Pathogenicity and selective constraint on variation near splice sites

Splice site recognition - deciphering Exon-Intron transitions for genetic insights using Enhanced integrated Block-Level gated LSTM model

Bioinformatics is a contemporary interdisciplinary area focused on analyzing the growing number of genome sequences. Gene variants are differences in DNA sequences among individuals within a population. Splice site recognition is a crucial step in the process of gene expression, where the coding sequences of genes are joined together to form mature messenger RNA (mRNA). These genetic variants that disrupt genes are believed to be the primary reason for neuro-developmental disorders like ASD (Autism Spectrum Disorder) is a neuro-developmental disorder that is diagnosed in individuals, families, and society and occurs as the developmental delay in one among the hundred genes that are associated with these disorders. Missense variants, premature stop codons, or deletions alter both the quality and quantity of encoded proteins. Predicting genes within exons and introns presents main challenges, such as dealing with sequencing errors, short reads, incomplete genes, overlapping, and more. Although many traditional techniques have been utilized in creating an exon prediction system, the primary challenge lies in accurately identifying the length and spliced strand location classification of exons in conjunction with introns. From now on, the suggested approach utilizes a Deep Learning algorithm to analyze intricate and extensive genomic datasets. M-LSTM is utilized to categorize three binary combinations (EI as 1, IE as 2, and none as 3) using spliced DNA strands. The M-LSTM system is able to sequence extensive datasets, ensuring that long information can be stored without any impact on the current input or output. This enables it to recognize and address long-term connections and problems with rapidly increasing gradients. The proposed model is compared internally with Naïve Bayes and Random Forest to assess its efficacy. Additionally, the proposed model's performance is forecasted by utilizing probabilistic parameters like recall, F1-score, precision, and accuracy to assess the effectiveness of the proposed system.

Association Study Between Kynurenine 3-Monooxygenase (KMO) Gene and Parkinson's Disease Patients

The influence of various risk factors such as aging, intricate cellular molecular processes, and lifestyle factors like smoking, alcohol consumption, caffeine intake, and occupational factors has received increased focus in relation to the risk and development of Parkinson's disease (PD). Limited research has been conducted on the assessment of lifestyle impact on kynurenine 3-monooxygenase (KMO) gene in PD. A total of 164 subjects, including 82 PD cases and 82 healthy individuals, were recruited based on specific inclusion and exclusion criteria. The severity of PD and clinical assessment were evaluated using the Unified Parkinson's Disease Rating Scale (UPDRS) and Hoehn and Yahr (HY) scaling. Sanger sequencing was performed to analyse the KMO gene in the recruited subjects, and case-control studies were conducted. The UPDRS assessment revealed significant impairments in smell, tremors, walking, and posture instability in the late-onset PD cohorts. The HY scaling indicated a higher proportion of late-onset cohorts in stage 2. Moreover, both alcoholic and non-alcoholic groups showed significantly increased levels of 3-HK in late-onset PD. Gene analysis identified missense variants at position g.241593373 T > A (rs752312199) and intronic variants at positions g.241592623A > G (rs640718), g.241592800C > A (rs990388262), g.241592802A > C (rs1350160268), g.241592808 T > C (rs1478255936), and g.241592812G > T (rs948928931). The alterations in the KMO gene were found to influence the levels of kynurenic acid (KYNA) and 3-hydroxykynurenine (3-HK). Genomic analysis revealed a high prevalence of missense mutations in the late-onset PD groups, leading to a decline in 3-HK levels in patients. This leads to the reduction of the progression of disease in late-onset groups which shows that this mutation may lead to the protective effect on the PD subjects. This study suggests the use of KYNA and 3-HK as potential biomarkers in analysing the progression of disease. This study is limited by its small sample size. To overcome this limitation, a larger study involving in greater number of participants is needed to thoroughly investigate the KMO gene and KP metabolites, to enhance our understanding of Parkinson's disease progression, and to enhance diagnostic capabilities.

Achieving an optimal pregnancy outcome through the combined utilization of micro-TESE and ICSI in cryptorchidism associated with a non-canonical splicing variant in RXFP2

PURPOSE

To identify the genetic cause of a cryptorchidism patient carrying a non-canonical splicing variant highlighted by SPCards platform in RXFP2 and to provide a comprehensive overview of RXFP2 variants with cryptorchidism correlation.

METHODS

We identified a homozygous non-canonical splicing variant by whole-exome sequencing and Sanger sequencing in a case with cryptorchidism and non-obstructive azoospermia (NOA). As the pathogenicity of this non-canonical splicing variant remained unclear, we initially utilized the SPCards platform to predict its pathogenicity. Subsequently, we employed a minigene splicing assay to further evaluate the influence of the identified splicing variant. Microdissection testicular sperm extraction (micro-TESE) combined with intracytoplasmic sperm injection (ICSI) was performed. PubMed and Human Genome Variant Database (HGMD) were queried to search for RXFP2 variants.

RESULTS

We identified a homozygous non-canonical splicing variant (NM_130806: c.1376-12A > G) in RXFP2, and confirmed this variant caused aberrant splicing of exons 15 and 16 of the RXFP2 gene: 11 bases were added in front of exon 16, leading to an abnormal transcript initiation and a frameshift. Fortunately, the patient successfully obtained his biological offspring through micro-TESE combined with ICSI. Four cryptorchidism-associated variants in RXFP2 from 90 patients with cryptorchidism were identified through a literature search in PubMed and HGMD, with different inheritance patterns.

CONCLUSION

This is the first cryptorchidism case carrying a novel causative non-canonical splicing RXFP2 variant. The combined approach of micro-TESE and ICSI contributed to an optimal pregnancy outcome. Our literature review demonstrated that RXFP2 variants caused cryptorchidism in a recessive inheritance pattern, rather than a dominant pattern.

Predicting the impact of rare variants on RNA splicing in CAGI6

Variants which disrupt splicing are a frequent cause of rare disease that have been under-ascertained clinically. Accurate and efficient methods to predict a variant's impact on splicing are needed to interpret the growing number of variants of unknown significance (VUS) identified by exome and genome sequencing. Here, we present the results of the CAGI6 Splicing VUS challenge, which invited predictions of the splicing impact of 56 variants ascertained clinically and functionally validated to determine splicing impact. The performance of 12 prediction methods, along with SpliceAI and CADD, was compared on the 56 functionally validated variants. The maximum accuracy achieved was 82% from two different approaches, one weighting SpliceAI scores by minor allele frequency, and one applying the recently published Splicing Prediction Pipeline (SPiP). SPiP performed optimally in terms of sensitivity, while an ensemble method combining multiple prediction tools and information from databases exceeded all others for specificity. Several challenge methods equalled or exceeded the performance of SpliceAI, with ultimate choice of prediction method likely to depend on experimental or clinical aims. One quarter of the variants were incorrectly predicted by at least 50% of the methods, highlighting the need for further improvements to splicing prediction methods for successful clinical application.

Quantifying negative selection in human 3' UTRs uncovers constrained targets of RNA-binding proteins

Many non-coding variants associated with phenotypes occur in 3' untranslated regions (3' UTRs), and may affect interactions with RNA-binding proteins (RBPs) to regulate gene expression post-transcriptionally. However, identifying functional 3' UTR variants has proven difficult. We use allele frequencies from the Genome Aggregation Database (gnomAD) to identify classes of 3' UTR variants under strong negative selection in humans. We develop intergenic mutability-adjusted proportion singleton (iMAPS), a generalized measure related to MAPS, to quantify negative selection in non-coding regions. This approach, in conjunction with in vitro and in vivo binding data, identifies precise RBP binding sites, miRNA target sites, and polyadenylation signals (PASs) under strong selection. For each class of sites, we identify thousands of gnomAD variants under selection comparable to missense coding variants, and find that sites in core 3' UTR regions upstream of the most-used PAS are under strongest selection. Together, this work improves our understanding of selection on human genes and validates approaches for interpreting genetic variants in human 3' UTRs.

Prioritizing de novo potential non-canonical splicing variants in neurodevelopmental disorders

BACKGROUND

Genomic variants outside of the canonical splicing site (±2) may generate abnormal mRNA splicing, which are defined as non-canonical splicing variants (NCSVs). However, the clinical interpretation of NCSVs in neurodevelopmental disorders (NDDs) is largely unknown.

METHODS

We investigated the contribution of NCSVs to NDDs from 345,787 de novo variants (DNVs) in 47,574 patients with NDDs. We performed functional enrichment and protein-protein interaction analysis to assess the association between genes carrying prioritised NCSVs and NDDs. Minigene was used to validate the impact of NCSVs on mRNA splicing.

FINDINGS

We observed significantly more NCSVs (p = 0.02, odds ratio [OR] = 2.05) among patients with NDD than in controls. Both canonical splicing variants (CSVs) and NCSVs contributed to an equal proportion of patients with NDD (0.76% vs. 0.82%). The candidate genes carrying NCSVs were associated with glutamatergic synapse and chromatin remodelling. Minigene successfully validated 59 of 79 (74.68%) NCSVs that led to abnormal splicing in 40 candidate genes, and 9 of the genes (ARID1B, KAT6B, TCF4, SMARCA2, SHANK3, PDHA1, WDR45, SCN2A, SYNGAP1) harboured recurrent NCSVs with the same variant present in more than two unrelated patients with NDD. Moreover, 36 of 59 (61.02%) NCSVs are novel clinically relevant variants, including 34 unreported and 2 clinically conflicting interpretations or of uncertain significance NCSVs in the ClinVar database.

INTERPRETATION

This study highlights the common pathology and clinical importance of NCSVs in unsolved patients with NDD.

FUNDING

The present study was funded by grants from the National Natural Science Foundation of China, China Postdoctoral Science Foundation, the Hunan Youth Science and Technology Innovation Talent Project, the Provincial Natural Science Foundation of Hunan, The Scientific Research Program of FuRong laboratory, and the Natural Science Project of the University of Anhui Province.

Benchmarking splice variant prediction algorithms using massively parallel splicing assays

BACKGROUND

Variants that disrupt mRNA splicing account for a sizable fraction of the pathogenic burden in many genetic disorders, but identifying splice-disruptive variants (SDVs) beyond the essential splice site dinucleotides remains difficult. Computational predictors are often discordant, compounding the challenge of variant interpretation. Because they are primarily validated using clinical variant sets heavily biased to known canonical splice site mutations, it remains unclear how well their performance generalizes.

RESULTS

We benchmark eight widely used splicing effect prediction algorithms, leveraging massively parallel splicing assays (MPSAs) as a source of experimentally determined ground-truth. MPSAs simultaneously assay many variants to nominate candidate SDVs. We compare experimentally measured splicing outcomes with bioinformatic predictions for 3,616 variants in five genes. Algorithms' concordance with MPSA measurements, and with each other, is lower for exonic than intronic variants, underscoring the difficulty of identifying missense or synonymous SDVs. Deep learning-based predictors trained on gene model annotations achieve the best overall performance at distinguishing disruptive and neutral variants, and controlling for overall call rate genome-wide, SpliceAI and Pangolin have superior sensitivity. Finally, our results highlight two practical considerations when scoring variants genome-wide: finding an optimal score cutoff, and the substantial variability introduced by differences in gene model annotation, and we suggest strategies for optimal splice effect prediction in the face of these issues.

CONCLUSION

SpliceAI and Pangolin show the best overall performance among predictors tested, however, improvements in splice effect prediction are still needed especially within exons.

Structural and non-coding variants increase the diagnostic yield of clinical whole genome sequencing for rare diseases

BACKGROUND

Whole genome sequencing is increasingly being used for the diagnosis of patients with rare diseases. However, the diagnostic yields of many studies, particularly those conducted in a healthcare setting, are often disappointingly low, at 25-30%. This is in part because although entire genomes are sequenced, analysis is often confined to in silico gene panels or coding regions of the genome.

METHODS

We undertook WGS on a cohort of 122 unrelated rare disease patients and their relatives (300 genomes) who had been pre-screened by gene panels or arrays. Patients were recruited from a broad spectrum of clinical specialties. We applied a bioinformatics pipeline that would allow comprehensive analysis of all variant types. We combined established bioinformatics tools for phenotypic and genomic analysis with our novel algorithms (SVRare, ALTSPLICE and GREEN-DB) to detect and annotate structural, splice site and non-coding variants.

RESULTS

Our diagnostic yield was 43/122 cases (35%), although 47/122 cases (39%) were considered solved when considering novel candidate genes with supporting functional data into account. Structural, splice site and deep intronic variants contributed to 20/47 (43%) of our solved cases. Five genes that are novel, or were novel at the time of discovery, were identified, whilst a further three genes are putative novel disease genes with evidence of causality. We identified variants of uncertain significance in a further fourteen candidate genes. The phenotypic spectrum associated with RMND1 was expanded to include polymicrogyria. Two patients with secondary findings in FBN1 and KCNQ1 were confirmed to have previously unidentified Marfan and long QT syndromes, respectively, and were referred for further clinical interventions. Clinical diagnoses were changed in six patients and treatment adjustments made for eight individuals, which for five patients was considered life-saving.

CONCLUSIONS

Genome sequencing is increasingly being considered as a first-line genetic test in routine clinical settings and can make a substantial contribution to rapidly identifying a causal aetiology for many patients, shortening their diagnostic odyssey. We have demonstrated that structural, splice site and intronic variants make a significant contribution to diagnostic yield and that comprehensive analysis of the entire genome is essential to maximise the value of clinical genome sequencing.

DECIPHER: Improving Genetic Diagnosis Through Dynamic Integration of Genomic and Clinical Data

DECIPHER (Database of Genomic Variation and Phenotype in Humans Using Ensembl Resources) shares candidate diagnostic variants and phenotypic data from patients with genetic disorders to facilitate research and improve the diagnosis, management, and therapy of rare diseases. The platform sits at the boundary between genomic research and the clinical community. DECIPHER aims to ensure that the most up-to-date data are made rapidly available within its interpretation interfaces to improve clinical care. Newly integrated cardiac case-control data that provide evidence of gene-disease associations and inform variant interpretation exemplify this mission. New research resources are presented in a format optimized for use by a broad range of professionals supporting the delivery of genomic medicine. The interfaces within DECIPHER integrate and contextualize variant and phenotypic data, helping to determine a robust clinico-molecular diagnosis for rare-disease patients, which combines both variant classification and clinical fit. DECIPHER supports discovery research, connecting individuals within the rare-disease community to pursue hypothesis-driven research.

Benchmarking splice variant prediction algorithms using massively parallel splicing assays

Background

Variants that disrupt mRNA splicing account for a sizable fraction of the pathogenic burden in many genetic disorders, but identifying splice-disruptive variants (SDVs) beyond the essential splice site dinucleotides remains difficult. Computational predictors are often discordant, compounding the challenge of variant interpretation. Because they are primarily validated using clinical variant sets heavily biased to known canonical splice site mutations, it remains unclear how well their performance generalizes.

Results

We benchmarked eight widely used splicing effect prediction algorithms, leveraging massively parallel splicing assays (MPSAs) as a source of experimentally determined ground-truth. MPSAs simultaneously assay many variants to nominate candidate SDVs. We compared experimentally measured splicing outcomes with bioinformatic predictions for 3,616 variants in five genes. Algorithms' concordance with MPSA measurements, and with each other, was lower for exonic than intronic variants, underscoring the difficulty of identifying missense or synonymous SDVs. Deep learning-based predictors trained on gene model annotations achieved the best overall performance at distinguishing disruptive and neutral variants. Controlling for overall call rate genome-wide, SpliceAI and Pangolin also showed superior overall sensitivity for identifying SDVs. Finally, our results highlight two practical considerations when scoring variants genome-wide: finding an optimal score cutoff, and the substantial variability introduced by differences in gene model annotation, and we suggest strategies for optimal splice effect prediction in the face of these issues.

Conclusion

SpliceAI and Pangolin showed the best overall performance among predictors tested, however, improvements in splice effect prediction are still needed especially within exons.

Genomic Diagnosis of Rare Pediatric Disease in the United Kingdom and Ireland

BACKGROUND

Pediatric disorders include a range of highly penetrant, genetically heterogeneous conditions amenable to genomewide diagnostic approaches. Finding a molecular diagnosis is challenging but can have profound lifelong benefits.

METHODS

We conducted a large-scale sequencing study involving more than 13,500 families with probands with severe, probably monogenic, difficult-to-diagnose developmental disorders from 24 regional genetics services in the United Kingdom and Ireland. Standardized phenotypic data were collected, and exome sequencing and microarray analyses were performed to investigate novel genetic causes. We developed an iterative variant analysis pipeline and reported candidate variants to clinical teams for validation and diagnostic interpretation to inform communication with families. Multiple regression analyses were performed to evaluate factors affecting the probability of diagnosis.

RESULTS

A total of 13,449 probands were included in the analyses. On average, we reported 1.0 candidate variant per parent-offspring trio and 2.5 variants per singleton proband. Using clinical and computational approaches to variant classification, we made a diagnosis in approximately 41% of probands (5502 of 13,449). Of 3599 probands in trios who received a diagnosis by clinical assertion, approximately 76% had a pathogenic de novo variant. Another 22% of probands (2997 of 13,449) had variants of uncertain significance in genes that were strongly linked to monogenic developmental disorders. Recruitment in a parent-offspring trio had the largest effect on the probability of diagnosis (odds ratio, 4.70; 95% confidence interval [CI], 4.16 to 5.31). Probands were less likely to receive a diagnosis if they were born extremely prematurely (i.e., 22 to 27 weeks' gestation; odds ratio, 0.39; 95% CI, 0.22 to 0.68), had in utero exposure to antiepileptic medications (odds ratio, 0.44; 95% CI, 0.29 to 0.67), had mothers with diabetes (odds ratio, 0.52; 95% CI, 0.41 to 0.67), or were of African ancestry (odds ratio, 0.51; 95% CI, 0.31 to 0.78).

CONCLUSIONS

Among probands with severe, probably monogenic, difficult-to-diagnose developmental disorders, multimodal analysis of genomewide data had good diagnostic power, even after previous attempts at diagnosis. (Funded by the Health Innovation Challenge Fund and Wellcome Sanger Institute.).

Functional Analysis of a Novel, Non-Canonical RPGR Splice Variant Causing X-Linked Retinitis Pigmentosa

X-linked retinitis pigmentosa (XLRP) caused by mutations in the RPGR gene is one of the most severe forms of RP due to its early onset and intractable progression. Most cases have been associated with genetic variants within the purine-rich exon ORF15 region of this gene. RPGR retinal gene therapy is currently being investigated in several clinical trials. Therefore, it is crucial to report and functionally characterize (all novel) potentially pathogenic DNA sequence variants. Whole-exome sequencing (WES) was performed for the index patient. The splicing effects of a non-canonical splice variant were tested on cDNA from whole blood and a minigene assay. WES revealed a rare, non-canonical splice site variant predicted to disrupt the wildtype splice acceptor and create a novel acceptor site 8 nucleotides upstream of RPGR exon 12. Reverse-transcription PCR analyses confirmed the disruption of the correct splicing pattern, leading to the insertion of eight additional nucleotides in the variant transcript. Transcript analyses with minigene assays and cDNA from peripheral blood are useful tools for the characterization of splicing defects due to variants in the RPGR and may increase the diagnostic yield in RP. The functional analysis of non-canonical splice variants is required to classify those variants as pathogenic according to the ACMG's criteria.

Novel noncanonical splice site variant causes mild CHD7-related disorder with variable intrafamilial expressivity

The clinical diagnosis criteria for CHARGE syndrome have been revised several times in the last 25 years. Variable expressivity and reduced penetrance are known, particularly in mild and familial cases. Therefore, it has been proposed to include the detection of a pathogenic CHD7 variant as a major diagnostic criterion. However, intronic variants not located at the canonical splice site are still underrepresented in mutation databases, often because functional analysis is not performed in the diagnostic setting. Here, we report a two-generation family that did not meet the criteria for CHARGE syndrome, until the molecular findings were taken into account. By exome sequencing, we detected an intronic variant in a male individual, who presented with unilateral external ear malformation, bilateral semicircular canal aplasia, polydactyly, vertebral body fusion and a heart defect. The variant was inherited by his mother, who also had bilateral semicircular canal aplasia additionally to unilateral sensorineural hearing impairment, unilateral mandibular palpebral synkinesia, orofacial cleft, and dysphagia. Using RNA studies, we were able to demonstrate that aberrant splicing occurs at an upstream cryptic splice acceptor site, resulting in a frameshift and premature stop of translation. Our data show causality of the noncanonical intronic CHD7 variant and end the diagnostic odyssey of this unsolved phenotype of the family.

Recurrent AKR1D1 c.580-13T>A Variant: A Cause of Δ4-3-Oxosteroid-5β-Reductase Deficiency

Δ⁴-3-oxosteroid 5β-reductase (AKR1D1) deficiency presents with neonatal cholestasis and liver failure in early infancy and features high levels of 3-oxo-Δ⁴-bile acids in urine. Genetic analysis is needed for definitive diagnosis, because in the neonatal period it can be difficult to distinguish a primary from a secondary enzyme deficiency. By re-analysis of the gene-sequencing data, one AKR1D1 noncanonical splice-site variant (NM_005989.4: c.580-13T>A) with controversial pathogenicity was discovered to be enriched in eight families with clinical and biochemically confirmed AKR1D1 deficiency. Further RNA sequencing of liver tissue suggested this variant causes complete degradation of mRNA. An in vitro minigene experiment indicated that this variant led to partial intron retention or exon jumping, which then leads to coding sequence frameshift and nonsense-mediated mRNA decay. Thus, AKR1D1 variant c.580-13T>A was considered pathogenic and, therefore, should be screened during genetic studies in infants with a suspicion of a congenital bile acid synthetic disorder.

Pathogenicity of Intronic and Synonymous Variants of ATP7B in Wilson Disease

Wilson disease (WD) is a hereditary disorder of copper metabolism, resulting from mutations within ATP7B. Early diagnosis is essential for affected individuals. However, there are still patients with clinically suspected WD who do not have detectable pathogenic variants, which makes diagnosis difficult and delays treatment. This study included such patients from the authors' center and screened for the full-length sequence of ATP7B by next-generation sequencing. Newly identified synonymous and intronic variants were then analyzed with in silico tools. A minigene system was constructed to determine the pathogenicity of these variants in terms of splicing and blood RNA extraction, and RT-PCR experiments were performed on several patients to verify the splicing alterations. The phenotypes of the patients were also analyzed. Fourteen suspected pathogenic variants, including nine synonymous and five intronic variants, were detected in 12 patients with clinically suspected WD. Among them, four synonymous variants (c.1050G>A, c.1122C>G, c.3243G>A, and c.4014T>A) and four intronic variants (c.1543 +40G>A, c.1707+6_1707+16del, c.1870-49A>G, and c.2731-67A>G) resulted in splicing changes in ATP7B. After the above analysis, the diagnosis of WD could be confirmed in eight clinically suspected patients with WD who showed a late age of onset.

Computational prediction of human deep intronic variation

BACKGROUND

The adoption of whole-genome sequencing in genetic screens has facilitated the detection of genetic variation in the intronic regions of genes, far from annotated splice sites. However, selecting an appropriate computational tool to discriminate functionally relevant genetic variants from those with no effect is challenging, particularly for deep intronic regions where independent benchmarks are scarce.

RESULTS

In this study, we have provided an overview of the computational methods available and the extent to which they can be used to analyze deep intronic variation. We leveraged diverse datasets to extensively evaluate tool performance across different intronic regions, distinguishing between variants that are expected to disrupt splicing through different molecular mechanisms. Notably, we compared the performance of SpliceAI, a widely used sequence-based deep learning model, with that of more recent methods that extend its original implementation. We observed considerable differences in tool performance depending on the region considered, with variants generating cryptic splice sites being better predicted than those that potentially affect splicing regulatory elements. Finally, we devised a novel quantitative assessment of tool interpretability and found that tools providing mechanistic explanations of their predictions are often correct with respect to the ground - information, but the use of these tools results in decreased predictive power when compared to black box methods.

CONCLUSIONS

Our findings translate into practical recommendations for tool usage and provide a reference framework for applying prediction tools in deep intronic regions, enabling more informed decision-making by practitioners.

Functional Assays Reclassify Suspected Splice-Altering Variants of Uncertain Significance in Mendelian Channelopathies

BACKGROUND

Rare protein-altering variants in SCN5A, KCNQ1, and KCNH2 are major causes of Brugada syndrome and the congenital long QT syndrome. While splice-altering variants lying outside 2-bp canonical splice sites can cause these diseases, their role remains poorly described. We implemented 2 functional assays to assess 12 recently reported putative splice-altering variants of uncertain significance and 1 likely pathogenic variant without functional data observed in Brugada syndrome and long QT syndrome probands.

METHODS

We deployed minigene assays to assess the splicing consequences of 10 variants. Three variants incompatible with the minigene approach were introduced into control induced pluripotent stem cells by CRISPR genome editing. We differentiated cells into induced pluripotent stem cell-derived cardiomyocytes and studied splicing outcomes by reverse transcription-polymerase chain reaction. We used the American College of Medical Genetics and Genomics functional assay criteria (PS3/BS3) to reclassify variants.

RESULTS

We identified aberrant splicing, with presumed disruption of protein sequence, in 8/10 variants studied using the minigene assay and 1/3 studied in induced pluripotent stem cell-derived cardiomyocytes. We reclassified 8 variants of uncertain significance to likely pathogenic, 1 variant of uncertain significance to likely benign, and 1 likely pathogenic variant to pathogenic.

CONCLUSIONS

Functional assays reclassified splice-altering variants outside canonical splice sites in Brugada Syndrome- and long QT syndrome-associated genes.

Selection of Diagnostically Significant Regions of the SLC26A4 Gene Involved in Hearing Loss

Screening pathogenic variants in the SLC26A4 gene is an important part of molecular genetic testing for hearing loss (HL) since they are one of the common causes of hereditary HL in many populations. However, a large size of the SLC26A4 gene (20 coding exons) predetermines the difficulties of its complete mutational analysis, especially in large samples of patients. In addition, the regional or ethno-specific prevalence of SLC26A4 pathogenic variants has not yet been fully elucidated, except variants c.919-2A>G and c.2168A>G (p.His723Arg), which have been proven to be most common in Asian populations. We explored the distribution of currently known pathogenic and likely pathogenic (PLP) variants across the SLC26A4 gene sequence presented in the Deafness Variation Database for the selection of potential diagnostically important parts of this gene. As a result of this bioinformatic analysis, we found that molecular testing ten SLC26A4 exons (4, 6, 10, 11, 13−17 and 19) with flanking intronic regions can provide a diagnostic rate of 61.9% for all PLP variants in the SLC26A4 gene. The primary sequencing of these SLC26A4 regions may be applied as an initial effective diagnostic testing in samples of patients of unknown ethnicity or as a subsequent step after the targeted testing of already-known ethno- or region-specific pathogenic SLC26A4 variants.

Exploration of Tools for the Interpretation of Human Non-Coding Variants

The advent of Whole Genome Sequencing (WGS) broadened the genetic variation detection range, revealing the presence of variants even in non-coding regions of the genome, which would have been missed using targeted approaches. One of the most challenging issues in WGS analysis regards the interpretation of annotated variants. This review focuses on tools suitable for the functional annotation of variants falling into non-coding regions. It couples the description of non-coding genomic areas with the results and performance of existing tools for a functional interpretation of the effect of variants in these regions. Tools were tested in a controlled genomic scenario, representing the ground-truth and allowing us to determine software performance.

A systematic analysis of splicing variants identifies new diagnoses in the 100,000 Genomes Project

BACKGROUND

Genomic variants which disrupt splicing are a major cause of rare genetic diseases. However, variants which lie outside of the canonical splice sites are difficult to interpret clinically. Improving the clinical interpretation of non-canonical splicing variants offers a major opportunity to uplift diagnostic yields from whole genome sequencing data.

METHODS

Here, we examine the landscape of splicing variants in whole-genome sequencing data from 38,688 individuals in the 100,000 Genomes Project and assess the contribution of non-canonical splicing variants to rare genetic diseases. We use a variant-level constraint metric (the mutability-adjusted proportion of singletons) to identify constrained functional variant classes near exon-intron junctions and at putative splicing branchpoints. To identify new diagnoses for individuals with unsolved rare diseases in the 100,000 Genomes Project, we identified individuals with de novo single-nucleotide variants near exon-intron boundaries and at putative splicing branchpoints in known disease genes. We identified candidate diagnostic variants through manual phenotype matching and confirmed new molecular diagnoses through clinical variant interpretation and functional RNA studies.

RESULTS

We show that near-splice positions and splicing branchpoints are highly constrained by purifying selection and harbour potentially damaging non-coding variants which are amenable to systematic analysis in sequencing data. From 258 de novo splicing variants in known rare disease genes, we identify 35 new likely diagnoses in probands with an unsolved rare disease. To date, we have confirmed a new diagnosis for six individuals, including four in whom RNA studies were performed.

CONCLUSIONS

Overall, we demonstrate the clinical value of examining non-canonical splicing variants in individuals with unsolved rare diseases.

Recommendations for clinical interpretation of variants found in non-coding regions of the genome

BACKGROUND

The majority of clinical genetic testing focuses almost exclusively on regions of the genome that directly encode proteins. The important role of variants in non-coding regions in penetrant disease is, however, increasingly being demonstrated, and the use of whole genome sequencing in clinical diagnostic settings is rising across a large range of genetic disorders. Despite this, there is no existing guidance on how current guidelines designed primarily for variants in protein-coding regions should be adapted for variants identified in other genomic contexts.

METHODS

We convened a panel of nine clinical and research scientists with wide-ranging expertise in clinical variant interpretation, with specific experience in variants within non-coding regions. This panel discussed and refined an initial draft of the guidelines which were then extensively tested and reviewed by external groups.

RESULTS

We discuss considerations specifically for variants in non-coding regions of the genome. We outline how to define candidate regulatory elements, highlight examples of mechanisms through which non-coding region variants can lead to penetrant monogenic disease, and outline how existing guidelines can be adapted for the interpretation of these variants.

CONCLUSIONS

These recommendations aim to increase the number and range of non-coding region variants that can be clinically interpreted, which, together with a compatible phenotype, can lead to new diagnoses and catalyse the discovery of novel disease mechanisms.

Rescue of mis-splicing of a common SLC26A4 mutant associated with sensorineural hearing loss by antisense oligonucleotides

A wide spectrum of SLC26A4 mutations causes Pendred syndrome and enlarged vestibular aqueduct, both associated with sensorineural hearing loss (SNHL). A splice-site mutation, c.919-2A>G (A-2G), which is common in Asian populations, impairs the 3′ splice site of intron 7, resulting in exon 8 skipping during pre-mRNA splicing and a subsequent frameshift that creates a premature termination codon in the following exon. Currently, there is no effective drug treatment for SHNL. For A-2G-triggered SNHL, molecules that correct mis-splicing of the mutant hold promise to treat the disease. Antisense oligonucleotides (ASOs) can promote exon inclusion when targeting specific splicing silencers. Here, we systematically screened a large number of ASOs in a minigene system and identified a few that markedly repressed exon 8 skipping. A lead ASO, which targets a heterogeneous nuclear ribonucleoprotein (hnRNP) A1/A2 intronic splicing silencer (ISS) in intron 8, promoted efficient exon 8 inclusion in cultured peripheral blood mononuclear cells derived from two homozygous patients. In a partially humanized Slc26a4 A-2G mouse model, two subcutaneous injections of the ASO at 160 mg/kg significantly rescued exon 8 splicing in the liver. Our results demonstrate that the ISS-targeting ASO has therapeutic potential to treat genetic hearing loss caused by the A-2G mutation in SLC26A4.

Possible Catch-Up Developmental Trajectories for Children with Mild Developmental Delay Caused by NAA15 Pathogenic Variants

Variants in NAA15 are closely related to neurodevelopmental disorders (NDDs). In this study, we investigated the spectrum and clinical features of NAA15 variants in a Chinese NDD cohort of 769 children. Four novel NAA15 pathogenic variants were detected by whole-exome sequencing, including three de novo variants and one maternal variant. The in vitro minigene splicing assay confirmed one noncanonical splicing variant (c.1410+5G>C), which resulted in abnormal mRNA splicing. All affected children presented mild developmental delay, and catch-up trajectories were noted in three patients based on their developmental scores at different ages. Meanwhile, the literature review also showed that half of the reported patients with NAA15 variants presented mild/moderate developmental delay or intellectual disability, and possible catch-up sign was indicated for three affected patients. Taken together, our study expanded the spectrum of NAA15 variants in NDD patients. The affected patients presented mild developmental delay, and possible catch-up developmental trajectories were suggested. Studying the natural neurodevelopmental trajectories of NDD patients with pathogenic variants and their benefits from physical rehabilitations are needed in the future for precise genetic counseling and clinical management.

ECNano: A cost-effective workflow for target enrichment sequencing and accurate variant calling on 4800 clinically significant genes using a single MinION flowcell

BACKGROUND

The application of long-read sequencing using the Oxford Nanopore Technologies (ONT) MinION sequencer is getting more diverse in the medical field. Having a high sequencing error of ONT and limited throughput from a single MinION flowcell, however, limits its applicability for accurate variant detection. Medical exome sequencing (MES) targets clinically significant exon regions, allowing rapid and comprehensive screening of pathogenic variants. By applying MES with MinION sequencing, the technology can achieve a more uniform capture of the target regions, shorter turnaround time, and lower sequencing cost per sample.

METHOD

We introduced a cost-effective optimized workflow, ECNano, comprising a wet-lab protocol and bioinformatics analysis, for accurate variant detection at 4800 clinically important genes and regions using a single MinION flowcell. The ECNano wet-lab protocol was optimized to perform long-read target enrichment and ONT library preparation to stably generate high-quality MES data with adequate coverage. The subsequent variant-calling workflow, Clair-ensemble, adopted a fast RNN-based variant caller, Clair, and was optimized for target enrichment data. To evaluate its performance and practicality, ECNano was tested on both reference DNA samples and patient samples.

RESULTS

ECNano achieved deep on-target depth of coverage (DoC) at average > 100× and > 98% uniformity using one MinION flowcell. For accurate ONT variant calling, the generated reads sufficiently covered 98.9% of pathogenic positions listed in ClinVar, with 98.96% having at least 30× DoC. ECNano obtained an average read length of 1000 bp. The long reads of ECNano also covered the adjacent splice sites well, with 98.5% of positions having ≥ 30× DoC. Clair-ensemble achieved > 99% recall and accuracy for SNV calling. The whole workflow from wet-lab protocol to variant detection was completed within three days.

CONCLUSION

We presented ECNano, an out-of-the-box workflow comprising (1) a wet-lab protocol for ONT target enrichment sequencing and (2) a downstream variant detection workflow, Clair-ensemble. The workflow is cost-effective, with a short turnaround time for high accuracy variant calling in 4800 clinically significant genes and regions using a single MinION flowcell. The long-read exon captured data has potential for further development, promoting the application of long-read sequencing in personalized disease treatment and risk prediction.

Further delineation of phenotypic spectrum of SCN2A-related disorder

SCN2A-related disorders include intellectual disability, autism spectrum disorder, seizures, episodic ataxia, and schizophrenia. In this study, the phenotype-genotype association in SCN2A-related disorders was further delineated by collecting detailed clinical and molecular characteristics. Using previously proposed genotype-phenotype hypotheses based on variant function and position, the potential of phenotype prediction from the variants found was examined. Patients were identified through the Deciphering Developmental Disorders study and gene matching strategies. Phenotypic information and variant interpretation evidence were collated. Seventeen previously unreported patients and five patients who had been previously reported (but with minimal phenotypic and segregation data) were included (10 males, 12 females; median age 10.5 years). All patients had developmental delays and the majority had intellectual disabilities. Seizures were reported in 15 of 22 (68.2%), four of 22 (18.2%) had autism spectrum disorder and no patients were reported with episodic ataxia. The majority of variants were de novo. One family had presumed gonadal mosaicism. The correlation of the use of sodium channel-blocking antiepileptic drugs with phenotype or genotype was variable. These data suggest that variant type and position alone can provide some predictive information about the phenotype in a proportion of cases, but more precise assessment of variant function is needed for meaningful phenotype prediction.

Insights of Noncanonical Splice-site Variants on RNA Splicing in Patients With Congenital Hypothyroidism

CONTEXT

Congenital hypothyroidism (CH) is caused by mutations in the genes for thyroid hormone synthesis. In our previous investigation of CH patients, approximately 53% of patients had mutations in either coding exons or canonical splice sites of causative genes. Noncanonical splice-site variants in the intron were detected but their pathogenic significance was not known.

OBJECTIVE

This work aims to evaluate noncanonical splice-site variants on pre-messenger RNA (pre-mRNA) splicing of CH-causing genes.

METHODS

Next-generation sequencing data of 55 CH cases in 47 families were analyzed to identify rare intron variants. The effects of variants on pre-mRNA splicing were investigated by minigene RNA-splicing assay.

RESULTS

Four intron variants were found in 3 patients: solute carrier family 26 member 4 (SLC26A4) c.1544+9C>T and c.1707+94C>T in one patient, and solute carrier family 5 member 5 (SLC5A5) c.970-48G>C and c.1652-97A>C in 2 other patients. The c.1707+94C>T and c.970-48G>C caused exons 15 and 16 skipping, and exon 8 skipping, respectively. The remaining variants had no effect on RNA splicing. Furthermore, we analyzed 28 previously reported noncanonical splice-site variants (4 in TG and 24 in SLC26A4). Among them, 15 variants (~ 54%) resulted in aberrant splicing and 13 variants had no effect on RNA splicing. These data were compared with 3 variant-prediction programs (FATHMM-XF, FATHMM-MKL, and CADD). Among 32 variants, FATHMM-XF, FATHMM-MKL, and CADD correctly predicted 20 (63%), 17 (53%), and 26 (81%) variants, respectively.

CONCLUSION

Two novel deep intron mutations have been identified in SLC26A4 and SLC5A5, bringing the total number of solved families with disease-causing mutations to approximately 45% in our cohort. Approximately 46% (13/28) of reported noncanonical splice-site mutations do not disrupt pre-mRNA splicing. CADD provides highest prediction accuracy of noncanonical splice-site variants.

Hereditary spastic paraplegia associated with a novel homozygous intronic noncanonical splice site variant in the AP4B1 gene

Pathogenic variants in the AP4B1 gene lead to a rare form of hereditary spastic paraplegia (HSP) known as SPG47. We report on a patient with a clinical suspicion of complicated HSP of the lower limbs with intellectual disability, as well as a novel homozygous noncanonical splice site variant in the AP4B1 gene, in which the effect on splicing was validated by RNA analysis. We sequenced 152 genes associated with HSP using Next-Generation Sequencing (NGS). We isolated total RNA from peripheral blood and generated cDNA using reverse transcription-polymerase chain reaction (RT-PCR). A region of AP4B1 mRNA was amplified by PCR and the fragments obtained were purified from the agarose gel and sequenced. We found a homozygous variant of uncertain significance in the AP4B1 gene NM_006594.4: c.1511-6C>G in the proband. Two different AP4B1 mRNA fragments were obtained in the patient and his carrier parents. The shorter fragment was the predominant fragment in the patient and revealed a deletion with skipping of the AP4B1 exon 10. The patient's longer fragment corresponded to an insertion of the last five nucleotides of AP4B1 intron 9. We confirmed that this variant affects the normal splicing of RNA, sustaining the molecular diagnosis of SPG47 in the patient.

Profile of Basal Cell Carcinoma Mutations and Copy Number Alterations - Focus on Gene-Associated Noncoding Variants

Basal cell carcinoma (BCC) of the skin is the most common cancer in humans, characterized by the highest mutation rate among cancers, and is mostly driven by mutations in genes involved in the hedgehog pathway. To date, almost all BCC genetic studies have focused exclusively on protein-coding sequences; therefore, the impact of noncoding variants on the BCC genome is unrecognized. In this study, with the use of whole-exome sequencing of 27 tumor/normal pairs of BCC samples, we performed an analysis of somatic mutations in both protein-coding sequences and gene-associated noncoding regions, including 5'UTRs, 3'UTRs, and exon-adjacent intron sequences. Separately, in each region, we performed hotspot identification, mutation enrichment analysis, and cancer driver identification with OncodriveFML. Additionally, we performed a whole-genome copy number alteration analysis with GISTIC2. Of the >80,000 identified mutations, ~50% were localized in noncoding regions. The results of the analysis generally corroborated the previous findings regarding genes mutated in coding sequences, including PTCH1, TP53, and MYCN, but more importantly showed that mutations were also clustered in specific noncoding regions, including hotspots. Some of the genes specifically mutated in noncoding regions were identified as highly potent cancer drivers, of which BAD had a mutation hotspot in the 3'UTR, DHODH had a mutation hotspot in the Kozak sequence in the 5'UTR, and CHCHD2 frequently showed mutations in the 5'UTR. All of these genes are functionally implicated in cancer-related processes (e.g., apoptosis, mitochondrial metabolism, and de novo pyrimidine synthesis) or the pathogenesis of UV radiation-induced cancers. We also found that the identified BAD and CHCHD2 mutations frequently occur in melanoma but not in other cancers via The Cancer Genome Atlas analysis. Finally, we identified a frequent deletion of chr9q, encompassing PTCH1, and unreported frequent copy number gain of chr9p, encompassing the genes encoding the immune checkpoint ligands PD-L1 and PD-L2. In conclusion, this study is the first systematic analysis of coding and noncoding mutations in BCC and provides a strong basis for further analyses of the variants in BCC and cancer in general.

Detecting cryptic clinically relevant structural variation in exome-sequencing data increases diagnostic yield for developmental disorders

Structural variation (SV) describes a broad class of genetic variation greater than 50 bp in size. SVs can cause a wide range of genetic diseases and are prevalent in rare developmental disorders (DDs). Individuals presenting with DDs are often referred for diagnostic testing with chromosomal microarrays (CMAs) to identify large copy-number variants (CNVs) and/or with single-gene, gene-panel, or exome sequencing (ES) to identify single-nucleotide variants, small insertions/deletions, and CNVs. However, individuals with pathogenic SVs undetectable by conventional analysis often remain undiagnosed. Consequently, we have developed the tool InDelible, which interrogates short-read sequencing data for split-read clusters characteristic of SV breakpoints. We applied InDelible to 13,438 probands with severe DDs recruited as part of the Deciphering Developmental Disorders (DDD) study and discovered 63 rare, damaging variants in genes previously associated with DDs missed by standard SNV, indel, or CNV discovery approaches. Clinical review of these 63 variants determined that about half (30/63) were plausibly pathogenic. InDelible was particularly effective at ascertaining variants between 21 and 500 bp in size and increased the total number of potentially pathogenic variants identified by DDD in this size range by 42.9%. Of particular interest were seven confirmed de novo variants in MECP2, which represent 35.0% of all de novo protein-truncating variants in MECP2 among DDD study participants. InDelible provides a framework for the discovery of pathogenic SVs that are most likely missed by standard analytical workflows and has the potential to improve the diagnostic yield of ES across a broad range of genetic diseases.

The intronic branch point sequence is under strong evolutionary constraint in the bovine and human genome

The branch point sequence is a cis-acting intronic motif required for mRNA splicing. Despite their functional importance, branch point sequences are not routinely annotated. Here we predict branch point sequences in 179,476 bovine introns and investigate their variability using a catalogue of 29.4 million variants detected in 266 cattle genomes. We localize the bovine branch point within a degenerate heptamer "nnyTrAy". An adenine residue at position 6, that acts as branch point, and a thymine residue at position 4 of the heptamer are more strongly depleted for mutations than coding sequences suggesting extreme purifying selection. We provide evidence that mutations affecting these evolutionarily constrained residues lead to alternative splicing. We confirm evolutionary constraints on branch point sequences using a catalogue of 115 million SNPs established from 3,942 human genomes of the gnomAD database.

Germline RAD51B variants confer susceptibility to breast and ovarian cancers deficient in homologous recombination

Pathogenic germline mutations in the RAD51 paralog genes RAD51C and RAD51D, are known to confer susceptibility to ovarian and triple-negative breast cancer. Here, we investigated whether germline loss-of-function variants affecting another RAD51 paralog gene, RAD51B, are also associated with breast and ovarian cancer. Among 3422 consecutively accrued breast and ovarian cancer patients consented to tumor/germline sequencing, the observed carrier frequency of loss-of-function germline RAD51B variants was significantly higher than control cases from the gnomAD population database (0.26% vs 0.09%), with an odds ratio of 2.69 (95% CI: 1.4-5.3). Furthermore, we demonstrate that tumors harboring biallelic RAD51B alteration are deficient in homologous recombination DNA repair deficiency (HRD), as evidenced by analysis of sequencing data and in vitro functional assays. Our findings suggest that RAD51B should be considered as an addition to clinical germline testing panels for breast and ovarian cancer susceptibility.

A Case Series of Familial ARID1B Variants Illustrating Variable Expression and Suggestions to Update the ACMG Criteria

ARID1B is one of the most frequently mutated genes in intellectual disability (~1%). Most variants are readily classified, since they are de novo and are predicted to lead to loss of function, and therefore classified as pathogenic according to the American College of Medical Genetics and Genomics (ACMG) guidelines for the interpretation of sequence variants. However, familial loss-of-function variants can also occur and can be challenging to interpret. Such variants may be pathogenic with variable expression, causing only a mild phenotype in a parent. Alternatively, since some regions of the ARID1B gene seem to be lacking pathogenic variants, loss-of-function variants in those regions may not lead to ARID1B haploinsufficiency and may therefore be benign. We describe 12 families with potential loss-of-function variants, which were either familial or with unknown inheritance and were in regions where pathogenic variants have not been described or are otherwise challenging to interpret. We performed detailed clinical and DNA methylation studies, which allowed us to confidently classify most variants. In five families we observed transmission of pathogenic variants, confirming their highly variable expression. Our findings provide further evidence for an alternative translational start site and we suggest updates for the ACMG guidelines for the interpretation of sequence variants to incorporate DNA methylation studies and facial analyses.

High-throughput splicing assays identify missense and silent splice-disruptive POU1F1 variants underlying pituitary hormone deficiency

Pituitary hormone deficiency occurs in ∼1:4,000 live births. Approximately 3% of the cases are due to mutations in the alpha isoform of POU1F1, a pituitary-specific transcriptional activator. We found four separate heterozygous missense variants in unrelated individuals with hypopituitarism that were predicted to affect a minor isoform, POU1F1 beta, which can act as a transcriptional repressor. These variants retain repressor activity, but they shift splicing to favor the expression of the beta isoform, resulting in dominant-negative loss of function. Using a high-throughput splicing reporter assay, we tested 1,070 single-nucleotide variants in POU1F1. We identified 96 splice-disruptive variants, including 14 synonymous variants. In separate cohorts, we found two additional synonymous variants nominated by this screen that co-segregate with hypopituitarism. This study underlines the importance of evaluating the impact of variants on splicing and provides a catalog for interpretation of variants of unknown significance in POU1F1.

Splicing in the Diagnosis of Rare Disease: Advances and Challenges

Mutations which affect splicing are significant contributors to rare disease, but are frequently overlooked by diagnostic sequencing pipelines. Greater ascertainment of pathogenic splicing variants will increase diagnostic yields, ending the diagnostic odyssey for patients and families affected by rare disorders, and improving treatment and care strategies. Advances in sequencing technologies, predictive modeling, and understanding of the mechanisms of splicing in recent years pave the way for improved detection and interpretation of splice affecting variants, yet several limitations still prohibit their routine ascertainment in diagnostic testing. This review explores some of these advances in the context of clinical application and discusses challenges to be overcome before these variants are comprehensively and routinely recognized in diagnostics.

Refinement of the clinical variant interpretation framework by statistical evidence and machine learning

BACKGROUND

Although the American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines for variant interpretation are used widely in clinical genetics, there is room for improvement of these knowledge-based guidelines.

METHODS

Statistical assessment of average deleteriousness of start-lost, stop-lost, and in-frame insertion and deletion (indel) variants and extraction of deleterious subsets was performed, being informed by proportions of rare variants in the general population of the Genome Aggregation Database (gnomAD). A machine learning-based model scoring the pathogenicity of start-lost variants (the PoStaL model) was constructed by predicting possible translation initiation sites on transcripts by deep learning and training a random forest on known pathogenic and likely benign variants.

FINDINGS

The proportion of rare variants was highest in stop-lost variants, followed by in-frame indels and start-lost variants, suggesting that the criteria in the ACMG/AMP guidelines assigning PVS (pathogenic very strong) to start-lost variants and PM (pathogenic moderate) to stop-lost and in-frame indel variants would not be appropriate. Regarding deleterious subsets, stop-lost variants introducing extensions of more than 30 amino acids and in-frame indels computationally predicted to be damaging are enriched for rare and known pathogenic variants. For start-lost variants, we developed the PoStaL model, which outperforms existing tools. We also provide comprehensive lists of the PoStaL scores for start-lost variants and the length of extended amino acids by stop-lost variants.

CONCLUSIONS

Our study could contribute to refinement of the ACMG/AMP guidelines, provides resources for future investigation, and provides an example of how to improve knowledge-based frameworks by data-driven approaches.

FUNDING

The study was supported by grants from the Japan Agency for Medical Research and Development (AMED) and the Japan Society for the Promotion of Science (JSPS).

Different types of disease-causing noncoding variants revealed by genomic and gene expression analyses in families with X-linked intellectual disability

The pioneering discovery research of X-linked intellectual disability (XLID) genes has benefitted thousands of individuals worldwide; however, approximately 30% of XLID families still remain unresolved. We postulated that noncoding variants that affect gene regulation or splicing may account for the lack of a genetic diagnosis in some cases. Detecting pathogenic, gene-regulatory variants with the same sensitivity and specificity as structural and coding variants is a major challenge for Mendelian disorders. Here, we describe three pedigrees with suggestive XLID where distinctive phenotypes associated with known genes guided the identification of three different noncoding variants. We used comprehensive structural, single-nucleotide, and repeat expansion analyses of genome sequencing. RNA-Seq from patient-derived cell lines, reverse-transcription polymerase chain reactions, Western blots, and reporter gene assays were used to confirm the functional effect of three fundamentally different classes of pathogenic noncoding variants: a retrotransposon insertion, a novel intronic splice donor, and a canonical splice variant of an untranslated exon. In one family, we excluded a rare coding variant in ARX, a known XLID gene, in favor of a regulatory noncoding variant in OFD1 that correlated with the clinical phenotype. Our results underscore the value of genomic research on unresolved XLID families to aid novel, pathogenic noncoding variant discovery.

Spectrum of splicing variants in disease genes and the ability of RNA analysis to reduce uncertainty in clinical interpretation

The complexities of gene expression pose challenges for the clinical interpretation of splicing variants. To better understand splicing variants and their contribution to hereditary disease, we evaluated their prevalence, clinical classifications, and associations with diseases, inheritance, and functional characteristics in a 689,321-person clinical cohort and two large public datasets. In the clinical cohort, splicing variants represented 13% of all variants classified as pathogenic (P), likely pathogenic (LP), or variants of uncertain significance (VUSs). Most splicing variants were outside essential splice sites and were classified as VUSs. Among all individuals tested, 5.4% had a splicing VUS. If RNA analysis were to contribute supporting evidence to variant interpretation, we estimated that splicing VUSs would be reclassified in 1.7% of individuals in our cohort. This would result in a clinically significant result (i.e., P/LP) in 0.1% of individuals overall because most reclassifications would change VUSs to likely benign. In ClinVar, splicing VUSs were 4.8% of reported variants and could benefit from RNA analysis. In the Genome Aggregation Database (gnomAD), splicing variants comprised 9.4% of variants in protein-coding genes; most were rare, precluding unambiguous classification as benign. Splicing variants were depleted in genes associated with dominant inheritance and haploinsufficiency, although some genes had rare variants at essential splice sites or had common splicing variants that were most likely compatible with normal gene function. Overall, we describe the contribution of splicing variants to hereditary disease, the potential utility of RNA analysis for reclassifying splicing VUSs, and how natural variation may confound clinical interpretation of splicing variants.

Applying genomic and transcriptomic advances to mitochondrial medicine

Next-generation sequencing (NGS) has increased our understanding of the molecular basis of many primary mitochondrial diseases (PMDs). Despite this progress, many patients with suspected PMD remain without a genetic diagnosis, which restricts their access to in-depth genetic counselling, reproductive options and clinical trials, in addition to hampering efforts to understand the underlying disease mechanisms. Although they represent a considerable improvement over their predecessors, current methods for sequencing the mitochondrial and nuclear genomes have important limitations, and molecular diagnostic techniques are often manual and time consuming. However, recent advances in genomics and transcriptomics offer realistic solutions to these challenges. In this Review, we discuss the current genetic testing approach for PMDs and the opportunities that exist for increased use of whole-genome NGS of nuclear and mitochondrial DNA (mtDNA) in the clinical environment. We consider the possible role for long-read approaches in sequencing of mtDNA and in the identification of novel nuclear genomic causes of PMDs. We examine the expanding applications of RNA sequencing, including the detection of cryptic variants that affect splicing and gene expression and the interpretation of rare and novel mitochondrial transfer RNA variants.

Evaluating variants classified as pathogenic in ClinVar in the DDD Study

PURPOSE

Automated variant filtering is an essential part of diagnostic genome-wide sequencing but may generate false negative results. We sought to investigate whether some previously identified pathogenic variants may be being routinely excluded by standard variant filtering pipelines.

METHODS

We evaluated variants that were previously classified as pathogenic or likely pathogenic in ClinVar in known developmental disorder genes using exome sequence data from the Deciphering Developmental Disorders (DDD) study.

RESULTS

Of these ClinVar pathogenic variants, 3.6% were identified among 13,462 DDD probands, and 1134/1352 (83.9%) had already been independently communicated to clinicians using DDD variant filtering pipelines as plausibly pathogenic. The remaining 218 variants failed consequence, inheritance, or other automated variant filters. Following clinical review of these additional variants, we were able to identify 112 variants in 107 (0.8%) DDD probands as potential diagnoses.

CONCLUSION

Lower minor allele frequency (<0.0005%) and higher gold star review status in ClinVar (>1 star) are good predictors of a previously identified variant being plausibly diagnostic for developmental disorders. However, around half of previously identified pathogenic variants excluded by automated variant filtering did not appear to be disease-causing, underlining the continued need for clinical evaluation of candidate variants as part of the diagnostic process.

RET compound inheritance in Chinese patients with Hirschsprung disease: lack of penetrance from insufficient gene dysfunction

Hirschsprung disease (HSCR) is a neurocristopathy characterized by the absence of enteric ganglia along variable lengths of the intestine. Genetic defects play a major role in HSCR pathogenesis with nearly 50% of patients having a structural or regulatory deficiency in the major susceptibility gene RET. However, complete molecular defects remain poorly characterized in most patients. Here, we performed detailed genetic, molecular, and populational investigations of rare null mutations and modifiers at the RET locus. We first verified the pathogenicity of three RET splice site mutants (c.1879 + 1G > A, c.2607 + 5G > A and c.2608-3C > G) at the RNA level. We also identified significantly higher risk allele (genotype) frequencies, and their over-transmission, from unaffected parents to affected offspring of three functionally independent enhancer variants (rs2506030, rs7069590 and rs2435357, with odd ratios (OR) of 2.09, 2.71 and 7.59, respectively, P < 0.001). These three common variants are in significant (P < 4.64 × 10^-186) linkage disequilibrium in the Han Chinese population with ~ 60% of them carrying at least one copy and > 10% with two copies. We show that RET compound inheritance of rare and common variants prevails in 64% (seven out of 11) of Chinese HSCR families. This study supports the idea that common RET variants can modify the penetrance of rare null RET mutations in HSCR, and the combined high susceptibility allele dosage may constitute the unique raised "risk baseline" among the Chinese population.

Interactive Web-Based Resource for Annotation of Genetic Variants Causing Hereditary Angioedema (HADA): Database Development, Implementation, and Validation

BACKGROUND

Hereditary angioedema is a rare genetic condition caused by C1 esterase inhibitor deficiency, dysfunction, or kinin cascade dysregulation, leading to an increased bradykinin plasma concentration. Hereditary angioedema is a poorly recognized clinical entity and is very often misdiagnosed as a histaminergic angioedema. Despite its genetic nature, first-line genetic screening is not integrated in routine diagnosis. Consequently, a delay in the diagnosis, and inaccurate or incomplete diagnosis and treatment of hereditary angioedema are common.

OBJECTIVE

In agreement with recent recommendations from the International Consensus on the Use of Genetics in the Management of Hereditary Angioedema, to facilitate the clinical diagnosis and adapt it to the paradigm of precision medicine and next-generation sequencing-based genetic tests, we aimed to develop a genetic annotation tool, termed Hereditary Angioedema Database Annotation (HADA).

METHODS

HADA is built on top of a database of known variants affecting function, including precomputed pathogenic assessment of each variant and a ranked classification according to the current guidelines from the American College of Medical Genetics and Genomics.

RESULTS

HADA is provided as a freely accessible, user-friendly web-based interface with versatility for the entry of genetic information. The underlying database can also be incorporated into automated command-line stand-alone annotation tools.

CONCLUSIONS

HADA can achieve the rapid detection of variants affecting function for different hereditary angioedema types, and further integrates useful information to reduce the diagnosis odyssey and improve its delay.

Disrupted minor intron splicing is prevalent in Mendelian disorders

Background

Splicing is crucial for proper gene expression, and is predominately executed by the major spliceosome. Conversely, 722 introns in 699 human minor intron‐containing genes (MIGs) are spliced by the minor spliceosome. Splicing of these minor introns is disrupted in diseases caused by pathogenic variants in the minor spliceosome, ultimately leading to the aberrant expression of a subset of these MIGs. However, the effect of variants in minor introns and MIGs on diseases remains unexplored.

Methods

Variants in MIGs and associated clinical manifestations were identified using ClinVar. The HPO database was then used to curate the related symptoms and affected organ systems. Results: We found pathogenic variants in 211 MIGs, which commonly resulted in intellectual disability, seizures and microcephaly. This revealed a subset of MIGs whose aberrant splicing may contribute to the pathogenesis of minor spliceosome‐related diseases. Moreover, we identified 51 pathogenic variants in minor intron splice sites that reduce the splice site strength and can induce alternative splicing.

Conclusion

These findings highlight that disrupted minor intron splicing has a broader impact on human diseases than previously appreciated. The hope is that this knowledge will aid in the development of therapeutic strategies that incorporate the minor intron splicing pathway.

Characterising the loss-of-function impact of 5' untranslated region variants in 15,708 individuals

Upstream open reading frames (uORFs) are tissue-specific cis-regulators of protein translation. Isolated reports have shown that variants that create or disrupt uORFs can cause disease. Here, in a systematic genome-wide study using 15,708 whole genome sequences, we show that variants that create new upstream start codons, and variants disrupting stop sites of existing uORFs, are under strong negative selection. This selection signal is significantly stronger for variants arising upstream of genes intolerant to loss-of-function variants. Furthermore, variants creating uORFs that overlap the coding sequence show signals of selection equivalent to coding missense variants. Finally, we identify specific genes where modification of uORFs likely represents an important disease mechanism, and report a novel uORF frameshift variant upstream of NF2 in neurofibromatosis. Our results highlight uORF-perturbing variants as an under-recognised functional class that contribute to penetrant human disease, and demonstrate the power of large-scale population sequencing data in studying non-coding variant classes.

Clinical impact of splicing in neurodevelopmental disorders

Clinical exome sequencing is frequently used to identify gene-disrupting variants in individuals with neurodevelopmental disorders. While splice-disrupting variants are known to contribute to these disorders, clinical interpretation of cryptic splice variants outside of the canonical splice site has been challenging. Here, we discuss papers that improve such detection.

De Novo Truncating Variants in the Last Exon of SEMA6B Cause Progressive Myoclonic Epilepsy

De novo variants (DNVs) cause many genetic diseases. When DNVs are examined in the whole coding regions of genes in next-generation sequencing analyses, pathogenic DNVs often cluster in a specific region. One such region is the last exon and the last 50 bp of the penultimate exon, where truncating DNVs cause escape from nonsense-mediated mRNA decay [NMD(-) region]. Such variants can have dominant-negative or gain-of-function effects. Here, we first developed a resource of rates of truncating DNVs in NMD(-) regions under the null model of DNVs. Utilizing this resource, we performed enrichment analysis of truncating DNVs in NMD(-) regions in 346 developmental and epileptic encephalopathy (DEE) trios. We observed statistically significant enrichment of truncating DNVs in semaphorin 6B (SEMA6B) (p value: 2.8 × 10^-8; exome-wide threshold: 2.5 × 10^-6). The initial analysis of the 346 individuals and additional screening of 1,406 and 4,293 independent individuals affected by DEE and developmental disorders collectively identified four truncating DNVs in the SEMA6B NMD(-) region in five individuals who came from unrelated families (p value: 1.9 × 10^-13) and consistently showed progressive myoclonic epilepsy. RNA analysis of lymphoblastoid cells established from an affected individual showed that the mutant allele escaped NMD, indicating stable production of the truncated protein. Importantly, heterozygous truncating variants in the NMD(+) region of SEMA6B are observed in general populations, and SEMA6B is most likely loss-of-function tolerant. Zebrafish expressing truncating variants in the NMD(-) region of SEMA6B orthologs displayed defective development of brain neurons and enhanced pentylenetetrazole-induced seizure behavior. In summary, we show that truncating DNVs in the final exon of SEMA6B cause progressive myoclonic epilepsy.

Increasing the Genetic Diagnosis Yield in Inherited Retinal Dystrophies: Assigning Pathogenicity to Novel Non-canonical Splice Site Variants

Aims: We aimed to validate the pathogenicity of genetic variants identified in inherited retinal dystrophy (IRD) patients, which were located in non-canonical splice sites (NCSS). Methods: After next generation sequencing (NGS) analysis (target gene panels or whole exome sequencing (WES)), NCSS variants were prioritized according to in silico predictions. In vivo and in vitro functional tests were used to validate their pathogenicity. Results: Four novel NCSS variants have been identified. They are located in intron 33 and 34 of ABCA4 (c.4774-9G>A and c.4849-8C>G, respectively), intron 2 of POC1B (c.101-3T>G) and intron 3 of RP2 (c.884-14G>A). Functional analysis detected different aberrant splicing events, including intron retention, exon skipping and intronic nucleotide addition, whose molecular effect was either the disruption or the elongation of the open reading frame of the corresponding gene. Conclusions: Our data increase the genetic diagnostic yield of IRD patients and expand the landscape of pathogenic variants, which will have an impact on the genotype–phenotype correlations and allow patients to opt for the emerging gene and cell therapies.

Integrative analysis reveals RNA G-quadruplexes in UTRs are selectively constrained and enriched for functional associations

G-quadruplex (G4) sequences are abundant in untranslated regions (UTRs) of human messenger RNAs, but their functional importance remains unclear. By integrating multiple sources of genetic and genomic data, we show that putative G-quadruplex forming sequences (pG4) in 5' and 3' UTRs are selectively constrained, and enriched for cis-eQTLs and RNA-binding protein (RBP) interactions. Using over 15,000 whole-genome sequences, we find that negative selection acting on central guanines of UTR pG4s is comparable to that of missense variation in protein-coding sequences. At multiple GWAS-implicated SNPs within pG4 UTR sequences, we find robust allelic imbalance in gene expression across diverse tissue contexts in GTEx, suggesting that variants affecting G-quadruplex formation within UTRs may also contribute to phenotypic variation. Our results establish UTR G4s as important cis-regulatory elements and point to a link between disruption of UTR pG4 and disease.

The diagnosis of inborn errors of metabolism by an integrative "multi-omics" approach: A perspective encompassing genomics, transcriptomics, and proteomics

Given the rapidly decreasing cost and increasing speed and accessibility of massively parallel technologies, the integration of comprehensive genomic, transcriptomic, and proteomic data into a "multi-omics" diagnostic pipeline is within reach. Even though genomic analysis has the capability to reveal all possible perturbations in our genetic code, analysis typically reaches a diagnosis in just 35% of cases, with a diagnostic gap arising due to limitations in prioritization and interpretation of detected variants. Here we review the utility of complementing genetic data with transcriptomic data and give a perspective for the introduction of proteomics into the diagnostic pipeline. Together these methodologies enable comprehensive capture of the functional consequence of variants, unobtainable by the analysis of each methodology in isolation. This facilitates functional annotation and reprioritization of candidate genes and variants-a promising approach to shed light on the underlying molecular cause of a patient's disease, increasing diagnostic rate, and allowing actionability in clinical practice.