanisms of regulation to ensure correct gene expression.

Exome and whole-genome sequencing are becoming increasingly routine approaches in Mendelian disease diagnosis. Despite their success, the current diagnostic rate for genomic analyses across a variety of rare diseases is approximately 25 to 50%. We explore the utility of transcriptome sequencing [RNA sequencing (RNA-seq)] as a complementary diagnostic tool in a cohort of 50 patients with genetically undiagnosed rare muscle disorders. We describe an integrated approach to analyze patient muscle RNA-seq, leveraging an analysis framework focused on the detection of transcript-level changes that are unique to the patient compared to more than 180 control skeletal muscle samples. We demonstrate the power of RNA-seq to validate candidate splice-disrupting mutations and to identify splice-altering variants in both exonic and deep intronic regions, yielding an overall diagnosis rate of 35%. We also report the discovery of a highly recurrent de novo intronic mutation in COL6A1 that results in a dominantly acting splice-gain event, disrupting the critical glycine repeat motif of the triple helical domain. We identify this pathogenic variant in a total of 27 genetically unsolved patients in an external collagen VI-like dystrophy cohort, thus explaining approximately 25% of patients clinically suggestive of having collagen VI dystrophy in whom prior genetic analysis is negative. Overall, this study represents a large systematic application of transcriptome sequencing to rare disease diagnosis and highlights its utility for the detection and interpretation of variants missed by current standard diagnostic approaches. 2017, National Institutes of Health (Grant GM096911), National Institute of General Medical Sciences (Grants F32GM115208 and 4T32GM007748)