Blood RNA analysis can increase clinical diagnostic rate and resolve variants of uncertain significance

Evaluation of pathogenicity of WT1 intron variants by in vitro splicing analysis

BACKGROUND

Wilms tumor 1 (WT1; NM_024426) causes Denys-Drash syndrome, Frasier syndrome, or isolated focal segmental glomerulosclerosis. Several WT1 intron variants are pathogenic; however, the pathogenicity of some variants remains undefined. Whether a candidate variant detected in a patient is pathogenic is very important for determining the therapeutic options for the patient.

METHODS

In this study, we evaluated the pathogenicity of WT1 gene intron variants with undetermined pathogenicity by comparing their splicing patterns with those of the wild-type using an in vitro splicing assay using minigenes. The three variants registered as likely disease-causing genes: Mut1 (c.1017-9 T > C(IVS5)), Mut2 (c.1355-28C > T(IVS8)), Mut3 (c.1447 + 1G > C(IVS9)), were included as subjects along the 34 splicing variants registered in the Human Gene Mutation Database (HGMD)®.

RESULTS

The results showed no significant differences in splicing patterns between Mut1 or Mut2 and the wild-type; however, significant differences were observed in Mut3.

CONCLUSION

We concluded that Mut1 and Mut2 do not possess pathogenicity although they were registered as likely pathogenic, whereas Mut3 exhibits pathogenicity. Our results suggest that the pathogenicity of intronic variants detected in patients should be carefully evaluated.

Prediction of tumor-specific splicing from somatic mutations as a source of neoantigen candidates

Motivation

Neoantigens are promising targets for cancer immunotherapies and might arise from alternative splicing. However, detecting tumor-specific splicing is challenging because many non-canonical splice junctions identified in tumors also appear in healthy tissues. To increase tumor-specificity, we focused on splicing caused by somatic mutations as a source for neoantigen candidates in individual patients.

Results

We developed the tool splice2neo with multiple functionalities to integrate predicted splice effects from somatic mutations with splice junctions detected in tumor RNA-seq and to annotate the resulting transcript and peptide sequences. Additionally, we provide the tool EasyQuant for targeted RNA-seq read mapping to candidate splice junctions. Using a stringent detection rule, we predicted 1.7 splice junctions per patient as splice targets with a false discovery rate below 5% in a melanoma cohort. We confirmed tumor-specificity using independent, healthy tissue samples. Furthermore, using tumor-derived RNA, we confirmed individual exon-skipping events experimentally. Most target splice junctions encoded neoepitope candidates with predicted major histocompatibility complex (MHC)-I or MHC-II binding. Compared to neoepitope candidates from non-synonymous point mutations, the splicing-derived MHC-I neoepitope candidates had lower self-similarity to corresponding wild-type peptides. In conclusion, we demonstrate that identifying mutation-derived, tumor-specific splice junctions can lead to additional neoantigen candidates to expand the target repertoire for cancer immunotherapies.

Availability and implementation

The R package splice2neo and the python package EasyQuant are available at https://github.com/TRON-Bioinformatics/splice2neo and https://github.com/TRON-Bioinformatics/easyquant, respectively.

Low-frequency and rare genetic variants associated with rheumatoid arthritis risk

Rheumatoid arthritis (RA) has an estimated heritability of nearly 50%, which is particularly high in seropositive RA. HLA alleles account for a large proportion of this heritability, in addition to many common single-nucleotide polymorphisms with smaller individual effects. Low-frequency and rare variants, such as those captured by next-generation sequencing, can also have a large role in heritability in some individuals. Rare variant discovery has informed the development of drugs such as inhibitors of PCSK9 and Janus kinases. Some 34 low-frequency and rare variants are currently associated with RA risk. One variant (19:10352442G>C in TYK2) was identified in five separate studies, and might therefore represent a promising therapeutic target. Following a set of best practices in future studies, including studying diverse populations, using large sample sizes, validating RA and serostatus, replicating findings, adjusting for other variants and performing functional assessment, could help to ensure the relevance of identified variants. Exciting opportunities are now on the horizon for genetics in RA, including larger datasets and consortia, whole-genome sequencing and direct applications of findings in the management, and especially treatment, of RA.

De novo variants in FRYL are associated with developmental delay, intellectual disability, and dysmorphic features

FRY-like transcription coactivator (FRYL) belongs to a Furry protein family that is evolutionarily conserved from yeast to humans. The functions of FRYL in mammals are largely unknown, and variants in FRYL have not previously been associated with a Mendelian disease. Here, we report fourteen individuals with heterozygous variants in FRYL who present with developmental delay, intellectual disability, dysmorphic features, and other congenital anomalies in multiple systems. The variants are confirmed de novo in all individuals except one. Human genetic data suggest that FRYL is intolerant to loss of function (LoF). We find that the fly FRYL ortholog, furry (fry), is expressed in multiple tissues, including the central nervous system where it is present in neurons but not in glia. Homozygous fry LoF mutation is lethal at various developmental stages, and loss of fry in mutant clones causes defects in wings and compound eyes. We next modeled four out of the five missense variants found in affected individuals using fry knockin alleles. One variant behaves as a severe LoF variant, whereas two others behave as partial LoF variants. One variant does not cause any observable defect in flies, and the corresponding human variant is not confirmed to be de novo, suggesting that this is a variant of uncertain significance. In summary, our findings support that fry is required for proper development in flies and that the LoF variants in FRYL cause a dominant disorder with developmental and neurological symptoms due to haploinsufficiency.

Deciphering the impact of coding and non-coding SCN1A gene variants on RNA splicing

Variants that disrupt normal pre-mRNA splicing are increasingly being recognized as a major cause of monogenic disorders. The SCN1A gene, a key epilepsy gene that is linked to various epilepsy phenotypes, is no exception. Approximately 10% of all reported variants in the SCN1A gene are designated as splicing variants, with many located outside of the canonical donor and acceptor splice sites, and most have not been functionally investigated. However, given its restricted expression pattern, functional analysis of splicing variants in the SCN1A gene could not be routinely performed. In this study, we conducted a comprehensive analysis of all reported SCN1A variants and their potential to impact SCN1A splicing and conclude that splicing variants are substantially misannotated and under-represented. We created a splicing reporter system consisting of 18 splicing vectors covering all 26 protein-coding exons with different genomic contexts and several promoters of varying strengths in order to reproduce the wild-type splicing pattern of the SCN1A gene, revealing cis-regulatory elements essential for proper recognition of SCN1A exons. Functional analysis of 95 SCN1A variants was carried out, including all 68 intronic variants reported in the literature, located outside of the splice sites canonical dinucleotides; 21 exonic variants of different classes (synonymous, missense, nonsense and in-frame deletion) and six variants observed in patients with epilepsy. Interestingly, almost 20% of tested intronic variants had no influence on SCN1A splicing, despite being reported as causative in the literature. Moreover, we confirmed that the majority of predicted exonic variants affect splicing unravelling their true molecular mechanism. We used functional data to perform genotype-phenotype correlation, revealing distinct distribution patterns for missense and splice-affecting 'missense' variants and observed no difference in the phenotype severity of variants leading to in-frame and out-of-frame isoforms, indicating that the Nav1.1 protein is highly intolerant to structural variations. Our work demonstrates the importance of functional analysis in proper variant annotation and provides a tool for high-throughput delineation of splice-affecting variants in SCN1A in a whole-gene manner.

Aberrant splicing caused by a novel KMT2A variant in Wiedemann-Steiner syndrome

INTRODUCTION

Wiedemann-Steiner syndrome (WSS) is a rare autosomal-dominant disorder caused by KMT2A variants. The aim of this study was to characterize a novel KMT2A variant in a child with WSS and demonstrate integrated diagnostic approaches.

METHODS

A 3-year-old female with developmental delay, distinctive facial features, and anal fistula underwent whole exome sequencing (WES). RNA analysis was performed to assess splicing effects caused by a novel variant.

RESULTS

WES identified novel heterozygous KMT2A c.5664+6T>C variant initially classified as a variant of uncertain significance. RNA analysis provided evidence of aberrant splicing (exon 20 skipping), allowing reclassification to likely pathogenic. The patient exhibited typical WSS features along with a potential novel finding of anal fistula.

CONCLUSION

This report describes a novel non-canonical splice site variant in KMT2A associated with WSS. RNA analysis was critical for variant reclassification. Detailed phenotypic evaluation revealed common and expanded WSS manifestations. This case highlights the importance of combining clinical assessment, DNA testing, and RNA functional assays for the diagnosis of rare genetic disorders.

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.

RNA sequencing and target long-read sequencing reveal an intronic transposon insertion causing aberrant splicing

More than half of cases with suspected genetic disorders remain unsolved by genetic analysis using short-read sequencing such as exome sequencing (ES) and genome sequencing (GS). RNA sequencing (RNA-seq) and long-read sequencing (LRS) are useful for interpretation of candidate variants and detection of structural variants containing repeat sequences, respectively. Recently, adaptive sampling on nanopore sequencers enables target LRS more easily. Here, we present a Japanese girl with premature chromatid separation (PCS)/mosaic variegated aneuploidy (MVA) syndrome. ES detected a known pathogenic maternal heterozygous variant (c.1402-5A>G) in intron 10 of BUB1B (NM_001211.6), a known responsive gene for PCS/MVA syndrome with autosomal recessive inheritance. Minigene splicing assay revealed that almost all transcripts from the c.1402-5G allele have mis-splicing with 4-bp insertion. GS could not detect another pathogenic variant, while RNA-seq revealed abnormal reads in intron 2. To extensively explore variants in intron 2, we performed adaptive sampling and identified a paternal 3.0 kb insertion. Consensus sequence of 16 reads spanning the insertion showed that the insertion consists of Alu and SVA elements. Realignment of RNA-seq reads to the new reference sequence containing the insertion revealed that 16 reads have 5' splice site within the insertion and 3' splice site at exon 3, demonstrating causal relationship between the insertion and aberrant splicing. In addition, immunoblotting showed severely diminished BUB1B protein level in patient derived cells. These data suggest that detection of transcriptomic abnormalities by RNA-seq can be a clue for identifying pathogenic variants, and determination of insert sequences is one of merits of LRS.

Diagnostic Outcomes of Concurrent DNA and RNA Sequencing in Individuals Undergoing Hereditary Cancer Testing

Importance

Personalized surveillance, prophylaxis, and cancer treatment options for individuals with hereditary cancer predisposition are informed by results of germline genetic testing. Improvements to genomic technology, such as the availability of RNA sequencing, may increase identification of individuals eligible for personalized interventions by improving the accuracy and yield of germline testing.

Objective

To assess the cumulative association of paired DNA and RNA testing with detection of disease-causing germline genetic variants and resolution of variants of uncertain significance (VUS).

Design, Setting, and Participants

Paired DNA and RNA sequencing was performed on individuals undergoing germline testing for hereditary cancer indication at a single diagnostic laboratory from March 2019 through April 2020. Demographic characteristics, clinical data, and test results were curated as samples were received, and changes to variant classification were assessed over time. Data analysis was performed from May 2020 to June 2023.

Main Outcomes and Measures

Main outcomes were increase in diagnostic yield, decrease in VUS rate, the overall results by variant type, the association of RNA evidence with variant classification, and the corresponding predicted effect on cancer risk management.

Results

A total of 43 524 individuals were included (median [range] age at testing, 54 [2-101] years; 37 373 female individuals [85.7%], 6224 male individuals [14.3%], and 2 individuals of unknown sex [<0.1%]), with 43 599 tests. A total of 2197 (5.0%) were Ashkenazi Jewish, 1539 (3.5%) were Asian, 3077 (7.1%) were Black, 2437 (5.6%) were Hispanic, 27 793 (63.7%) were White, and 2049 (4.7%) were other race, and for 4507 individuals (10.3%), race and ethnicity were unknown. Variant classification was impacted in 549 individuals (1.3%). Medically significant upgrades were made in 97 individuals, including 70 individuals who had a variant reclassified from VUS to pathogenic/likely pathogenic (P/LP) and 27 individuals who had a novel deep intronic P/LP variant that would not have been detected using DNA sequencing alone. A total of 93 of 545 P/LP splicing variants (17.1%) were dependent on RNA evidence for classification, and 312 of 439 existing splicing VUS (71.1%) were resolved by RNA evidence. Notably, the increase in positive rate (3.1%) and decrease in VUS rate (-3.9%) was higher in Asian, Black, and Hispanic individuals combined compared to White individuals (1.6%; P = .02; and -2.5%; P < .001).

Conclusions and Relevance

Findings of this diagnostic study demonstrate that the ability to perform RNA sequencing concurrently with DNA sequencing represents an important advancement in germline genetic testing by improving detection of novel variants and classification of existing variants. This expands the identification of individuals with hereditary cancer predisposition and increases opportunities for personalization of therapeutics and surveillance.

Predicting the impact of rare variants on RNA splicing in CAGI6

Variants which disrupt splicing are a frequent cause of rare disease that have been under-ascertained clinically. Accurate and efficient methods to predict a variant's impact on splicing are needed to interpret the growing number of variants of unknown significance (VUS) identified by exome and genome sequencing. Here, we present the results of the CAGI6 Splicing VUS challenge, which invited predictions of the splicing impact of 56 variants ascertained clinically and functionally validated to determine splicing impact. The performance of 12 prediction methods, along with SpliceAI and CADD, was compared on the 56 functionally validated variants. The maximum accuracy achieved was 82% from two different approaches, one weighting SpliceAI scores by minor allele frequency, and one applying the recently published Splicing Prediction Pipeline (SPiP). SPiP performed optimally in terms of sensitivity, while an ensemble method combining multiple prediction tools and information from databases exceeded all others for specificity. Several challenge methods equalled or exceeded the performance of SpliceAI, with ultimate choice of prediction method likely to depend on experimental or clinical aims. One quarter of the variants were incorrectly predicted by at least 50% of the methods, highlighting the need for further improvements to splicing prediction methods for successful clinical application.

Challenges and opportunities to bridge translational to clinical research for personalized mitochondrial medicine

Mitochondrial disorders are a group of rare and heterogeneous genetic diseases characterized by dysfunctional mitochondria leading to deficient adenosine triphosphate synthesis and chronic energy deficit in patients. The majority of these patients exhibit a wide range of phenotypic manifestations targeting several organ systems, making their clinical diagnosis and management challenging. Bridging translational to clinical research is crucial for improving the early diagnosis and prognosis of these intractable mitochondrial disorders and for discovering novel therapeutic drug candidates and modalities. This review provides the current state of clinical testing in mitochondrial disorders, discusses the challenges and opportunities for converting basic discoveries into clinical settings, explores the most suited patient-centric approaches to harness the extraordinary heterogeneity among patients affected by the same primary mitochondrial disorder, and describes the current outlook of clinical trials.

Prioritizing de novo potential non-canonical splicing variants in neurodevelopmental disorders

BACKGROUND

Genomic variants outside of the canonical splicing site (±2) may generate abnormal mRNA splicing, which are defined as non-canonical splicing variants (NCSVs). However, the clinical interpretation of NCSVs in neurodevelopmental disorders (NDDs) is largely unknown.

METHODS

We investigated the contribution of NCSVs to NDDs from 345,787 de novo variants (DNVs) in 47,574 patients with NDDs. We performed functional enrichment and protein-protein interaction analysis to assess the association between genes carrying prioritised NCSVs and NDDs. Minigene was used to validate the impact of NCSVs on mRNA splicing.

FINDINGS

We observed significantly more NCSVs (p = 0.02, odds ratio [OR] = 2.05) among patients with NDD than in controls. Both canonical splicing variants (CSVs) and NCSVs contributed to an equal proportion of patients with NDD (0.76% vs. 0.82%). The candidate genes carrying NCSVs were associated with glutamatergic synapse and chromatin remodelling. Minigene successfully validated 59 of 79 (74.68%) NCSVs that led to abnormal splicing in 40 candidate genes, and 9 of the genes (ARID1B, KAT6B, TCF4, SMARCA2, SHANK3, PDHA1, WDR45, SCN2A, SYNGAP1) harboured recurrent NCSVs with the same variant present in more than two unrelated patients with NDD. Moreover, 36 of 59 (61.02%) NCSVs are novel clinically relevant variants, including 34 unreported and 2 clinically conflicting interpretations or of uncertain significance NCSVs in the ClinVar database.

INTERPRETATION

This study highlights the common pathology and clinical importance of NCSVs in unsolved patients with NDD.

FUNDING

The present study was funded by grants from the National Natural Science Foundation of China, China Postdoctoral Science Foundation, the Hunan Youth Science and Technology Innovation Talent Project, the Provincial Natural Science Foundation of Hunan, The Scientific Research Program of FuRong laboratory, and the Natural Science Project of the University of Anhui Province.

The Efficacy of Whole Genome Sequencing and RNA-Seq in the Diagnosis of Whole Exome Sequencing Negative Patients with Complex Neurological Phenotypes

Whole-genome sequencing (WGS) is being increasingly utilized for the diagnosis of neurological disease by sequencing both the exome and the remaining 98 to 99% of the genetic code. In addition to more complete coverage, WGS can detect structural variants (SVs) and intronic variants (SNVs) that cannot be identified by whole exome sequencing (WES) or chromosome microarray (CMA). Other multi-omics tools, such as RNA sequencing (RNA-Seq), can be used in conjunction with WGS to functionally validate certain variants by detecting changes in gene expression and splicing. The objective of this retrospective study was to measure the diagnostic yield of duo/trio-based WGS and RNA-Seq in a cohort of 22 patients (20 families) with pediatric onset neurological phenotypes and negative or inconclusive WES results in lieu of reanalysis. WGS with RNA-Seq resulted in a definite diagnosis of an additional 25% of cases. Sixty percent of these solved cases arose from the identification of variants that were missed by WES. Variants that could not be unequivocally proven to be causative of the patients' condition were identified in an additional 5% of cases.

Intronic Germline DICER1 Variants in Patients With Sertoli-Leydig Cell Tumor

Germline pathogenic loss-of-function (pLOF) variants in DICER1 are associated with a predisposition for a variety of solid neoplasms, including pleuropulmonary blastoma and Sertoli-Leydig cell tumor (SLCT). The most common DICER1 pLOF variants include small insertions or deletions leading to frameshifts, and base substitutions leading to nonsense codons or altered splice sites. Larger deletions and pathogenic missense variants occur less frequently. Identifying these variants can trigger surveillance algorithms with potential for early detection of DICER1-related cancers and cascade testing of family members. However, some patients with DICER1-associated tumors have no pLOF variants detected by germline or tumor testing. Here, we present two patients with SLCT whose tumor sequencing showed only a somatic missense DICER1 RNase IIIb variant. Conventional exon-directed germline sequencing revealed no pLOF variants. Using a custom capture panel, we discovered novel intronic variants, ENST00000343455.7: c.1752+213A>G and c.1509+16A>G, that appear to interfere with normal splicing. We suggest that when no DICER1 pLOF variants or large deletions are discovered in exonic regions despite strong clinical suspicion, intron sequencing and splicing analysis should be performed.

All reported non-canonical splice site variants in GLA cause aberrant splicing

BACKGROUND

Fabry disease is an X-linked lysosomal storage disorder caused by insufficient α-galactosidase A (GLA) activity resulting from variants in the GLA gene, which leads to glycosphingolipid accumulation and life-threatening, multi-organ complications. Approximately 50 variants have been reported that cause splicing abnormalities in GLA. Most were found within canonical splice sites, which are highly conserved GT and AG splice acceptor and donor dinucleotides, whereas one-third were located outside canonical splice sites, making it difficult to interpret their pathogenicity. In this study, we aimed to investigate the genetic pathogenicity of variants located in non-canonical splice sites within the GLA gene.

METHODS

13 variants, including four deep intronic variants, were selected from the Human Gene Variant Database Professional. We performed an in vitro splicing assay to identify splicing abnormalities in the variants.

RESULTS

All candidate non-canonical splice site variants in GLA caused aberrant splicing. Additionally, all but one variant was protein-truncating. The four deep intronic variants generated abnormal transcripts, including a cryptic exon, as well as normal transcripts, with the proportion of each differing in a cell-specific manner.

CONCLUSIONS

Validation of splicing effects using an in vitro splicing assay is useful for confirming pathogenicity and determining associations with clinical phenotypes.

Diagnosis, treatment, and research status of rare diseases related to birth defects

Rare diseases are diseases that occur at low prevalence, and most of them are chronic and serious diseases that are often life-threatening. Currently, there is no unified definition for rare diseases. The diagnosis, treatment, and research of rare diseases have become the focus of medicine and biopharmacology, as well as the breakthrough point of clinical and basic research. Birth defects are the hard-hit area of rare diseases and the frontiers of its research. Since most of these defects have a genetic basis, early screening and diagnosis have important scientific value and social significance for the prevention and control of such diseases. At present, there is no effective treatment for most rare diseases, but progress in prenatal diagnosis and screening can prevent the occurrence of diseases and help prevent and treat rare diseases. This article discusses the progress in genetic-related birth defects and rare diseases.

Atypical splicing variants in PKD1 explain most undiagnosed typical familial ADPKD

Autosomal dominant polycystic kidney disease (ADPKD) is the most common monogenic cause of kidney failure and is primarily associated with PKD1 or PKD2. Approximately 10% of patients remain undiagnosed after standard genetic testing. We aimed to utilise short and long-read genome sequencing and RNA studies to investigate undiagnosed families. Patients with typical ADPKD phenotype and undiagnosed after genetic diagnostics were recruited. Probands underwent short-read genome sequencing, PKD1 and PKD2 coding and non-coding analyses and then genome-wide analysis. Targeted RNA studies investigated variants suspected to impact splicing. Those undiagnosed then underwent Oxford Nanopore Technologies long-read genome sequencing. From over 172 probands, 9 met inclusion criteria and consented. A genetic diagnosis was made in 8 of 9 (89%) families undiagnosed on prior genetic testing. Six had variants impacting splicing, five in non-coding regions of PKD1. Short-read genome sequencing identified novel branchpoint, AG-exclusion zone and missense variants generating cryptic splice sites and a deletion causing critical intron shortening. Long-read sequencing confirmed the diagnosis in one family. Most undiagnosed families with typical ADPKD have splice-impacting variants in PKD1. We describe a pragmatic method for diagnostic laboratories to assess PKD1 and PKD2 non-coding regions and validate suspected splicing variants through targeted RNA studies.

Abnormal mRNA Splicing Effect of COL4A3 to COL4A5 Unclassified Variants

Introduction

Genetic diagnosis of Alport syndrome (AS), which results from pathogenic variants in COL4A3, COL4A4, or COL4A5 genes, is hindered by large numbers of unclassified variants detected using next-generation sequencing (NGS). We examined the impact on splicing of variants of uncertain significance in COL4A3 to COL4A5.

Methods

Nine unrelated patients with clinical diagnosis or suspicion of AS were enrolled according to the criteria. Their clinical and genetic data were collected. Blood and urine samples were obtained from the patients and their family members. Sanger sequencing was used to confirm the 9 COL4A3 to COL4A5 unclassified variants identified by NGS. COL4A3 to COL4A5 mRNAs from urine were analyzed using targeted reverse transcription polymerase chain reaction and direct sequencing.

Results

Nine COL4A3 to COL4A5 unclassified variants were found to alter mRNAs splicing. Skipping of an exon or an exon fragment was induced by variants COL4A3 c.828+5G>A; COL4A4 c.3506-13_3528del; and COL4A5 c.451A>G (p. [Ile151Val]), c.2042-9 T>G, c.2689 G>C (p. [Glu897Gln]) and c.1033-10_1033-2delGGTAATAAA. Retention of an intron fragment was caused by variants COL4A3 c.3211-30G＞T, and COL4A5 c.4316-20T>A and c.1033-10 G>A, respectively. The 9 families in this study obtained genetic diagnosis of AS, including 3 with autosomal recessive AS and 6 with X-linked AS.

Conclusions

Our findings demonstrate that urine mRNA analysis facilitates the identification of abnormal splicing of unclassified variants in Alport genes, which provides evidence of routine use of RNA analysis to improve genetic diagnosis of AS.

Generation of tandem alternative splice acceptor sites and CLTC haploinsufficiency: A cause of CLTC-related disorder

Tandem splice acceptors (NAGN_n AG) are a common mechanism of alternative splicing, but variants that are likely to generate or to disrupt tandem splice sites have rarely been reported as disease causing. We identify a pathogenic intron 23 CLTC variant (NM_004859.4:c.[3766-13_3766-5del];[=]) in a propositus with intellectual disability and behavioral problems. By RNAseq analysis of peripheral blood mRNA, this variant generates transcripts using cryptic proximal splice acceptors (NM_004859.4: r.3765_3766insTTCACAGAAAGGAACTAG, and NM_004859.4:r.3765_3766insAAAGGAACTAG). Given that the propositus expresses 38% the level of CLTC transcripts as unaffected controls, these variant transcripts, which encode premature termination codons, likely undergo nonsense mediated mRNA decay (NMD). This is the first functional evidence for CLTC haploinsufficiency as a cause of CLTC-related disorder and the first evidence that the generation of tandem alternative splice sites causes CLTC-related disorder. We suggest that variants creating tandem alternative splice sites are an underreported disease mechanism and that transcriptome-level analysis should be routinely pursued to define the pathogenicity of such variants.

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.

A deep intronic TCTN2 variant activating a cryptic exon predicted by SpliceRover in a patient with Joubert syndrome

The recent introduction of genome sequencing in genetic analysis has led to the identification of pathogenic variants located in deep introns. Recently, several new tools have emerged to predict the impact of variants on splicing. Here, we present a Japanese boy of Joubert syndrome with biallelic TCTN2 variants. Exome sequencing identified only a heterozygous maternal nonsense TCTN2 variant (NM_024809.5:c.916C >T, p.(Gln306Ter)). Subsequent genome sequencing identified a deep intronic variant (c.1033+423G>A) inherited from his father. The machine learning algorithms SpliceAI, Squirls, and Pangolin were unable to predict alterations in splicing by the c.1033+423G>A variant. SpliceRover, a tool for splice site prediction using FASTA sequence, was able to detect a cryptic exon which was 85-bp away from the variant and within the inverted Alu sequence while SpliceRover scores for these splice sites showed slight increase (donor) or decrease (acceptor) between the reference and mutant sequences. RNA sequencing and RT-PCR using urinary cells confirmed inclusion of the cryptic exon. The patient showed major symptoms of TCTN2-related disorders such as developmental delay, dysmorphic facial features and polydactyly. He also showed uncommon features such as retinal dystrophy, exotropia, abnormal pattern of respiration, and periventricular heterotopia, confirming these as one of features of TCTN2-related disorders. Our study highlights usefulness of genome sequencing and RNA sequencing using urinary cells for molecular diagnosis of genetic disorders and suggests that database of cryptic splice sites predicted in introns by SpliceRover using the reference sequences can be helpful in extracting candidate variants from large numbers of intronic variants in genome sequencing.

An intronic variant in TBX4 in a single family with variable and severe pulmonary manifestations

A male infant presented at term with neonatal respiratory failure and pulmonary hypertension. His respiratory symptoms improved initially, but he exhibited a biphasic clinical course, re-presenting at 15 months of age with tachypnea, interstitial lung disease, and progressive pulmonary hypertension. We identified an intronic TBX4 gene variant in close proximity to the canonical donor splice site of exon 3 (hg 19; chr17:59543302; c.401 + 3 A > T), also carried by his father who had a typical TBX4-associated skeletal phenotype and mild pulmonary hypertension, and by his deceased sister who died shortly after birth of acinar dysplasia. Analysis of patient-derived cells demonstrated a significant reduction in TBX4 expression resulting from this intronic variant. Our study illustrates the variable expressivity in cardiopulmonary phenotype conferred by TBX4 mutation and the utility of genetic diagnostics in enabling accurate identification and classification of more subtly affected family members.

Trio RNA sequencing in a cohort of medically complex children

Genome sequencing (GS) is a powerful test for the diagnosis of rare genetic disorders. Although GS can enumerate most non-coding variation, determining which non-coding variants are disease-causing is challenging. RNA sequencing (RNA-seq) has emerged as an important tool to help address this issue, but its diagnostic utility remains understudied, and the added value of a trio design is unknown. We performed GS plus RNA-seq from blood using an automated clinical-grade high-throughput platform on 97 individuals from 39 families where the proband was a child with unexplained medical complexity. RNA-seq was an effective adjunct test when paired with GS. It enabled clarification of putative splice variants in three families, but it did not reveal variants not already identified by GS analysis. Trio RNA-seq decreased the number of candidates requiring manual review when filtering for de novo dominant disease-causing variants, allowing for the exclusion of 16% of gene-expression outliers and 27% of allele-specific-expression outliers. However, clear diagnostic benefit from the trio design was not observed. Blood-based RNA-seq can facilitate genome analysis in children with suspected undiagnosed genetic disease. In contrast to DNA sequencing, the clinical advantages of a trio RNA-seq design may be more limited.

vaRHC: an R package for semi-automation of variant classification in hereditary cancer genes according to ACMG/AMP and gene-specific ClinGen guidelines

MOTIVATION

Germline variant classification allows accurate genetic diagnosis and risk assessment. However, it is a tedious iterative process integrating information from several sources and types of evidence. It should follow gene-specific (if available) or general updated international guidelines. Thus, it is the main burden of the incorporation of next-generation sequencing into the clinical setting.

RESULTS

We created the vaRiants in HC (vaRHC) R package to assist the process of variant classification in hereditary cancer by: (i) collecting information from diverse databases; (ii) assigning or denying different types of evidence according to updated American College of Molecular Genetics and Genomics/Association of Molecular Pathologist gene-specific criteria for ATM, CDH1, CHEK2, MLH1, MSH2, MSH6, PMS2, PTEN, and TP53 and general criteria for other genes; (iii) providing an automated classification of variants using a Bayesian metastructure and considering CanVIG-UK recommendations; and (iv) optionally printing the output to an .xlsx file. A validation using 659 classified variants demonstrated the robustness of vaRHC, presenting a better criteria assignment than Cancer SIGVAR, an available similar tool.

AVAILABILITY AND IMPLEMENTATION

The source code can be consulted in the GitHub repository (https://github.com/emunte/vaRHC) Additionally, it will be submitted to CRAN soon.

Bridging clinical care and research in Ontario, Canada: Maximizing diagnoses from reanalysis of clinical exome sequencing data

We examined the utility of clinical and research processes in the reanalysis of publicly-funded clinical exome sequencing data in Ontario, Canada. In partnership with eight sites, we recruited 287 families with suspected rare genetic diseases tested between 2014 and 2020. Data from seven laboratories was reanalyzed with the referring clinicians. Reanalysis of clinically relevant genes identified diagnoses in 4% (13/287); four were missed by clinical testing. Translational research methods, including analysis of novel candidate genes, identified candidates in 21% (61/287). Of these, 24 families have additional evidence through data sharing to support likely diagnoses (8% of cohort). This study indicates few diagnoses are missed by clinical laboratories, the incremental gain from reanalysis of clinically-relevant genes is modest, and the highest yield comes from validation of novel disease-gene associations. Future implementation of translational research methods, including continued reporting of compelling genes of uncertain significance by clinical laboratories, should be considered to maximize diagnoses.

Systematic analysis of CNGA3 splice variants identifies different mechanisms of aberrant splicing

Achromatopsia is an autosomal recessive cone photoreceptor disease that is frequently caused by pathogenic variants in the CNGA3 gene. Here, we present a systematic functional analysis of 20 CNGA3 splice site variants detected in our large cohort of achromatopsia patients and/or listed in common variant databases. All variants were analyzed by functional splice assays based on the pSPL3 exon trapping vector. We demonstrated that ten variants, both at canonical and non-canonical splice sites, induced aberrant splicing, including intronic nucleotide retention, exonic nucleotide deletion and exon skipping, resulting in 21 different aberrant transcripts. Of these, eleven were predicted to introduce a premature termination codon. The pathogenicity of all variants was assessed based on established guidelines for variant classification. Incorporation of the results of our functional analyses enabled re-classification of 75% of variants previously classified as variants of uncertain significance into either likely benign or likely pathogenic. Our study is the first in which a systematic characterization of putative CNGA3 splice variants has been performed. We demonstrated the utility of pSPL3 based minigene assays in the effective assessment of putative splice variants. Our findings improve the diagnosis of achromatopsia patients, who may thus benefit from future gene-based therapeutic strategies.

SpliceAI-visual: a free online tool to improve SpliceAI splicing variant interpretation

SpliceAI is an open-source deep learning splicing prediction algorithm that has demonstrated in the past few years its high ability to predict splicing defects caused by DNA variations. However, its outputs present several drawbacks: (1) although the numerical values are very convenient for batch filtering, their precise interpretation can be difficult, (2) the outputs are delta scores which can sometimes mask a severe consequence, and (3) complex delins are most often not handled. We present here SpliceAI-visual, a free online tool based on the SpliceAI algorithm, and show how it complements the traditional SpliceAI analysis. First, SpliceAI-visual manipulates raw scores and not delta scores, as the latter can be misleading in certain circumstances. Second, the outcome of SpliceAI-visual is user-friendly thanks to the graphical presentation. Third, SpliceAI-visual is currently one of the only SpliceAI-derived implementations able to annotate complex variants (e.g., complex delins). We report here the benefits of using SpliceAI-visual and demonstrate its relevance in the assessment/modulation of the PVS1 classification criteria. We also show how SpliceAI-visual can elucidate several complex splicing defects taken from the literature but also from unpublished cases. SpliceAI-visual is available as a Google Colab notebook and has also been fully integrated in a free online variant interpretation tool, MobiDetails ( https://mobidetails.iurc.montp.inserm.fr/MD ).

Dravet syndrome and hemorrhagic shock and encephalopathy syndrome associated with an intronic deletion of SCN1A

OBJECTIVE

Hemorrhagic shock and encephalopathy syndrome (HSES) is a serious condition that requires intensive care and is associated with a high mortality rate. However, its pathogenesis remains unclear. In the present study, a genetic analysis was performed to determine the genetic background of patients with clinically suspected Dravet syndrome (DS) who developed HSES.

METHODS

Whole exome sequencing was performed, followed by minigene analysis of the intron variant detected by whole exome sequencing to confirm its effect on splicing.

RESULTS

Whole exome sequencing revealed a novel 21-bp deletion in intron 3 of SCN1A NM_001165963.4 (NC_000002.11:g.166073675_166073695del). This deletion was not found in the patient's parents and was proven to be de novo. Minigene analysis revealed an aberrant mRNA lacking 40 and 106 bp from the 5' end of exon 4 of SCN1A. Therefore, we diagnosed this case as DS due to the deletion in intron 3 of SCN1A.

CONCLUSIONS

We report a case of DS with HSES caused by a 21-bp deletion in the intron of SCN1A that was confirmed by minigene analysis. The present case met Levin's criteria for HSES and the splicing analysis of SCN1A is an important finding. This study has important implications for understanding HSES pathogenesis.

A novel PTEN mutant caused by polymorphism in cis-regulatory elements is involved in chemosensitivity in breast cancer

Phosphatase and tensin homolog (PTEN) is one of the most important tumor suppressor genes. Although studies have shown the association between cancer and genetic polymorphisms of PTEN, the underlying molecular mechanisms of breast cancer (BC) chemosensitivity that results from PTEN polymorphism is still unclear. This study aims to investigate potential links between PTEN polymorphisms in cis-regulatory elements and BC chemosensitivity in the Chinese population. A total of 172 BC patients who received neoadjuvant chemotherapy were included in the study, including 104 chemosensitive cases and 68 chemoresistant cases. The results showed a significant association between the rs786204926 polymorphism and BC chemosensitivity. Logistic multivariate regression analysis showed that age, lymph node metastasis, and the rs786204926 genotype were risk factors for BC chemoresistance. The G allele of rs786204926 is more prone to increasing the risk of chemosensitivity in BC. Additionally, analysis using Alamut Visual showed a preference of the G allele of rs786204926 to produce a novel PTEN mutant with an insertion of 18 bases from intron 4. While the transcriptional level of PTEN remained similar in chemosensitivity and chemoresistant samples, its protein level changed significantly. Interestingly, there were significant differences in both transcription and protein levels of the novel PTEN mutant between the two groups. Furthermore, we found that the mutant was more susceptible to dephosphorylation compared with wildtype PTEN, leading to chemosensitivity through the PI3K-AKT signaling pathway. These findings indicate that novel PTEN mutants caused by polymorphisms in cis-regulatory elements may be involved in BC chemosensitivity.

Aberrant splicing caused by exonic single nucleotide variants positioned 2nd or 3rd to the last nucleotide in the COL4A5 gene

BACKGROUND AND OBJECTIVES

The evident genotype-phenotype correlation shown by the X-linked Alport syndrome warrants the assessment of the impact of identified gene variants on aberrant splicing. We previously reported that single nucleotide variants (SNVs) in the last nucleotide of exons in COL4A5 cause aberrant splicing. It is known that the nucleotides located 2nd and 3rd to the last nucleotides of exons can also play an essential role in the first step of the splicing process. In this study, we aimed to investigate whether SNVs positioned 2nd or 3rd to the last nucleotide of exons in COL4A5 resulted in aberrant splicing.

METHODS

We selected eight candidate variants: six from the Human Gene Variant Database Professional and two from our cohort. We performed an in-vitro splicing assay and reverse transcription-polymerase chain reaction (RT-PCR) for messenger RNA obtained from patients, if available.

RESULTS

The candidate variants were initially classified into the following groups: three nonsense, two missense, and three synonymous variants. Splicing assays and RT-PCR for messenger RNA revealed that six of the eight variants caused aberrant splicing. Four variants, initially classified as non-truncating variants, were found to be truncating ones, which usually show relatively more severe phenotypes.

CONCLUSION

We revealed that exonic SNVs positioned 2nd or 3rd to the last nucleotide of exons in the COL4A5 were responsible for aberrant splicing. The results of our study suggest that attention should be paid when interpreting the pathogenicity of exonic SNVs near the 5' splice site.

Diagnostic potential of the amniotic fluid cells transcriptome in deciphering mendelian disease: a proof-of-concept

RNA sequencing (RNA-seq) is emerging in genetic diagnoses as it provides functional support for the interpretation of variants of uncertain significance. However, the use of amniotic fluid (AF) cells for RNA-seq has not yet been explored. Here, we examined the expression of clinically relevant genes in AF cells (n = 48) compared with whole blood and fibroblasts. The number of well-expressed genes in AF cells was comparable to that in fibroblasts and much higher than that in blood across different disease categories. We found AF cells RNA-seq feasible and beneficial in prenatal diagnosis (n = 4) as transcriptomic data elucidated the molecular consequence leading to the pathogenicity upgrade of variants in CHD7 and COL1A2 and revising the in silico prediction of a variant in MYRF. AF cells RNA-seq could become a reasonable choice for postnatal patients with advantages over fibroblasts and blood as it prevents invasive procedures.

A Novel Synonymous Variant of PHEX in a Patient with X-Linked Hypophosphatemia

X-linked dominant hypophosphatemia (XLH), the most common form of hereditary hypophosphatemic rickets/osteomalacia, is caused by loss-of-function phosphate-regulating endopeptidase homolog X-linked gene (PHEX) variants. However, synonymous PHEX variants are rare in XLH. We report a 7-year-old boy with hypophosphatemia, short stature, and lower limb deformity. Whole-exome sequencing, reverse transcription-polymerase chain reaction, and Sanger sequencing were performed to identify the pathogenicity of the variant. A novel synonymous PHEX variant (NM_000444.4:c.1530 C&gt;T, p.Arg510Arg) was detected in the proband. Further analysis revealed a 58-bp deletion at the 5' site of exon 14 during splicing. This study extends the genetic spectrum of XLH and confirms the rarity and significance of synonymous PHEX variants.

Characterization of a possible founder synonymous variant in TECTA in multiple individuals with autosomal recessive hearing loss

Synonymous variants have been shown to alter the correct splicing of pre-mRNAs and generate disease-causing transcripts. These variants are not an uncommon etiology of genetic disease; however, they are frequently overlooked during genetic testing in the absence of functional and clinical data. Here, we describe the occurrence of a synonymous variant [NM_005422.4 (TECTA):c.327C>T, p.(Gly109=)] in seven individuals with hearing loss from six unrelated families. The variant is not located near exonic/intronic boundaries but is predicted to impact splicing by activating a cryptic splicing donor site in exon 4 of TECTA. In vitro minigene assays show that the variant disrupts the reading frame of the canonical transcript, which is predicted to cause a premature termination codon 48 amino acids downstream of the variant, leading to nonsense-mediated decay. The variant is present in population databases, predominantly in Latinos of African ancestry, but is rare in other ethnic groups. Our findings suggest that this synonymous variant is likely pathogenic for TECTA-associated autosomal recessive hearing loss and seems to have arisen as a founder variant in this specific Latino subpopulation. This study demonstrates that synonymous variants need careful splicing assessment and support from additional testing methodologies to determine their clinical impact.

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.

Transcriptome analysis provides critical answers to the "variants of uncertain significance" conundrum

While whole-genome and exome sequencing have transformed our collective understanding of genetics' role in disease pathogenesis, there are certain conditions and populations for whom DNA-level data fails to identify the underlying genetic etiology. Specifically, patients of non-White race and non-European ancestry are disproportionately affected by "variants of unknown/uncertain significance" (VUS), limiting the scope of precision medicine for minority patients and perpetuating health disparities. VUS often include deep intronic and splicing variants which are difficult to interpret from DNA data alone. RNA analysis can illuminate the consequences of VUS, thereby allowing for their reclassification as pathogenic versus benign. Here we review the critical role transcriptome analysis plays in clarifying VUS in both neoplastic and non-neoplastic diseases.

Comparison of In Silico Tools for Splice-Altering Variant Prediction Using Established Spliceogenic Variants: An End-User’s Point of View

Assessing the impact of variants of unknown significance on splicing has become a critical issue and a bottleneck, especially with the widespread implementation of whole-genome or exome sequencing. Although multiple in silico tools are available, the interpretation and application of these tools are difficult and practical guidelines are still lacking. A streamlined decision-making process can facilitate the downstream RNA analysis in a more efficient manner. Therefore, we evaluated the performance of 8 in silico tools (Splice Site Finder, MaxEntScan, Splice-site prediction by neural network, GeneSplicer, Human Splicing Finder, SpliceAI, Splicing Predictions in Consensus Elements, and SpliceRover) using 114 NF1 spliceogenic variants, experimentally validated at the mRNA level. The change in the predicted score incurred by the variant of the nearest wild-type splice site was analyzed, and for type II, III, and IV splice variants, the change in the prediction score of de novo or cryptic splice site was also analyzed. SpliceAI and SpliceRover, tools based on deep learning, outperformed all other tools, with AUCs of 0.972 and 0.924, respectively. For de novo and cryptic splice sites, SpliceAI outperformed all other tools and showed a sensitivity of 95.7% at an optimal cut-off of 0.02 score change. Our results show that deep learning algorithms, especially those of SpliceAI, are validated at a significantly higher rate than other in silico tools for clinically relevant NF1 variants. This suggests that deep learning algorithms outperform traditional probabilistic approaches and classical machine learning tools in predicting the de novo and cryptic splice sites.

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.

Can tandem alternative splicing and evasion of premature termination codon surveillance contribute to attenuated Peutz-Jeghers syndrome?

Alternative use of short distance tandem sites such as NAGN_n AG are a common mechanism of alternative splicing; however, single nucleotide variants are rarely reported as likely to generate or to disrupt tandem splice sites. We identify a pathogenic intron 5 STK11 variant (NM_000455.4:c.[735-6A>G];[=]) segregating with the mucocutaneous features but not the hamartomatous polyps of Peutz-Jeghers syndrome in two individuals. By RNAseq analysis of peripheral blood mRNA, this variant was shown to generate a novel and preferentially used tandem proximal splice acceptor (AAGTGAAG). The variant transcript (NM_000455.4:c.734_734 + 1insTGAAG), which encodes a frameshift (p.[Tyr246Glufs*43]) constituted 36%-43% of STK11 transcripts suggesting partial escape from nonsense mediated mRNA decay and translation of a truncated protein. A review of the ClinVar database identified other similar variants. We suggest that nucleotide changes creating or disrupting tandem alternative splice sites are a pertinent disease mechanism and require contextualization for clinical reporting. Additionally, we hypothesize that some pathogenic STK11 variants cause an attenuated phenotype.

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.

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.

Recommendations for clinical interpretation of variants found in non-coding regions of the genome

BACKGROUND

The majority of clinical genetic testing focuses almost exclusively on regions of the genome that directly encode proteins. The important role of variants in non-coding regions in penetrant disease is, however, increasingly being demonstrated, and the use of whole genome sequencing in clinical diagnostic settings is rising across a large range of genetic disorders. Despite this, there is no existing guidance on how current guidelines designed primarily for variants in protein-coding regions should be adapted for variants identified in other genomic contexts.

METHODS

We convened a panel of nine clinical and research scientists with wide-ranging expertise in clinical variant interpretation, with specific experience in variants within non-coding regions. This panel discussed and refined an initial draft of the guidelines which were then extensively tested and reviewed by external groups.

RESULTS

We discuss considerations specifically for variants in non-coding regions of the genome. We outline how to define candidate regulatory elements, highlight examples of mechanisms through which non-coding region variants can lead to penetrant monogenic disease, and outline how existing guidelines can be adapted for the interpretation of these variants.

CONCLUSIONS

These recommendations aim to increase the number and range of non-coding region variants that can be clinically interpreted, which, together with a compatible phenotype, can lead to new diagnoses and catalyse the discovery of novel disease mechanisms.

Unclassified white matter disorders: A diagnostic journey requiring close collaboration between clinical and laboratory services

BACKGROUND

Next generation sequencing studies have revealed an ever-increasing number of causes for genetic disorders of central nervous system white matter. A substantial number of disorders are identifiable from their specific pattern of biochemical and/or imaging findings for which single gene testing may be indicated. Beyond this group, the causes of genetic white matter disorders are unclear and a broader approach to genomic testing is recommended.

AIM

This study aimed to identify the genetic causes for a group of individuals with unclassified white matter disorders with suspected genetic aetiology and highlight the investigations required when the initial testing is non-diagnostic.

METHODS

Twenty-six individuals from 22 families with unclassified white matter disorders underwent deep phenotyping and genome sequencing performed on trio, or larger, family groups. Functional studies and transcriptomics were used to resolve variants of uncertain significance with potential clinical relevance.

RESULTS

Causative or candidate variants were identified in 15/22 (68.2%) families. Six of the 15 implicated genes had been previously associated with white matter disease (COL4A1, NDUFV1, SLC17A5, TUBB4A, BOLA3, DARS2). Patients with variants in the latter two presented with an atypical phenotype. The other nine genes had not been specifically associated with white matter disease at the time of diagnosis and included genes associated with monogenic syndromes, developmental disorders, and developmental and epileptic encephalopathies (STAG2, LSS, FIG4, GLS, PMPCA, SPTBN1, AGO2, SCN2A, SCN8A). Consequently, only 46% of the diagnoses would have been made via a current leukodystrophy gene panel test.

DISCUSSION

These results confirm the importance of broad genomic testing for patients with white matter disorders. The high diagnostic yield reflects the integration of deep phenotyping, whole genome sequencing, trio analysis, functional studies, and transcriptomic analyses.

CONCLUSIONS

Genetic white matter disorders are genetically and phenotypically heterogeneous. Deep phenotyping together with a range of genomic technologies underpin the identification of causes of unclassified white matter disease. A molecular diagnosis is essential for prognostication, appropriate management, and accurate reproductive counseling.

Identification of Spliceogenic Variants beyond Canonical GT-AG Splice Sites in Hereditary Cancer Genes

Pathogenic/likely pathogenic variants in susceptibility genes that interrupt RNA splicing are a well-documented mechanism of hereditary cancer syndromes development. However, if RNA studies are not performed, most of the variants beyond the canonical GT-AG splice site are characterized as variants of uncertain significance (VUS). To decrease the VUS burden, we have bioinformatically evaluated all novel VUS detected in 732 consecutive patients tested in the routine genetic counseling process. Twelve VUS that were predicted to cause splicing defects were selected for mRNA analysis. Here, we report a functional characterization of 12 variants located beyond the first two intronic nucleotides using RNAseq in APC, ATM, FH, LZTR1, MSH6, PALB2, RAD51C, and TP53 genes. Based on the analysis of mRNA, we have successfully reclassified 50% of investigated variants. 25% of variants were downgraded to likely benign, whereas 25% were upgraded to likely pathogenic leading to improved clinical management of the patient and the family members.

Short amplicon reverse transcription-polymerase chain reaction detects aberrant splicing in genes with low expression in blood missed by ribonucleic acid sequencing analysis for clinical diagnosis

Use of blood RNA sequencing (RNA-seq) as a splicing analysis tool for clinical interpretation of variants of uncertain significance (VUSs) found via whole-genome and exome sequencing can be difficult for genes that have low expression in the blood due to insufficient read count coverage aligned to specific genes of interest. Here, we present a short amplicon reverse transcription-polymerase chain reaction(RT-PCR) for the detection of genes with low blood expression. Short amplicon RT-PCR, is designed to span three exons where an exon harboring a variant is flanked by one upstream and one downstream exon. We tested short amplicon RT-PCRs for genes that have median transcripts per million (TPM) values less than one according to the genotype-tissue expression database. Median TPM values of genes analyzed in this study are SYN1 = 0.8549, COL1A1 = 0.6275, TCF4 = 0.4009, DSP = .2894, TTN = 0.2851, COL5A2 = 0.1036, TERT = 0.04452, NTRK2 = 0.0344, ABCA4 = 0.00744, PRPH = 0, and WT1 = 0. All these genes show insufficient exon-spanning read coverage in our RNA-seq data to allow splicing analysis. We successfully detected all genes tested except PRPH and WT1. Aberrant splicing was detected in SYN1, TCF4, NTRK2, TTN, and TERT VUSs. Therefore, our results show short amplicon RT-PCR is a useful alternative for the analysis of splicing events in genes with low TPM in blood RNA for clinical diagnostics.

Case Report: Phenotype-Driven Diagnosis of Atypical Dravet-Like Syndrome Caused by a Novel Splicing Variant in the SCN2A Gene

Febrile-associated epileptic encephalopathy is a large genetically heterogeneous group that is associated with pathogenic variants in SCN1A, PCDH19, SCN2A, SCN8A, and other genes. The disease onset ranges from neonatal or early-onset epileptic encephalopathy to late-onset epilepsy after 18 months. Some etiology-specific epileptic encephalopathies have target therapy which can serve as a clue for the correct genetic diagnosis. We present genetic, clinical, electroencephalographic, and behavioral features of a 4-year-old girl with epileptic encephalopathy related to a de novo intronic variant in the SCN2A gene. Initial NGS analysis revealed a frameshift variant in the KDM6A gene and a previously reported missense variant in SCN1A. Due to lack of typical clinical signs of Kabuki syndrome, we performed X-chromosome inactivation that revealed nearly complete skewed inactivation. Segregation analysis showed that the SCN1A variant was inherited from a healthy father. The proband had resistance to multiple antiseizure medications but responded well to sodium channel inhibitor Carbamazepine. Reanalysis of NGS data by a neurogeneticist revealed a previously uncharacterized heterozygous variant c.1035-7A>G in the SCN2A gene. Minigene assay showed that the c.1035-7A>G variant activates a cryptic intronic acceptor site which leads to 6-nucleotide extension of exon 9 (NP_066287.2:p.(Gly345_Gln346insTyrSer). SCN2A encephalopathy is a recognizable severe phenotype. Its electro-clinical and treatment response features can serve as a hallmark. In such a patient, reanalysis of genetic data is strongly recommended in case of negative or conflicting results of DNA analysis.

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.