Pathogenic Abnormal Splicing Due to Intronic Deletions that Induce Biophysical Space Constraint for Spliceosome Assembly

Refining clinically relevant parameters for mis-splicing risk in shortened introns with donor-to-branchpoint space constraint

Intronic deletions that critically shorten donor-to-branchpoint (D-BP) distance of a precursor mRNA impose biophysical space constraint on assembly of the U1/U2 spliceosomal complex, leading to canonical splicing failure. Here we use a series of β-globin (HBB) gene constructs with intron 1 deletions to define D-BP lengths that present low/no risk of mis-splicing and lengths which are critically short and likely elicit clinically relevant mis-splicing. We extend our previous observation in EMD intron 5 of 46 nt as the minimal productive D-BP length, demonstrating spliceosome assembly constraint persists at D-BP lengths of 47-56 nt. We exploit the common HBB exon 1 β-thalassemia variant that strengthens a cryptic donor (NM_000518.5(HBB):c.79G > A) to provide a simple barometer for the earliest signs of space constraint, via cryptic donor activation. For clinical evaluation of intronic deletions, we assert D-BP lengths > 60 nt present low mis-splicing risk while space constraint increases exponentially with D-BP lengths < 55 nt, with critical risk and profound splicing abnormalities with D-BP lengths < 50 nt.

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.

Genome and RNA sequencing boost neuromuscular diagnoses to 62% from 34% with exome sequencing alone

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.

Atypical splicing variants in PKD1 explain most undiagnosed typical familial ADPKD

Autosomal dominant polycystic kidney disease (ADPKD) is the most common monogenic cause of kidney failure and is primarily associated with PKD1 or PKD2. Approximately 10% of patients remain undiagnosed after standard genetic testing. We aimed to utilise short and long-read genome sequencing and RNA studies to investigate undiagnosed families. Patients with typical ADPKD phenotype and undiagnosed after genetic diagnostics were recruited. Probands underwent short-read genome sequencing, PKD1 and PKD2 coding and non-coding analyses and then genome-wide analysis. Targeted RNA studies investigated variants suspected to impact splicing. Those undiagnosed then underwent Oxford Nanopore Technologies long-read genome sequencing. From over 172 probands, 9 met inclusion criteria and consented. A genetic diagnosis was made in 8 of 9 (89%) families undiagnosed on prior genetic testing. Six had variants impacting splicing, five in non-coding regions of PKD1. Short-read genome sequencing identified novel branchpoint, AG-exclusion zone and missense variants generating cryptic splice sites and a deletion causing critical intron shortening. Long-read sequencing confirmed the diagnosis in one family. Most undiagnosed families with typical ADPKD have splice-impacting variants in PKD1. We describe a pragmatic method for diagnostic laboratories to assess PKD1 and PKD2 non-coding regions and validate suspected splicing variants through targeted RNA studies.

Introme accurately predicts the impact of coding and noncoding variants on gene splicing, with clinical applications

Predicting the impact of coding and noncoding variants on splicing is challenging, particularly in non-canonical splice sites, leading to missed diagnoses in patients. Existing splice prediction tools are complementary but knowing which to use for each splicing context remains difficult. Here, we describe Introme, which uses machine learning to integrate predictions from several splice detection tools, additional splicing rules, and gene architecture features to comprehensively evaluate the likelihood of a variant impacting splicing. Through extensive benchmarking across 21,000 splice-altering variants, Introme outperformed all tools (auPRC: 0.98) for the detection of clinically significant splice variants. Introme is available at https://github.com/CCICB/introme .

SpliceVault predicts the precise nature of variant-associated mis-splicing

Even for essential splice-site variants that are almost guaranteed to alter mRNA splicing, no current method can reliably predict whether exon-skipping, cryptic activation or multiple events will result, greatly complicating clinical interpretation of pathogenicity. Strikingly, ranking the four most common unannotated splicing events across 335,663 reference RNA-sequencing (RNA-seq) samples (300K-RNA Top-4) predicts the nature of variant-associated mis-splicing with 92% sensitivity. The 300K-RNA Top-4 events correctly identify 96% of exon-skipping events and 86% of cryptic splice sites for 140 clinical cases subject to RNA testing, showing higher sensitivity and positive predictive value than SpliceAI. Notably, RNA re-analyses showed we had missed 300K-RNA Top-4 events for several clinical cases tested before the development of this empirical predictive method. Simply, mis-splicing events that happen around a splice site in RNA-seq data are those most likely to be activated by a splice-site variant. The SpliceVault web portal allows users easy access to 300K-RNA for informed splice-site variant interpretation and classification.

Unbiased prediction of off-target sites in genome-edited rice using SITE-Seq analysis on a web-based platform

Genome-editing using the CRISPR-Cas9 system has the potential to substantially accelerate crop breeding. Since off-target editing is one of problems, a reliable method for comprehensively detecting off-target sites is needed. A number of in silico methods based on homology to on-target sequence have been developed, however the prediction without false negative is still under discussion. In this study, we performed a SITE-Seq analysis to predict potential off-target sites. SITE-Seq analysis is a comprehensive method that can detect double-strand breaks in vitro. Furthermore, we developed a systematic method using SITE-Seq in combination with web-based Galaxy system (Galaxy for Cut Site Detection), which can perform reproducible analyses without command line operations. We conducted a SITE-Seq analysis of a rice genome targeted by OsFH15 gRNA-Cas9 as a model, and found 41 candidate off-target sites in the annotated regions. Detailed amplicon-sequencing revealed mutations at one off-target site in actual genome-edited rice. Since this off-target site has an uncommon protospacer adjacent motif, it is difficult to predict using in silico methods alone. Therefore, we propose a novel off-target assessment scheme for genome-edited crops that combines the prediction of off-target candidates by SITE-Seq and in silico programs and the validation of off-target sites by amplicon-sequencing.

Biallelic loss-of-function variants in EXOC6B are associated with impaired primary ciliogenesis and cause spondylo-epi-metaphyseal dysplasia with joint laxity type 3

Spondylo-epi-metaphyseal dysplasias with joint laxity, type 3 (SEMDJL3) is a genetic skeletal disorder characterized by multiple joint dislocations, caused by biallelic pathogenic variants in the EXOC6B gene. Only four individuals from two families have been reported to have this condition to date. The molecular pathogenesis related to primary ciliogenesis has not been enumerated in subjects with SEMDJL3. In this study, we report two additional affected individuals from unrelated families with biallelic pathogenic variants, c.2122+15447_2197-59588del and c.401T>G in EXOC6B identified by exome sequencing. One of the affected individuals had an intellectual disability and central nervous system anomalies, including hydrocephalus, hypoplastic mesencephalon, and thin corpus callosum. Using the fibroblast cell lines, we demonstrate the primary evidence for the abrogation of exocytosis in an individual with SEMDLJ3 leading to impaired primary ciliogenesis. Osteogenesis differentiation and pathways related to the extracellular matrix were also found to be reduced. Additionally, we provide a review of the clinical and molecular profile of all the mutation-proven patients reported hitherto, thereby further characterizing SEMDJL3. SEMDJL3 with biallelic pathogenic variants in EXOC6B might represent yet another ciliopathy with central nervous system involvement and joint dislocations.

Centers for Mendelian Genomics: A decade of facilitating gene discovery

PURPOSE

Mendelian disease genomic research has undergone a massive transformation over the past decade. With increasing availability of exome and genome sequencing, the role of Mendelian research has expanded beyond data collection, sequencing, and analysis to worldwide data sharing and collaboration.

METHODS

Over the past 10 years, the National Institutes of Health-supported Centers for Mendelian Genomics (CMGs) have played a major role in this research and clinical evolution.

RESULTS

We highlight the cumulative gene discoveries facilitated by the program, biomedical research leveraged by the approach, and the larger impact on the research community. Beyond generating a list of gene-phenotype relationships and participating in widespread data sharing, the CMGs have created resources, tools, and training for the larger community to foster understanding of genes and genome variation. The CMGs have participated in a wide range of data sharing activities, including deposition of all eligible CMG data into the Analysis, Visualization, and Informatics Lab-space (AnVIL), sharing candidate genes through the Matchmaker Exchange and the CMG website, and sharing variants in Genotypes to Mendelian Phenotypes (Geno2MP) and VariantMatcher.

CONCLUSION

The work is far from complete; strengthening communication between research and clinical realms, continued development and sharing of knowledge and tools, and improving access to richly characterized data sets are all required to diagnose the remaining molecularly undiagnosed patients.

Empirical prediction of variant-activated cryptic splice donors using population-based RNA-Seq data

Predicting which cryptic-donors may be activated by a splicing variant in patient DNA is notoriously difficult. Through analysis of 5145 cryptic-donors (versus 86,963 decoy-donors not used; any GT or GC), we define an empirical method predicting cryptic-donor activation with 87% sensitivity and 95% specificity. Strength (according to four algorithms) and proximity to the annotated-donor appear important determinants of cryptic-donor activation. However, other factors such as splicing regulatory elements, which are difficult to identify, play an important role and are likely responsible for current prediction inaccuracies. We find that the most frequently recurring natural mis-splicing events at each exon-intron junction, summarised over 40,233 RNA-sequencing samples (40K-RNA), predict with accuracy which cryptic-donor will be activated in rare disease. 40K-RNA provides an accurate, evidence-based method to predict variant-activated cryptic-donors in genetic disorders, assisting pathology consideration of possible consequences of a variant for the encoded protein and RNA diagnostic testing strategies.

Genetic variants affecting the consensus splicing motifs can alter binding of spliceosomal components and induce mis-splicing. Here, the authors develop a method, showing that ranking the most common recurring mis-splicing events in public RNA-Seq data can predict the activation of cryptic-donors.

Standardized practices for RNA diagnostics using clinically accessible specimens reclassifies 75% of putative splicing variants

PURPOSE

Genetic variants causing aberrant premessenger RNA splicing are increasingly being recognized as causal variants in genetic disorders. In this study, we devise standardized practices for polymerase chain reaction (PCR)-based RNA diagnostics using clinically accessible specimens (blood, fibroblasts, urothelia, biopsy).

METHODS

A total of 74 families with diverse monogenic conditions (31% prenatal-congenital onset, 47% early childhood, and 22% teenage-adult onset) were triaged into PCR-based RNA testing, with comparative RNA sequencing for 19 cases.

RESULTS

Informative RNA assay data were obtained for 96% of cases, enabling variant reclassification for 75% variants that can be used for genetic counseling (71%), to inform clinical care (32%) and prenatal counseling (41%). Variant-associated mis-splicing was highly reproducible for 28 cases with samples from ≥2 affected individuals or heterozygotes and 10 cases with ≥2 biospecimens. PCR amplicons encompassing another segregated heterozygous variant was vital for clinical interpretation of 22 of 79 variants to phase RNA splicing events and discern complete from partial mis-splicing.

CONCLUSION

RNA diagnostics enabled provision of a genetic diagnosis for 64% of recruited cases. PCR-based RNA diagnostics has capacity to analyze 81.3% of clinically significant genes, with long amplicons providing an advantage over RNA sequencing to phase RNA splicing events. The Australasian Consortium for RNA Diagnostics (SpliceACORD) provide clinically-endorsed, standardized protocols and recommendations for interpreting RNA assay data.

Deep clinicopathological phenotyping identifies a previously unrecognized pathogenic EMD splice variant

Exome sequencing (ES) has revolutionized rare disease management, yet only ~25%-30% of patients receive a molecular diagnosis. A limiting factor is the quality of available phenotypic data. Here, we describe how deep clinicopathological phenotyping yielded a molecular diagnosis for a 19-year-old proband with muscular dystrophy and negative clinical ES. Deep phenotypic analysis identified two critical data points: (1) the absence of emerin protein in muscle biopsy and (2) clinical features consistent with Emery-Dreifuss muscular dystrophy. Sequencing data analysis uncovered an ultra-rare, intronic variant in EMD, the gene encoding emerin. The variant, NM_000117.3: c.188-6A > G, is predicted to impact splicing by in silico tools. This case thus illustrates how better integration of clinicopathologic data into ES analysis can enhance diagnostic yield with implications for clinical practice.

What's Wrong in a Jump? Prediction and Validation of Splice Site Variants

Alternative splicing (AS) is a crucial process to enhance gene expression driving organism development. Interestingly, more than 95% of human genes undergo AS, producing multiple protein isoforms from the same transcript. Any alteration (e.g., nucleotide substitutions, insertions, and deletions) involving consensus splicing regulatory sequences in a specific gene may result in the production of aberrant and not properly working proteins. In this review, we introduce the key steps of splicing mechanism and describe all different types of genomic variants affecting this process (splicing variants in acceptor/donor sites or branch point or polypyrimidine tract, exonic, and deep intronic changes). Then, we provide an updated approach to improve splice variants detection. First, we review the main computational tools, including the recent Machine Learning-based algorithms, for the prediction of splice site variants, in order to characterize how a genomic variant interferes with splicing process. Next, we report the experimental methods to validate the predictive analyses are defined, distinguishing between methods testing RNA (transcriptomics analysis) or proteins (proteomics experiments). For both prediction and validation steps, benefits and weaknesses of each tool/procedure are accurately reported, as well as suggestions on which approaches are more suitable in diagnostic rather than in clinical research.

Deletion of a pseudogene within a fragile site triggers the oncogenic expression of the mitotic CCSER1 gene

The oncogenic role of common fragile sites (CFS), focal and pervasive gaps in the cancer genome arising from replicative stress, remains controversial. Exploiting the TCGA dataset, we found that in most CFS the genes residing within the associated focal deletions are down-regulated, including proteins involved in tumour immune recognition. In a subset of CFS, however, the residing genes are surprisingly overexpressed. Within the most frequent CFS in this group, FRA4F, which is deleted in up to 18% of cancer cases and harbours the CCSER1 gene, we identified a region which includes an intronic, antisense pseudogene, TMSB4XP8. TMSB4XP8 focal ablation or transcriptional silencing elicits the overexpression of CCSER1, through a cis-acting mechanism. CCSER1 overexpression increases proliferation and triggers centrosome amplifications, multinuclearity, and aberrant mitoses. Accordingly, FRA4F is associated in patient samples to mitotic genes deregulation and genomic instability. As a result, cells overexpressing CCSER1 become sensitive to the treatment with aurora kinase inhibitors. Our findings point to a novel tumourigenic mechanism where focal deletions increase the expression of a new class of "dormant" oncogenes.

Rare Recurrent Variants in Noncoding Regions Impact Attention-Deficit Hyperactivity Disorder (ADHD) Gene Networks in Children of both African American and European American Ancestry

Attention-deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder with poorly understood molecular mechanisms that results in significant impairment in children. In this study, we sought to assess the role of rare recurrent variants in non-European populations and outside of coding regions. We generated whole genome sequence (WGS) data on 875 individuals, including 205 ADHD cases and 670 non-ADHD controls. The cases included 116 African Americans (AA) and 89 European Americans (EA), and the controls included 408 AA and 262 EA. Multiple novel rare recurrent variants were identified in exonic regions, functionally classified as stop-gains and frameshifts for known ADHD genes. Deletion in introns of the protocadherins families and the ncRNA HGB8P were identified in two independent EA ADHD patients. A meta-analysis of the two ethnicities for differential ADHD recurrent variants compared to controls shows a small number of overlaps. These results suggest that rare recurrent variants in noncoding regions may be involved in the pathogenesis of ADHD in children of both AA and EA ancestry; thus, WGS could be a powerful discovery tool for studying the molecular mechanisms of ADHD.

WGS and RNA Studies Diagnose Noncoding DMD Variants in Males With High Creatine Kinase

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.

Biallelic deletion in a minimal CAPN15 intron in siblings with a recognizable syndrome of congenital malformations and developmental delay

Calpainopathies constitute a heterogeneous group of disorders resulting from deficiencies in calpains, calcium-specific proteases that modulate substrates by limited proteolysis. Clinical manifestations depend on tissue-specific expression of the defective calpain and substrate specificity. CAPN15, encoding the Drosophila small optic lobes (sol) homolog, was recently found to cause various eye defects in individuals carrying bi-allelic missense variants. Here we report on two siblings with manifestations reminiscent of Johanson-Blizzard syndrome including failure to thrive, microcephaly, global developmental delay, dysmorphic features, endocrine abnormalities and congenital malformations, in addition to eye abnormalities. Exome sequencing identified a homozygous 47 base-pair deletion in a minimal intron of CAPN15, including the splice donor site. Sequencing of cDNA revealed single exon skipping, resulting in an out-of-frame deletion with a predicted premature termination codon. These findings expand the phenotypic spectrum associated with CAPN15 variants, and suggest that complete loss-of-function is associated with a recognizable syndrome of congenital malformations and developmental delay, overlapping Johanson-Blizzard syndrome and the recently observed brain defects in Capn15 knockout (KO) mice. Moreover, the data highlight the unique opportunity for indel detection in minimal introns.

Autosomal recessive cardiomyopathy and sudden cardiac death associated with variants in MYL3

Purpose

Variants in genes encoding sarcomeric proteins are the most common cause of inherited cardiomyopathies. However, the underlying genetic cause remains unknown in many cases. We used exome sequencing to reveal the genetic etiology in patients with recessive familial cardiomyopathy.

Methods

Exome sequencing was carried out in three consanguineous families. Functional assessment of the variants was performed.

Results

Affected individuals presented with hypertrophic or dilated cardiomyopathy of variable severity from infantile- to early adulthood–onset and sudden cardiac death. We identified a homozygous missense substitution (c.170C>A, p.[Ala57Asp]), a homozygous translation stop codon variant (c.106G>T, p.[Glu36Ter]), and a presumable homozygous essential splice acceptor variant (c.482-1G>A, predicted to result in skipping of exon 5). Morpholino knockdown of the MYL3 orthologue in zebrafish, cmlc1, resulted in compromised cardiac function, which could not be rescued by reintroduction of MYL3 carrying either the nonsense c.106G>T or the missense c.170C>A variants. Minigene assay of the c.482-1G>A variant indicated a splicing defect likely resulting in disruption of the EF-hand Ca²⁺ binding domains.

Conclusions

Our data demonstrate that homozygous MYL3 loss-of-function variants can cause of recessive cardiomyopathy and occurrence of sudden cardiac death, most likely due to impaired or loss of myosin essential light chain function.

Heterozygous CAPN3 missense variants causing autosomal-dominant calpainopathy in seven unrelated families

AIMS

Recessive variants in CAPN3 gene are the cause of the commonest form of autosomal recessive limb girdle muscle dystrophy. However, two distinct in-frame deletions in CAPN3 (NM_000070.3:c.643_663del21 and c.598_621del15) and more recently, Gly445Arg and Arg572Pro substitutions have been linked to autosomal dominant (AD) forms of calpainopathy. We report 21 affected individuals from seven unrelated families presenting with an autosomal dominant form of muscular dystrophy associated with five different heterozygous missense variants in CAPN.

METHODS

We have used massively parallel gene sequencing (MPS) to determine the genetic basis of a dominant form of limb girdle muscular dystrophy in affected individuals from seven unrelated families.

RESULTS

The c.700G> A, [p.(Gly234Arg)], c.1327T> C [p.(Ser443Pro], c.1333G> A [p.(Gly445Arg)], c.1661A> C [p.(Tyr554Ser)] and c.1706T> C [p.(Phe569Ser)] CAPN3 variants were identified. Affected individuals presented in young adulthood with progressive proximal and axial weakness, waddling walking and scapular winging or with isolated hyperCKaemia. Muscle imaging showed fatty replacement of paraspinal muscles, variable degrees of involvement of the gluteal muscles, and the posterior compartment of the thigh and minor changes at the mid-leg level. Muscle biopsies revealed mild myopathic changes. Western blot analysis revealed a clear reduction in calpain 3 in skeletal muscle relative to controls. Protein modelling of these variants on the predicted structure of calpain 3 revealed that all variants are located in proximity to the calmodulin-binding site and are predicted to interfere with proteolytic activation.

CONCLUSIONS

We expand the genotypic spectrum of CAPN3-associated muscular dystrophy due to autosomal dominant missense variants.

Pathogenic deep intronic MTM1 variant activates a pseudo-exon encoding a nonsense codon resulting in severe X-linked myotubular myopathy

X-linked myotubular myopathy (XLMTM) is a severe congenital myopathy characterised by generalised weakness and respiratory insufficiency. XLMTM is associated with pathogenic variants in MTM1; a gene encoding the lipid phosphatase myotubularin. Whole genome sequencing (WGS) of an exome-negative male proband with severe hypotonia, respiratory insufficiency and centralised nuclei on muscle biopsy identified a deep intronic MTM1 variant NG_008199.1(NM_000252.2):c.1468-577A>G, which strengthened a cryptic 5' splice site (A>G substitution at the +5 position). Muscle RNA sequencing was non-diagnostic due to low read depth. Reverse transcription PCR (RT-PCR) of muscle RNA confirmed the c.1468-577A>G variant activates inclusion of a pseudo-exon encoding a premature stop codon into all detected MTM1 transcripts. Western blot analysis establishes deficiency of myotubularin protein, consistent with the severe XLMTM phenotype. We expand the genotypic spectrum of XLMTM and highlight benefits of screening non-coding regions of MTM1 in male probands with phenotypically concordant XLMTM who remain undiagnosed following exome sequencing.

The Role of Noncoding Variants in Heritable Disease

The genetic basis of disease has largely focused on coding regions. However, it has become clear that a large proportion of the noncoding genome is functional and harbors genetic variants that contribute to disease etiology. Here, we review recent examples of inherited noncoding alterations that are responsible for Mendelian disorders or act to influence complex traits. We explore both rare and common genetic variants and discuss the wide range of mechanisms by which they affect gene regulation to promote disease. We also debate the challenges and progress associated with identifying and interpreting the functional and clinical significance of genetic variation in the context of the noncoding regulatory landscape.

Machine Learning Approaches for the Prioritization of Genomic Variants Impacting Pre-mRNA Splicing

Defects in pre-mRNA splicing are frequently a cause of Mendelian disease. Despite the advent of next-generation sequencing, allowing a deeper insight into a patient's variant landscape, the ability to characterize variants causing splicing defects has not progressed with the same speed. To address this, recent years have seen a sharp spike in the number of splice prediction tools leveraging machine learning approaches, leaving clinical geneticists with a plethora of choices for in silico analysis. In this review, some basic principles of machine learning are introduced in the context of genomics and splicing analysis. A critical comparative approach is then used to describe seven recent machine learning-based splice prediction tools, revealing highly diverse approaches and common caveats. We find that, although great progress has been made in producing specific and sensitive tools, there is still much scope for personalized approaches to prediction of variant impact on splicing. Such approaches may increase diagnostic yields and underpin improvements to patient care.