Variant effect on splicing regulatory elements, branchpoint usage, and pseudoexonization: Strategies to enhance bioinformatic prediction using hereditary cancer genes as exemplars

All exons are not created equal-exon vulnerability determines the effect of exonic mutations on splicing

It is now widely accepted that aberrant splicing of constitutive exons is often caused by mutations affecting cis-acting splicing regulatory elements (SREs), but there is a misconception that all exons have an equal dependency on SREs and thus a similar vulnerability to aberrant splicing. We demonstrate that some exons are more likely to be affected by exonic splicing mutations (ESMs) due to an inherent vulnerability, which is context dependent and influenced by the strength of exon definition. We have developed VulExMap, a tool which is based on empirical data that can designate whether a constitutive exon is vulnerable. Using VulExMap, we find that only 25% of all exons can be categorized as vulnerable, whereas two-thirds of 359 previously reported ESMs in 75 disease genes are located in vulnerable exons. Because VulExMap analysis is based on empirical data on splicing of exons in their endogenous context, it includes all features important in determining the vulnerability. We believe that VulExMap will be an important tool when assessing the effect of exonic mutations by pinpointing whether they are located in exons vulnerable to ESMs.

Comprehensive splicing analysis of the alternatively spliced CHEK2 exons 8 and 10 reveals three enhancer/silencer-rich regions and 38 spliceogenic variants

Splicing is controlled by a large set of regulatory elements (SREs) including splicing enhancers and silencers, which are involved in exon recognition. Variants at these motifs may dysregulate splicing and trigger loss-of-function transcripts associated with disease. Our goal here was to study the alternatively spliced exons 8 and 10 of the breast cancer susceptibility gene CHEK2. For this purpose, we used a previously published minigene with exons 6-10 that produced the expected minigene full-length transcript and replicated the naturally occurring events of exon 8 [Δ(E8)] and exon 10 [Δ(E10)] skipping. We then introduced 12 internal microdeletions of exons 8 and 10 by mutagenesis in order to map SRE-rich intervals by splicing assays in MCF-7 cells. We identified three minimal (10-, 11-, 15-nt) regions essential for exon recognition: c.863_877del [ex8, Δ(E8): 75%] and c.1073_1083del and c.1083_1092del [ex10, Δ(E10): 97% and 62%, respectively]. Then 87 variants found within these intervals were introduced into the wild-type minigene and tested functionally. Thirty-eight of them (44%) impaired splicing, four of which (c.883G>A, c.883G>T, c.884A>T, and c.1080G>T) induced negligible amounts (<5%) of the minigene full-length transcript. Another six variants (c.886G>A, c.886G>T, c.1075G>A, c.1075G>T, c.1076A>T, and c.1078G>T) showed significantly strong impacts (20-50% of the minigene full-length transcript). Thirty-three of the 38 spliceogenic variants were annotated as missense, three as nonsense, and two as synonymous, underlying the fact that any exonic change is capable of disrupting splicing. Moreover, c.883G>A, c.883G>T, and c.884A>T were classified as pathogenic/likely pathogenic variants according to ACMG/AMP (American College of Medical Genetics and Genomics/Association for Molecular Pathology)-based criteria. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

The clinical utility and costs of whole-genome sequencing to detect cancer susceptibility variants-a multi-site prospective cohort study

BACKGROUND

Many families and individuals do not meet criteria for a known hereditary cancer syndrome but display unusual clusters of cancers. These families may carry pathogenic variants in cancer predisposition genes and be at higher risk for developing cancer.

METHODS

This multi-centre prospective study recruited 195 cancer-affected participants suspected to have a hereditary cancer syndrome for whom previous clinical targeted genetic testing was either not informative or not available. To identify pathogenic disease-causing variants explaining participant presentation, germline whole-genome sequencing (WGS) and a comprehensive cancer virtual gene panel analysis were undertaken.

RESULTS

Pathogenic variants consistent with the presenting cancer(s) were identified in 5.1% (10/195) of participants and pathogenic variants considered secondary findings with potential risk management implications were identified in another 9.7% (19/195) of participants. Health economic analysis estimated the marginal cost per case with an actionable variant was significantly lower for upfront WGS with virtual panel ($8744AUD) compared to standard testing followed by WGS ($24,894AUD). Financial analysis suggests that national adoption of diagnostic WGS testing would require a ninefold increase in government annual expenditure compared to conventional testing.

CONCLUSIONS

These findings make a case for replacing conventional testing with WGS to deliver clinically important benefits for cancer patients and families. The uptake of such an approach will depend on the perspectives of different payers on affordability.

Branchpoints as potential targets of exon-skipping therapies for genetic disorders

Fukutin (FKTN) c.647+2084G>T creates a pseudo-exon with a premature stop codon, which causes Fukuyama congenital muscular dystrophy (FCMD). We aimed to ameliorate aberrant splicing of FKTN caused by this variant. We screened compounds focusing on splicing regulation using the c.647+2084G>T splicing reporter and discovered that the branchpoint, which is essential for splicing reactions, could be a potential therapeutic target. To confirm the effectiveness of branchpoints as targets for exon skipping, we designed branchpoint-targeted antisense oligonucleotides (BP-AONs). This restored normal FKTN mRNA and protein production in FCMD patient myotubes. We identified a functional BP by detecting splicing intermediates and creating BP mutations in the FKTN reporter gene; this BP was non-redundant and sufficiently blocked by BP-AONs. Next, a BP-AON was designed for a different FCMD-causing variant, which induces pathogenic exon trapping by a common SINE-VNTR-Alu-type retrotransposon. Notably, this BP-AON also restored normal FKTN mRNA and protein production in FCMD patient myotubes. Our findings suggest that BPs could be potential targets in exon-skipping therapeutic strategies for genetic disorders.

Using the ACMG/AMP framework to capture evidence related to predicted and observed impact on splicing: Recommendations from the ClinGen SVI Splicing Subgroup

The American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) framework for classifying variants uses six evidence categories related to the splicing potential of variants: PVS1, PS3, PP3, BS3, BP4, and BP7. However, the lack of guidance on how to apply such codes has contributed to variation in the specifications developed by different Clinical Genome Resource (ClinGen) Variant Curation Expert Panels. The ClinGen Sequence Variant Interpretation Splicing Subgroup was established to refine recommendations for applying ACMG/AMP codes relating to splicing data and computational predictions. We utilized empirically derived splicing evidence to (1) determine the evidence weighting of splicing-related data and appropriate criteria code selection for general use, (2) outline a process for integrating splicing-related considerations when developing a gene-specific PVS1 decision tree, and (3) exemplify methodology to calibrate splice prediction tools. We propose repurposing the PVS1_Strength code to capture splicing assay data that provide experimental evidence for variants resulting in RNA transcript(s) with loss of function. Conversely, BP7 may be used to capture RNA results demonstrating no splicing impact for intronic and synonymous variants. We propose that the PS3/BS3 codes are applied only for well-established assays that measure functional impact not directly captured by RNA-splicing assays. We recommend the application of PS1 based on similarity of predicted RNA-splicing effects for a variant under assessment in comparison with a known pathogenic variant. The recommendations and approaches for consideration and evaluation of RNA-assay evidence described aim to help standardize variant pathogenicity classification processes when interpreting splicing-based evidence.

Current and emerging targeted therapies for spinal muscular atrophy

INTRODUCTION

Spinal muscular atrophy (SMA) is a progressive neurodegenerative disorder caused by insufficiency or total absence of the survival motor neuron protein due to a mutation in the SMN1 gene. The copy number of its paralog, SMN2, influences disease onset and phenotype severity. Current therapeutic approaches include viral and non-viral modalities affecting gene expression. Regulatory-approved drugs Spinraza (Nusinersen), Zolgensma (Onasemnogene abeparvovec), and Evrysdi (Risdiplam) are still being investigated during clinical trials and show benefits in the long-term for symptomatic and pre-symptomatic patients. However, some ongoing interventions require repeated drug administration.

AREAS COVERED

In this review, the authors describe the existing therapy based on point of application, focusing on recent clinical trials of antisense oligonucleotides, viral gene therapy, and splice modulators and thepotential routes for correcting the mutation to provide therapeutic levels of SMN protein.

EXPERT OPINION

In the opinion of the authors, multiple treatment options for patients with SMA shifted the treatment paradigm from palliative supportive care to improvedmotor function, increased survival, and greater quality of life for such patients. They further believe that the future in SMA treatment development lies incombining existing treatment options, targeting aspects of the disease refractory to these treatments, and using gene editing technologies.

APPLICATION OF THE ACMG/AMP FRAMEWORK TO CAPTURE EVIDENCE RELEVANT TO PREDICTED AND OBSERVED IMPACT ON SPLICING: RECOMMENDATIONS FROM THE CLINGEN SVI SPLICING SUBGROUP

The American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) framework for classifying variants uses six evidence categories related to the splicing potential of variants: PVS1 (null variant in a gene where loss-of-function is the mechanism of disease), PS3 (functional assays show damaging effect on splicing), PP3 (computational evidence supports a splicing effect), BS3 (functional assays show no damaging effect on splicing), BP4 (computational evidence suggests no splicing impact), and BP7 (silent change with no predicted impact on splicing). However, the lack of guidance on how to apply such codes has contributed to variation in the specifications developed by different Clinical Genome Resource (ClinGen) Variant Curation Expert Panels. The ClinGen Sequence Variant Interpretation (SVI) Splicing Subgroup was established to refine recommendations for applying ACMG/AMP codes relating to splicing data and computational predictions. Our study utilised empirically derived splicing evidence to: 1) determine the evidence weighting of splicing-related data and appropriate criteria code selection for general use, 2) outline a process for integrating splicing-related considerations when developing a gene-specific PVS1 decision tree, and 3) exemplify methodology to calibrate bioinformatic splice prediction tools. We propose repurposing of the PVS1_Strength code to capture splicing assay data that provide experimental evidence for variants resulting in RNA transcript(s) with loss of function. Conversely BP7 may be used to capture RNA results demonstrating no impact on splicing for both intronic and synonymous variants, and for missense variants if protein functional impact has been excluded. Furthermore, we propose that the PS3 and BS3 codes are applied only for well-established assays that measure functional impact that is not directly captured by RNA splicing assays. We recommend the application of PS1 based on similarity of predicted RNA splicing effects for a variant under assessment in comparison to a known Pathogenic variant. The recommendations and approaches for consideration and evaluation of RNA assay evidence described aim to help standardise variant pathogenicity classification processes and result in greater consistency when interpreting splicing-based evidence.

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.

Clinical, splicing, and functional analysis to classify BRCA2 exon 3 variants: Application of a points-based ACMG/AMP approach

Skipping of BRCA2 exon 3 (∆E3) is a naturally occurring splicing event, complicating clinical classification of variants that may alter ∆E3 expression. This study used multiple evidence types to assess pathogenicity of 85 variants in/near BRCA2 exon 3. Bioinformatically predicted spliceogenic variants underwent mRNA splicing analysis using minigenes and/or patient samples. ∆E3 was measured using quantitative analysis. A mouse embryonic stem cell (mESC) based assay was used to determine the impact of 18 variants on mRNA splicing and protein function. For each variant, population frequency, bioinformatic predictions, clinical data, and existing mRNA splicing and functional results were collated. Variant class was assigned using a gene-specific adaptation of ACMG/AMP guidelines, following a recently proposed points-based system. mRNA and mESC analysis combined identified six variants with transcript and/or functional profiles interpreted as loss of function. Cryptic splice site use for acceptor site variants generated a transcript encoding a shorter protein that retains activity. Overall, 69/85 (81%) variants were classified using the points-based approach. Our analysis shows the value of applying gene-specific ACMG/AMP guidelines using a points-based approach and highlights the consideration of cryptic splice site usage to appropriately assign PVS1 code strength.

Computational approaches for predicting variant impact: An overview from resources, principles to applications

One objective of human genetics is to unveil the variants that contribute to human diseases. With the rapid development and wide use of next-generation sequencing (NGS), massive genomic sequence data have been created, making personal genetic information available. Conventional experimental evidence is critical in establishing the relationship between sequence variants and phenotype but with low efficiency. Due to the lack of comprehensive databases and resources which present clinical and experimental evidence on genotype-phenotype relationship, as well as accumulating variants found from NGS, different computational tools that can predict the impact of the variants on phenotype have been greatly developed to bridge the gap. In this review, we present a brief introduction and discussion about the computational approaches for variant impact prediction. Following an innovative manner, we mainly focus on approaches for non-synonymous variants (nsSNVs) impact prediction and categorize them into six classes. Their underlying rationale and constraints, together with the concerns and remedies raised from comparative studies are discussed. We also present how the predictive approaches employed in different research. Although diverse constraints exist, the computational predictive approaches are indispensable in exploring genotype-phenotype relationship.

Modeling splicing outcome by combining 5'ss strength and splicing regulatory elements

Correct pre-mRNA processing in higher eukaryotes vastly depends on splice site recognition. Beyond conserved 5'ss and 3'ss motifs, splicing regulatory elements (SREs) play a pivotal role in this recognition process. Here, we present in silico designed sequences with arbitrary a priori prescribed splicing regulatory HEXplorer properties that can be concatenated to arbitrary length without changing their regulatory properties. We experimentally validated in silico predictions in a massively parallel splicing reporter assay on more than 3000 sequences and exemplarily identified some SRE binding proteins. Aiming at a unified 'functional splice site strength' encompassing both U1 snRNA complementarity and impact from neighboring SREs, we developed a novel RNA-seq based 5'ss usage landscape, mapping the competition of pairs of high confidence 5'ss and neighboring exonic GT sites along HBond and HEXplorer score coordinate axes on human fibroblast and endothelium transcriptome datasets. These RNA-seq data served as basis for a logistic 5'ss usage prediction model, which greatly improved discrimination between strong but unused exonic GT sites and annotated highly used 5'ss. Our 5'ss usage landscape offers a unified view on 5'ss and SRE neighborhood impact on splice site recognition, and may contribute to improved mutation assessment in human genetics.

Estimating the proportion of pathogenic variants from breast cancer case-control data: Application to calibration of ACMG/AMP variant classification criteria

For genes with reliable estimates of disease risk associated with loss-of-function variants, case-control data can be used to estimate the proportion of variants of typical risk effect for defined groups of variants, of relevance for variant classification. A calculation was derived for a maximum likelihood estimate of the proportion of pathogenic variants of typical effect from case-control data and applied to rare variant counts for ATM, BARD1, BRCA1, BRCA2, CHEK2, PALB2, RAD51C, and RAD51D from published breast cancer studies: BEACCON (5770 familial cases and 5741 controls) and breast cancer risk after diagnostic sequencing (60,466 familial and population-based cases and 53,461 controls). There was significant evidence of pathogenic variants among rare noncoding variants, in particular deeper intronic variants, for BRCA1 (13%, p = 8.3 × 10^-7 ), BRCA2 (6%, p = 0.016) and PALB2 (13%, p = 0.001). The estimated proportion of pathogenic missense variants varied markedly between genes, generally with enrichment in familial cases, for example, 9% for BRCA2 versus 60%-90% for CHEK2. Stratifying missense variants by position indicated that, for most genes, location within a functional domain significantly predicted pathogenicity, whereas location outside domains provided robust evidence against pathogenicity. Our approach provides novel insights into the spectrum of pathogenic variants of specific breast cancer genes and has wider application to inform gene-focused specifications of American College of Medical Genetics and Genomics (ACMG)/Association of Molecular Pathology (AMP) codes for variant curation.

ABCA4 c.859-25A>G, a Frequent Palestinian Founder Mutation Affecting the Intron 7 Branchpoint, Is Associated With Early-Onset Stargardt Disease

Purpose

The effect of noncoding variants is often unknown in the absence of functional assays. Here, we characterized an ABCA4 intron 7 variant, c.859-25A>G, identified in Palestinian probands with Stargardt disease (STGD) or cone-rod dystrophy (CRD). We investigated the effect of this variant on the ABCA4 mRNA and retinal phenotype, and its prevalence in Palestine.

Methods

The ABCA4 gene was sequenced completely or partially in 1998 cases with STGD or CRD. The effect of c.859-25A>G on splicing was investigated in silico using SpliceAI and in vitro using splice assays. Homozygosity mapping was performed for 16 affected individuals homozygous for c.859-25A>G. The clinical phenotype was assessed using functional and structural analyses including visual acuity, full-field electroretinography, and multimodal imaging.

Results

The smMIPs-based ABCA4 sequencing revealed c.859-25A>G in 10 Palestinian probands from Hebron and Jerusalem. SpliceAI predicted a significant effect of this putative branchpoint-inactivating variant on the nearby intron 7 splice acceptor site. Splice assays revealed exon 8 skipping and two partial inclusions of intron 7, each having a deleterious effect. Additional genotyping revealed another 46 affected homozygous or compound heterozygous individuals carrying variant c.859-25A>G. Homozygotes shared a genomic segment of 59.6 to 87.9 kb and showed severe retinal defects on ophthalmoscopic evaluation.

Conclusions

The ABCA4 variant c.859-25A>G disrupts a predicted branchpoint, resulting in protein truncation because of different splice defects, and is associated with early-onset STGD1 when present in homozygosity. This variant was found in 25/525 Palestinian inherited retinal dystrophy probands, representing one of the most frequent inherited retinal disease-causing variants in West-Bank Palestine.

The splicing effect of variants at branchpoint elements in cancer genes

PURPOSE

Branchpoint elements are required for intron removal, and variants at these elements can result in aberrant splicing. We aimed to assess the value of branchpoint annotations generated from recent large-scale studies to select branchpoint-abrogating variants, using hereditary cancer genes as model.

METHODS

We identified branchpoint elements in 119 genes associated with hereditary cancer from 3 genome-wide experimentally-inferred and 2 predicted branchpoint data sets. We then identified variants that occur within branchpoint elements from public databases. We compared conservation, unique variant observations, and population frequencies at different nucleotides within branchpoint motifs. Finally, selected minigene assays were performed to assess the splicing effect of variants at branchpoint elements within mismatch repair genes.

RESULTS

There was poor overlap between predicted and experimentally-inferred branchpoints. Our analysis of cancer genes suggested that variants at -2 nucleotide, -1 nucleotide, and branchpoint positions in experimentally-inferred canonical motifs are more likely to be clinically relevant. Minigene assay data showed the -2 nucleotide to be more important to branchpoint motif integrity but also showed fluidity in branchpoint usage.

CONCLUSION

Data from cancer gene analysis suggest that there are few high-risk alleles that severely impact function via branchpoint abrogation. Results of this study inform a general scheme to prioritize branchpoint motif variants for further study.

Analysis of Pathogenic Pseudoexons Reveals Novel Mechanisms Driving Cryptic Splicing

Understanding pre-mRNA splicing is crucial to accurately diagnosing and treating genetic diseases. However, mutations that alter splicing can exert highly diverse effects. Of all the known types of splicing mutations, perhaps the rarest and most difficult to predict are those that activate pseudoexons, sometimes also called cryptic exons. Unlike other splicing mutations that either destroy or redirect existing splice events, pseudoexon mutations appear to create entirely new exons within introns. Since exon definition in vertebrates requires coordinated arrangements of numerous RNA motifs, one might expect that pseudoexons would only arise when rearrangements of intronic DNA create novel exons by chance. Surprisingly, although such mutations do occur, a far more common cause of pseudoexons is deep-intronic single nucleotide variants, raising the question of why these latent exon-like tracts near the mutation sites have not already been purged from the genome by the evolutionary advantage of more efficient splicing. Possible answers may lie in deep intronic splicing processes such as recursive splicing or poison exon splicing. Because these processes utilize intronic motifs that benignly engage with the spliceosome, the regions involved may be more susceptible to exonization than other intronic regions would be. We speculated that a comprehensive study of reported pseudoexons might detect alignments with known deep intronic splice sites and could also permit the characterisation of novel pseudoexon categories. In this report, we present and analyse a catalogue of over 400 published pseudoexon splice events. In addition to confirming prior observations of the most common pseudoexon mutation types, the size of this catalogue also enabled us to suggest new categories for some of the rarer types of pseudoexon mutation. By comparing our catalogue against published datasets of non-canonical splice events, we also found that 15.7% of pseudoexons exhibit some splicing activity at one or both of their splice sites in non-mutant cells. Importantly, this included seven examples of experimentally confirmed recursive splice sites, confirming for the first time a long-suspected link between these two splicing phenomena. These findings have the potential to improve the fidelity of genetic diagnostics and reveal new targets for splice-modulating therapies.

Pseudoexon activation in disease by non-splice site deep intronic sequence variation - wild type pseudoexons constitute high-risk sites in the human genome

Accuracy of pre-messenger RNA (pre-mRNA) splicing is crucial for normal gene expression. Complex regulation supports the spliceosomal distinction between authentic exons and the many seemingly functional splice sites delimiting pseudoexons. Pseudoexons are nonfunctional intronic sequences that can be activated for aberrant inclusion in mRNA, which may cause disease. Pseudoexon activation is very challenging to predict, in particular when activation occurs by sequence variants that alter the splicing regulatory environment without directly affecting splice sites. As pseudoexon inclusion often evades detection due to activation of nonsense-mediated mRNA decay, and because conventional diagnostic procedures miss deep intronic sequence variation, pseudoexon activation is a heavily underreported disease mechanism. Pseudoexon characteristics have mainly been studied based on in silico predicted sequences. Moreover, because recognition of sequence variants that create or strengthen splice sites is possible by comparison with well-established consensus sequences, this type of pseudoexon activation is by far the most frequently reported. Here we review all known human disease-associated pseudoexons that carry functional splice sites and are activated by deep intronic sequence variants located outside splice site sequences. We delineate common characteristics that make this type of wild type pseudoexons distinct high-risk sites in the human genome.

A spotter's guide to SNPtic exons: The common splice variants underlying some SNP-phenotype correlations

BACKGROUND

Cryptic exons are typically characterised as deleterious splicing aberrations caused by deep intronic mutations. However, low-level splicing of cryptic exons is sometimes observed in the absence of any pathogenic mutation. Five recent reports have described how low-level splicing of cryptic exons can be modulated by common single-nucleotide polymorphisms (SNPs), resulting in phenotypic differences amongst different genotypes.

METHODS

We sought to investigate whether additional 'SNPtic' exons may exist, and whether these could provide an explanatory mechanism for some of the genotype-phenotype correlations revealed by genome-wide association studies. We thoroughly searched the literature for reported cryptic exons, cross-referenced their genomic coordinates against the dbSNP database of common SNPs, then screened out SNPs with no reported phenotype associations.

RESULTS

This method discovered five probable SNPtic exons in the genes APC, FGB, GHRL, MYPBC3 and OTC. For four of these five exons, we observed that the phenotype associated with the SNP was compatible with the predicted splicing effect of the nucleotide change, whilst the fifth (in GHRL) likely had a more complex splice-switching effect.

CONCLUSION

Application of our search methods could augment the knowledge value of future cryptic exon reports and aid in generating better hypotheses for genome-wide association studies.

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.

Role of Splicing Regulatory Elements and In Silico Tools Usage in the Identification of Deep Intronic Splicing Variants in Hereditary Breast/Ovarian Cancer Genes

Simple Summary

There is a significant percentage of hereditary breast and ovarian cancer (HBOC) cases that remain undiagnosed, because no pathogenic variant is detected through massively parallel sequencing of coding exons and exon-intron boundaries of high-moderate susceptibility risk genes. Deep intronic regions may contain variants affecting RNA splicing, leading ultimately to disease, and hence they may explain several cases where the genetic cause of HBOC is unknown. This study aims to characterize intronic regions to identify a landscape of “exonizable” zones and test the efficiency of two in silico tools to detect deep intronic variants affecting the mRNA splicing process.

Abstract

The contribution of deep intronic splice-altering variants to hereditary breast and ovarian cancer (HBOC) is unknown. Current computational in silico tools to predict spliceogenic variants leading to pseudoexons have limited efficiency. We assessed the performance of the SpliceAI tool combined with ESRseq scores to identify spliceogenic deep intronic variants by affecting cryptic sites or splicing regulatory elements (SREs) using literature and experimental datasets. Our results with 233 published deep intronic variants showed that SpliceAI, with a 0.05 threshold, predicts spliceogenic deep intronic variants affecting cryptic splice sites, but is less effective in detecting those affecting SREs. Next, we characterized the SRE profiles using ESRseq, showing that pseudoexons are significantly enriched in SRE-enhancers compared to adjacent intronic regions. Although the combination of SpliceAI with ESRseq scores (considering ∆ESRseq and SRE landscape) showed higher sensitivity, the global performance did not improve because of the higher number of false positives. The combination of both tools was tested in a tumor RNA dataset with 207 intronic variants disrupting splicing, showing a sensitivity of 86%. Following the pipeline, five spliceogenic deep intronic variants were experimentally identified from 33 variants in HBOC genes. Overall, our results provide a framework to detect deep intronic variants disrupting splicing.

RAD51D Aberrant Splicing in Breast Cancer: Identification of Splicing Regulatory Elements and Minigene-Based Evaluation of 53 DNA Variants

RAD51D loss-of-function variants increase lifetime risk of breast and ovarian cancer. Splicing disruption is a frequent pathogenic mechanism associated with variants in susceptibility genes. Herein, we have assessed the splicing and clinical impact of splice-site and exonic splicing enhancer (ESE) variants identified through the study of ~113,000 women of the BRIDGES cohort. A RAD51D minigene with exons 2-9 was constructed in splicing vector pSAD. Eleven BRIDGES splice-site variants (selected by MaxEntScan) were introduced into the minigene by site-directed mutagenesis and tested in MCF-7 cells. The 11 variants disrupted splicing, collectively generating 25 different aberrant transcripts. All variants but one produced negligible levels (<3.4%) of the full-length (FL) transcript. In addition, ESE elements of the alternative exon 3 were mapped by testing four overlapping exonic microdeletions (≥30-bp), revealing an ESE-rich interval (c.202_235del) with critical sequences for exon 3 recognition that might have been affected by germline variants. Next, 26 BRIDGES variants and 16 artificial exon 3 single-nucleotide substitutions were also assayed. Thirty variants impaired splicing with variable amounts (0-65.1%) of the FL transcript, although only c.202G>A demonstrated a complete aberrant splicing pattern without the FL transcript. On the other hand, c.214T>C increased efficiency of exon 3 recognition, so only the FL transcript was detected (100%). In conclusion, 41 RAD51D spliceogenic variants (28 of which were from the BRIDGES cohort) were identified by minigene assays. We show that minigene-based mapping of ESEs is a powerful approach for identifying ESE hotspots and ESE-disrupting variants. Finally, we have classified nine variants as likely pathogenic according to ACMG/AMP-based guidelines, highlighting the complex relationship between splicing alterations and variant interpretation.

Comprehensive Functional Characterization and Clinical Interpretation of 20 Splice-Site Variants of the RAD51C Gene

Hereditary breast and/or ovarian cancer is a highly heterogeneous disease with more than 10 known disease-associated genes. In the framework of the BRIDGES project (Breast Cancer Risk after Diagnostic Gene Sequencing), the RAD51C gene has been sequenced in 60,466 breast cancer patients and 53,461 controls. We aimed at functionally characterizing all the identified genetic variants that are predicted to disrupt the splicing process. Forty RAD51C variants of the intron-exon boundaries were bioinformatically analyzed, 20 of which were selected for splicing functional assays. To test them, a splicing reporter minigene with exons 2 to 8 was designed and constructed. This minigene generated a full-length transcript of the expected size (1062 nucleotides), sequence, and structure (Vector exon V1- RAD51C exons_2-8- Vector exon V2). The 20 candidate variants were genetically engineered into the wild type minigene and functionally assayed in MCF-7 cells. Nineteen variants (95%) impaired splicing, while 18 of them produced severe splicing anomalies. At least 35 transcripts were generated by the mutant minigenes: 16 protein-truncating, 6 in-frame, and 13 minor uncharacterized isoforms. According to ACMG/AMP-based standards, 15 variants could be classified as pathogenic or likely pathogenic variants: c.404G > A, c.405-6T > A, c.571 + 4A > G, c.571 + 5G > A, c.572-1G > T, c.705G > T, c.706-2A > C, c.706-2A > G, c.837 + 2T > C, c.905-3C > G, c.905-2A > C, c.905-2_905-1del, c.965 + 5G > A, c.1026 + 5_1026 + 7del, and c.1026 + 5G > T.

Missing heritability in Bloom syndrome: First report of a deep intronic variant leading to pseudo-exon activation in the BLM gene

Pathogenic biallelic variants in the BLM/RECQL3 gene cause a rare autosomal recessive disorder called Bloom syndrome (BS). This syndrome is characterized by severe growth delay, immunodeficiency, dermatological manifestations and a predisposition to a wide variety of cancers, often multiple and very early in life. Literature shows that the main mode of BLM inactivation is protein translation termination. We expanded the molecular spectrum of BS by reporting the first deep intronic variant causing intron exonisation. We describe a patient with a clinical phenotype of BS and a strong increase in sister chromatid exchanges (SCE), who was found to be compound heterozygous for a novel nonsense variant c.3379C>T, p.(Gln1127Ter) in exon 18 and a deep intronic variant c.3020-258A>G in intron 15 of the BLM gene. The deep intronic variant creates a high-quality de novo donor splice site, which leads to retention of two intron segments. Both pseudo-exons introduce a premature stop codon into the reading frame and abolish BLM protein expression, confirmed by Western Blot analysis. These findings illustrate the role of non-coding variation in Mendelian disorders and herewith highlight an unmet need in routine testing of Mendelian disorders, being the added value of RNA-based approaches to provide a complete molecular diagnosis.