Assessment of branch point prediction tools to predict physiological branch points and their alteration by variants

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

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

DeepSplice: a deep learning approach for accurate prediction of alternative splicing events in the human genome

Alternative splicing (AS) is a crucial process in genetic information processing that generates multiple mRNA molecules from a single gene, producing diverse proteins. Accurate prediction of AS events is essential for understanding various physiological aspects, including disease progression and prognosis. Machine learning (ML) techniques have been widely employed in bioinformatics to address this challenge. However, existing models have limitations in capturing AS events in the presence of mutations and achieving high prediction performance. To overcome these limitations, this research presents deep splicing code (DSC), a deep learning (DL)-based model for AS prediction. The proposed model aims to improve predictive ability by investigating state-of-the-art techniques in AS and developing a DL model specifically designed to predict AS events accurately. The performance of the DSC model is evaluated against existing techniques, revealing its potential to enhance the understanding and predictive power of DL algorithms in AS. It outperforms other models by achieving an average AUC score of 92%. The significance of this research lies in its contribution to identifying functional implications and potential therapeutic targets associated with AS, with applications in genomics, bioinformatics, and biomedical research. The findings of this study have the potential to advance the field and pave the way for more precise and reliable predictions of AS events, ultimately leading to a deeper understanding of genetic information processing and its impact on human physiology and disease.

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 .

Familial cases with adult-onset FGF23-related hypophosphatemic osteomalacia -A PHEX 3'-UTR change as a possible cause

Excessive actions of FGF23 cause several kinds of hypophosphatemic rickets/osteomalacia. It is possible that there still remain unknown causes or mechanisms for FGF23-related hypophosphatemic diseases. We report two male cousins who had been suffering form FGF23-related hypophosphatemic osteomalacia. Sequencing of exons and exon-intron junctions of known causative genes for FGF23-related hypophosphatemic diseases and whole genome sequencing were conducted. Luciferase assay was used to evaluate the effect of a detected nucleotide change on mRNA stability. Two cousins showed hypophosphatemia with impaired proximal tubular phosphate reabsorption and high FGF23. Serum phosphate of their mothers was within the reference range. Exome sequencing of the proband detected no mutations. Whole genome sequencing of the patients and their mothers identified a nucleotide change in the 3'-UTR of phosphate-regulating gene with homologies to endopeptidases on the X chromosome (PHEX) gene (c.*1280_*1287dupGTGTGTGT) which is heterozygous in the mothers and hemizygous in the patients. While sixteen is the most prevalent number of GT repeats, this family had twenty repeats. Luciferase assay indicated that mRNA with 3'-UTR of PHEX with 20 GT repeats was more unstable than that with 16 repeats. Sequencing of exons and exon-intron junctions of known causative genes for FGF23-related hypophosphatemic diseases cannot identify all the genetic causes. Our results strongly suggest that changes of PHEX expression by a nucleotide change in the 3'-UTR is a novel mechanism of FGF23-related hypophosphatemic osteomalacia.

Exonic splicing code and coordination of divalent metals in proteins

Exonic sequences contain both protein-coding and RNA splicing information but the interplay of the protein and splicing code is complex and poorly understood. Here, we have studied traditional and auxiliary splicing codes of human exons that encode residues coordinating two essential divalent metals at the opposite ends of the Irving-Williams series, a universal order of relative stabilities of metal-organic complexes. We show that exons encoding Zn2+-coordinating amino acids are supported much less by the auxiliary splicing motifs than exons coordinating Ca2+. The handicap of the former is compensated by stronger splice sites and uridine-richer polypyrimidine tracts, except for position -3 relative to 3' splice junctions. However, both Ca2+ and Zn2+ exons exhibit close-to-constitutive splicing in multiple tissues, consistent with their critical importance for metalloprotein function and a relatively small fraction of expendable, alternatively spliced exons. These results indicate that constraints imposed by metal coordination spheres on RNA splicing have been efficiently overcome by the plasticity of exon-intron architecture to ensure adequate metalloprotein expression.

Variations of intronic branchpoint motif: identification and functional implications in splicing and disease

The branchpoint (BP) motif is an essential intronic element for spliceosomal pre-mRNA splicing. In mammals, its sequence composition, distance to the downstream exon, and number of BPs per 3´ splice site are highly variable, unlike the GT/AG dinucleotides at the intron ends. These variations appear to provide evolutionary advantages for fostering alternative splicing, satisfying more diverse cellular contexts, and promoting resilience to genetic changes, thus contributing to an extra layer of complexity for gene regulation. Importantly, variants in the BP motif itself or in genes encoding BP-interacting factors cause human genetic diseases or cancers, highlighting the critical function of BP motif and the need to precisely identify functional BPs for faithful interpretation of their roles in splicing. In this perspective, we will succinctly summarize the major findings related to BP motif variations, discuss the relevant issues/challenges, and provide our insights.

ABCA4 c.6480-35A>G, a novel branchpoint variant associated with Stargardt disease

Introduction: Inherited retinal dystrophies (IRDs) can be caused by variants in more than 280 genes. The ATP-binding cassette transporter type A4 (ABCA4) gene is one of these genes and has been linked to Stargardt disease type 1 (STGD1), fundus flavimaculatus, cone-rod dystrophy (CRD), and pan-retinal CRD. Approximately 25% of the reported ABCA4 variants affect RNA splicing. In most cases, it is necessary to perform a functional assay to determine the effect of these variants. Methods: Whole genome sequencing (WGS) was performed in one Spanish proband with Stargardt disease. The putative pathogenicity of c.6480-35A>G on splicing was investigated both in silico and in vitro. The in silico approach was based on the deep-learning tool SpliceAI. For the in vitro approach we used a midigene splice assay in HEK293T cells, based on a previously established wild-type midigene (BA29) containing ABCA4 exons 46 to 48. Results: Through the analysis of WGS data, we identified two candidate variants in ABCA4 in one proband: a previously described deletion, c.699_768+342del (p.(Gln234Phefs*5)), and a novel branchpoint variant, c.6480-35A>G. Segregation analysis confirmed that the variants were in trans. For the branchpoint variant, SpliceAI predicted an acceptor gain with a high score (0.47) at position c.6480-47. A midigene splice assay in HEK293T cells revealed the inclusion of the last 47 nucleotides of intron 47 creating a premature stop codon and allowed to categorize the variant as moderately severe. Subsequent analysis revealed the presence of this variant as a second allele besides c.1958G>A p.(Arg653His) in an additional Spanish proband in a large cohort of IRD cases. Conclusion: A splice-altering effect of the branchpoint variant, confirmed by the midigene splice assay, along with the identification of this variant in a second unrelated individual affected with STGD, provides sufficient evidence to classify the variant as likely pathogenic. In addition, this research highlights the importance of studying non-coding regions and performing functional assays to provide a conclusive molecular diagnosis.

Evidence-Based Guide to Using Artificial Introns for Tissue-Specific Knockout in Mice

Up until recently, methods for generating floxed mice either conventionally or by CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)-Cas9 (CRISPR-associated protein 9) editing have been technically challenging, expensive and error-prone, or time-consuming. To circumvent these issues, several labs have started successfully using a small artificial intron to conditionally knockout (KO) a gene of interest in mice. However, many other labs are having difficulty getting the technique to work. The key problem appears to be either a failure in achieving correct splicing after the introduction of the artificial intron into the gene or, just as crucial, insufficient functional KO of the gene's protein after Cre-induced removal of the intron's branchpoint. Presented here is a guide on how to choose an appropriate exon and where to place the recombinase-regulated artificial intron (rAI) in that exon to prevent disrupting normal gene splicing while maximizing mRNA degradation after recombinase treatment. The reasoning behind each step in the guide is also discussed. Following these recommendations should increase the success rate of this easy, new, and alternative technique for producing tissue-specific KO mice.

Genome-wide identification of tandem repeats associated with splicing variation across 49 tissues in humans

Tandem repeats (TRs) are one of the largest sources of polymorphism, and their length is associated with gene regulation. Although previous studies reported several tandem repeats regulating gene splicing in cis (spl-TRs), no large-scale study has been conducted. In this study, we established a genome-wide catalog of 9537 spl-TRs with a total of 58,290 significant TR-splicing associations across 49 tissues (false discovery rate 5%) by using Genotype-Tissue expression (GTex) Project data. Regression models explaining splicing variation by using spl-TRs and other flanking variants suggest that at least some of the spl-TRs directly modulate splicing. In our catalog, two spl-TRs are known loci for repeat expansion diseases, spinocerebellar ataxia 6 (SCA6) and 12 (SCA12). Splicing alterations by these spl-TRs were compatible with those observed in SCA6 and SCA12. Thus, our comprehensive spl-TR catalog may help elucidate the pathomechanism of genetic diseases.

All differential on the splicing front: Host alternative splicing alters the landscape of virus-host conflict

Alternative RNA splicing is a co-transcriptional process that richly increases proteome diversity, and is dynamically regulated based on cell species, lineage, and activation state. Virus infection in vertebrate hosts results in rapid host transcriptome-wide changes, and regulation of alternative splicing can direct a combinatorial effect on the host transcriptome. There has been a recent increase in genome-wide studies evaluating host alternative splicing during viral infection, which integrates well with prior knowledge on viral interactions with host splicing proteins. A critical challenge remains in linking how these individual events direct global changes, and whether alternative splicing is an overall favorable pathway for fending off or supporting viral infection. Here, we introduce the process of alternative splicing, discuss how to analyze splice regulation, and detail studies on genome-wide and splice factor changes during viral infection. We seek to highlight where the field can focus on moving forward, and how incorporation of a virus-host co-evolutionary perspective can benefit this burgeoning subject.

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/.

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.

Genome-wide detection of human variants that disrupt intronic branchpoints

Pre-messenger RNA splicing is initiated with the recognition of a single-nucleotide intronic branchpoint (BP) within a BP motif by spliceosome elements. Forty-eight rare variants in 43 human genes have been reported to alter splicing and cause disease by disrupting BP. However, until now, no computational approach was available to efficiently detect such variants in massively parallel sequencing data. We established a comprehensive human genome-wide BP database by integrating existing BP data and generating new BP data from RNA sequencing of lariat debranching enzyme DBR1-mutated patients and from machine-learning predictions. We characterized multiple features of BP in major and minor introns and found that BP and BP-2 (two nucleotides upstream of BP) positions exhibit a lower rate of variation in human populations and higher evolutionary conservation than the intronic background, while being comparable to the exonic background. We developed BPHunter as a genome-wide computational approach to systematically and efficiently detect intronic variants that may disrupt BP recognition. BPHunter retrospectively identified 40 of the 48 known pathogenic BP variants, in which we summarized a strategy for prioritizing BP variant candidates. The remaining eight variants all create AG-dinucleotides between the BP and acceptor site, which is the likely reason for missplicing. We demonstrated the practical utility of BPHunter prospectively by using it to identify a novel germline heterozygous BP variant of STAT2 in a patient with critical COVID-19 pneumonia and a novel somatic intronic 59-nucleotide deletion of ITPKB in a lymphoma patient, both of which were validated experimentally. BPHunter is publicly available from https://hgidsoft.rockefeller.edu/BPHunter and https://github.com/casanova-lab/BPHunter.

Prevalence, parameters, and pathogenic mechanisms for splice-altering acceptor variants that disrupt the AG exclusion zone

Predicting the pathogenicity of acceptor splice-site variants outside the essential AG is challenging, due to high sequence diversity of the extended splice-site region. Critical analysis of 24,445 intronic extended acceptor splice-site variants reported in ClinVar and the Leiden Open Variation Database (LOVD) demonstrates 41.9% of pathogenic variants create an AG dinucleotide between the predicted branchpoint and acceptor (AG-creating variants in the AG exclusion zone), 28.4% result in loss of a pyrimidine at the -3 position, and 15.1% result in loss of one or more pyrimidines in the polypyrimidine tract. Pathogenicity of AG-creating variants was highly influenced by their position. We define a high-risk zone for pathogenicity: > 6 nucleotides downstream of the predicted branchpoint and >5 nucleotides upstream from the acceptor, where 93.1% of pathogenic AG-creating variants arise and where naturally occurring AG dinucleotides are concordantly depleted (5.8% of natural AGs). SpliceAI effectively predicts pathogenicity of AG-creating variants, achieving 95% sensitivity and 69% specificity. We highlight clinical examples showing contrasting mechanisms for mis-splicing arising from AG variants: (1) cryptic acceptor created; (2) splicing silencer created: an introduced AG silences the acceptor, resulting in exon skipping, intron retention, and/or use of an alternative existing cryptic acceptor; and (3) splicing silencer disrupted: loss of a deep intronic AG activates inclusion of a pseudo-exon. In conclusion, we establish AG-creating variants as a common class of pathogenic extended acceptor variant and outline factors conferring critical risk for mis-splicing for AG-creating variants in the AG exclusion zone, between the branchpoint and acceptor.

A systematic analysis of splicing variants identifies new diagnoses in the 100,000 Genomes Project

BACKGROUND

Genomic variants which disrupt splicing are a major cause of rare genetic diseases. However, variants which lie outside of the canonical splice sites are difficult to interpret clinically. Improving the clinical interpretation of non-canonical splicing variants offers a major opportunity to uplift diagnostic yields from whole genome sequencing data.

METHODS

Here, we examine the landscape of splicing variants in whole-genome sequencing data from 38,688 individuals in the 100,000 Genomes Project and assess the contribution of non-canonical splicing variants to rare genetic diseases. We use a variant-level constraint metric (the mutability-adjusted proportion of singletons) to identify constrained functional variant classes near exon-intron junctions and at putative splicing branchpoints. To identify new diagnoses for individuals with unsolved rare diseases in the 100,000 Genomes Project, we identified individuals with de novo single-nucleotide variants near exon-intron boundaries and at putative splicing branchpoints in known disease genes. We identified candidate diagnostic variants through manual phenotype matching and confirmed new molecular diagnoses through clinical variant interpretation and functional RNA studies.

RESULTS

We show that near-splice positions and splicing branchpoints are highly constrained by purifying selection and harbour potentially damaging non-coding variants which are amenable to systematic analysis in sequencing data. From 258 de novo splicing variants in known rare disease genes, we identify 35 new likely diagnoses in probands with an unsolved rare disease. To date, we have confirmed a new diagnosis for six individuals, including four in whom RNA studies were performed.

CONCLUSIONS

Overall, we demonstrate the clinical value of examining non-canonical splicing variants in individuals with unsolved rare diseases.

Identification of an elusive spliceogenic MYBPC3 variant in an otherwise genotype-negative hypertrophic cardiomyopathy pedigree

The finding of a genotype-negative hypertrophic cardiomyopathy (HCM) pedigree with several affected members indicating a familial origin of the disease has driven this study to discover causative gene variants. Genetic testing of the proband and subsequent family screening revealed the presence of a rare variant in the MYBPC3 gene, c.3331−26T>G in intron 30, with evidence supporting cosegregation with the disease in the family. An analysis of potential splice-altering activity using several splicing algorithms consistently yielded low scores. Minigene expression analysis at the mRNA and protein levels revealed that c.3331−26T>G is a spliceogenic variant with major splice-altering activity leading to undetectable levels of properly spliced transcripts or the corresponding protein. Minigene and patient mRNA analyses indicated that this variant induces complete and partial retention of intron 30, which was expected to lead to haploinsufficiency in carrier patients. As most spliceogenic MYBPC3 variants, c.3331−26T>G appears to be non-recurrent, since it was identified in only two additional unrelated probands in our large HCM cohort. In fact, the frequency analysis of 46 known splice-altering MYBPC3 intronic nucleotide substitutions in our HCM cohort revealed 9 recurrent and 16 non-recurrent variants present in a few probands (≤ 4), while 21 were not detected. The identification of non-recurrent elusive MYBPC3 spliceogenic variants that escape detection by in silico algorithms represents a challenge for genetic diagnosis of HCM and contributes to solving a fraction of genotype-negative HCM cases.

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

Purpose

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

Methods

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

Results

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

Conclusions

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

Non-canonical splice junction processing increases the diversity of RBFOX2 splicing isoforms

The underlying mechanisms of splicing regulation through non-canonical splice junction processing remain largely unknown. Here, we identified two RBFOX2 splicing isoforms by alternative 3' splice site selection of exon 9; the non-canonical splice junction processed RBFOX2 transcript (RBFOX2-N.C.) was expressed by the selection of the 3' splice GG acceptor sequence. The cytoplasmic localization of RBFOX2-C., a canonical splice junction-processed RBFOX2 transcript, was different from that of RBFOX2-N.C., which showed nuclear localization. In addition, we confirmed that RBFOX2-C. showed a significantly stronger localization into stress granules than RBFOX2-N.C. upon sodium arsenite treatment. Next, we investigated the importance of non-canonical 3' splice GG sequence selection of specific cis-regulatory elements using minigene constructs of the RBFOX2 gene. We found that the non-canonical 3' splice GG sequence and suboptimal branch point site adjacent region were critical for RBFOX2-N.C. expression through a non-canonical 3' splice selection. Our results suggest a regulatory mechanism for the non-canonical 3' splice selection in the RBFOX2 gene, providing a basis for studies related to the regulation of alternative pre-mRNA splicing through non-canonical splice junction processing.

The splicing effect of variants at branchpoint elements in cancer genes

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

RNA and protein expression analysis of HLA-DQB1*03:01:01:21Q allele: A null allele renamed as HLA-DQB1*03:01:01:21N

The characterization of the expression profile of HLA questionable alleles (Q) is clinically relevant in allogeneic hematopoietic stem cell transplantation (HSTC) because an aberrant expression of these alleles could lead to transplantation-related complications. HLA-DQB1*03:01:01:21Q shows a substitution at the donor splice site of intron 3 that potentially could affect the expression of this allele. In order to determine their expression profile at RNA and protein level, we analyzed the presence of the HLA-DQ7 molecule by complement-dependent cytotoxicity test (CDC) and flow cytometry, and their RNA processing by cDNA analyses and sequencing by Sanger methods. Our results reveal that HLA-DQ7 is not detectable by serological methods, this is confirmed by cDNA methods demonstrating the absence of specific HLA-DQB1*03:01:01:21Q mRNA, probably due to an intron 3 retention that creates a premature TGA stop codon, leading to mRNA degradation via nonsense-mediated decay (NMD). These findings demonstrate that the HLA-DQB1*03:01:01:21Q allele is nonexpressed, thus it has been renamed as DQB1*03:01:01:21N.

Missense RHD single nucleotide variants induce weakened D antigen expression by altering splicing and/or protein expression

BACKGROUND

Although D variant phenotype is known to be due to genetic defects, including rare missense single nucleotide variants (SNVs), within the RHD gene, few studies have addressed the molecular and cellular mechanisms driving this altered expression. We and others showed previously that splicing is commonly disrupted by SNVs in constitutive splice sites and their vicinity. We thus sought to investigate whether rare missense SNVs located in "deep" exonic regions could also impair this mechanism.

STUDY DESIGN AND METHODS

Forty-six missense SNVs reported within exons 6 and 7 were first selected from the Human RhesusBase. Their respective effect on splicing was assessed by using an in vitro assay. An RhD-negative cell model was further generated by using the CRISPR-Cas9 approach. RhD-mutated proteins were overexpressed in the newly created model, and cell membrane expression of the D antigen was measured by flow cytometry.

RESULTS

Minigene splicing assay showed that 14 of 46 (30.4%) missense SNVs alter splicing. Very interestingly, further investigation of two missense SNVs, which both affect codon 338 and confer a weak D phenotype, showed various mechanisms: c.1012C>G (p.Leu338Val) disrupts splicing only, while c.1013T>C (p.Leu338Pro) alters only the protein structure, in agreement with in silico prediction tools and 3D protein structure visualization.

CONCLUSION

Our functional data set suggests that missense SNVs damage quantitatively D antigen expression by, at least, two different mechanisms (splicing alteration and protein destabilization) that may act independently. These data thereby contribute to extend the current knowledge of the molecular mechanisms governing weakened D expression.

Learning the Regulatory Code of Gene Expression

Data-driven machine learning is the method of choice for predicting molecular phenotypes from nucleotide sequence, modeling gene expression events including protein-DNA binding, chromatin states as well as mRNA and protein levels. Deep neural networks automatically learn informative sequence representations and interpreting them enables us to improve our understanding of the regulatory code governing gene expression. Here, we review the latest developments that apply shallow or deep learning to quantify molecular phenotypes and decode the cis-regulatory grammar from prokaryotic and eukaryotic sequencing data. Our approach is to build from the ground up, first focusing on the initiating protein-DNA interactions, then specific coding and non-coding regions, and finally on advances that combine multiple parts of the gene and mRNA regulatory structures, achieving unprecedented performance. We thus provide a quantitative view of gene expression regulation from nucleotide sequence, concluding with an information-centric overview of the central dogma of molecular biology.

Successful pregnancies in an adult with Meier-Gorlin syndrome harboring biallelic CDT1 variants

Meier-Gorlin syndrome is an autosomal recessively inherited disorder of growth retardation, accompanied by microtia and patellae a/hypoplasia and characteristic facies. Pathogenic variants in genes associated with the initiation of DNA replication underlie the condition, with biallelic variants in CDT1 the most common cause. Using 10× Chromium genome sequencing, we report CDT1 variants in an adult female, with an inframe amino acid deletion inherited in trans with a deep intronic variant which likely serves as the branchpoint site in Intron 8. Splicing defects arising from this variant were confirmed through in vitro analysis. At 49 years, she represents the oldest patient with a molecular diagnosis described in the literature and is the first reported patient with Meier-Gorlin syndrome to have carried a successful pregnancy to term. Both of her pregnancies were complicated by postpartum hemorrhage and upon subsequent necessary hysterectomy, revealed uterine abnormalities. There is scant knowledge on reproductive ability and success in patients with Meier-Gorlin syndrome. Successful pregnancies among other clinically recognizable forms of primordial dwarfism have also not been described previously. This case is therefore of clinical interest for many forms of inherited growth retardation, and will assist in providing more information and clinical guidance for females of reproductive age.

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.

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.

HRness in Breast and Ovarian Cancers

Ovarian and breast cancers are currently defined by the main pathways involved in the tumorigenesis. The majority are carcinomas, originating from epithelial cells that are in constant division and subjected to cyclical variations of the estrogen stimulus during the female hormonal cycle, therefore being vulnerable to DNA damage. A portion of breast and ovarian carcinomas arises in the context of DNA repair defects, in which genetic instability is the backdrop for cancer initiation and progression. For these tumors, DNA repair deficiency is now increasingly recognized as a target for therapeutics. In hereditary breast/ovarian cancers (HBOC), tumors with BRCA1/2 mutations present an impairment of DNA repair by homologous recombination (HR). For many years, BRCA1/2 mutations were only screened on germline DNA, but now they are also searched at the tumor level to personalize treatment. The reason of the inactivation of this pathway remains uncertain for most cases, even in the presence of a HR-deficient signature. Evidence indicates that identifying the mechanism of HR inactivation should improve both genetic counseling and therapeutic response, since they can be useful as new biomarkers of response.