Genomic HEXploring allows landscaping of novel potential splicing regulatory elements

Splicing analysis of STAT3 tandem donor suggests non-canonical binding registers for U1 and U6 snRNAs

Tandem donor splice sites (5'ss) are unique regions with at least two GU dinucleotides serving as splicing cleavage sites. The Δ3 tandem 5'ss are a specific subclass of 5'ss separated by 3 nucleotides which can affect protein function by inserting/deleting a single amino acid. One 5'ss is typically preferred, yet factors governing particular 5'ss choice are not fully understood. A highly conserved exon 21 of the STAT3 gene was chosen as a model to study Δ3 tandem 5'ss splicing mechanisms. Based on multiple lines of experimental evidence, endogenous U1 snRNA most likely binds only to the upstream 5'ss. However, the downstream 5'ss is used preferentially, and the splice site choice is not dependent on the exact U1 snRNA binding position. Downstream 5'ss usage was sensitive to exact nucleotide composition and dependent on the presence of downstream regulatory region. The downstream 5'ss usage could be best explained by two novel interactions with endogenous U6 snRNA. U6 snRNA enables the downstream 5'ss usage in STAT3 exon 21 by two mechanisms: (i) binding in a novel non-canonical register and (ii) establishing extended Watson-Crick base pairing with the downstream regulatory region. This study suggests that U6:5'ss interaction is more flexible than previously thought.

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.

Pleiotropic effects of different exonic nucleotide changes at the same position contribute to hemophilia B phenotypic variation

BACKGROUND

The disease-causing effects of genetic variations often depend on their location within a gene. Exonic changes generally lead to alterations in protein production, secretion, activity, or clearance. However, owing to the overlap between proteins and splicing codes, missense variants can also affect messenger RNA splicing, thus adding a layer of complexity and influencing disease phenotypes.

OBJECTIVES

To extensively characterize a panel of 13 exonic variants in the F9 gene occurring at 6 different factor IX positions and associated with varying severities of hemophilia B (HB).

METHODS

Computational predictions, splicing analysis, and recombinant factor IX assays were exploited to characterize F9 variants.

RESULTS

We demonstrated that 5 (38%) of 13 selected F9 exonic variants have pleiotropic effects. Although bioinformatic approaches accurately classified effects, extensive experimental assays were required to elucidate and deepen the molecular mechanisms underlying the pleiotropic effects. Importantly, their characterization was instrumental in developing tailored RNA therapeutics based on engineered U7 small nuclear RNA to mask cryptic splice sites and compensatory U1 small nuclear RNA to enhance exon definition.

CONCLUSION

Overall, albeit a multitool bioinformatic approach suggested the molecular effects of multiple HB variants, the deep investigation of molecular mechanisms revealed insights into the HB phenotype-genotype relationship, enabling accurate classification of HB variants. Importantly, knowledge of molecular mechanisms allowed the development of tailored RNA therapeutics, which can also be translated to other genetic diseases.

Regulating PCCA gene expression by modulation of pseudoexon splicing patterns to rescue enzyme activity in propionic acidemia

Pseudoexons are nonfunctional intronic sequences that can be activated by deep-intronic sequence variation. Activation increases pseudoexon inclusion in mRNA and interferes with normal gene expression. The PCCA c.1285-1416A>G variation activates a pseudoexon and causes the severe metabolic disorder propionic acidemia by deficiency of the propionyl-CoA carboxylase enzyme encoded by PCCA and PCCB. We characterized this pathogenic pseudoexon activation event in detail and identified hnRNP A1 to be important for normal repression. The PCCA c.1285-1416A>G variation disrupts an hnRNP A1-binding splicing silencer and simultaneously creates a splicing enhancer. We demonstrate that blocking this region of regulation with splice-switching antisense oligonucleotides restores normal splicing and rescues enzyme activity in patient fibroblasts and in a cellular model created by CRISPR gene editing. Interestingly, the PCCA pseudoexon offers an unexploited potential to upregulate gene expression because healthy tissues show relatively high inclusion levels. By blocking inclusion of the nonactivated wild-type pseudoexon, we can increase both PCCA and PCCB protein levels, which increases the activity of the heterododecameric enzyme. Surprisingly, we can increase enzyme activity from residual levels in not only patient fibroblasts harboring PCCA missense variants but also those harboring PCCB missense variants. This is a potential treatment strategy for propionic acidemia.

Exploring noncoding variants in genetic diseases: from detection to functional insights

Previous studies on genetic diseases predominantly focused on protein-coding variations, overlooking the vast noncoding regions in the human genome. The development of high-throughput sequencing technologies and functional genomics tools has enabled the systematic identification of functional noncoding variants. These variants can impact gene expression, regulation, and chromatin conformation, thereby contributing to disease pathogenesis. Understanding the mechanisms that underlie the impact of noncoding variants on genetic diseases is indispensable for the development of precisely targeted therapies and the implementation of personalized medicine strategies. The intricacies of noncoding regions introduce a multitude of challenges and research opportunities. In this review, we introduce a spectrum of noncoding variants involved in genetic diseases, along with research strategies and advanced technologies for their precise identification and in-depth understanding of the complexity of the noncoding genome. We will delve into the research challenges and propose potential solutions for unraveling the genetic basis of rare and complex diseases.

Srsf1 and Elavl1 act antagonistically on neuronal fate choice in the developing neocortex by controlling TrkC receptor isoform expression

The seat of higher-order cognitive abilities in mammals, the neocortex, is a complex structure, organized in several layers. The different subtypes of principal neurons are distributed in precise ratios and at specific positions in these layers and are generated by the same neural progenitor cells (NPCs), steered by a spatially and temporally specified combination of molecular cues that are incompletely understood. Recently, we discovered that an alternatively spliced isoform of the TrkC receptor lacking the kinase domain, TrkC-T1, is a determinant of the corticofugal projection neuron (CFuPN) fate. Here, we show that the finely tuned balance between TrkC-T1 and the better known, kinase domain-containing isoform, TrkC-TK+, is cell type-specific in the developing cortex and established through the antagonistic actions of two RNA-binding proteins, Srsf1 and Elavl1. Moreover, our data show that Srsf1 promotes the CFuPN fate and Elavl1 promotes the callosal projection neuron (CPN) fate in vivo via regulating the distinct ratios of TrkC-T1 to TrkC-TK+. Taken together, we connect spatio-temporal expression of Srsf1 and Elavl1 in the developing neocortex with the regulation of TrkC alternative splicing and transcript stability and neuronal fate choice, thus adding to the mechanistic and functional understanding of alternative splicing in vivo.

In silico methods for predicting functional synonymous variants

Single nucleotide variants (SNVs) contribute to human genomic diversity. Synonymous SNVs are previously considered to be "silent," but mounting evidence has revealed that these variants can cause RNA and protein changes and are implicated in over 85 human diseases and cancers. Recent improvements in computational platforms have led to the development of numerous machine-learning tools, which can be used to advance synonymous SNV research. In this review, we discuss tools that should be used to investigate synonymous variants. We provide supportive examples from seminal studies that demonstrate how these tools have driven new discoveries of functional synonymous SNVs.

Splicing annotation of endometrial cancer GWAS risk loci reveals potentially causal variants and supports a role for NF1 and SKAP1 as susceptibility genes

Alternative splicing contributes to cancer development. Indeed, splicing analysis of cancer genome-wide association study (GWAS) risk variants has revealed likely causal variants. To systematically assess GWAS variants for splicing effects, we developed a prioritization workflow using a combination of splicing prediction tools, alternative transcript isoforms, and splicing quantitative trait locus (sQTL) annotations. Application of this workflow to candidate causal variants from 16 endometrial cancer GWAS risk loci highlighted single-nucleotide polymorphisms (SNPs) that were predicted to upregulate alternative transcripts. For two variants, sQTL data supported the predicted impact on splicing. At the 17q11.2 locus, the protective allele for rs7502834 was associated with increased splicing of an exon in a NF1 alternative transcript encoding a truncated protein in adipose tissue and is consistent with an endometrial cancer transcriptome-wide association study (TWAS) finding in adipose tissue. Notably, NF1 haploinsufficiency is protective for obesity, a well-established risk factor for endometrial cancer. At the 17q21.32 locus, the rs2278868 risk allele was predicted to upregulate a SKAP1 transcript that is subject to nonsense-mediated decay, concordant with a corresponding sQTL in lymphocytes. This is consistent with a TWAS finding that indicates decreased SKAP1 expression in blood increases endometrial cancer risk. As SKAP1 is involved in T cell immune responses, decreased SKAP1 expression may impact endometrial tumor immunosurveillance. In summary, our analysis has identified potentially causal endometrial cancer GWAS risk variants with plausible biological mechanisms and provides a splicing annotation workflow to aid interpretation of other GWAS datasets.

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.

SPiP: Splicing Prediction Pipeline, a machine learning tool for massive detection of exonic and intronic variant effects on mRNA splicing

Modeling splicing is essential for tackling the challenge of variant interpretation as each nucleotide variation can be pathogenic by affecting pre-mRNA splicing via disruption/creation of splicing motifs such as 5'/3' splice sites, branch sites, or splicing regulatory elements. Unfortunately, most in silico tools focus on a specific type of splicing motif, which is why we developed the Splicing Prediction Pipeline (SPiP) to perform, in one single bioinformatic analysis based on a machine learning approach, a comprehensive assessment of the variant effect on different splicing motifs. We gathered a curated set of 4616 variants scattered all along the sequence of 227 genes, with their corresponding splicing studies. The Bayesian analysis provided us with the number of control variants, that is, variants without impact on splicing, to mimic the deluge of variants from high-throughput sequencing data. Results show that SPiP can deal with the diversity of splicing alterations, with 83.13% sensitivity and 99% specificity to detect spliceogenic variants. Overall performance as measured by area under the receiving operator curve was 0.986, better than SpliceAI and SQUIRLS (0.965 and 0.766) for the same data set. SPiP lends itself to a unique suite for comprehensive prediction of spliceogenicity in the genomic medicine era. SPiP is available at: https://sourceforge.net/projects/splicing-prediction-pipeline/.

Combining genetic constraint with predictions of alternative splicing to prioritize deleterious splicing in rare disease studies

Background

Despite numerous molecular and computational advances, roughly half of patients with a rare disease remain undiagnosed after exome or genome sequencing. A particularly challenging barrier to diagnosis is identifying variants that cause deleterious alternative splicing at intronic or exonic loci outside of canonical donor or acceptor splice sites.

Results

Several existing tools predict the likelihood that a genetic variant causes alternative splicing. We sought to extend such methods by developing a new metric that aids in discerning whether a genetic variant leads to deleterious alternative splicing. Our metric combines genetic variation in the Genome Aggregate Database with alternative splicing predictions from SpliceAI to compare observed and expected levels of splice-altering genetic variation. We infer genic regions with significantly less splice-altering variation than expected to be constrained. The resulting model of regional splicing constraint captures differential splicing constraint across gene and exon categories, and the most constrained genic regions are enriched for pathogenic splice-altering variants. Building from this model, we developed ConSpliceML. This ensemble machine learning approach combines regional splicing constraint with multiple per-nucleotide alternative splicing scores to guide the prediction of deleterious splicing variants in protein-coding genes. ConSpliceML more accurately distinguishes deleterious and benign splicing variants than state-of-the-art splicing prediction methods, especially in “cryptic” splicing regions beyond canonical donor or acceptor splice sites.

Conclusion

Integrating a model of genetic constraint with annotations from existing alternative splicing tools allows ConSpliceML to prioritize potentially deleterious splice-altering variants in studies of rare human diseases.

Familial history and prevalence of BRCA1, BRCA2 and TP53 pathogenic variants in HBOC Brazilian patients from a public healthcare service

Several studies have demonstrated the cost-effectiveness of genetic testing for surveillance and treatment of carriers of germline pathogenic variants associated with hereditary breast/ovarian cancer syndrome (HBOC). In Brazil, seventy percent of the population is assisted by the public Unified Health System (SUS), where genetic testing is still unavailable. And few studies were performed regarding the prevalence of HBOC pathogenic variants in this context. Here, we estimated the prevalence of germline pathogenic variants in BRCA1, BRCA2 and TP53 genes in Brazilian patients suspected of HBOC and referred to public healthcare service. Predictive power of risk prediction models for detecting mutation carriers was also evaluated. We found that 41 out of 257 tested patients (15.9%) were carriers of pathogenic variants in the analyzed genes. Most frequent pathogenic variant was the founder Brazilian mutation TP53 c.1010G > A (p.Arg337His), adding to the accumulated evidence that supports inclusion of TP53 in routine testing of Brazilian HBOC patients. Surprisingly, BRCA1 c.5266dupC (p.Gln1756fs), a frequently reported pathogenic variant in Brazilian HBOC patients, was not observed. Regarding the use of predictive models, we found that familial history of cancer might be used to improve selection or prioritization of patients for genetic testing, especially in a context of limited resources.

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.

Protocol to identify host-viral protein interactions between coagulation-related proteins and their genetic variants with SARS-CoV-2 proteins

Here, we describe a bioinformatics pipeline that evaluates the interactions between coagulation-related proteins and genetic variants with SARS-CoV-2 proteins. This pipeline searches for host proteins that may bind to viral protein and identifies and scores the protein genetic variants to predict the disease pathogenesis in specific subpopulations. Additionally, it is able to find structurally similar motifs and identify potential binding sites within the host-viral protein complexes to unveil viral impact on regulated biological processes and/or host-protein impact on viral invasion or reproduction. For complete details on the use and execution of this protocol, please refer to Holcomb et al. (2021).

Splicing mutations in the CFTR gene as therapeutic targets

The marketing approval, about ten years ago, of the first disease modulator for patients with cystic fibrosis harboring specific CFTR genotypes (~5% of all patients) brought new hope for their treatment. To date, several therapeutic strategies have been approved and the number of CFTR mutations targeted by therapeutic agents is increasing. Although these drugs do not reverse the existing disease, they help to increase the median life expectancy. However, on the basis of their CFTR genotype, ~10% of patients presently do not qualify for any of the currently available CFTR modulator therapies, particularly patients with splicing mutations (~12% of the reported CFTR mutations). Efforts are currently made to develop therapeutic agents that target disease-causing CFTR variants that affect splicing. This highlights the need to fully identify them by scanning non-coding regions and systematically determine their functional consequences. In this review, we present some examples of CFTR alterations that affect splicing events and the different therapeutic options that are currently developed and tested for splice switching.

Altered HIV-1 mRNA Splicing Due to Drug-Resistance-Associated Mutations in Exon 2/2b

The underlying molecular mechanism and their general effect on the replication capacity of HIV 1 drug-resistance-associated mutations is often poorly understood. To elucidate the effect of two such mutations located in a region with a high density of spicing regulatory elements on the HIV-1-splicing outcome, bioinformatic predictions were combined with transfection and infection experiments. Results show that the previously described R263K drug-resistance-associated integrase mutation has additionally a severe effect on the ESE2b splicing regulatory element (SRE) in exon 2b, which causes loss of SD2b recognition. This was confirmed by an R263R silent mutation with a similar predicted effect on the exon 2b SRE. In contrast, a V260I mutation and its silent counterpart with a lower effect on ESS2b did not exhibit any differences in the splicing pattern. Since HIV-1 highly relies on a balanced splicing reaction, changes in the splicing outcome can contribute to changes in viral replication and might add to the effect of escape mutations toward antiviral drugs. Thus, a classification of mutations purely addressing proteins is insufficient.

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.

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.

Let It Go: HIV-1 cis-Acting Repressive Sequences

After human immunodeficiency virus type 1 (HIV-1) was identified in the early 1980s, intensive work began to understand the molecular basis of HIV-1 gene expression. Subgenomic HIV-1 RNA regions, spread throughout the viral genome, were described to have a negative impact on the nuclear export of some viral transcripts. Those studies revealed an intrinsic RNA code as a new form of nuclear export regulation. Since such regulatory regions were later also identified in other viruses, as well as in cellular genes, it can be assumed that, during evolution, viruses took advantage of them to achieve more sophisticated replication mechanisms. Here, we review HIV-1 cis-acting repressive sequences that have been identified, and we discuss their possible underlying mechanisms and importance. Additionally, we show how current bioinformatic tools might allow more predictive approaches to identify and investigate them.

An artificial neural network approach integrating plasma proteomics and genetic data identifies PLXNA4 as a new susceptibility locus for pulmonary embolism

Venous thromboembolism is the third common cardiovascular disease and is composed of two entities, deep vein thrombosis (DVT) and its potential fatal form, pulmonary embolism (PE). While PE is observed in ~ 40% of patients with documented DVT, there is limited biomarkers that can help identifying patients at high PE risk. To fill this need, we implemented a two hidden-layers artificial neural networks (ANN) on 376 antibodies and 19 biological traits measured in the plasma of 1388 DVT patients, with or without PE, of the MARTHA study. We used the LIME algorithm to obtain a linear approximate of the resulting ANN prediction model. As MARTHA patients were typed for genotyping DNA arrays, a genome wide association study (GWAS) was conducted on the LIME estimate. Detected single nucleotide polymorphisms (SNPs) were tested for association with PE risk in MARTHA. Main findings were replicated in the EOVT study composed of 143 PE patients and 196 DVT only patients. The derived ANN model for PE achieved an accuracy of 0.89 and 0.79 in our training and testing sets, respectively. A GWAS on the LIME approximate identified a strong statistical association peak (rs1424597: p = 5.3 × 10^-7) at the PLXNA4 locus. Homozygote carriers for the rs1424597-A allele were then more frequently observed in PE than in DVT patients from the MARTHA (2% vs. 0.4%, p = 0.005) and the EOVT (3% vs. 0%, p = 0.013) studies. In a sample of 112 COVID-19 patients known to have endotheliopathy leading to acute lung injury and an increased risk of PE, decreased PLXNA4 levels were associated (p = 0.025) with worsened respiratory function. Using an original integrated proteomics and genetics strategy, we identified PLXNA4 as a new susceptibility gene for PE whose exact role now needs to be further elucidated.

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.

Modifying splice site usage with ModCon: Maintaining the genetic code while changing the underlying mRNP code

Codon degeneracy of amino acid sequences permits an additional “mRNP code” layer underlying the genetic code that is related to RNA processing. In pre-mRNA splicing, splice site usage is determined by both intrinsic strength and sequence context providing RNA binding sites for splicing regulatory proteins. In this study, we systematically examined modification of splicing regulatory properties in the neighborhood of a GT site, i.e. potential splice site, without altering the encoded amino acids.

We quantified the splicing regulatory properties of the neighborhood around a potential splice site by its Splice Site HEXplorer Weight (SSHW) based on the HEXplorer score algorithm. To systematically modify GT site neighborhoods, either minimizing or maximizing their SSHW, we designed the novel stochastic optimization algorithm ModCon that applies a genetic algorithm with stochastic crossover, insertion and random mutation elements supplemented by a heuristic sliding window approach.

To assess the achievable range in SSHW in human splice donors without altering the encoded amino acids, we applied ModCon to a set of 1000 randomly selected Ensembl annotated human splice donor sites, achieving substantial and accurate changes in SSHW. Using ModCon optimization, we successfully switched splice donor usage in a splice site competition reporter containing coding sequences from FANCA, FANCB or BRCA2, while retaining their amino acid coding information.

The ModCon algorithm and its R package implementation can assist in reporter design by either introducing novel splice sites, silencing accidental, undesired splice sites, and by generally modifying the entire mRNP code while maintaining the genetic code.

Hotspot exons are common targets of splicing perturbations

High-throughput splicing assays have demonstrated that many exonic variants can disrupt splicing; however, splice-disrupting variants distribute non-uniformly across genes. We propose the existence of exons that are particularly susceptible to splice-disrupting variants, which we refer to as hotspot exons. Hotspot exons are also more susceptible to splicing perturbation through drug treatment and knock-down of RNA-binding proteins. We develop a classifier for exonic splice-disrupting variants and use it to infer hotspot exons. We estimate that 1400 exons in the human genome are hotspots. Using panels of splicing reporters, we demonstrate how the ability of an exon to tolerate a mutation is inversely proportional to the strength of its neighboring splice sites.

Splicing-disrupting mutations are linked to diseases. By employing a machine learning approach, the authors show that certain exons, termed hotspot exons, are enriched for splicing-disruption variants and susceptible to splicing perturbations.

Functional Analysis of the PCCA and PCCB Gene Variants Predicted to Affect Splicing

It is estimated that up to one-third of all variants causing inherited diseases affect splicing; however, their deleterious effects and roles in disease pathogenesis are often not fully characterized. Given their prevalence and the development of various antisense-based splice-modulating approaches, pathogenic splicing variants have become an important object of genomic medicine. To improve the accuracy of variant interpretation in public mutation repositories, we applied the minigene splicing assay to study the effects of 24 variants that were predicted to affect normal splicing in the genes associated with propionic acidemia (PA)—PCCA and PCCB. As a result, 13 variants (including one missense and two synonymous variants) demonstrated a significant alteration of splicing with the predicted deleterious effect at the protein level and were characterized as spliceogenic loss-of-function variants. The analysis of the available data for the studied variants and application of the American College of Medical Genetics and the Association for Molecular Pathology (ACMG/AMP) guidelines allowed us to precisely classify five of the variants and change the pathogenic status of nine. Using the example of the PA genes, we demonstrated the utility of the minigene splicing assay in the fast and effective assessment of the spliceogenic effect for identified variants and highlight the necessity of their standardized classification.

Gene variants of coagulation related proteins that interact with SARS-CoV-2

Thrombosis is a recognized complication of Coronavirus disease of 2019 (COVID-19) and is often associated with poor prognosis. There is a well-recognized link between coagulation and inflammation, however, the extent of thrombotic events associated with COVID-19 warrants further investigation. Poly(A) Binding Protein Cytoplasmic 4 (PABPC4), Serine/Cysteine Proteinase Inhibitor Clade G Member 1 (SERPING1) and Vitamin K epOxide Reductase Complex subunit 1 (VKORC1), which are all proteins linked to coagulation, have been shown to interact with SARS proteins. We computationally examined the interaction of these with SARS-CoV-2 proteins and, in the case of VKORC1, we describe its binding to ORF7a in detail. We examined the occurrence of variants of each of these proteins across populations and interrogated their potential contribution to COVID-19 severity. Potential mechanisms, by which some of these variants may contribute to disease, are proposed. Some of these variants are prevalent in minority groups that are disproportionally affected by severe COVID-19. Therefore, we are proposing that further investigation around these variants may lead to better understanding of disease pathogenesis in minority groups and more informed therapeutic approaches.

Functional characterization of ABCC8 variants of unknown significance based on bioinformatics predictions, splicing assays, and protein analyses: Benefits for the accurate diagnosis of congenital hyperinsulinism

ABCC8 encodes the SUR1 subunit of the β-cell ATP-sensitive potassium channel whose loss of function causes congenital hyperinsulinism (CHI). Molecular diagnosis is critical for optimal management of CHI patients. Unfortunately, assessing the impact of ABCC8 variants on RNA splicing remains very challenging as this gene is poorly expressed in leukocytes. Here, we performed bioinformatics analysis and cell-based minigene assays to assess the impact on splicing of 13 ABCC8 variants identified in 20 CHI patients. Next, channel properties of SUR1 proteins expected to originate from minigene-detected in-frame splicing defects were analyzed after ectopic expression in COSm6 cells. Out of the analyzed variants, seven induced out-of-frame splicing defects and were therefore classified as recessive pathogenic, whereas two led to skipping of in-frame exons. Channel functional analysis of the latter demonstrated their pathogenicity. Interestingly, the common rs757110 SNP increased exon skipping in our system suggesting that it may act as a disease modifier factor. Our strategy allowed determining the pathogenicity of all selected ABCC8 variants, and CHI-inheritance pattern for 16 out of the 20 patients. This study highlights the value of combining RNA and protein functional approaches in variant interpretation and reveals the minigene splicing assay as a new tool for CHI molecular diagnostics.

Exon identity influences splicing induced by exonic variants and in silico prediction efficacy

BACKGROUND

Minigenes and in silico prediction tools are commonly used to assess the impact on splicing of CFTR variants. Exon skipping is often neglected though it could impact the efficacy of targeted therapies. The aim of the study was to identify exon skipping associated with CFTR variants and to evaluate in silico predictions of seven freely available software.

METHODS

CFTR basal exon skipping was evaluated on endogenous mRNA extracted from non-CF nasal cells and on two CFTR minigene banks. In silico tools and minigene systems were used to evaluate the impact of CFTR exonic variants on exon skipping.

RESULTS

Data showed that out of 65 CFTR variants tested, 26 enhanced exon skipping and that in silico prediction efficacy was of 50%-66%. Some in silico tools presented predictions with a bias towards the occurrence of splicing events while others presented a bias towards the absence of splicing events (non-detection including true negatives and false negatives). Classification of exons depending on their basal exon skipping level increased prediction rates up to 80%.

CONCLUSION

This study indicates that taking basal exon skipping into account could orientate the choice of the in silico tools to improve prediction rates. It also highlights the need to validate effects using in vitro assays or mRNA studies in patients. Eventually, it shows that variant-guided therapy should also target exon skipping associated with variants.

Intronic tRNAs of mitochondrial origin regulate constitutive and alternative splicing

BACKGROUND

The presence of nuclear mitochondrial DNA (numtDNA) has been reported within several nuclear genomes. Next to mitochondrial protein-coding genes, numtDNA sequences also encode for mitochondrial tRNA genes. However, the biological roles of numtDNA remain elusive.

RESULTS

Employing in silico analysis, we identify 281 mitochondrial tRNA homologs in the human genome, which we term nimtRNAs (nuclear intronic mitochondrial-derived tRNAs), being contained within introns of 76 nuclear host genes. Despite base changes in nimtRNAs when compared to their mtRNA homologs, a canonical tRNA cloverleaf structure is maintained. To address potential functions of intronic nimtRNAs, we insert them into introns of constitutive and alternative splicing reporters and demonstrate that nimtRNAs promote pre-mRNA splicing, dependent on the number and positioning of nimtRNA genes and splice site recognition efficiency. A mutational analysis reveals that the nimtRNA cloverleaf structure is required for the observed splicing increase. Utilizing a CRISPR/Cas9 approach, we show that a partial deletion of a single endogenous nimtRNALys within intron 28 of the PPFIBP1 gene decreases inclusion of the downstream-located exon 29 of the PPFIBP1 mRNA. By employing a pull-down approach followed by mass spectrometry, a 3'-splice site-associated protein network is identified, including KHDRBS1, which we show directly interacts with nimtRNATyr by an electrophoretic mobility shift assay.

CONCLUSIONS

We propose that nimtRNAs, along with associated protein factors, can act as a novel class of intronic splicing regulatory elements in the human genome by participating in the regulation of splicing.

Splicing analysis of SLC40A1 missense variations and contribution to hemochromatosis type 4 phenotypes

Hemochromatosis type 4, or ferroportin disease, is considered as the second leading cause of primary iron overload after HFE-related hemochromatosis. The disease, which is predominantly associated with missense variations in the SLC40A1 gene, is characterized by wide clinical heterogeneity. We tested the possibility that some of the reported missense mutations, despite their positions within exons, cause splicing defects. Fifty-eight genetic variants were selected from the literature based on two criteria: a precise description of the nucleotide change and individual evidence of iron overload. The selected variants were investigated by different in silico prediction tools and prioritized for midigene splicing assays. Of the 15 variations tested in vitro, only two were associated with splicing changes. We confirm that the c.1402G>A transition (p.Gly468Ser) disrupts the exon 7 donor site, leading to the use of an exonic cryptic splicing site and the generation of a truncated reading frame. We observed, for the first time, that the p.Gly468Ser substitution has no effect on the ferroportin iron export function. We demonstrate alternative splicing of exon 5 in different cell lines and show that the c.430A>G (p.Asn144Asp) variant promotes exon 5 inclusion. This could be part of a gain-of-function mechanism. We conclude that splicing mutations rarely contribute to hemochromatosis type 4 phenotypes. An in-depth investigation of exon 5 auxiliary splicing sequences may help to elucidate the mechanism by which splicing regulatory proteins regulate the production of the full length SLC40A1 transcript and to clarify its physiological importance.

VarCon: An R Package for Retrieving Neighboring Nucleotides of an SNV

Reporting of a single nucleotide variant (SNV) follows the Sequence Variant Nomenclature (http://varnomen.hgvs.org/), using an unambiguous numbering scheme specific for coding and noncoding DNA. However, the corresponding sequence neighborhood of a given SNV, which is required to assess its impact on splicing regulation, is not easily accessible from this nomenclature. Providing fast and easy access to this neighborhood just from a given SNV reference, the novel tool VarCon combines information of the Ensembl human reference genome and the corresponding transcript table for accurate retrieval. VarCon also displays splice site scores (HBond and MaxEnt scores) and HEXplorer profiles of an SNV neighborhood, reflecting position-dependent splice enhancing and silencing properties.

A model of k-mer surprisal to quantify local sequence information content surrounding splice regions

Molecular sequences carry information. Analysis of sequence conservation between homologous loci is a proven approach with which to explore the information content of molecular sequences. This is often done using multiple sequence alignments to support comparisons between homologous loci. These methods therefore rely on sufficient underlying sequence similarity with which to construct a representative alignment. Here we describe a method using a formal metric of information, surprisal, to analyse biological sub-sequences without alignment constraints. We applied our model to the genomes of five different species to reveal similar patterns across a panel of eukaryotes. As the surprisal of a sub-sequence is inversely proportional to its occurrence within the genome, the optimal size of the sub-sequences was selected for each species under consideration. With the model optimized, we found a strong correlation between surprisal and CG dinucleotide usage. The utility of our model was tested by examining the sequences of genes known to undergo splicing. We demonstrate that our model can identify biological features of interest such as known donor and acceptor sites. Analysis across all annotated coding exon junctions in Homo sapiens reveals the information content of coding exons to be greater than the surrounding intron regions, a consequence of increased suppression of the CG dinucleotide in intronic space. Sequences within coding regions proximal to exon junctions exhibited novel patterns within DNA and coding mRNA that are not a function of the encoded amino acid sequence. Our findings are consistent with the presence of secondary information encoding features such as DNA and RNA binding sites, multiplexed through the coding sequence and independent of the information required to define the corresponding amino-acid sequence. We conclude that surprisal provides a complementary methodology with which to locate regions of interest in the genome, particularly in situations that lack an appropriate multiple sequence alignment.

Potential impact on coagulopathy of gene variants of coagulation related proteins that interact with SARS-CoV-2

Thrombosis has been one of the complications of the Coronavirus disease of 2019 (COVID-19), often associated with poor prognosis. There is a well-recognized link between coagulation and inflammation, however, the extent of thrombotic events associated with COVID-19 warrants further investigation. Poly(A) Binding Protein Cytoplasmic 4 (PABPC4), Serine/Cysteine Proteinase Inhibitor Clade G Member 1 (SERPING1) and Vitamin K epOxide Reductase Complex subunit 1 (VKORC1), which are all proteins linked to coagulation, have been shown to interact with SARS proteins. We computationally examined the interaction of these with SARS-CoV-2 proteins and, in the case of VKORC1, we describe its binding to ORF7a in detail. We examined the occurrence of variants of each of these proteins across populations and interrogated their potential contribution to COVID-19 severity. Potential mechanisms by which some of these variants may contribute to disease are proposed. Some of these variants are prevalent in minority groups that are disproportionally affected by severe COVID-19. Therefore, we are proposing that further investigation around these variants may lead to better understanding of disease pathogenesis in minority groups and more informed therapeutic approaches.

Author summary

Increased blood clotting, especially in the lungs, is a common complication of COVID-19. Infectious diseases cause inflammation which in turn can contribute to increased blood clotting. However, the extent of clot formation that is seen in the lungs of COVID-19 patients suggests that there may be a more direct link. We identified three human proteins that are involved indirectly in the blood clotting cascade and have been shown to interact with proteins of SARS virus, which is closely related to the novel coronavirus. We examined computationally the interaction of these human proteins with the viral proteins. We looked for genetic variants of these proteins and examined how these variants are distributed across populations. We investigated whether variants of these genes could impact severity of COVID-19. Further investigation around these variants may provide clues for the pathogenesis of COVID-19 particularly in minority groups.

JMJD6 Regulates Splicing of Its Own Gene Resulting in Alternatively Spliced Isoforms with Different Nuclear Targets

Jumonji-domain-containing protein 6 (JMJD6) is a Fe(II) and 2-oxogluterate (2OG) dependent oxygenase involved in gene regulation through post-translationally modifying nuclear proteins. It is highly expressed in many cancer types and linked to tumor progression and metastasis. Four alternatively-spliced jmjd6 transcripts were annotated. Here, we focus on the two most abundantly expressed ones, which we call jmjd6-2 and jmjd6-Ex5. TCGA SpliceSeq data revealed a significant decrease of jmjd6-Ex5 transcripts in patients and postmortem tissue of several tumors. The two protein isoforms are distinguished by their C-terminal sequences, which include a serine-rich region (polyS-domain) in JMJD6-2 that is not present in JMJD6-Ex5. Immunoprecipitation followed by LC-MS/MS for JMJD6-Ex5 shows that different sets of proteins interact with JMJD6-2 and JMJD6-Ex5 with only a few overlaps. In particular, we found TFIIF-associating CTD phosphatase (FCP1), proteins of the survival of motor neurons (SMN) complex, heterogeneous nuclear ribonucleoproteins (hnRNPs) and upstream binding factor (UBF) to interact with JMJD6-Ex5. Like JMJD6-2, both UBF and FCP1 comprise a polyS-domain. The polyS domain of JMJD6-2 might block the interaction with polyS-domains of other proteins. In contrast, JMJD6-2 interacts with many SR-like proteins with arginine/serine-rich (RS)-domains, including several splicing factors. In an HIV-based splicing reporter assay, co-expression of JMJD6-2 inhibited exon inclusion, whereas JMJD6-Ex5 did not have any effect. Furthermore, the silencing of jmjd6 by siRNAs favored jmjd6-Ex5 transcripts, suggesting that JMJD6 controls splicing of its own pre-mRNA. The distinct molecular properties of JMJD6-2 and JMJD6-Ex5 open a lead into the functional implications of the variations of their relative abundance in tumors.

Splicing Enhancers at Intron-Exon Borders Participate in Acceptor Splice Sites Recognition

Acceptor splice site recognition (3′ splice site: 3′ss) is a fundamental step in precursor messenger RNA (pre-mRNA) splicing. Generally, the U2 small nuclear ribonucleoprotein (snRNP) auxiliary factor (U2AF) heterodimer recognizes the 3′ss, of which U2AF35 has a dual function: (i) It binds to the intron–exon border of some 3′ss and (ii) mediates enhancer-binding splicing activators’ interactions with the spliceosome. Alternative mechanisms for 3′ss recognition have been suggested, yet they are still not thoroughly understood. Here, we analyzed 3′ss recognition where the intron–exon border is bound by a ubiquitous splicing regulator SRSF1. Using the minigene analysis of two model exons and their mutants, BRCA2 exon 12 and VARS2 exon 17, we showed that the exon inclusion correlated much better with the predicted SRSF1 affinity than 3′ss quality, which were assessed using the Catalog of Inferred Sequence Binding Preferences of RNA binding proteins (CISBP-RNA) database and maximum entropy algorithm (MaxEnt) predictor and the U2AF35 consensus matrix, respectively. RNA affinity purification proved SRSF1 binding to the model 3′ss. On the other hand, knockdown experiments revealed that U2AF35 also plays a role in these exons’ inclusion. Most probably, both factors stochastically bind the 3′ss, supporting exon recognition, more apparently in VARS2 exon 17. Identifying splicing activators as 3′ss recognition factors is crucial for both a basic understanding of splicing regulation and human genetic diagnostics when assessing variants’ effects on splicing.

Large-scale comparative evaluation of user-friendly tools for predicting variant-induced alterations of splicing regulatory elements

Discriminating which nucleotide variants cause disease or contribute to phenotypic traits remains a major challenge in human genetics. In theory, any intragenic variant can potentially affect RNA splicing by altering splicing regulatory elements (SREs). However, these alterations are often ignored mainly because pioneer SRE predictors have proved inefficient. Here, we report the first large-scale comparative evaluation of four user-friendly SRE-dedicated algorithms (QUEPASA, HEXplorer, SPANR, and HAL) tested both as standalone tools and in multiple combined ways based on two independent benchmark datasets adding up to >1,300 exonic variants studied at the messenger RNA level and mapping to 89 different disease-causing genes. These methods display good predictive power, based on decision thresholds derived from the receiver operating characteristics curve analyses, with QUEPASA and HAL having the best accuracies either as standalone or in combination. Still, overall there was a tight race between the four predictors, suggesting that all methods may be of use. Additionally, QUEPASA and HEXplorer may be beneficial as well for predicting variant-induced creation of pseudoexons deep within introns. Our study highlights the potential of SRE predictors as filtering tools for identifying disease-causing candidates among the plethora of variants detected by high-throughput DNA sequencing and provides guidance for their use in genomic medicine settings.

Profiling of cis- and trans-acting factors supporting noncanonical splice site activation

Recently, by combining transcriptomics with functional splicing reporter assays we were able to identify GT > GC > TT as the three highest ranked dinucleotides of human 5' splice sites (5'ss). Here, we have extended our investigations to the proteomic characterization of nuclear proteins that bind to canonical and noncanonical 5'ss. Surprisingly, we found that U1 snRNP binding to functional 5'ss sequences prevented components of the DNA damage response (DDR) from binding to the RNA, suggesting a close link between spliceosome arrangement and genome stability. We demonstrate that all tested noncanonical 5'ss sequences are bona-fide targets of the U2-type spliceosome and are bound by U1 snRNP, including U1-C, in the presence of splicing enhancers. The quantity of precipitated U1-C protein was similar for all noncanonical 5'ss dinucleotides, so that the highly different 5'ss usage was likely due to a later step after early U1 snRNP binding. In addition, we show that an internal GT at positions +5/+6 can be advantageous for splicing at position +1 of noncanonical splice sites. Likewise, and in agreement with previous observations, splicing inactive U1 snRNP binding sites could serve as splicing enhancers, which may also explain the higher abundance of U1 snRNPs compared to other U snRNPs. Finally, we observe that an arginine-serine (RS)-rich domain recruitment to stem loop I of the U1 snRNA is functionally sufficient to promote exon-definition and upstream 3'ss activation.

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

It is possible to estimate the prior probability of pathogenicity for germline disease gene variants based on bioinformatic prediction of variant effect/s. However, routinely used approaches have likely led to the underestimation and underreporting of variants located outside donor and acceptor splice site motifs that affect messenger RNA (mRNA) processing. This review presents information about hereditary cancer gene germline variants, outside native splice sites, with experimentally validated splicing effects. We list 95 exonic variants that impact splicing regulatory elements (SREs) in BRCA1, BRCA2, MLH1, MSH2, MSH6, and PMS2. We utilized a pre-existing large-scale BRCA1 functional data set to map functional SREs, and assess the relative performance of different tools to predict effects of 283 variants on such elements. We also describe rare examples of intronic variants that impact branchpoint (BP) sites and create pseudoexons. We discuss the challenges in predicting variant effect on BP site usage and pseudoexonization, and suggest strategies to improve the bioinformatic prioritization of such variants for experimental validation. Importantly, our review and analysis highlights the value of considering impact of variants outside donor and acceptor motifs on mRNA splicing and disease causation.

Calibration of Pathogenicity Due to Variant-Induced Leaky Splicing Defects by Using BRCA2 Exon 3 as a Model System

BRCA2 is a clinically actionable gene implicated in breast and ovarian cancer predisposition that has become a high priority target for improving the classification of variants of unknown significance (VUS). Among all BRCA2 VUS, those causing partial/leaky splicing defects are the most challenging to classify because the minimal level of full-length (FL) transcripts required for normal function remains to be established. Here, we explored BRCA2 exon 3 (BRCA2e3) as a model for calibrating variant-induced spliceogenicity and estimating thresholds for BRCA2 haploinsufficiency. In silico predictions, minigene splicing assays, patients' RNA analyses, a mouse embryonic stem cell (mESC) complementation assay and retrieval of patient-related information were combined to determine the minimal requirement of FL BRCA2 transcripts. Of 100 BRCA2e3 variants tested in the minigene assay, 64 were found to be spliceogenic, causing mild to severe RNA defects. Splicing defects were also confirmed in patients' RNA when available. Analysis of a neutral leaky variant (c.231T>G) showed that a reduction of approximately 60% of FL BRCA2 transcripts from a mutant allele does not cause any increase in cancer risk. Moreover, data obtained from mESCs suggest that variants causing a decline in FL BRCA2 with approximately 30% of wild-type are not pathogenic, given that mESCs are fully viable and resistant to DNA-damaging agents in those conditions. In contrast, mESCs producing lower relative amounts of FL BRCA2 exhibited either null or hypomorphic phenotypes. Overall, our findings are likely to have broader implications on the interpretation of BRCA2 variants affecting the splicing pattern of other essential exons. SIGNIFICANCE: These findings demonstrate that BRCA2 tumor suppressor function tolerates substantial reduction in full-length transcripts, helping to determine the pathogenicity of BRCA2 leaky splicing variants, some of which may not increase cancer risk.

Splicing mutations in inherited retinal diseases

Mutations which induce aberrant transcript splicing represent a distinct class of disease-causing genetic variants in retinal disease genes. Such mutations may either weaken or erase regular splice sites or create novel splice sites which alter exon recognition. While mutations affecting the canonical GU-AG dinucleotides at the splice donor and splice acceptor site are highly predictive to cause a splicing defect, other variants in the vicinity of the canonical splice sites or those affecting additional cis-acting regulatory sequences within exons or introns are much more difficult to assess or even to recognize and require additional experimental validation. Splicing mutations are unique in that the actual outcome for the transcript (e.g. exon skipping, pseudoexon inclusion, intron retention) and the encoded protein can be quite different depending on the individual mutation. In this article, we present an overview on the current knowledge about and impact of splicing mutations in inherited retinal diseases. We introduce the most common sub-classes of splicing mutations including examples from our own work and others and discuss current strategies for the identification and validation of splicing mutations, as well as therapeutic approaches, open questions, and future perspectives in this field of research.

Mutational bias and the protein code shape the evolution of splicing enhancers

Exonic splicing enhancers (ESEs) are enriched in exons relative to introns and bind splicing activators. This study considers a fundamental question of co-evolution: How did ESE motifs become enriched in exons prior to the evolution of ESE recognition? We hypothesize that the high exon to intron motif ratios necessary for ESE function were created by mutational bias coupled with purifying selection on the protein code. These two forces retain certain coding motifs in exons while passively depleting them from introns. Through the use of simulations, genomic analyses, and high throughput splicing assays, we confirm the key predictions of this hypothesis, including an overlap between protein and splicing information in ESEs. We discuss the implications of mutational bias as an evolutionary driver in other cis-regulatory systems.

Splicing is regulated by cis-acting elements in pre-mRNAs such as exonic or intronic splicing enhancers and silencers. Here the authors show that exonic splicing enhancers are enriched in exons compared to introns due to mutational bias coupled with purifying selection on the protein code.

RNA Splicing Defects in Hypertrophic Cardiomyopathy: Implications for Diagnosis and Therapy

Hypertrophic cardiomyopathy (HCM), the most common inherited heart disease, is predominantly caused by mutations in genes that encode sarcomere-associated proteins. Effective gene-based diagnosis is critical for the accurate clinical management of patients and their family members. However, the introduction of high-throughput DNA sequencing approaches for clinical diagnostics has vastly expanded the number of variants of uncertain significance, leading to many inconclusive results that limit the clinical utility of genetic testing. More recently, developments in RNA analysis have been improving diagnostic outcomes by identifying new variants that interfere with splicing. This review summarizes recent discoveries of RNA mis-splicing in HCM and provides an overview of research that aims to apply the concept of RNA therapeutics to HCM.

A scale-free analysis of the HIV-1 genome demonstrates multiple conserved regions of structural and functional importance

HIV-1 replicates via a low-fidelity polymerase with a high mutation rate; strong conservation of individual nucleotides is highly indicative of the presence of critical structural or functional properties. Identifying such conservation can reveal novel insights into viral behaviour. We analysed 3651 publicly available sequences for the presence of nucleic acid conservation beyond that required by amino acid constraints, using a novel scale-free method that identifies regions of outlying score together with a codon scoring algorithm. Sequences with outlying score were further analysed using an algorithm for producing local RNA folds whilst accounting for alignment properties. 11 different conserved regions were identified, some corresponding to well-known cis-acting functions of the HIV-1 genome but also others whose conservation has not previously been noted. We identify rational causes for many of these, including cis functions, possible additional reading frame usage, a plausible mechanism by which the central polypurine tract primes second-strand DNA synthesis and a conformational stabilising function of a region at the 5′ end of env.

HIV-1 is a very rapidly mutating organism, however some parts of its genetic material change more than others. We looked for coding regions of HIV-1 that change relatively little, by turning the problem of finding such regions into a problem in signal processing, and solving this using a novel analytical approach that we recently described. We investigated why the regions we identified change less, including using the genetic code in the regions we found to prime an algorithm to predict their structures. In some cases there are already known functions for the features we found, in others they provide new insights into the properties of known regions, and in some cases we identify new regions that vary less for as yet unknown functional reasons.

Future directions for high-throughput splicing assays in precision medicine

Classification of variants of unknown significance is a challenging technical problem in clinical genetics. As up to one-third of disease-causing mutations are thought to affect pre-mRNA splicing, it is important to accurately classify splicing mutations in patient sequencing data. Several consortia and healthcare systems have conducted large-scale patient sequencing studies, which discover novel variants faster than they can be classified. Here, we compare the advantages and limitations of several high-throughput splicing assays aimed at mitigating this bottleneck, and describe a data set of ~5,000 variants that we analyzed using our Massively Parallel Splicing Assay (MaPSy). The Critical Assessment of Genome Interpretation group (CAGI) organized a challenge, in which participants submitted machine learning models to predict the splicing effects of variants in this data set. We discuss the winning submission of the challenge (MMSplice) which outperformed existing software. Finally, we highlight methods to overcome the limitations of MaPSy and similar assays, such as tissue-specific splicing, the effect of surrounding sequence context, classifying intronic variants, synthesizing large exons, and amplifying complex libraries of minigene species. Further development of these assays will greatly benefit the field of clinical genetics, which lack high-throughput methods for variant interpretation.

Assessment of the functional impact on the pre-mRNA splicing process of 28 nucleotide variants associated with Pompe disease in GAA exon 2 and their recovery using antisense technology

Glycogen storage disease II (GSDII), also called Pompe disease, is an autosomal recessive inherited disease caused by a defect in glycogen metabolism due to the deficiency of the enzyme acid alpha-glucosidase (GAA) responsible for its degradation. So far, more than 500 sequence variants of the GAA gene have been reported but their possible involvement on the pre-messenger RNA splicing mechanism has not been extensively studied. In this work, we have investigated, by an in vitro functional assay, all putative splicing variants within GAA exon 2 and flanking introns. Our results show that many variants falling in the canonical splice site or the exon can induce GAA exon 2 skipping. In these cases, therefore, therapeutic strategies aimed at restoring protein folding of partially active mutated GAA proteins might not be sufficient. Regarding this issue, we have tested the effect of antisense oligonucleotides (AMOs) that were previously shown capable of rescuing splicing misregulation caused by the common c.-32-13T>G variant associated with the childhood/adult phenotype of GSDII. Interestingly, our results show that these AMOs are also quite effective in rescuing the splicing impairment of several exonic splicing variants, thus widening the potential use of these effectors for GSDII treatment.

Splicing dysregulation contributes to the pathogenicity of several F9 exonic point variants

Background

Pre‐mRNA splicing is a complex process requiring the identification of donor site, acceptor site, and branch point site with an adjacent polypyrimidine tract sequence. Splicing is regulated by splicing regulatory elements (SREs) with both enhancer and suppressor functions. Variants located in exonic regions can impact splicing through dysregulation of native splice sites, SREs, and cryptic splice site activation. While splicing dysregulation is considered primary disease‐inducing mechanism of synonymous variants, its contribution toward disease phenotype of non‐synonymous variants is underappreciated.

Methods

In this study, we analyzed 415 disease‐causing and 120 neutral F9 exonic point variants including both synonymous and non‐synonymous for their effect on splicing using a series of in silico splice site prediction tools, SRE prediction tools, and in vitro minigene assays.

Results

The use of splice site and SRE prediction tools in tandem provided better prediction but were not always in agreement with the minigene assays. The net effect of splicing dysregulation caused by variants was context dependent. Minigene assays revealed that perturbed splicing can be found.

Conclusion

Synonymous variants primarily cause disease phenotype via splicing dysregulation while additional mechanisms such as translation rate also play an important role. Splicing dysregulation is likely to contribute to the disease phenotype of several non‐synonymous variants.

High-throughput analysis revealed mutations' diverging effects on SMN1 exon 7 splicing

Splicing-affecting mutations can disrupt gene function by altering the transcript assembly. To ascertain splicing dysregulation principles, we modified a minigene assay for the parallel high-throughput evaluation of different mutations by next-generation sequencing. In our model system, all exonic and six intronic positions of the SMN1 gene's exon 7 were mutated to all possible nucleotide variants, which amounted to 180 unique single-nucleotide mutants and 470 double mutants. The mutations resulted in a wide range of splicing aberrations. Exonic splicing-affecting mutations resulted either in substantial exon skipping, supposedly driven by predicted exonic splicing silencer or cryptic donor splice site (5'ss) and de novo 5'ss strengthening and use. On the other hand, a single disruption of exonic splicing enhancer was not sufficient to cause major exon skipping, suggesting these elements can be substituted during exon recognition. While disrupting the acceptor splice site led only to exon skipping, some 5'ss mutations potentiated the use of three different cryptic 5'ss. Generally, single mutations supporting cryptic 5'ss use displayed better pre-mRNA/U1 snRNA duplex stability and increased splicing regulatory element strength across the original 5'ss. Analyzing double mutants supported the predominating splicing regulatory elements' effect, but U1 snRNA binding could contribute to the global balance of splicing isoforms. Based on these findings, we suggest that creating a new splicing enhancer across the mutated 5'ss can be one of the main factors driving cryptic 5'ss use.

Context matters: Regulation of splice donor usage

Elaborate research on splicing, starting in the late seventies, evolved from the discovery that 5' splice sites are recognized by their complementarity to U1 snRNA towards the realization that RNA duplex formation cannot be the sole basis for 5'ss selection. Rather, their recognition is highly influenced by a number of context factors including transcript architecture as well as splicing regulatory elements (SREs) in the splice site neighborhood. In particular, proximal binding of splicing regulatory proteins highly influences splicing outcome. The importance of SRE integrity especially becomes evident in the light of human pathogenic mutations where single nucleotide changes in SREs can severely affect the resulting transcripts. Bioinformatics tools nowadays greatly assist in the computational evaluation of 5'ss, their neighborhood and the impact of pathogenic mutations. Although predictions are already quite robust, computational evaluation of the splicing regulatory landscape still faces challenges to increase future reliability. This article is part of a Special Issue entitled: RNA structure and splicing regulation edited by Francisco Baralle, Ravindra Singh and Stefan Stamm.

Effect of inbreeding on intellectual disability revisited by trio sequencing

In outbred Western populations, most individuals with intellectual disability (ID) are sporadic cases, dominant de novo mutations (DNM) are frequent, and autosomal recessive ID (ARID) is very rare. Because of the high rate of parental consanguinity, which raises the risk for ARID and other recessive disorders, the prevalence of ID is significantly higher in near- and middle-east countries. Indeed, homozygosity mapping and sequencing in consanguineous families have already identified a plethora of ARID genes, but because of the design of these studies, DNMs could not be systematically assessed, and the proportion of cases that are potentially preventable by avoiding consanguineous marriages or through carrier testing is hitherto unknown. This prompted us to perform whole-exome sequencing in 100 sporadic ID patients from Iran and their healthy consanguineous parents. In 61 patients, we identified apparently causative changes in known ID genes. Of these, 44 were homozygous recessive and 17 dominant DNMs. Assuming that the DNM rate is stable, these results suggest that parental consanguinity raises the ID risk about 3.6-fold, and about 4.1 to 4.25-fold for children of first-cousin unions. These results do not rhyme with recent opinions that consanguinity-related health risks are generally small and have been "overstated" in the past.