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

Unraveling noncoding DNA variants and epimutations: a paradigm shift in hereditary cancer research

Exhaustive efforts have been dedicated to uncovering genomic aberrations linked to cancer susceptibility. Noncoding sequence variants and epigenetic alterations significantly influence gene regulation and could contribute to cancer development. However, exploring noncoding regions in hereditary cancer susceptibility demands cutting-edge methodologies for functionally characterizing genomic discoveries. Additionally, comprehending the impact on cancer development of variants in noncoding DNA and the epigenome necessitates integrating diverse data through bioinformatic analyses. As novel technologies and analytical methods continue to advance, this realm of research is rapidly gaining traction. Within this mini-review, we delve into future research domains concerning aberrations in noncoding DNA regions, such as pseudoexons, promoter variants and cis-epimutations.

QR-1011 restores defective ABCA4 splicing caused by multiple severe ABCA4 variants underlying Stargardt disease

Stargardt disease type 1 (STGD1), the most common form of hereditary macular dystrophy, can be caused by biallelic combinations of over 2200 variants in the ABCA4 gene. This leads to reduced or absent ABCA4 protein activity, resulting in toxic metabolite accumulation in the retina and damage of the retinal pigment epithelium and photoreceptors. Approximately 21% of all ABCA4 variants that contribute to disease influence ABCA4 pre-mRNA splicing. This emphasizes the need for therapies to restore disrupted ABCA4 splicing and halt STGD1 progression. Previously, QR-1011, an antisense oligonucleotide (AON), successfully corrected splicing abnormalities and restored normal ABCA4 protein translation in human retinal organoids carrying the prevalent disease-causing variant c.5461-10T>C in ABCA4. Here, we investigated whether QR-1011 could also correct splicing in four less common non-canonical splice site (NCSS) variants flanking ABCA4 exon 39: c.5461-8T>G, c.5461-6T>C, c.5584+5G>A and c.5584+6T>C. We administered QR-1011 and three other AONs to midigene-transfected cells and demonstrate that QR-1011 had the most pronounced effect on splicing compared to the others. Moreover, QR-1011 significantly increased full-length ABCA4 transcript levels for c.5461-8T>G and c.5584+6T>C. Splicing restoration could not be achieved in the other two variants, suggesting their more severe effect on splicing. Overall, QR-1011, initially developed for a single ABCA4 variant, exhibited potent splice correction capabilities for two additional severe NCSS variants nearby. This suggests the possibility of a broader therapeutic impact of QR-1011 extending beyond its original target and highlights the potential for treating a larger population of STGD1 patients affected by multiple severe ABCA4 variants with a single AON.

Systematic Minigene-Based Splicing Analysis and Tentative Clinical Classification of 52 CHEK2 Splice-Site Variants

BACKGROUND

Disrupted pre-mRNA splicing is a frequent deleterious mechanism in hereditary cancer. We aimed to functionally analyze candidate spliceogenic variants of the breast cancer susceptibility gene CHEK2 by splicing reporter minigenes.

METHODS

A total of 128 CHEK2 splice-site variants identified in the Breast Cancer After Diagnostic Gene Sequencing (BRIDGES) project (https://cordis.europa.eu/project/id/634935) were analyzed with MaxEntScan and subsetted to 52 variants predicted to impact splicing. Three CHEK2 minigenes, which span all 15 exons, were constructed and validated. The 52 selected variants were then genetically engineered into the minigenes and assayed in MCF-7 (human breast adenocarcinoma) cells.

RESULTS

Of 52 variants, 46 (88.5%) impaired splicing. Some of them led to complex splicing patterns with up to 11 different transcripts. Thirty-four variants induced splicing anomalies without any trace or negligible amounts of the full-length transcript. A total of 89 different transcripts were annotated, which derived from different events: single- or multi-exon skipping, alternative site-usage, mutually exclusive exon inclusion, intron retention or combinations of the abovementioned events. Fifty-nine transcripts were predicted to introduce premature termination codons, 7 kept the original open-reading frame, 5 removed the translation start codon, 6 affected the 5'UTR (Untranslated Region), and 2 included missense variations. Analysis of variant c.684-2A > G revealed the activation of a non-canonical TG-acceptor site and exon 6 sequences critical for its recognition.

CONCLUSIONS

Incorporation of minigene read-outs into an ACMG/AMP (American College of Medical Genetics and Genomics/Association for Molecular Pathology)-based classification scheme allowed us to classify 32 CHEK2 variants (27 pathogenic/likely pathogenic and 5 likely benign). However, 20 variants (38%) remained of uncertain significance, reflecting in part the complex splicing patterns of this gene.

Parallel DNA/RNA NGS Using an Identical Target Enrichment Panel in the Analysis of Hereditary Cancer Predisposition

Germline DNA testing using the next-gene-ration sequencing (NGS) technology has become the analytical standard for the diagnostics of hereditary diseases, including cancer. Its increasing use places high demands on correct sample identification, independent confirmation of prioritized variants, and their functional and clinical interpretation. To streamline these processes, we introduced parallel DNA and RNA capture-based NGS using identical capture panel CZECANCA, which is routinely used for DNA analysis of hereditary cancer predisposition. Here, we present the analytical workflow for RNA sample processing and its analytical and diagnostic performance. Parallel DNA/RNA analysis allowed credible sample identification by calculating the kinship coefficient. The RNA capture-based approach enriched transcriptional targets for the majority of clinically relevant cancer predisposition genes to a degree that allowed analysis of the effect of identified DNA variants on mRNA processing. By comparing the panel and whole-exome RNA enrichment, we demonstrated that the tissue-specific gene expression pattern is independent of the capture panel. Moreover, technical replicates confirmed high reproducibility of the tested RNA analysis. We concluded that parallel DNA/RNA NGS using the identical gene panel is a robust and cost-effective diagnostic strategy. In our setting, it allows routine analysis of 48 DNA/RNA pairs using NextSeq 500/550 Mid Output Kit v2.5 (150 cycles) in a single run with sufficient coverage to analyse 226 cancer predisposition and candidate ge-nes. This approach can replace laborious Sanger confirmatory sequencing, increase testing turnaround, reduce analysis costs, and improve interpretation of the impact of variants by analysing their effect on mRNA processing.

Stargardt disease-associated missense and synonymous ABCA4 variants result in aberrant splicing

Missense variants in ABCA4 constitute ~50% of causal variants in Stargardt disease (STGD1). Their pathogenicity is attributed to their direct effect on protein function, whilst their potential impact on pre-mRNA splicing disruption remains poorly understood. Interestingly, synonymous ABCA4 variants have previously been classified as 'severe' variants based on in silico analyses. Here, we systemically investigated the role of synonymous and missense variants in ABCA4 splicing by combining computational predictions and experimental assays. To identify variants of interest, we used SpliceAI to ascribe defective splice predictions on a dataset of 5579 biallelic STGD1 probands. We selected those variants with predicted delta scores for acceptor/donor gain > 0.20, and no previous reports on their effect on splicing. Fifteen ABCA4 variants were selected, 4 of which were predicted to create a new splice acceptor site and 11 to create a new splice donor site. In addition, three variants of interest with delta scores < 0.20 were included. The variants were introduced in wild-type midigenes that contained 4-12 kb of ABCA4 genomic sequence, which were subsequently expressed in HEK293T cells. By using RT-PCR and Sanger sequencing, we identified splice aberrations for 16 of 18 analyzed variants. SpliceAI correctly predicted the outcomes for 15 out of 18 variants, illustrating its reliability in predicting the impact of coding ABCA4 variants on splicing. Our findings highlight a causal role for coding ABCA4 variants in splicing aberrations, improving the severity assessment of missense and synonymous ABCA4 variants, and guiding to new treatment strategies for STGD1.

PDIVAS: Pathogenicity predictor for Deep-Intronic Variants causing Aberrant Splicing

BACKGROUND

Deep-intronic variants that alter RNA splicing were ineffectively evaluated in the search for the cause of genetic diseases. Determination of such pathogenic variants from a vast number of deep-intronic variants (approximately 1,500,000 variants per individual) represents a technical challenge to researchers. Thus, we developed a Pathogenicity predictor for Deep-Intronic Variants causing Aberrant Splicing (PDIVAS) to easily detect pathogenic deep-intronic variants.

RESULTS

PDIVAS was trained on an ensemble machine-learning algorithm to classify pathogenic and benign variants in a curated dataset. The dataset consists of manually curated pathogenic splice-altering variants (SAVs) and commonly observed benign variants within deep introns. Splicing features and a splicing constraint metric were used to maximize the predictive sensitivity and specificity, respectively. PDIVAS showed an average precision of 0.92 and a maximum MCC of 0.88 in classifying these variants, which were the best of the previous predictors. When PDIVAS was applied to genome sequencing analysis on a threshold with 95% sensitivity for reported pathogenic SAVs, an average of 27 pathogenic candidates were extracted per individual. Furthermore, the causative variants in simulated patient genomes were more efficiently prioritized than the previous predictors.

CONCLUSION

Incorporating PDIVAS into variant interpretation pipelines will enable efficient detection of disease-causing deep-intronic SAVs and contribute to improving the diagnostic yield. PDIVAS is publicly available at https://github.com/shiro-kur/PDIVAS .

Introns and Their Therapeutic Applications in Biomedical Researches

Context

Although for a long time, it was thought that intervening sequences (introns) were junk DNA without any function, their critical roles and the underlying molecular mechanisms in genome regulation have only recently come to light. Introns not only carry information for splicing, but they also play many supportive roles in gene regulation at different levels. They are supposed to function as useful tools in various biological processes, particularly in the diagnosis and treatment of diseases. Introns can contribute to numerous biological processes, including gene silencing, gene imprinting, transcription, mRNA metabolism, mRNA nuclear export, mRNA localization, mRNA surveillance, RNA editing, NMD, translation, protein stability, ribosome biogenesis, cell growth, embryonic development, apoptosis, molecular evolution, genome expansion, and proteome diversity through various mechanisms.

Evidence Acquisition

In order to fulfill the objectives of this study, the following databases were searched: Medline, Scopus, Web of Science, EBSCO, Open Access Journals, and Google Scholar. Only articles published in English were included.

Results & Conclusions

The intervening sequences of eukaryotic genes have critical functions in genome regulation, as well as in molecular evolution. Here, we summarize recent advances in our understanding of how introns influence genome regulation, as well as their effects on molecular evolution. Moreover, therapeutic strategies based on intron sequences are discussed. According to the obtained results, a thorough understanding of intron functional mechanisms could lead to new opportunities in disease diagnosis and therapies, as well as in biotechnology applications.

Minigene Assay as an Effective Molecular Diagnostic Strategy in Determining the Pathogenicity of Noncanonical Splice-Site Variants in FLCN

Primary spontaneous pneumothorax (PSP) or pulmonary cyst is one of the manifestations of Birt-Hogg-Dubé syndrome, which is caused by pathogenic variants in FLCN gene. Genetic testing in patients with PSP identifies a certain number of missense or intronic variants. These variants are usually considered as variants of uncertain significance, whose functional interpretations pose a challenge in clinical genetics. To improve recognition of pathogenic splice-altering variants in FLCN gene, computational tools are used to prioritize potential splice-altering variants and then a hybrid minigene assay is performed to verify the RNA splicing pattern. Herein, variants in FLCN exon 11 and its flanking sequence are focused. Eight variants detected in 11 patients with PSP are evaluated, and six variants are prioritized by in silico tools as potential splice-altering variants of uncertain significance. Four variants (c.1177-5_1177-3delCTC, c.1292_1300+4del, c.1300+4C>T, and c.1300+5G>A) are demonstrated by minigene assay to alter RNA splicing of FLCN, and the last three of them are novel. RT-PCR of patient-derived RNA gives consistent results. Genotype-phenotype correlation analysis in patients with PSP with these variants demonstrates good concordance. Our results underline the importance of RNA analysis, which could provide molecular evidence for pathogenicity of a variant, and provide essential information for the clinical interpretation of variants. Combining the clinical information, a definitive diagnosis could be made.

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 risk variants for multiple sclerosis are linked to differences in alternative pre-mRNA splicing

BACKGROUND

Multiple sclerosis (MS) is a chronic immune-mediated disease of the central nervous system to which a genetic predisposition contributes. Over 200 genetic regions have been associated with increased disease risk, but the disease-causing variants and their functional impact at the molecular level are mostly poorly defined. We hypothesized that single-nucleotide polymorphisms (SNPs) have an impact on pre-mRNA splicing in MS.

METHODS

Our study focused on 10 bioinformatically prioritized SNP-gene pairs, in which the SNP has a high potential to alter alternative splicing events (ASEs). We tested for differential gene expression and differential alternative splicing in B cells from MS patients and healthy controls. We further examined the impact of the SNP genotypes on ASEs and on splice isoform expression levels. Novel genotype-dependent effects on splicing were verified with splicing reporter minigene assays.

RESULTS

We were able to confirm previously described findings regarding the relation of MS-associated SNPs with the ASEs of the pre-mRNAs from GSDMB and SP140. We also observed an increased IL7R exon 6 skipping when comparing relapsing and progressive MS patients to healthy subjects. Moreover, we found evidence that the MS risk alleles of the SNPs rs3851808 (EFCAB13), rs1131123 (HLA-C), rs10783847 (TSFM), and rs2014886 (TSFM) may contribute to a differential splicing pattern. Of particular interest is the genotype-dependent exon skipping of TSFM due to the SNP rs2014886. The minor allele T creates a donor splice site, resulting in the expression of the exon 3 and 4 of a short TSFM transcript isoform, whereas in the presence of the MS risk allele C, this donor site is absent, and thus the short transcript isoform is not expressed.

CONCLUSION

In summary, we found that genetic variants from MS risk loci affect pre-mRNA splicing. Our findings substantiate the role of ASEs with respect to the genetics of MS. Further studies on how disease-causing genetic variants may modify the interactions between splicing regulatory sequence elements and RNA-binding proteins can help to deepen our understanding of the genetic susceptibility to MS.

Application of Multigene Panels Testing for Hereditary Cancer Syndromes

BACKGROUND

Approximately 5-10% of all cancers are associated with hereditary cancer predisposition syndromes (HCPS). Early identification of HCPS is facilitated by widespread use of next-generation sequencing (NGS) and brings significant benefits to both the patient and their relatives. This study aims to evaluate the landscape of genetic variants in patients with personal and/or family history of cancer using NGS-based multigene panel testing.

MATERIALS AND METHODS

The study cohort included 1117 probands from Russia: 1060 (94.9%) patients with clinical signs of HCPS and 57 (5.1%) healthy individuals with family history of cancer. NGS analysis of 76 HCPS genes was performed using a custom Roche NimbleGen enrichment panel.

RESULTS

Pathogenic/likely pathogenic variants were identified in 378 of 1117 individuals (33.8%). The predominant number (59.8%) of genetic variants was identified in BRCA1/BRCA2 genes. CHEK2 was the second most commonly altered gene with a total of 28 (7.4%) variants, and 124 (32.8%) genetic variants were found in other 35 cancer-associated genes with variable penetrance.

CONCLUSIONS

Multigene panel testing allows for a differential diagnosis and identification of high-risk group for oncological diseases. Our results demonstrate that inclusion of non-coding gene regions into HCPS gene panels is highly important for the identification of rare spliceogenic variants with high penetrance.

Minigene-based splicing analysis and ACMG/AMP-based tentative classification of 56 ATM variants

The ataxia telangiectasia-mutated (ATM) protein is a major coordinator of the DNA damage response pathway. ATM loss-of-function variants are associated with 2-fold increased breast cancer risk. We aimed at identifying and classifying spliceogenic ATM variants detected in subjects of the large-scale sequencing project BRIDGES. A total of 381 variants at the intron-exon boundaries were identified, 128 of which were predicted to be spliceogenic. After further filtering, we ended up selecting 56 variants for splicing analysis. Four functional minigenes (mgATM) spanning exons 4-9, 11-17, 25-29, and 49-52 were constructed in the splicing plasmid pSAD. Selected variants were genetically engineered into the four constructs and assayed in MCF-7/HeLa cells. Forty-eight variants (85.7%) impaired splicing, 32 of which did not show any trace of the full-length (FL) transcript. A total of 43 transcripts were identified where the most prevalent event was exon/multi-exon skipping. Twenty-seven transcripts were predicted to truncate the ATM protein. A tentative ACMG/AMP (American College of Medical Genetics and Genomics/Association for Molecular Pathology)-based classification scheme that integrates mgATM data allowed us to classify 29 ATM variants as pathogenic/likely pathogenic and seven variants as likely benign. Interestingly, the likely pathogenic variant c.1898+2T>G generated 13% of the minigene FL-transcript due to the use of a noncanonical GG-5'-splice-site (0.014% of human donor sites). Circumstantial evidence in three ATM variants (leakiness uncovered by our mgATM analysis together with clinical data) provides some support for a dosage-sensitive expression model in which variants producing ≥30% of FL-transcripts would be predicted benign, while variants producing ≤13% of FL-transcripts might be pathogenic. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

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.

Phenotype from SAMD9 Mutation at 7p21.1 Appears Attenuated by Novel Compound Heterozygous Variants at RUNX2 and SALL1

Sterile α motif domain-containing protein 9 (SAMD9) is a regulatory protein centrally involved in cell proliferation and apoptosis. Mapped to 7p21.2, variants in SAMD9 have been reported in <50 pediatric cases worldwide, typically with early lethality. Germline gain-of-function SAMD9 variants are associated with MIRAGE syndrome (myelodysplasia, infection, restricted growth, adrenal hypoplasia, genital anomalies, and enteropathy). Spalt like transcription factor 1 (SALL1) is a zinc finger transcriptional repressor located at 16q12.1 where only two transcript variants in SALL1 are known. RUNX2 (6p21.1) encodes a nuclear protein with a Runt DNA-binding domain critical for osteoblastic differentiation, skeletal morphogenesis, and serves as a scaffold for nucleic acids and regulatory factors involved in skeletal gene expression. RUNX2 and SALL1 are thus both “master regulators” of tissue organization and embryo development. Here, we describe exome sequencing and copy number variants in two previously unknown mutations—R824Q in SAMD9, and Q253H in SALL1. A multiexon 3′ terminal duplication of RUNX2 not previously encountered is also reported. This is the first known phenotype assessment for an intersection of all three variants in a healthy 46,XX adult. Focusing on developmental progress, ultrastructural renal anatomy, and selected reproductive aspects, we describe this unique genotype diagnosed incidentally during coronavirus disease 2019 (COVID-19) illness. Individually, disruption in SAMD9, RUNX2, or SALL1 would be expected to give a bleak prognosis. However, this variant convergence appears to dampen severe pathology perhaps by cross-gene silencing of effects normally deleterious when such changes occur alone.