Hotspot exons are common targets of splicing perturbations

One-Size-Fits-Many: Antisense oligonucleotides for rescuing splicing mutations in hotspot exons

Mutations that impact splicing play a significant role in disease etiology but are not fully understood. To characterize the impact of exonic variants on splicing in 71 clinically-actionable disease genes in asymptomatic people, we analyzed 32,112 exonic mutations from ClinVar and Geisinger MyCode using a minigene reporter assay. We identify 1,733 splice-disrupting mutations, of which the most extreme 1-2% of variants are likely to be deleterious. We report that these variants are not distributed evenly across exons but are mostly concentrated in the ∼8% of exons that are most susceptible to splicing mutations (i.e. hotspot exons). We demonstrate that splicing defects in these exons can be reverted by ASOs targeting the splice sites of either their upstream or downstream flanking exons. This finding supports the feasibility of developing single therapeutic ASOs that could revert all splice-altering variants localized to a particular exon.

Decoding biology with massively parallel reporter assays and machine learning

Massively parallel reporter assays (MPRAs) are powerful tools for quantifying the impacts of sequence variation on gene expression. Reading out molecular phenotypes with sequencing enables interrogating the impact of sequence variation beyond genome scale. Machine learning models integrate and codify information learned from MPRAs and enable generalization by predicting sequences outside the training data set. Models can provide a quantitative understanding of cis-regulatory codes controlling gene expression, enable variant stratification, and guide the design of synthetic regulatory elements for applications from synthetic biology to mRNA and gene therapy. This review focuses on cis-regulatory MPRAs, particularly those that interrogate cotranscriptional and post-transcriptional processes: alternative splicing, cleavage and polyadenylation, translation, and mRNA decay.

Long-read RNA-seq demarcates cis- and trans-directed alternative RNA splicing

Genetic regulation of alternative splicing constitutes an important link between genetic variation and disease. Nonetheless, RNA splicing is regulated by both cis-acting elements and trans-acting splicing factors. Determining splicing events that are directed primarily by the cis- or trans-acting mechanisms will greatly inform our understanding of the genetic basis of disease. Here, we show that long-read RNA-seq, combined with our new method isoLASER, enables a clear segregation of cis- and trans-directed splicing events for individual samples. The genetic linkage of splicing is largely individual-specific, in stark contrast to the tissue-specific pattern of splicing profiles. Analysis of long-read RNA-seq data from human and mouse revealed thousands of cis-directed splicing events susceptible to genetic regulation. We highlight such events in the HLA genes whose analysis was challenging with short-read data. We also highlight novel cis-directed splicing events in Alzheimer's disease-relevant genes such as MAPT and BIN1. Together, the clear demarcation of cis- and trans-directed splicing paves ways for future studies of the genetic basis of disease.

Quantifying negative selection on synonymous variants

Widespread adoption of DNA sequencing has resulted in large numbers of genetic variants, whose contribution to disease is not easily determined. Although many types of variation are known to disrupt cellular processes in predictable ways, for some categories of variants, the effects may not be directly detectable. A particular example is synonymous variants, that is, those single-nucleotide variants that create a codon substitution, such that the produced amino acid sequence is unaffected. Contrary to the original theory suggesting that synonymous variants are benign, there is a growing volume of research showing that, despite their "silent" mechanism of action, some synonymous variation may be deleterious. Here, we studied the extent of the negative selective pressure acting on different classes of synonymous variants by analyzing the relative enrichment of synonymous singleton variants in the human exomes provided by gnomAD. Using a modification of the mutability-adjusted proportion of singletons (MAPS) metric as a measure of purifying selection, we found that some classes of synonymous variants are subject to stronger negative selection than others. For instance, variants that reduce codon optimality undergo stronger selection than optimality-increasing variants. Besides, selection affects synonymous variants implicated in splice-site-loss or splice-site-gain events. To understand what drives this negative selection, we tested a number of predictors in the aim to explain the variability in the selection scores. Our findings provide insights into the effects of synonymous variants at the population level, highlighting the specifics of the role that these variants play in health and disease.

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.

Large-scale functional screen identifies genetic variants with splicing effects in modern and archaic humans

Humans coexisted and interbred with other hominins which later became extinct. These archaic hominins are known to us only through fossil records and for two cases, genome sequences. Here, we engineer Neanderthal and Denisovan sequences into thousands of artificial genes to reconstruct the pre-mRNA processing patterns of these extinct populations. Of the 5,169 alleles tested in this massively parallel splicing reporter assay (MaPSy), we report 962 exonic splicing mutations that correspond to differences in exon recognition between extant and extinct hominins. Using MaPSy splicing variants, predicted splicing variants, and splicing quantitative trait loci, we show that splice-disrupting variants experienced greater purifying selection in anatomically modern humans than that in Neanderthals. Adaptively introgressed variants were enriched for moderate-effect splicing variants, consistent with positive selection for alternative spliced alleles following introgression. As particularly compelling examples, we characterized a unique tissue-specific alternative splicing variant at the adaptively introgressed innate immunity gene TLR1, as well as a unique Neanderthal introgressed alternative splicing variant in the gene HSPG2 that encodes perlecan. We further identified potentially pathogenic splicing variants found only in Neanderthals and Denisovans in genes related to sperm maturation and immunity. Finally, we found splicing variants that may contribute to variation among modern humans in total bilirubin, balding, hemoglobin levels, and lung capacity. Our findings provide unique insights into natural selection acting on splicing in human evolution and demonstrate how functional assays can be used to identify candidate causal variants underlying differences in gene regulation and phenotype.

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.

Rescue of blood coagulation Factor VIII exon-16 mis-splicing by antisense oligonucleotides

The human Factor VIII ( F8 ) protein is essential for the blood coagulation cascade and specific F8 mutations cause the rare bleeding disorder Hemophilia A (HA). Here, we investigated the impact of HA-causing single-nucleotide mutations on F8 pre-mRNA splicing. We found that 14/97 (∼14.4%) coding sequence mutations tested in our study induced exon skipping. Splicing patterns of 4/11 (∼36.4%) F8 exons tested were especially sensitive to the presence of common disease-causing mutations. RNA-chemical probing analyses revealed a three-way junction structure at the 3' end of intron 15 (TWJ-3-15). TWJ-3-15 sequesters the polypyrimidine tract, a key determinant of 3' splice site strength. Using exon-16 of the F8 gene as a model, we designed specific antisense oligonucleotides (ASOs) that target TWJ-3-15 and identified three that promote the splicing of F8 exon-16. Interaction of TWJ-3-15 with ASOs increases accessibility of the polypyrimidine tract and inhibits the binding of hnRNPA1-dependent splicing silencing factors. Moreover, ASOs targeting TWJ-3-15 rescue diverse splicing-sensitive HA-causing mutations, most of which are distal to the 3' splice site being impacted. The TWJ-3-15 structure and its effect on mRNA splicing provide a model for HA etiology in patients harboring specific F8 mutations and provide a framework for precision RNA-based HA therapies.

High-throughput mutagenesis identifies mutations and RNA-binding proteins controlling CD19 splicing and CART-19 therapy resistance

Following CART-19 immunotherapy for B-cell acute lymphoblastic leukaemia (B-ALL), many patients relapse due to loss of the cognate CD19 epitope. Since epitope loss can be caused by aberrant CD19 exon 2 processing, we herein investigate the regulatory code that controls CD19 splicing. We combine high-throughput mutagenesis with mathematical modelling to quantitatively disentangle the effects of all mutations in the region comprising CD19 exons 1-3. Thereupon, we identify ~200 single point mutations that alter CD19 splicing and thus could predispose B-ALL patients to developing CART-19 resistance. Furthermore, we report almost 100 previously unknown splice isoforms that emerge from cryptic splice sites and likely encode non-functional CD19 proteins. We further identify cis-regulatory elements and trans-acting RNA-binding proteins that control CD19 splicing (e.g., PTBP1 and SF3B4) and validate that loss of these factors leads to pervasive CD19 mis-splicing. Our dataset represents a comprehensive resource for identifying predictive biomarkers for CART-19 therapy.

Multiple alternative splicing events in CD19 mRNA have been associated with resistance/relapse to CD19 CAR-T therapy in patients with B cell malignancies. Here, by combining patient data and a high-throughput mutagenesis screen, the authors identify single point mutations and RNA-binding proteins that can control CD19 splicing and be associated with CD19 CAR-T therapy resistance.

Alternative splicing as a source of phenotypic diversity

A major goal of evolutionary genetics is to understand the genetic processes that give rise to phenotypic diversity in multicellular organisms. Alternative splicing generates multiple transcripts from a single gene, enriching the diversity of proteins and phenotypic traits. It is well established that alternative splicing contributes to key innovations over long evolutionary timescales, such as brain development in bilaterians. However, recent developments in long-read sequencing and the generation of high-quality genome assemblies for diverse organisms has facilitated comparisons of splicing profiles between closely related species, providing insights into how alternative splicing evolves over shorter timescales. Although most splicing variants are probably non-functional, alternative splicing is nonetheless emerging as a dynamic, evolutionarily labile process that can facilitate adaptation and contribute to species divergence.

A genetic screen in C. elegans reveals roles for KIN17 and PRCC in maintaining 5' splice site identity

Pre-mRNA splicing is an essential step of eukaryotic gene expression carried out by a series of dynamic macromolecular protein/RNA complexes, known collectively and individually as the spliceosome. This series of spliceosomal complexes define, assemble on, and catalyze the removal of introns. Molecular model snapshots of intermediates in the process have been created from cryo-EM data, however, many aspects of the dynamic changes that occur in the spliceosome are not fully understood. Caenorhabditis elegans follow the GU-AG rule of splicing, with almost all introns beginning with 5’ GU and ending with 3’ AG. These splice sites are identified early in the splicing cycle, but as the cycle progresses and “custody” of the pre-mRNA splice sites is passed from factor to factor as the catalytic site is built, the mechanism by which splice site identity is maintained or re-established through these dynamic changes is unclear. We performed a genetic screen in C. elegans for factors that are capable of changing 5’ splice site choice. We report that KIN17 and PRCC are involved in splice site choice, the first functional splicing role proposed for either of these proteins. Previously identified suppressors of cryptic 5’ splicing promote distal cryptic GU splice sites, however, mutations in KIN17 and PRCC instead promote usage of an unusual proximal 5’ splice site which defines an intron beginning with UU, separated by 1nt from a GU donor. We performed high-throughput mRNA sequencing analysis and found that mutations in PRCC, and to a lesser extent KIN17, changed alternative 5’ splice site usage at native sites genome-wide, often promoting usage of nearby non-consensus sites. Our work has uncovered both fine and coarse mechanisms by which the spliceosome maintains splice site identity during the complex assembly process.

Pre-messenger RNA splicing is an important regulator of eukaryotic gene expression, changing the content, frame, and functionality of both coding and non-coding transcripts. Our understanding of how the spliceosome chooses where to cut has focused on the initial identification of splice sites. However, our results suggest that the spliceosome also relies on other components in later steps to maintain the identity of the splice donor sites. We are currently in the midst of a “resolution revolution”, with ever-clearer cryo-EM snapshots of stalled complexes, allowing researchers to visualize moments in time in the splicing cycle. These models are illuminating, but do not always elucidate mechanistic functioning of a highly dynamic ribonucleoprotein complex. Therefore, our lab takes a complementary approach, using the power of genetics in a multicellular animal to gain functional insights into the spliceosome. Using a C.elegans genetic screen, we have found novel functional splicing roles for two proteins, KIN17 and PRCC. Mutations in PRCC in particular promote nearby alternative 5’ splice sites at native loci. This work improves our understanding of how the spliceosome maintains the identity of where to cut the pre-mRNA, and thus how genes are expressed and used in multicellular animals.