Using positional distribution to identify splicing elements and predict pre-mRNA processing defects in human genes. Proc Natl Acad Sci U S A. 2011;108:11093-11098. [PMID: 21685335 DOI: 10.1073/pnas.1101135108]

Light regulates nuclear detainment of intron-retained transcripts through COP1-spliceosome to modulate photomorphogenesis

Intron retention (IR) is the most common alternative splicing event in Arabidopsis. An increasing number of studies have demonstrated the major role of IR in gene expression regulation. The impacts of IR on plant growth and development and response to environments remain underexplored. Here, we found that IR functions directly in gene expression regulation on a genome-wide scale through the detainment of intron-retained transcripts (IRTs) in the nucleus. Nuclear-retained IRTs can be kept away from translation through this mechanism. COP1-dependent light modulation of the IRTs of light signaling genes, such as PIF4, RVE1, and ABA3, contribute to seedling morphological development in response to changing light conditions. Furthermore, light-induced IR changes are under the control of the spliceosome, and in part through COP1-dependent ubiquitination and degradation of DCS1, a plant-specific spliceosomal component. Our data suggest that light regulates the activity of the spliceosome and the consequent IRT nucleus detainment to modulate photomorphogenesis through COP1.

SpliceAPP: an interactive web server to predict splicing errors arising from human mutations

BACKGROUND

Splicing variants are a major class of pathogenic mutations, with their severity equivalent to nonsense mutations. However, redundant and degenerate splicing signals hinder functional assessments of sequence variations within introns, particularly at branch sites. We have established a massively parallel splicing assay to assess the impact on splicing of 11,191 disease-relevant variants. Based on the experimental results, we then applied regression-based methods to identify factors determining splicing decisions and their respective weights.

RESULTS

Our statistical modeling is highly sensitive, accurately annotating the splicing defects of near-exon intronic variants, outperforming state-of-the-art predictive tools. We have incorporated the algorithm and branchpoint information into a web-based tool, SpliceAPP, to provide an interactive application. This user-friendly website allows users to upload any genetic variants with genome coordinates (e.g., chr15 74,687,208 A G), and the tool will output predictions for splicing error scores and evaluate the impact on nearby splice sites. Additionally, users can query branch site information within the region of interest.

CONCLUSIONS

In summary, SpliceAPP represents a pioneering approach to screening pathogenic intronic variants, contributing to the development of precision medicine. It also facilitates the annotation of splicing motifs. SpliceAPP is freely accessible using the link https://bc.imb.sinica.edu.tw/SpliceAPP . Source code can be downloaded at https://github.com/hsinnan75/SpliceAPP .

Three exonic variants in the PHEX gene cause aberrant splicing in a minigene assay

Background: X-linked hypophosphatemia (XLH, OMIM 307800) is a rare phosphorus metabolism disorder caused by PHEX gene variants. Many variants simply classified as missense or nonsense variants were only analyzed at the DNA level. However, growing evidence indicates that some of these variants may alter pre-mRNA splicing, causing diseases. Therefore, this study aimed to use bioinformatics tools and a minigene assay to ascertain the effects of PHEX variations on pre-mRNA splicing. Methods: We analyzed 174 variants in the PHEX gene described as missense or nonsense variants. Finally, we selected eight candidate variants using bioinformatics tools to evaluate their effects on pre-mRNA splicing using a minigene assay system. The complementary DNA (cDNA) sequence for the PHEX gene (RefSeq NM_000444.6) serves as the basis for DNA variant numbering. Results: Of the eight candidate variants, three were found to cause abnormal splicing. Variants c.617T>G p.(Leu206Trp) and c.621T>A p.(Tyr207*) in exon 5 altered the splicing of pre-mRNA, owing to the activation of a cryptic splice site in exon 5, which produced an aberrant transcript lacking a part of exon 5, whereas variant c.1700G>C p.(Arg567Pro) in exon 16 led to the activation of a cryptic splice site in intron 16, resulting in a partial inclusion of intron 16. Conclusion: Our study employed a minigene system, which has a great degree of flexibility to assess abnormal splicing patterns under the circumstances of patient mRNA samples that are not available, to explore the impact of the exonic variants on pre-mRNA splicing. Based on the aforementioned experimental findings, we demonstrated the importance of analyzing exonic variants at the mRNA level.

CRISPR-dCas13d-based deep screening of proximal and distal splicing-regulatory elements

Pre-mRNA splicing, a key process in gene expression, can be therapeutically modulated using various drug modalities, including antisense oligonucleotides (ASOs). However, determining promising targets is hampered by the challenge of systematically mapping splicing-regulatory elements (SREs) in their native sequence context. Here, we use the catalytically inactive CRISPR-RfxCas13d RNA-targeting system (dCas13d/gRNA) as a programmable platform to bind SREs and modulate splicing by competing against endogenous splicing factors. SpliceRUSH, a high-throughput screening method, was developed to map SREs in any gene of interest using a lentivirus gRNA library that tiles the genetic region, including distal intronic sequences. When applied to SMN2, a therapeutic target for spinal muscular atrophy, SpliceRUSH robustly identifies not only known SREs but also a previously unknown distal intronic SRE, which can be targeted to alter exon 7 splicing using either dCas13d/gRNA or ASOs. This technology enables a deeper understanding of splicing regulation with applications for RNA-based drug discovery.

Combining full-length gene assay and SpliceAI to interpret the splicing impact of all possible SPINK1 coding variants

BACKGROUND

Single-nucleotide variants (SNVs) within gene coding sequences can significantly impact pre-mRNA splicing, bearing profound implications for pathogenic mechanisms and precision medicine. In this study, we aim to harness the well-established full-length gene splicing assay (FLGSA) in conjunction with SpliceAI to prospectively interpret the splicing effects of all potential coding SNVs within the four-exon SPINK1 gene, a gene associated with chronic pancreatitis.

RESULTS

Our study began with a retrospective analysis of 27 SPINK1 coding SNVs previously assessed using FLGSA, proceeded with a prospective analysis of 35 new FLGSA-tested SPINK1 coding SNVs, followed by data extrapolation, and ended with further validation. In total, we analyzed 67 SPINK1 coding SNVs, which account for 9.3% of the 720 possible coding SNVs. Among these 67 FLGSA-analyzed SNVs, 12 were found to impact splicing. Through detailed comparison of FLGSA results and SpliceAI predictions, we inferred that the remaining 653 untested coding SNVs in the SPINK1 gene are unlikely to significantly affect splicing. Of the 12 splice-altering events, nine produced both normally spliced and aberrantly spliced transcripts, while the remaining three only generated aberrantly spliced transcripts. These splice-impacting SNVs were found solely in exons 1 and 2, notably at the first and/or last coding nucleotides of these exons. Among the 12 splice-altering events, 11 were missense variants (2.17% of 506 potential missense variants), and one was synonymous (0.61% of 164 potential synonymous variants). Notably, adjusting the SpliceAI cut-off to 0.30 instead of the conventional 0.20 would improve specificity without reducing sensitivity.

CONCLUSIONS

By integrating FLGSA with SpliceAI, we have determined that less than 2% (1.67%) of all possible coding SNVs in SPINK1 significantly influence splicing outcomes. Our findings emphasize the critical importance of conducting splicing analysis within the broader genomic sequence context of the study gene and highlight the inherent uncertainties associated with intermediate SpliceAI scores (0.20 to 0.80). This study contributes to the field by being the first to prospectively interpret all potential coding SNVs in a disease-associated gene with a high degree of accuracy, representing a meaningful attempt at shifting from retrospective to prospective variant analysis in the era of exome and genome sequencing.

Frontiers and Challenges of Computing ncRNAs Biogenesis, Function and Modulation

Non-coding RNAs (ncRNAs), generated from nonprotein coding DNA sequences, constitute 98-99% of the human genome. Non-coding RNAs encompass diverse functional classes, including microRNAs, small interfering RNAs, PIWI-interacting RNAs, small nuclear RNAs, small nucleolar RNAs, and long non-coding RNAs. With critical involvement in gene expression and regulation across various biological and physiopathological contexts, such as neuronal disorders, immune responses, cardiovascular diseases, and cancer, non-coding RNAs are emerging as disease biomarkers and therapeutic targets. In this review, after providing an overview of non-coding RNAs' role in cell homeostasis, we illustrate the potential and the challenges of state-of-the-art computational methods exploited to study non-coding RNAs biogenesis, function, and modulation. This can be done by directly targeting them with small molecules or by altering their expression by targeting the cellular engines underlying their biosynthesis. Drawing from applications, also taken from our work, we showcase the significance and role of computer simulations in uncovering fundamental facets of ncRNA mechanisms and modulation. This information may set the basis to advance gene modulation tools and therapeutic strategies to address unmet medical needs.

Whole genome sequencing in clinical practice

Whole genome sequencing (WGS) is becoming the preferred method for molecular genetic diagnosis of rare and unknown diseases and for identification of actionable cancer drivers. Compared to other molecular genetic methods, WGS captures most genomic variation and eliminates the need for sequential genetic testing. Whereas, the laboratory requirements are similar to conventional molecular genetics, the amount of data is large and WGS requires a comprehensive computational and storage infrastructure in order to facilitate data processing within a clinically relevant timeframe. The output of a single WGS analyses is roughly 5 MIO variants and data interpretation involves specialized staff collaborating with the clinical specialists in order to provide standard of care reports. Although the field is continuously refining the standards for variant classification, there are still unresolved issues associated with the clinical application. The review provides an overview of WGS in clinical practice - describing the technology and current applications as well as challenges connected with data processing, interpretation and clinical reporting.

ZCCHC17 Modulates Neuronal RNA Splicing and Supports Cognitive Resilience in Alzheimer's Disease

ZCCHC17 is a putative master regulator of synaptic gene dysfunction in Alzheimer's disease (AD), and ZCCHC17 protein declines early in AD brain tissue, before significant gliosis or neuronal loss. Here, we investigate the function of ZCCHC17 and its role in AD pathogenesis using data from human autopsy tissue (consisting of males and females) and female human cell lines. Co-immunoprecipitation (co-IP) of ZCCHC17 followed by mass spectrometry analysis in human iPSC-derived neurons reveals that ZCCHC17's binding partners are enriched for RNA-splicing proteins. ZCCHC17 knockdown results in widespread RNA-splicing changes that significantly overlap with splicing changes found in AD brain tissue, with synaptic genes commonly affected. ZCCHC17 expression correlates with cognitive resilience in AD patients, and we uncover an APOE4-dependent negative correlation of ZCCHC17 expression with tangle burden. Furthermore, a majority of ZCCHC17 interactors also co-IP with known tau interactors, and we find a significant overlap between alternatively spliced genes in ZCCHC17 knockdown and tau overexpression neurons. These results demonstrate ZCCHC17's role in neuronal RNA processing and its interaction with pathology and cognitive resilience in AD, and suggest that the maintenance of ZCCHC17 function may be a therapeutic strategy for preserving cognitive function in the setting of AD pathology.

Defects of the spliceosomal gene SNRPB affect osteo- and chondro-differentiation

Although gene splicing occurs throughout the body, the phenotype of spliceosomal defects is largely limited to specific tissues. Cerebro-costo-mandibular syndrome (CCMS) is one such spliceosomal disease, which presents as congenital skeletal dysmorphism and is caused by mutations of SNRPB gene encoding Small Nuclear Ribonucleoprotein Polypeptides B/B' (SmB/B'). This study employed in vitro cell cultures to monitor osteo- and chondro-differentiation and examined the role of SmB/B' in the differentiation process. We found that low levels of SmB/B' by knockdown or mutations of SNRPB led to suppressed osteodifferentiation in Saos-2 osteoprogenitor-like cells, which was accompanied by affected splicing of Dlx5. On the other hand, low SmB/B' led to promoted chondrogenesis in HEPM mesenchymal stem cells. Consistent with other reports, osteogenesis was promoted by the Wnt/β-catenin pathway activator and suppressed by Wnt and BMP blockers, whereas chondrogenesis was promoted by Wnt inhibitors. Suppressed osteogenic markers by SNRPB knockdown were partly rescued by Wnt/β-catenin pathway activation. Reporter analysis revealed that suppression of SNRPB results in attenuated Wnt pathway and/or enhanced BMP pathway activities. SNRPB knockdown altered splicing of TCF7L2 which impacts Wnt/β-catenin pathway activities. This work helps unravel the mechanism underlying CCMS whereby reduced expression of spliceosomal proteins causes skeletal phenotypes.

Benchmarking splice variant prediction algorithms using massively parallel splicing assays

BACKGROUND

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

RESULTS

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

CONCLUSION

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

Heterogeneous splicing patterns resulting from KIF5A variants associated with amyotrophic lateral sclerosis

Single-nucleotide variants (SNVs) in the gene encoding Kinesin Family Member 5A (KIF5A), a neuronal motor protein involved in anterograde transport along microtubules, have been associated with amyotrophic lateral sclerosis (ALS). ALS is a rapidly progressive and fatal neurodegenerative disease that primarily affects the motor neurons. Numerous ALS-associated KIF5A SNVs are clustered near the splice-site junctions of the penultimate exon 27 and are predicted to alter the carboxy-terminal (C-term) cargo-binding domain of KIF5A. Mis-splicing of exon 27, resulting in exon exclusion, is proposed to be the mechanism by which these SNVs cause ALS. Whether all SNVs proximal to exon 27 result in exon exclusion is unclear. To address this question, we designed an in vitro minigene splicing assay in human embryonic kidney 293 cells, which revealed heterogeneous site-specific effects on splicing: only 5' splice-site (5'ss) SNVs resulted in exon skipping. We also quantified splicing in select clustered, regularly interspaced, short palindromic repeats-edited human stem cells, differentiated to motor neurons, and in neuronal tissues from a 5'ss SNV knock-in mouse, which showed the same result. Moreover, the survival of representative 3' splice site, 5'ss, and truncated C-term variant KIF5A (v-KIF5A) motor neurons was severely reduced compared with wild-type motor neurons, and overt morphological changes were apparent. While the total KIF5A mRNA levels were comparable across the cell lines, the total KIF5A protein levels were decreased for v-KIF5A lines, suggesting an impairment of protein synthesis or stability. Thus, despite the heterogeneous effect on ribonucleic acid splicing, KIF5A SNVs similarly reduce the availability of the KIF5A protein, leading to axonal transport defects and motor neuron pathology.

Mutations Causing X-Linked Amelogenesis Imperfecta Alter miRNA Formation from Amelogenin Exon4

Amelogenin plays a crucial role in tooth enamel formation, and mutations on X-chromosomal amelogenin cause X-linked amelogenesis imperfecta (AI). Amelogenin pre-messenger RNA (mRNA) is highly alternatively spliced, and during alternative splicing, exon4 is mostly skipped, leading to the formation of a microRNA (miR-exon4) that has been suggested to function in enamel and bone formation. While delivering the functional variation of amelogenin proteins, alternative splicing of exon4 is the decisive first step to producing miR-exon4. However, the factors that regulate the splicing of exon4 are not well understood. This study aimed to investigate the association between known mutations in exon4 and exon5 of X chromosome amelogenin that causes X-linked AI, the splicing of exon4, and miR-exon4 formation. Our results showed mutations in exon4 and exon5 of the amelogenin gene, including c.120T>C, c.152C>T, c.155C>G, and c.155delC, significantly affected the splicing of exon4 and subsequent miR-exon4 production. Using an amelogenin minigene transfected in HEK-293 cells, we observed increased inclusion of exon4 in amelogenin mRNA and reduced miR-exon4 production with these mutations. In silico analysis predicted that Ser/Arg-rich RNA splicing factor (SRSF) 2 and SRSF5 were the regulatory factors for exon4 and exon5 splicing, respectively. Electrophoretic mobility shift assay confirmed that SRSF2 binds to exon4 and SRSF5 binds to exon5, and mutations in each exon can alter SRSF binding. Transfection of the amelogenin minigene to LS8 ameloblastic cells suppressed expression of the known miR-exon4 direct targets, Nfia and Prkch, related to multiple pathways. Given the mutations on the minigene, the expression of Prkch has been significantly upregulated with c.155C>G and c.155delC mutations. Together, we confirmed that exon4 splicing is critical for miR-exon4 production, and mutations causing X-linked AI in exon4 and exon5 significantly affect exon4 splicing and following miR-exon4 production. The change in miR-exon4 would be an additional etiology of enamel defects seen in some X-linked AI.

Splicing defects in rare diseases: transcriptomics and machine learning strategies towards genetic diagnosis

Genomic variants affecting pre-messenger RNA splicing and its regulation are known to underlie many rare genetic diseases. However, common workflows for genetic diagnosis and clinical variant interpretation frequently overlook splice-altering variants. To better serve patient populations and advance biomedical knowledge, it has become increasingly important to develop and refine approaches for detecting and interpreting pathogenic splicing variants. In this review, we will summarize a few recent developments and challenges in using RNA sequencing technologies for rare disease investigation. Moreover, we will discuss how recent computational splicing prediction tools have emerged as complementary approaches for revealing disease-causing variants underlying splicing defects. We speculate that continuous improvements to sequencing technologies and predictive modeling will not only expand our understanding of splicing regulation but also bring us closer to filling the diagnostic gap for rare disease patients.

Deep screening of proximal and distal splicing-regulatory elements in a native sequence context

Pre-mRNA splicing, a key process in gene expression, can be therapeutically modulated using various drug modalities, including antisense oligonucleotides (ASOs). However, determining promising targets is impeded by the challenge of systematically mapping splicing-regulatory elements (SREs) in their native sequence context. Here, we use the catalytically dead CRISPR-RfxCas13d RNA-targeting system (dCas13d/gRNA) as a programmable platform to bind SREs and modulate splicing by competing against endogenous splicing factors. SpliceRUSH, a high-throughput screening method, was developed to map SREs in any gene of interest using a lentivirus gRNA library that tiles the genetic region, including distal intronic sequences. When applied to SMN2, a therapeutic target for spinal muscular atrophy, SpliceRUSH robustly identified not only known SREs, but also a novel distal intronic splicing enhancer, which can be targeted to alter exon 7 splicing using either dCas13d/gRNA or ASOs. This technology enables a deeper understanding of splicing regulation with applications for RNA-based drug discovery.

MicroRNA-Mediated Obstruction of Stem-loop Alternative Splicing (MIMOSAS): a global mechanism for the regulation of alternative splicing

While RNA secondary structures are critical to regulate alternative splicing of long-range pre-mRNA, the factors that modulate RNA structure and interfere with the recognition of the splice sites are largely unknown. Previously, we identified a small, non-coding microRNA that sufficiently affects stable stem structure formation of Nmnat pre-mRNA to regulate the outcomes of alternative splicing. However, the fundamental question remains whether such microRNA-mediated interference with RNA secondary structures is a global molecular mechanism for regulating mRNA splicing. We designed and refined a bioinformatic pipeline to predict candidate microRNAs that potentially interfere with pre-mRNA stem-loop structures, and experimentally verified splicing predictions of three different long-range pre-mRNAs in the Drosophila model system. Specifically, we observed that microRNAs can either disrupt or stabilize stem-loop structures to influence splicing outcomes. Our study suggests that MicroRNA-Mediated Obstruction of Stem-loop Alternative Splicing (MIMOSAS) is a novel regulatory mechanism for the transcriptome-wide regulation of alternative splicing, increases the repertoire of microRNA function and further indicates cellular complexity of post-transcriptional regulation.

MicroRNA-Mediated Obstruction of Stem-loop Alternative Splicing (MIMOSAS): a global mechanism for the regulation of alternative splicing

While RNA secondary structures are critical to regulate alternative splicing of long-range pre-mRNA, the factors that modulate RNA structure and interfere with the recognition of the splice sites are largely unknown. Previously, we identified a small, non-coding microRNA that sufficiently affects stable stem structure formation of Nmnat pre-mRNA to regulate the outcomes of alternative splicing. However, the fundamental question remains whether such microRNA-mediated interference with RNA secondary structures is a global molecular mechanism for regulating mRNA splicing. We designed and refined a bioinformatic pipeline to predict candidate microRNAs that potentially interfere with pre-mRNA stem-loop structures, and experimentally verified splicing predictions of three different long-range pre-mRNAs in the Drosophila model system. Specifically, we observed that microRNAs can either disrupt or stabilize stem-loop structures to influence splicing outcomes. Our study suggests that MicroRNA-Mediated Obstruction of Stem-loop Alternative Splicing (MIMOSAS) is a novel regulatory mechanism for the transcriptome-wide regulation of alternative splicing, increases the repertoire of microRNA function and further indicates cellular complexity of post-transcriptional regulation.

One-Sentence Summary

MicroRNA-Mediated Obstruction of Stem-loop Alternative Splicing (MIMOSAS) is a novel regulatory mechanism for the transcriptome-wide regulation of alternative splicing.

The Role of Splicing Factors in Adipogenesis and Thermogenesis

Obesity is a significant global health risk that can cause a range of serious metabolic problems, such as type 2 diabetes and cardiovascular diseases. Adipose tissue plays a pivotal role in regulating energy and lipid storage. New research has underlined the crucial role of splicing factors in the physiological and functional regulation of adipose tissue. By generating multiple transcripts from a single gene, alternative splicing allows for a greater diversity of the proteome and transcriptome, which subsequently influence adipocyte development and metabolism. In this review, we provide an outlook on the part of splicing factors in adipogenesis and thermogenesis, and investigate how the different spliced isoforms can affect the development and function of adipose tissue.

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

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

Benchmarking splice variant prediction algorithms using massively parallel splicing assays

Background

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

Results

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

Conclusion

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

ZCCHC17 modulates neuronal RNA splicing and supports cognitive resilience in Alzheimer's disease

ZCCHC17 is a putative master regulator of synaptic gene dysfunction in Alzheimer's Disease (AD), and ZCCHC17 protein declines early in AD brain tissue, before significant gliosis or neuronal loss. Here, we investigate the function of ZCCHC17 and its role in AD pathogenesis. Co-immunoprecipitation of ZCCHC17 followed by mass spectrometry analysis in human iPSC-derived neurons reveals that ZCCHC17's binding partners are enriched for RNA splicing proteins. ZCCHC17 knockdown results in widespread RNA splicing changes that significantly overlap with splicing changes found in AD brain tissue, with synaptic genes commonly affected. ZCCHC17 expression correlates with cognitive resilience in AD patients, and we uncover an APOE4 dependent negative correlation of ZCCHC17 expression with tangle burden. Furthermore, a majority of ZCCHC17 interactors also co-IP with known tau interactors, and we find significant overlap between alternatively spliced genes in ZCCHC17 knockdown and tau overexpression neurons. These results demonstrate ZCCHC17's role in neuronal RNA processing and its interaction with pathology and cognitive resilience in AD, and suggest that maintenance of ZCCHC17 function may be a therapeutic strategy for preserving cognitive function in the setting of AD pathology.

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.

Genetic diagnosis of Duchenne and Becker muscular dystrophy through mRNA analysis: new splicing events

Background

Up to 7% of patients with Duchenne muscular dystrophy (DMD) or Becker muscular dystrophy (BMD) remain genetically undiagnosed after routine genetic testing. These patients are thought to carry deep intronic variants, structural variants or splicing alterations not detected through multiplex ligation-dependent probe amplification or exome sequencing.

Methods

RNA was extracted from seven muscle biopsy samples of patients with genetically undiagnosed DMD/BMD after routine genetic diagnosis. RT-PCR of theDMDgene was performed to detect the presence of alternative transcripts. Droplet digital PCR and whole-genome sequencing were also performed in some patients.

Results

We identified an alteration in the mRNA level in all the patients. We detected three pseudoexons inDMDcaused by deep intronic variants, two of them not previously reported. We also identified a chromosomal rearrangement between Xp21.2 and 8p22. Furthermore, we detected three exon skipping events with unclear pathogenicity.

Conclusion

These findings indicate that mRNA analysis of theDMDgene is a valuable tool to reach a precise genetic diagnosis in patients with a clinical and anatomopathological suspicion of dystrophinopathy that remain genetically undiagnosed after routine genetic testing.

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.

Mechanism and modeling of human disease-associated near-exon intronic variants that perturb RNA splicing

It is estimated that 10%-30% of disease-associated genetic variants affect splicing. Splicing variants may generate deleteriously altered gene product and are potential therapeutic targets. However, systematic diagnosis or prediction of splicing variants is yet to be established, especially for the near-exon intronic splice region. The major challenge lies in the redundant and ill-defined branch sites and other splicing motifs therein. Here, we carried out unbiased massively parallel splicing assays on 5,307 disease-associated variants that overlapped with branch sites and collected 5,884 variants across the 5' splice region. We found that strong splice sites and exonic features preserve splicing from intronic sequence variation. Whereas the splice-altering mechanism of the 3' intronic variants is complex, that of the 5' is mainly splice-site destruction. Statistical learning combined with these molecular features allows precise prediction of altered splicing from an intronic variant. This statistical model provides the identity and ranking of biological features that determine splicing, which serves as transferable knowledge and out-performs the benchmarking predictive tool. Moreover, we demonstrated that intronic splicing variants may associate with disease risks in the human population. Our study elucidates the mechanism of splicing response of intronic variants, which classify disease-associated splicing variants for the promise of precision medicine.

Role of computational and structural biology in the development of small-molecule modulators of the spliceosome

INTRODUCTION

RNA splicing is a pivotal step of eukaryotic gene expression during which the introns are excised from the precursor (pre-)RNA and the exons are joined together to form mature RNA products (i.e a protein-coding mRNA or long non-coding (lnc)RNAs). The spliceosome, a complex ribonucleoprotein machine, performs pre-RNA splicing with extreme precision. Deregulated splicing is linked to cancer, genetic, and neurodegenerative diseases. Hence, the discovery of small-molecules targeting core spliceosome components represents an appealing therapeutic opportunity.

AREA COVERED

Several atomic-level structures of the spliceosome and distinct splicing-modulators bound to its protein/RNA components have been solved. Here, we review recent advances in the discovery of small-molecule splicing-modulators, discuss opportunities and challenges for their therapeutic applicability, and showcase how structural data and/or all-atom simulations can illuminate key facets of their mechanism, thus contributing to future drug-discovery campaigns.

EXPERT OPINION

This review highlights the potential of modulating pre-RNA splicing with small-molecules, and anticipates how the synergy of computer and wet-lab experiments will enrich our understanding of splicing regulation/deregulation mechanisms. This information will aid future structure-based drug-discovery efforts aimed to expand the currently limited portfolio of selective splicing-modulators.

Genetic analysis of human RNA binding motif protein 48 (RBM48) reveals an essential role in U12-type intron splicing

U12-type or minor introns are found in most multicellular eukaryotes and constitute ∼0.5% of all introns in species with a minor spliceosome. Although the biological significance for the evolutionary conservation of U12-type introns is debated, mutations disrupting U12 splicing cause developmental defects in both plants and animals. In human hematopoietic stem cells, U12 splicing defects disrupt proper differentiation of myeloid lineages and are associated with myelodysplastic syndrome, predisposing individuals to acute myeloid leukemia. Mutants in the maize ortholog of RNA binding motif protein 48 (RBM48) have aberrant U12-type intron splicing. Human RBM48 was recently purified biochemically as part of the minor spliceosome and shown to recognize the 5' end of the U6atac snRNA. In this report, we use CRISPR/Cas9-mediated ablation of RBM48 in human K-562 cells to show the genetic function of RBM48. RNA-seq analysis comparing wild-type and mutant K-562 genotypes found that 48% of minor intron-containing genes have significant U12-type intron retention in RBM48 mutants. Comparing these results to maize rbm48 mutants defined a subset of minor intron-containing genes disrupted in both species. Mutations in the majority of these orthologous minor intron-containing genes have been reported to cause developmental defects in both plants and animals. Our results provide genetic evidence that the primary defect of human RBM48 mutants is aberrant U12-type intron splicing, while a comparison of human and maize RNA-seq data identifies candidate genes likely to mediate mutant phenotypes of U12-type splicing defects.

Performance evaluation of differential splicing analysis methods and splicing analytics platform construction

A proportion of previously defined benign variants or variants of uncertain significance in humans, which are challenging to identify, may induce an abnormal splicing process. An increasing number of methods have been developed to predict splicing variants, but their performance has not been completely evaluated using independent benchmarks. Here, we manually sourced ∼50 000 positive/negative splicing variants from > 8000 studies and selected the independent splicing variants to evaluate the performance of prediction methods. These methods showed different performances in recognizing splicing variants in donor and acceptor regions, reminiscent of different weight coefficient applications to predict novel splicing variants. Of these methods, 66.67% exhibited higher specificities than sensitivities, suggesting that more moderate cut-off values are necessary to distinguish splicing variants. Moreover, the high correlation and consistent prediction ratio validated the feasibility of integration of the splicing prediction method in identifying splicing variants. We developed a splicing analytics platform called SPCards, which curates splicing variants from publications and predicts splicing scores of variants in genomes. SPCards also offers variant-level and gene-level annotation information, including allele frequency, non-synonymous prediction and comprehensive functional information. SPCards is suitable for high-throughput genetic identification of splicing variants, particularly those located in non-canonical splicing regions.

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.

High-Risk Human Papillomavirus Oncogenic E6/E7 mRNAs Splicing Regulation

High-risk human papillomavirus infection may develop into a persistent infection that is highly related to the progression of various cancers, including cervical cancer and head and neck squamous cell carcinomas. The most common high-risk subtypes are HPV16 and HPV18. The oncogenic viral proteins expressed by high-risk HPVs E6/E7 are tightly involved in cell proliferation, differentiation, and cancerous transformation since E6/E7 mRNAs are derived from the same pre-mRNA. Hence, the alternative splicing in the E6/E7-coding region affects the balance of the E6/E7 expression level. Interrupting the balance of E6 and E7 levels results in cell apoptosis. Therefore, it is crucial to understand the regulation of E6/E7 splice site selection and the interaction of splicing enhancers and silencers with cellular splicing factors. In this review, we concluded the relationship of different E6/E7 transcripts with cancer progression, the known splicing sites, and the identified cis-regulatory elements within high-risk HPV E6/E7-coding region. Finally, we also reviewed the role of various splicing factors in the regulation of high-risk HPV oncogenic E6/E7 mRNA splicing.

Carnosol, a diterpene present in rosemary, increases ELP1 levels in familial Dysautonomia (FD) patient-derived cells and healthy adults: a possible therapy for FD

Recent research on Familial Dysautonomia (FD) has focused on the development of therapeutics that facilitate the production of the correctly spliced, exon 20-containing, transcript in cells and individuals bearing the splice-altering, FD-causing, mutation in the ELP1 gene. We report here the ability of carnosol, a diterpene present in plant species of the Lamiaceae family, including rosemary, to enhance the cellular presence of the correctly spliced ELP1 transcript in FD patient-derived fibroblasts by upregulating transcription of the ELP1 gene and correcting the aberrant splicing of the ELP1 transcript. Carnosol treatment also elevates the level of the RBM24 and RBM38 proteins., two multifunctional RNA binding proteins. Transfection-mediated expression of either of these RBMs facilitates the inclusion of exon 20 sequence into the transcript generated from a minigene bearing ELP1 genomic sequence containing the FD-causing mutation. Suppression of the carnosol-mediated induction of either of these RBMs, using targeting siRNAs, limited the carnosol-mediated inclusion of the ELP1 exon 20 sequence. Carnosol treatment of FD patient PBMCs facilitates the inclusion of exon 20 into the ELP1 transcript. Increased levels of the ELP1 and RBM38 transcripts and the alternative splicing of the SIRT2 transcript, a sentinel for exon 20 inclusion in the FD-derived ELP1 transcript, are observed in RNA isolated from whole blood of healthy adults following the ingestion of carnosol-containing rosemary extract. These findings and the excellent safety profile of rosemary together justify an expedited clinical study of the impact of carnosol on the FD patient population.

Therapeutic RNA-silencing oligonucleotides in metabolic diseases

Recent years have seen unprecedented activity in the development of RNA-silencing oligonucleotide therapeutics for metabolic diseases. Improved oligonucleotide design and optimization of synthetic nucleic acid chemistry, in combination with the development of highly selective and efficient conjugate delivery technology platforms, have established and validated oligonucleotides as a new class of drugs. To date, there are five marketed oligonucleotide therapies, with many more in clinical studies, for both rare and common liver-driven metabolic diseases. Here, we provide an overview of recent developments in the field of oligonucleotide therapeutics in metabolism, review past and current clinical trials, and discuss ongoing challenges and possible future developments.

Characterization of Synonymous BRCA1:c.132C>T as a Pathogenic Variant

Breast cancer gene 1 (BRCA1) and BRCA2 are tumor suppressors involved in DNA damage response and repair. Carriers of germline pathogenic or likely pathogenic variants in BRCA1 or BRCA2 have significantly increased lifetime risks of breast cancer, ovarian cancer, and other cancer types; this phenomenon is known as hereditary breast and ovarian cancer (HBOC) syndrome. Accurate interpretation of BRCA1 and BRCA2 variants is important not only for disease management in patients, but also for determining preventative measures for their families. BRCA1:c.132C>T (p.Cys44=) is a synonymous variant recorded in the ClinVar database with “conflicting interpretations of its pathogenicity”. Here, we report our clinical tests in which we identified this variant in two unrelated patients, both of whom developed breast cancer at an early age with ovarian presentation a few years later and had a family history of relevant cancers. Minigene assay showed that this change caused a four-nucleotide loss at the end of exon 3, resulting in a truncated p.Cys44Tyrfs*5 protein. Reverse transcription-polymerase chain reaction identified two fragments (123 and 119 bp) using RNA isolated from patient blood samples, in consistency with the results of the minigene assay. Collectively, we classified BRCA1:c.132C>T (p.Cys44=) as a pathogenic variant, as evidenced by functional studies, RNA analysis, and the patients’ family histories. By analyzing variants recorded in the BRCA Exchange database, we found synonymous changes at the ends of exons could potentially influence splicing; meanwhile, current in silico tools could not predict splicing changes efficiently if the variants were in the middle of an exon, or in the deep intron region. Future studies should attempt to identify variants that influence gene expression and post-transcription modifications to improve our understanding of BRCA1 and BRCA2, as well as their related cancers.

Modeling Splicing Variants Amenable to Antisense Therapy by Use of CRISPR-Cas9-Based Gene Editing in HepG2 Cells

The field of splice modulating RNA therapy has gained new momentum with FDA approved antisense-based drugs for several rare diseases. In vitro splicing assays with minigenes or patient-derived cells are commonly employed for initial preclinical testing of antisense oligonucleotides aiming to modulate splicing. However, minigenes do not include the full genomic context of the exons under study and patients' samples are not always available, especially if the gene is expressed solely in certain tissues (e.g. liver or brain). This is the case for specific inherited metabolic diseases such as phenylketonuria (PKU) caused by mutations in the liver-expressed PAH gene.Herein we describe the generation of mutation-specific hepatic cellular models of PKU using CRISPR/Cas9 system, which is a versatile and easy-to-use gene editing tool. We describe in detail the selection of the appropriate cell line, guidelines for design of RNA guides and donor templates, transfection procedures and growth and selection of single-cell colonies with the desired variant , which should result in the accurate recapitulation of the splicing defect.

Autosomal dominant optic atrophy: A novel treatment for OPA1 splice defects using U1 snRNA adaption

Autosomal dominant optic atrophy (ADOA) is frequently caused by mutations in the optic atrophy 1 (OPA1) gene, with haploinsufficiency being the major genetic pathomechanism. Almost 30% of the OPA1-associated cases suffer from splice defects. We identified a novel OPA1 mutation, c.1065+5G>A, in patients with ADOA. In patient-derived fibroblasts, the mutation led to skipping of OPA1 exon 10, reducing the OPA1 protein expression by approximately 50%. We developed a molecular treatment to correct the splice defect in OPA1 using engineered U1 splice factors retargeted to different locations in OPA1 exon 10 or intron 10. The strongest therapeutic effect was detected when U1 binding was engineered to bind to intron 10 at position +18, a position predicted by bioinformatics to be a promising binding site. We were able to significantly silence the effect of the mutation (skipping of exon 10) and simultaneously increase the expression level of normal transcripts. Retargeting U1 to the canonical splice donor site did not lead to a detectable splice correction. This proof-of-concept study indicates for the first time the feasibility of splice mutation correction as a treatment option for ADOA. Increasing the amount of correctly spliced OPA1 transcripts may suffice to overcome the haploinsufficiency.

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.

Evidence in disease and non-disease contexts that nonsense mutations cause altered splicing via motif disruption

Transcripts containing premature termination codons (PTCs) can be subject to nonsense-associated alternative splicing (NAS). Two models have been evoked to explain this, scanning and splice motif disruption. The latter postulates that exonic cis motifs, such as exonic splice enhancers (ESEs), are disrupted by nonsense mutations. We employ genome-wide transcriptomic and k-mer enrichment methods to scrutinize this model. First, we show that ESEs are prone to disruptive nonsense mutations owing to their purine richness and paucity of TGA, TAA and TAG. The motif model correctly predicts that NAS rates should be low (we estimate 5–30%) and approximately in line with estimates for the rate at which random point mutations disrupt splicing (8–20%). Further, we find that, as expected, NAS-associated PTCs are predictable from nucleotide-based machine learning approaches to predict splice disruption and, at least for pathogenic variants, are enriched in ESEs. Finally, we find that both in and out of frame mutations to TAA, TGA or TAG are associated with exon skipping. While a higher relative frequency of such skip-inducing mutations in-frame than out of frame lends some credence to the scanning model, these results reinforce the importance of considering splice motif modulation to understand the etiology of PTC-associated disease.

Mutations at a split codon in the GTPase-encoding domain of OPA1 cause dominant optic atrophy through different molecular mechanisms

Exonic (i.e. coding) variants in genes associated with disease can exert pathogenic effects both at the protein and mRNA level, either by altering the amino acid sequence or by affecting pre-mRNA splicing. The latter is often neglected due to the lack of RNA analyses in genetic diagnostic testing. In this study we considered both pathomechanisms and performed a comprehensive analysis of nine exonic nucleotide changes in OPA1, which is the major gene underlying autosomal dominant optic atrophy (DOA) and is characterized by pronounced allelic heterogeneity. We focused on the GTPase-encoding domain of OPA1, which harbors most of the missense variants associated with DOA. Given that the consensus splice sites extend into the exons, we chose a split codon, namely codon 438, for our analyses. Variants at this codon are the second most common cause of disease in our large cohort of DOA patients harboring disease-causing variants in OPA1. In silico splice predictions, heterologous splice assays, analysis of patient’s RNA when available, and protein modeling revealed different molecular outcomes for variants at codon 438. The wildtype aspartate residue at amino acid position 438 is directly involved in the dimerization of OPA1 monomers. We found that six amino acid substitutions at codon 438 (i.e. all substitutions of the first and second nucleotide of the codon) destabilized dimerization while only substitutions of the first nucleotide of the codon caused exon skipping. Our study highlights the value of combining RNA analysis and protein modeling approaches to accurately assign patients to future precision therapies.

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.

Classification of MSH6 Variants of Uncertain Significance Using Functional Assays

Lynch syndrome (LS) is one of the most common hereditary cancer predisposition syndromes worldwide. Individuals with LS have a high risk of developing colorectal or endometrial cancer, as well as several other cancers. LS is caused by autosomal dominant pathogenic variants in one of the DNA mismatch repair (MMR) genes MLH1, MSH2, PMS2 or MSH6, and typically include truncating variants, such as frameshift, nonsense or splicing variants. However, a significant number of missense, intronic, or silent variants, or small in-frame insertions/deletions, are detected during genetic screening of the MMR genes. The clinical effects of these variants are often more difficult to predict, and a large fraction of these variants are classified as variants of uncertain significance (VUS). It is pivotal for the clinical management of LS patients to have a clear genetic diagnosis, since patients benefit widely from screening, preventive and personal therapeutic measures. Moreover, in families where a pathogenic variant is identified, testing can be offered to family members, where non-carriers can be spared frequent surveillance, while carriers can be included in cancer surveillance programs. It is therefore important to reclassify VUSs, and, in this regard, functional assays can provide insight into the effect of a variant on the protein or mRNA level. Here, we briefly describe the disorders that are related to MMR deficiency, as well as the structure and function of MSH6. Moreover, we review the functional assays that are used to examine VUS identified in MSH6 and discuss the results obtained in relation to the ACMG/AMP PS3/BS3 criterion. We also provide a compiled list of the MSH6 variants examined by these assays. Finally, we provide a future perspective on high-throughput functional analyses with specific emphasis on the MMR genes.

Isoform Age - Splice Isoform Profiling Using Long-Read Technologies

Alternative splicing (AS) of RNA is a key mechanism that results in the expression of multiple transcript isoforms from single genes and leads to an increase in the complexity of both the transcriptome and proteome. Regulation of AS is critical for the correct functioning of many biological pathways, while disruption of AS can be directly pathogenic in diseases such as cancer or cause risk for complex disorders. Current short-read sequencing technologies achieve high read depth but are limited in their ability to resolve complex isoforms. In this review we examine how long-read sequencing (LRS) technologies can address this challenge by covering the entire RNA sequence in a single read and thereby distinguish isoform changes that could impact RNA regulation or protein function. Coupling LRS with technologies such as single cell sequencing, targeted sequencing and spatial transcriptomics is producing a rapidly expanding suite of technological approaches to profile alternative splicing at the isoform level with unprecedented detail. In addition, integrating LRS with genotype now allows the impact of genetic variation on isoform expression to be determined. Recent results demonstrate the potential of these techniques to elucidate the landscape of splicing, including in tissues such as the brain where AS is particularly prevalent. Finally, we also discuss how AS can impact protein function, potentially leading to novel therapeutic targets for a range of diseases.

Assessing conservation of alternative splicing with evolutionary splicing graphs

Understanding how protein function has evolved and diversified is of great importance for human genetics and medicine. Here, we tackle the problem of describing the whole transcript variability observed in several species by generalizing the definition of splicing graph. We provide a practical solution to construct parsimonious evolutionary splicing graphs where each node is a minimal transcript building block defined across species. We show a clear link between the functional relevance, tissue regulation, and conservation of alternative transcripts on a set of 50 genes. By scaling up to the whole human protein-coding genome, we identify a few thousand genes where alternative splicing modulates the number and composition of pseudorepeats. We have implemented our approach in ThorAxe, an efficient, versatile, robust, and freely available computational tool.

IntSplice2: Prediction of the Splicing Effects of Intronic Single-Nucleotide Variants Using LightGBM Modeling

Prediction of the effect of a single-nucleotide variant (SNV) in an intronic region on aberrant pre-mRNA splicing is challenging except for an SNV affecting the canonical GU/AG splice sites (ss). To predict pathogenicity of SNVs at intronic positions −50 (Int-50) to −3 (Int-3) close to the 3’ ss, we developed light gradient boosting machine (LightGBM)-based IntSplice2 models using pathogenic SNVs in the human gene mutation database (HGMD) and ClinVar and common SNVs in dbSNP with 0.01 ≤ minor allelic frequency (MAF) < 0.50. The LightGBM models were generated using features representing splicing cis-elements. The average recall/sensitivity and specificity of IntSplice2 by fivefold cross-validation (CV) of the training dataset were 0.764 and 0.884, respectively. The recall/sensitivity of IntSplice2 was lower than the average recall/sensitivity of 0.800 of IntSplice that we previously made with support vector machine (SVM) modeling for the same intronic positions. In contrast, the specificity of IntSplice2 was higher than the average specificity of 0.849 of IntSplice. For benchmarking (BM) of IntSplice2 with IntSplice, we made a test dataset that was not used to train IntSplice. After excluding the test dataset from the training dataset, we generated IntSplice2-BM and compared it with IntSplice using the test dataset. IntSplice2-BM was superior to IntSplice in all of the seven statistical measures of accuracy, precision, recall/sensitivity, specificity, F1 score, negative predictive value (NPV), and matthews correlation coefficient (MCC). We made the IntSplice2 web service at https://www.med.nagoya-u.ac.jp/neurogenetics/IntSplice2.

A Novel Noncanonical Splicing Mutation of ANOS1 Gene in Siblings with Kallmann Syndrome Identified by Whole-Exome Sequencing

Kallmann syndrome (KS) is a rare genetic disorder that is characterized by idiopathic hypogonadotropic hypogonadism associated with anosmia. Genetic variants in ANOS1 gene are the most common mutations associated with X-linked recessive form of KS. Canonical ± 1 or 2 splice site variants in ANOS1 have been described to be responsible for KS. Here, we identified a novel noncanonical splice site variant (c.1062+4T>C) in ANOS1 gene in two siblings with KS by whole-exome sequencing (WES). Sanger sequencing showed this mutation was inherited from their mother, whose brother was a KS patient as well. Through the functional assay in vitro, we found that this mutation resulted in a 50-bp deletion of exon 7, which caused frameshift mutation leading to a premature termination of translation and a truncated anosmin-1 protein. Our results revealed that this noncanonical splice site variant is involved in KS. Thus, it is suggested that we should pay attention to the noncanonical splice site variants when using molecular genetic diagnostics of KS.

Functional Evaluation of Splicing for Variants of Uncertain Significance in Patients with Inherited Retinal Diseases

Inherited retinal diseases (IRD) comprise a heterogeneous set of clinical and genetic disorders that lead to blindness. Given the emerging opportunities in precision medicine and gene therapy, it has become increasingly important to determine whether DNA variants with uncertain significance (VUS) are responsible for patients’ IRD. This research was performed to assess the functional consequence of six VUS identified in patients with IRD. Clinical assessments included an ophthalmic examination, best-corrected visual acuity, and kinetic perimetry. Imaging was acquired with the Optos ultra-widefield camera and spectral domain optical coherence tomography (SD-OCT). Genetic testing was performed by Molecular Vision Laboratories. VUS that were predicted to alter splicing were analyzed with a minigene assay, which revealed that VUS in the genes OPA1, CNGB1, and CLUAP1 altered spicing mechanisms. Due to emerging gene and cell therapies, these results expand the genotype-phenotype correlations for patients diagnosed with an IRD.

A patient-based model of RNA mis-splicing uncovers treatment targets in Parkinson's disease

Parkinson's disease (PD) is a heterogeneous neurodegenerative disorder with monogenic forms representing prototypes of the underlying molecular pathology and reproducing to variable degrees the sporadic forms of the disease. Using a patient-based in vitro model of PARK7-linked PD, we identified a U1-dependent splicing defect causing a drastic reduction in DJ-1 protein and, consequently, mitochondrial dysfunction. Targeting defective exon skipping with genetically engineered U1-snRNA recovered DJ-1 protein expression in neuronal precursor cells and differentiated neurons. After prioritization of candidate drugs, we identified and validated a combinatorial treatment with the small-molecule compounds rectifier of aberrant splicing (RECTAS) and phenylbutyric acid, which restored DJ-1 protein and mitochondrial dysfunction in patient-derived fibroblasts as well as dopaminergic neuronal cell loss in mutant midbrain organoids. Our analysis of a large number of exomes revealed that U1 splice-site mutations were enriched in sporadic PD patients. Therefore, our study suggests an alternative strategy to restore cellular abnormalities in in vitro models of PD and provides a proof of concept for neuroprotection based on precision medicine strategies in PD.

Microexon alternative splicing of small GTPase regulators: Implication in central nervous system diseases

Microexons are small sized (≤51 bp) exons which undergo extensive alternative splicing in neurons, microglia, embryonic stem cells, and cancer cells, giving rise to cell type specific protein isoforms. Due to their small sizes, microexons provide a unique challenge for the splicing machinery. They frequently lack exon splicer enhancers/repressors and require specialized neighboring trans-regulatory and cis-regulatory elements bound by RNA binding proteins (RBPs) for their inclusion. The functional consequences of including microexons within mRNAs have been extensively documented in the central nervous system (CNS) and aberrations in their inclusion have been observed to lead to abnormal processes. Despite the increasing evidence for microexons impacting cellular physiology within CNS, mechanistic details illustrating their functional importance in diseases of the CNS is still limited. In this review, we discuss the unique characteristics of microexons, and how RBPs participate in regulating their inclusion and exclusion during splicing. We consider recent findings of microexon alternative splicing and their implication for regulating the function of small GTPases in the context of the microglia, and we extrapolate these findings to what is known in neurons. We further discuss the emerging evidence for dysregulation of the Rho GTPase pathway in CNS diseases and the consequences contributed by the mis-splicing of microexons. This article is categorized under: RNA Processing > Splicing Mechanisms RNA Processing > Splicing Regulation/Alternative Splicing RNA in Disease and Development > RNA in Disease.

Therapeutic Modulation of RNA Splicing in Malignant and Non-Malignant Disease

RNA splicing is the enzymatic process by which non-protein coding sequences are removed from RNA to produce mature protein-coding mRNA. Splicing is thereby a major mediator of proteome diversity as well as a dynamic regulator of gene expression. Genetic alterations disrupting splicing of individual genes or altering the function of splicing factors contribute to a wide range of human genetic diseases as well as cancer. These observations have resulted in the development of therapies based on oligonucleotides that bind to RNA sequences and modulate splicing for therapeutic benefit. In parallel, small molecules that bind to splicing factors to alter their function or modify RNA processing of individual transcripts are being pursued for monogenic disorders as well as for cancer.