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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 perfo

Genome sequencing adds an important diagnostic tool for patients with unsolved or atypical phenotypes. Here we describe the diagnostic journey in a patient with an atypical progressive course of riboflavin and thiamine responsive neurodegeneration, who is finally diagnosed with SMA through genome sequencing. The patient is a 28-year-old female presenting at age 4 years with fever, nausea, vomiting and leg pain, followed by itchy lesions on the soles of the feet, burning pain, frequent falls, and foot drop. At age 6-7 years, she developed progressive lower and then upper extremity weakness with loss of independent ambulation at age 10 years. She had scoliosis surgery at age 14 years and developed sudden respiratory failure requiring full-time ventilation via tracheostomy at age 19 years. She had progressive tongue and facial fasciculations with a dramatic response to high dose riboflavin and thiamine supplementation. Family history was significant for an undiagnosed older brother who passed away at age 7 years, who presented with a fever episode at age 2 years followed by progressive difficulty in walking and steppage gait. EMG and muscle biopsy revealed chronic neurogenic changes. Testing for SMN (RT-PCR) was negative. Repeat-SMN testing (MLPA) revealed heterozygous carrier status for the common SMN exon 7 deletion. Three independent WES studies were unrevealing. Research-based genome sequencing with an SMA centric re-analysis tool identified a novel missense variant c.809G>T p.(Ser270Ile) in SMN1, which was previously not recognized as located in SMN1. While exome sequencing did not allow the position of this variant to be unambiguously resolved between SMN1 and SMN2, genome sequencing did unambiguously position the variant on SMN1 via phasing with intronic sequence differences between SMN1 & SMN2. SMN2 copy number was 1. The parental data enabled a determination of compound heterozygosity. Location of intragenic mutations in SMN1 are expected to contribute to clinical severity. In the era of diseases modifying treatments, WGS, followed by direct gene sequencing, ended this diagnostic odyssey lasting more than two decades. [ABSTRACT FROM AUTHOR]

CHASERR encodes a human long nor}coding RNA (IncRNA) adjacent to CHDZ, decoding gene in which de novo loss-of-function variants cause developmental and epileptic encephalopathy. Here, we report our findings in three unrelated children with a syndromic, early-onset neurodevelopmental disorder, each of whOm had de novo deletion in the CHASERR locus. The children had severe encephalopathy, shared facial dysmorphisms, cortical atrophy, and cerebral hypomyelination - phenotype that is distinct from the phenotypes of patients with CHD2 haploinsuf ficiency. We found that the CHASERR deletion results in increased CHD2 protein abundance in patient-derived celllines and increased expression of the CHD2 transcript in cis. These findings indicate that CHD2 has bidirectional dosage sensitivity in human disease, and we recommend that other IncRNA-encoding genes be evaluated, particularly those upstream of genes associated with mendelian disorders. [ABSTRACT FROM AUTHOR]

BACKGROUND: Genetic variants that cause rare disorders may remain elusive even after expansive testing, such as exome sequencing. The diagnostic yield of genome sequencing, particularly after a negative evaluation, remains poorly defined. METHODS: We sequenced and analyzed the genomes of families with diverse phenotypes who were suspected to have a rare monogenic disease and for whom genetic testing had not revealed a diagnosis, as well as the genomes of a replication cohort at an independent clinical center. RESULTS: We sequenced the genomes of 822 families (744 in the initial cohort and 78 in the replication cohort) and made a molecular diagnosis in 218 of 744 families (29.3%). Of the 218 families, 61 (28.0%) -- 8.2% of families in the initial cohort -- had variants that required genome sequencing for identification, including coding variants, intronic variants, small structural variants, copy-neutral inversions, complex rearrangements, and tandem repeat expansions. Most families in which a molecular diagnosis was made after previous nondiagnostic exome sequencing (63.5%) had variants that could be detected by reanalysis of the exome-sequence data (53.4%) or by additional analytic methods, such as copy-number variant calling, to exome-sequence data (10.8%). We obtained similar results in the replication cohort: in 33% of the families in which a molecular diagnosis was made, or 8% of the cohort, genome sequencing was required, which showed the applicability of these findings to both research and clinical environments. CONCLUSIONS: The diagnostic yield of genome sequencing in a large, diverse research cohort and in a small clinical cohort of persons who had previously undergone genetic testing was approximately 8% and included several types of pathogenic variation that had not previously been detected by means of exome sequencing or other techniques. (Funded by the National Human Genome Research Institute and others.). [ABSTRACT FROM AUTHOR]

Pediatric neuromuscular diseases are a genetically and clinically heterogenous group of disorders of which 30-60% remain molecularly undiagnosed even after evaluation with exome or genome sequencing. Estimates for added diagnostic benefit of transcriptomic sequencing range between 7-32% across different disease groups. Recently, open-source computational tools designed to systematically survey transcriptomic sequencing data for aberrant events have become available. In this study we assess the sensitivity of DROP (OUTRIDER, FRASER and MAE), MINTIE, LeafcutterMD, and ANEVA-H to detect known outliers in pediatric neuromuscular cohorts in order to identify the optimal set of tools for diagnostic use. Each tool selected utilizes a different statistical strategy and experimental design geared for rare disease. Tools were run on three transcriptome cohorts from the NINDS Neuromuscular and Neurogenetic Diseases of Childhood Section: muscle tissue (n=71), cycloheximide treated fibroblasts (n=79) and untreated fibroblasts (n=37). For splicing tools, MINTIE is the best performing tool (recall rate = 9/21, 42%), followed by FRASER (recall rate = 16/41, 36%), then LeafcutterMD (recall rate = 0/41, 0%). For expression outliers, OUTRIDER detects 6% of true positives (1/15), while the addition of healthy GTEx controls does not improve detection. For monoallelic expression, MAE and ANEVA-H will be compared. Additional evaluations to identify the optimal RNA library preparation methodology for these tools is also in progress. Thus far, OUTRIDER yielded one new candidate diagnosis of TRIP4 related disease. Analysis for new candidate variants is ongoing. Based on these results, and those of ongoing experiments, we will provide recommendations for the use of these tools in diagnostic pipelines for rare pediatric neuromuscular disease. [ABSTRACT FROM AUTHOR]

Oculopharyngodistal myopathy (OPDM) is an inherited myopathy manifesting with ptosis, dysphagia and distal weakness. Pathologically it is characterised by rimmed vacuoles and intranuclear inclusions on muscle biopsy. In recent years CGG • CCG repeat expansion in four different genes were identified in OPDM individuals in Asian populations. None of these have been found in affected individuals of non-Asian ancestry. In this study we describe the identification of CCG expansions in ABCD3, ranging from 118 to 694 repeats, in 35 affected individuals across eight unrelated OPDM families of European ancestry. ABCD3 transcript appears upregulated in fibroblasts and skeletal muscle from OPDM individuals, suggesting a potential role of over-expression of CCG repeat containing ABCD3 transcript in progressive skeletal muscle degeneration. The study provides further evidence of the role of non-coding repeat expansions in unsolved neuromuscular diseases and strengthens the association between the CGG • CCG repeat motif and a specific pattern of muscle weakness., (© 2024. The Author(s).)

Purpose: To identify genetic etiologies and genotype/phenotype associations for unsolved ocular congenital cranial dysinnervation disorders (oCCDDs)., Methods: We coupled phenotyping with exome or genome sequencing of 467 probands (550 affected and 1108 total individuals) with genetically unsolved oCCDDs, integrating analyses of pedigrees, human and animal model phenotypes, and de novo variants to identify rare candidate single nucleotide variants, insertion/deletions, and structural variants disrupting protein-coding regions. Prioritized variants were classified for pathogenicity and evaluated for genotype/phenotype correlations., Results: Analyses elucidated phenotypic subgroups, identified pathogenic/likely pathogenic variant(s) in 43/467 probands (9.2%), and prioritized variants of uncertain significance in 70/467 additional probands (15.0%). These included known and novel variants in established oCCDD genes, genes associated with syndromes that sometimes include oCCDDs (e.g., MYH10, KIF21B, TGFBR2, TUBB6), genes that fit the syndromic component of the phenotype but had no prior oCCDD association (e.g., CDK13, TGFB2), genes with no reported association with oCCDDs or the syndromic phenotypes (e.g., TUBA4A, KIF5C, CTNNA1, KLB, FGF21), and genes associated with oCCDD phenocopies that had resulted in misdiagnoses., Conclusion: This study suggests that unsolved oCCDDs are clinically and genetically heterogeneous disorders often overlapping other Mendelian conditions and nominates many candidates for future replication and functional studies., (Copyright © 2024. Published by Elsevier Inc.)

Spinal muscular atrophy (SMA) is a genetic disorder that causes progressive degeneration of lower motor neurons and the subsequent loss of muscle function throughout the body. It is the second most common recessive disorder in individuals of European descent and is present in all populations. Accurate tools exist for diagnosing SMA from genome sequencing data. However, there are no publicly available tools for GRCh38-aligned data from panel or exome sequencing assays which continue to be used as first line tests for neuromuscular disorders. This deficiency creates a critical gap in our ability to diagnose SMA in large existing rare disease cohorts, as well as newly sequenced exome and panel datasets. We therefore developed and extensively validated a new tool - SMA Finder - that can diagnose SMA not only in genome, but also exome and panel sequencing samples aligned to GRCh37, GRCh38, or T2T-CHM13. It works by evaluating aligned reads that overlap the c.840 position of SMN1 and SMN2 in order to detect the most common molecular causes of SMA. We applied SMA Finder to 16,626 exomes and 3,911 genomes from heterogeneous rare disease cohorts sequenced at the Broad Institute Center for Mendelian Genomics as well as 1,157 exomes and 8,762 panel sequencing samples from Tartu University Hospital. SMA Finder correctly identified all 16 known SMA cases and reported nine novel diagnoses which have since been confirmed by clinical testing, with another four novel diagnoses undergoing validation. Notably, out of the 29 total SMA positive cases, 23 had an initial clinical diagnosis of muscular dystrophy, congenital myasthenic syndrome, or myopathy. This underscored the frequency with which SMA can be misdiagnosed as other neuromuscular disorders and confirmed the utility of using SMA Finder to reanalyze phenotypically diverse neuromuscular disease cohorts. Finally, we evaluated SMA Finder on 198,868 individuals that had both exome and genome sequencing data within the UK Biobank (UKBB) and found that SMA Finder's overall false positive rate was less than 1 / 200,000 exome samples, and its positive predictive value (PPV) was 97%. We also observed 100% concordance between UKBB exome and genome calls. This analysis showed that, even though it is located within a segmental duplication, the most common causal variant for SMA can be detected with comparable accuracy to monogenic disease variants in non-repetitive regions. Additionally, the high PPV demonstrated by SMA Finder, the existence of treatment options for SMA in which early diagnosis is imperative for therapeutic benefit, as well as widespread availability of clinical confirmatory testing for SMA, warrants the addition of SMN1 to the ACMG list of genes with reportable secondary findings after genome and exome sequencing., Competing Interests: HLR receives research funding from Microsoft and previously received funding from Illumina to support rare disease gene discovery and diagnosis. AODL has consulted for Tome Biosciences, Ono Pharma USA Inc, and Addition Therapeutics, and is member of the scientific advisory board for Congenica Inc and the Simons Foundation SPARK for Autism study. AL received honoraria for speaking at educational events for Biogen, PTC and Roche, is a subinvestigator in clinical trials by Roche and PTC, and is involved in a project supported by Biogen (POL-SMA-17-11166). PBK has received research support from ML Bio and Sarepta Therapeutics, and has consulted for Lupin, Neurogene, NS Pharma, and Teneofour.

Objective: Most families with heritable neuromuscular disorders do not receive a molecular diagnosis. Here we evaluate diagnostic utility of exome, genome, RNA sequencing, and protein studies and provide evidence-based recommendations for their integration into practice., Methods: In total, 247 families with suspected monogenic neuromuscular disorders who remained without a genetic diagnosis after standard diagnostic investigations underwent research-led massively parallel sequencing: neuromuscular disorder gene panel, exome, genome, and/or RNA sequencing to identify causal variants. Protein and RNA studies were also deployed when required., Results: Integration of exome sequencing and auxiliary genome, RNA and/or protein studies identified causal or likely causal variants in 62% (152 out of 247) of families. Exome sequencing alone informed 55% (83 out of 152) of diagnoses, with remaining diagnoses (45%; 69 out of 152) requiring genome sequencing, RNA and/or protein studies to identify variants and/or support pathogenicity. Arrestingly, novel disease genes accounted for <4% (6 out of 152) of diagnoses while 36.2% of solved families (55 out of 152) harbored at least one splice-altering or structural variant in a known neuromuscular disorder gene. We posit that contemporary neuromuscular disorder gene-panel sequencing could likely provide 66% (100 out of 152) of our diagnoses today., Interpretation: Our results emphasize thorough clinical phenotyping to enable deep scrutiny of all rare genetic variation in phenotypically consistent genes. Post-exome auxiliary investigations extended our diagnostic yield by 81% overall (34-62%). We present a diagnostic algorithm that details deployment of genomic and auxiliary investigations to obtain these diagnoses today most effectively. We hope this provides a practical guide for clinicians as they gain greater access to clinical genome and transcriptome sequencing., (© 2024 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.)

Purpose: Genome sequencing (GS)-specific diagnostic rates in prospective tightly ascertained exome sequencing (ES)-negative intellectual disability (ID) cohorts have not been reported extensively., Methods: ES, GS, epigenetic signatures, and long-read sequencing diagnoses were assessed in 74 trios with at least moderate ID., Results: The ES diagnostic yield was 42 of 74 (57%). GS diagnoses were made in 9 of 32 (28%) ES-unresolved families. Repeated ES with a contemporary pipeline on the GS-diagnosed families identified 8 of 9 single-nucleotide variations/copy-number variations undetected in older ES, confirming a GS-unique diagnostic rate of 1 in 32 (3%). Episignatures contributed diagnostic information in 9% with GS corroboration in 1 of 32 (3%) and diagnostic clues in 2 of 32 (6%). A genetic etiology for ID was detected in 51 of 74 (69%) families. Twelve candidate disease genes were identified. Contemporary ES followed by GS cost US$4976 (95% CI: $3704; $6969) per diagnosis and first-line GS at a cost of $7062 (95% CI: $6210; $8475) per diagnosis., Conclusion: Performing GS only in ID trios would be cost equivalent to ES if GS were available at $2435, about a 60% reduction from current prices. This study demonstrates that first-line GS achieves higher diagnostic rate than contemporary ES but at a higher cost., Competing Interests: Conflict of Interest The authors declare no conflicts of interest., (Copyright © 2024 American College of Medical Genetics and Genomics. Published by Elsevier Inc. All rights reserved.)

Background: A major obstacle faced by families with rare diseases is obtaining a genetic diagnosis. The average "diagnostic odyssey" lasts over five years and causal variants are identified in under 50%, even when capturing variants genome-wide. To aid in the interpretation and prioritization of the vast number of variants detected, computational methods are proliferating. Knowing which tools are most effective remains unclear. To evaluate the performance of computational methods, and to encourage innovation in method development, we designed a Critical Assessment of Genome Interpretation (CAGI) community challenge to place variant prioritization models head-to-head in a real-life clinical diagnostic setting., Methods: We utilized genome sequencing (GS) data from families sequenced in the Rare Genomes Project (RGP), a direct-to-participant research study on the utility of GS for rare disease diagnosis and gene discovery. Challenge predictors were provided with a dataset of variant calls and phenotype terms from 175 RGP individuals (65 families), including 35 solved training set families with causal variants specified, and 30 unlabeled test set families (14 solved, 16 unsolved). We tasked teams to identify causal variants in as many families as possible. Predictors submitted variant predictions with estimated probability of causal relationship (EPCR) values. Model performance was determined by two metrics, a weighted score based on the rank position of causal variants, and the maximum F-measure, based on precision and recall of causal variants across all EPCR values., Results: Sixteen teams submitted predictions from 52 models, some with manual review incorporated. Top performers recalled causal variants in up to 13 of 14 solved families within the top 5 ranked variants. Newly discovered diagnostic variants were returned to two previously unsolved families following confirmatory RNA sequencing, and two novel disease gene candidates were entered into Matchmaker Exchange. In one example, RNA sequencing demonstrated aberrant splicing due to a deep intronic indel in ASNS, identified in trans with a frameshift variant in an unsolved proband with phenotypes consistent with asparagine synthetase deficiency., Conclusions: Model methodology and performance was highly variable. Models weighing call quality, allele frequency, predicted deleteriousness, segregation, and phenotype were effective in identifying causal variants, and models open to phenotype expansion and non-coding variants were able to capture more difficult diagnoses and discover new diagnoses. Overall, computational models can significantly aid variant prioritization. For use in diagnostics, detailed review and conservative assessment of prioritized variants against established criteria is needed., (© 2024. The Author(s).)

Short-read genome sequencing (GS) holds the promise of becoming the primary diagnostic approach for the assessment of autism spectrum disorder (ASD) and fetal structural anomalies (FSAs). However, few studies have comprehensively evaluated its performance against current standard-of-care diagnostic tests: karyotype, chromosomal microarray (CMA), and exome sequencing (ES). To assess the clinical utility of GS, we compared its diagnostic yield against these three tests in 1,612 quartet families including an individual with ASD and in 295 prenatal families. Our GS analytic framework identified a diagnostic variant in 7.8% of ASD probands, almost 2-fold more than CMA (4.3%) and 3-fold more than ES (2.7%). However, when we systematically captured copy-number variants (CNVs) from the exome data, the diagnostic yield of ES (7.4%) was brought much closer to, but did not surpass, GS. Similarly, we estimated that GS could achieve an overall diagnostic yield of 46.1% in unselected FSAs, representing a 17.2% increased yield over karyotype, 14.1% over CMA, and 4.1% over ES with CNV calling or 36.1% increase without CNV discovery. Overall, GS provided an added diagnostic yield of 0.4% and 0.8% beyond the combination of all three standard-of-care tests in ASD and FSAs, respectively. This corresponded to nine GS unique diagnostic variants, including sequence variants in exons not captured by ES, structural variants (SVs) inaccessible to existing standard-of-care tests, and SVs where the resolution of GS changed variant classification. Overall, this large-scale evaluation demonstrated that GS significantly outperforms each individual standard-of-care test while also outperforming the combination of all three tests, thus warranting consideration as the first-tier diagnostic approach for the assessment of ASD and FSAs., Competing Interests: Declaration of interests M.E.T. and H.R. receive research funding from Microsoft Inc and/or research reagents from Illumina Inc. M.E.T. also received research funding from Levo Therapeutics and research reagents from Ionis Therapeutics for unrelated research projects., (Copyright © 2023 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Cerebellar ataxia, neuropathy and vestibular areflexia syndrome is a progressive, generally late-onset, neurological disorder associated with biallelic pentanucleotide expansions in Intron 2 of the RFC1 gene. The locus exhibits substantial genetic variability, with multiple pathogenic and benign pentanucleotide repeat alleles previously identified. To determine the contribution of pathogenic RFC1 expansions to neurological disease within an Australasian cohort and further investigate the heterogeneity exhibited at the locus, a combination of flanking and repeat-primed PCR was used to screen a cohort of 242 Australasian patients with neurological disease. Patients whose data indicated large gaps within expanded alleles following repeat-primed PCR, underwent targeted long-read sequencing to identify novel repeat motifs at the locus. To increase diagnostic yield, additional probes at the RFC1 repeat region were incorporated into the PathWest diagnostic laboratory targeted neurological disease gene panel to enable first-pass screening of the locus for all samples tested on the panel. Within the Australasian cohort, we detected known pathogenic biallelic expansions in 15.3% ( n = 37) of patients. Thirty indicated biallelic AAGGG expansions, two had biallelic 'Māori alleles' [(AAAGG) exp (AAGGG) exp ], two samples were compound heterozygous for the Māori allele and an AAGGG expansion, two samples had biallelic ACAGG expansions and one sample was compound heterozygous for the ACAGG and AAGGG expansions. Forty-five samples tested indicated the presence of biallelic expansions not known to be pathogenic. A large proportion (84%) showed complex interrupted patterns following repeat-primed PCR, suggesting that these expansions are likely to be comprised of more than one repeat motif, including previously unknown repeats. Using targeted long-read sequencing, we identified three novel repeat motifs in expanded alleles. Here, we also show that short-read sequencing can be used to reliably screen for the presence or absence of biallelic RFC1 expansions in all samples tested using the PathWest targeted neurological disease gene panel. Our results show that RFC1 pathogenic expansions make a substantial contribution to neurological disease in the Australasian population and further extend the heterogeneity of the locus. To accommodate the increased complexity, we outline a multi-step workflow utilizing both targeted short- and long-read sequencing to achieve a definitive genotype and provide accurate diagnoses for patients., Competing Interests: H.G. has previously received travel and accommodation expenses from ONT to speak at conferences. H.G. and I.W.D. have paid consultant roles with Sequin Pty Ltd., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain.)

CAG repeat expansions in exon 1 of the AR gene on the X chromosome cause spinal and bulbar muscular atrophy, a male-specific progressive neuromuscular disorder associated with a variety of extra-neurological symptoms. The disease has a reported male prevalence of approximately 1:30 000 or less, but the AR repeat expansion frequency is unknown. We established a pipeline, which combines the use of the ExpansionHunter tool and visual validation, to detect AR CAG expansion on whole-genome sequencing data, benchmarked it to fragment PCR sizing, and applied it to 74 277 unrelated individuals from four large cohorts. Our pipeline showed sensitivity of 100% [95% confidence interval (CI) 90.8-100%], specificity of 99% (95% CI 94.2-99.7%), and a positive predictive value of 97.4% (95% CI 84.4-99.6%). We found the mutation frequency to be 1:3182 (95% CI 1:2309-1:4386, n = 117 734) X chromosomes-10 times more frequent than the reported disease prevalence. Modelling using the novel mutation frequency led to estimate disease prevalence of 1:6887 males, more than four times more frequent than the reported disease prevalence. This discrepancy is possibly due to underdiagnosis of this neuromuscular condition, reduced penetrance, and/or pleomorphic clinical manifestations., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Objective: Duchenne muscular dystrophy (DMD) is caused by pathogenic variants in the dystrophin gene ( DMD ). Hypermethylated CGG expansions within DIP2B 5' UTR are associated with an intellectual development disorder. Here, we demonstrate the diagnostic utility of genomic short-read sequencing (SRS) and transcriptome sequencing to identify a novel DMD structural variant (SV) and a DIP2B CGG expansion in a patient with DMD for whom conventional diagnostic testing failed to yield a genetic diagnosis., Methods: We performed genomic SRS, skeletal muscle transcriptome sequencing, and targeted programmable long-read sequencing (LRS)., Results: The proband had a typical DMD clinical presentation, autism spectrum disorder (ASD), and dystrophinopathy on muscle biopsy. Transcriptome analysis identified 6 aberrantly expressed genes; DMD and DIP2B were the strongest underexpression and overexpression outliers, respectively. Genomic SRS identified a 216 kb paracentric inversion (NC&#95;000023.11: g.33162217-33378800) overlapping 2 DMD promoters. ExpansionHunter indicated an expansion of 109 CGG repeats within the 5' UTR of DIP2B . Targeted genomic LRS confirmed the SV and genotyped the DIP2B repeat expansion as 270 CGG repeats., Discussion: Here, transcriptome data heavily guided genomic analysis to resolve a complex DMD inversion and a DIP2B repeat expansion. Longitudinal follow-up will be important for clarifying the clinical significance of the DIP2B genotype., (Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

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., (© 2022. The Author(s).)

Objectives: Recently, the number of dinucleotide CA repeats in an intron of the STMN2 gene was reported to be associated with an increased risk for amyotrophic lateral sclerosis (ALS). Therefore, we sought to replicate this observation in an independent group of ALS patients and a much larger control group., Methods: Here, we used whole-genome sequencing and tested the STMN2 CA repeat in a case-control cohort of the European genetic background and in genomes from various populations in the gnomAD cohort to attempt to replicate this proposed association., Results: We find that repeats well above the previously reported pathogenic threshold of 19 are commonly observed in unaffected individuals across different populations. Furthermore, we did not observe an association between longer STMN2 CA repeats and ALS phenotype., Discussion: In summary, our results do not support a role of STMN2 CA repeats toward ALS risk. As TDP-43 aggregation is central to ALS pathogenesis, lowered expression of STMN2 could be used as a biomarker for ALS. Therefore, a variant associated both with the risk for ALS and the level of STMN2 expression would be clinically useful. However, for a variant to be actionable, it must be strongly replicated in independent cohorts and exceed the rigorous statistical thresholds applied., (Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

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., (© 2022 Wiley Periodicals LLC.)

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.

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., (Copyright © 2021. Published by Elsevier Inc.)

Objective: To 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., Methods: Exome, 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., Results: Splice-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., Conclusions: Whole-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., (Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

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., (© The Author(s) (2020). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

We propose an approach to decision support systems (DSS) that starts with the user first making their own unassisted decision αU and providing this decision as an input to the algorithm. Then, if the decision based of machine learning (ML) disagrees with the user's initial decision, it iteratively works with the user to converge to a common decision or at least make the user reconsider input values that are inconsistent with αU. We provide a detailed description of this approach along with examples, and then discuss potential benefits and limitations of this approach.

Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes 1 . Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases.

We present eight families with arthrogryposis multiplex congenita and myopathy bearing a TTN intron 213 extended splice-site variant (NM&#95;001267550.1:c.39974-11T>G), inherited in trans with a second pathogenic TTN variant. Muscle-derived RNA studies of three individuals confirmed mis-splicing induced by the c.39974-11T>G variant; in-frame exon 214 skipping or use of a cryptic 3' splice-site effecting a frameshift. Confounding interpretation of pathogenicity is the absence of exons 213-217 within the described skeletal muscle TTN N2A isoform. However, RNA-sequencing from 365 adult human gastrocnemius samples revealed that 56% specimens predominantly include exons 213-217 in TTN transcripts (inclusion rate ≥66%). Further, RNA-sequencing of five fetal muscle samples confirmed that 4/5 specimens predominantly include exons 213-217 (fifth sample inclusion rate 57%). Contractures improved significantly with age for four individuals, which may be linked to decreased expression of pathogenic fetal transcripts. Our study extends emerging evidence supporting a vital developmental role for TTN isoforms containing metatranscript-only exons., (© 2019 Wiley Periodicals, Inc.)

Motivation: The correct classification of missense variants as benign or pathogenic remains challenging. Pathogenic variants are expected to have higher deleterious prediction scores than benign variants in the same gene. However, most of the existing variant annotation tools do not reference the score range of benign population variants on gene level., Results: We present a web-application, Variant Score Ranker, which enables users to rapidly annotate variants and perform gene-specific variant score ranking on the population level. We also provide an intuitive example of how gene- and population-calibrated variant ranking scores can improve epilepsy variant prioritization., Availability and Implementation: http://vsranker.broadinstitute.org., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Rare disease investigators constantly face challenges in identifying additional cases to build evidence for gene-disease causality. The Matchmaker Exchange (MME) addresses this limitation by providing a mechanism for matching patients across genomic centers via a federated network. The MME has revolutionized searching for additional cases by making it possible to query across institutional boundaries, so that what was once a laborious and manual process of contacting researchers is now automated and computable. However, while the MME network is beginning to scale, the growth of additional nodes is limited by the lack of easy-to-use solutions that can be implemented by any rare disease database owner, even one without significant software engineering resources. Here, we describe matchbox, which is an open-source, platform-independent, portable bridge between any given rare disease genomic center and the MME network, which has already led to novel gene discoveries. We also describe how matchbox greatly reduces the barrier to participation by overcoming challenges for new databases to join the MME., (© 2018 Wiley Periodicals, Inc.)