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

A practical guide to interpreting germline variants that drive hematopoietic malignancies, bone marrow failure, and chronic cytopenias

PURPOSE

The American College of Medical Genetics and Genomics and the Association for Molecular Pathology guidelines for germline variant interpretation are implemented as a broad framework by standardizing variant interpretation. These rules were designed to be specified, but this process has not been performed for most of the 200 genes associated with inherited hematopoietic malignancies, bone marrow failure, and cytopenias. Because guidelines on how to perform these gene specifications are lacking, variant interpretation is less reliable and reproducible.

METHODS

We have used a variety of methods such as calculations of minor allele frequencies, quasi-case-control studies to establish thresholds, proband counting, and plotting of receiver operating characteristic curves to compare different in silico prediction tools to design recommendations for variant interpretation.

RESULTS

We herein provide practical recommendations for the creation of thresholds for minor allele frequencies, in silico predictions, counting of probands, identification of functional domains with minimal benign variation, use of constraint Z-scores and functional evidence, prediction of nonsense-mediated decay, and assessment of phenotype specificity.

CONCLUSION

These guidelines can be used by anyone interpreting variants associated with inherited hematopoietic malignancies, bone marrow failure, and cytopenias to develop criteria for reliable, accurate, and reproducible germline variant interpretation.

Possible Catch-Up Developmental Trajectories for Children with Mild Developmental Delay Caused by NAA15 Pathogenic Variants

Variants in NAA15 are closely related to neurodevelopmental disorders (NDDs). In this study, we investigated the spectrum and clinical features of NAA15 variants in a Chinese NDD cohort of 769 children. Four novel NAA15 pathogenic variants were detected by whole-exome sequencing, including three de novo variants and one maternal variant. The in vitro minigene splicing assay confirmed one noncanonical splicing variant (c.1410+5G>C), which resulted in abnormal mRNA splicing. All affected children presented mild developmental delay, and catch-up trajectories were noted in three patients based on their developmental scores at different ages. Meanwhile, the literature review also showed that half of the reported patients with NAA15 variants presented mild/moderate developmental delay or intellectual disability, and possible catch-up sign was indicated for three affected patients. Taken together, our study expanded the spectrum of NAA15 variants in NDD patients. The affected patients presented mild developmental delay, and possible catch-up developmental trajectories were suggested. Studying the natural neurodevelopmental trajectories of NDD patients with pathogenic variants and their benefits from physical rehabilitations are needed in the future for precise genetic counseling and clinical management.

RNA splicing analysis contributes to reclassifying variants of uncertain significance and improves the diagnosis of monogenic disorders

BACKGROUND

Numerous variants of uncertain significance (VUSs) have been identified by whole exome sequencing in clinical practice. However, VUSs are not currently considered medically actionable.

OBJECTIVE

To assess the splicing patterns of 49 VUSs in 48 families identified clinically to improve genetic counselling and family planning.

METHODS

Forty-nine participants with 49 VUSs were recruited from the Reproductive and Genetic Hospital of CITIC-Xiangya. Bioinformatic analysis was performed to preliminarily predict the splicing effects of these VUSs. RT-PCR and minigene analysis were used to assess the splicing patterns of the VUSs. According to the results obtained, couples opted for different methods of reproductive interventions to conceive a child, including prenatal diagnosis and preimplantation genetic testing (PGT).

RESULTS

Eleven variants were found to alter pre-mRNA splicing and one variant caused nonsense-mediated mRNA decay, which resulted in the reclassification of these VUSs as likely pathogenic. One couple chose to undergo in vitro fertilisation with PGT treatment; a healthy embryo was transferred and the pregnancy is ongoing. Three couples opted for natural pregnancy with prenatal diagnosis. One couple terminated the pregnancy because the fetus was affected by short-rib thoracic dysplasia and harboured the related variant. The infants of the other two couples were born and were healthy at their last recorded follow-up.

CONCLUSION

RNA splicing analysis is an important method to assess the impact of sequence variants on splicing in clinical practice and can contribute to the reclassification of a significant proportion of VUSs. RNA splicing analysis should be considered for genetic disease diagnostics.

MRSD: A quantitative approach for assessing suitability of RNA-seq in the investigation of mis-splicing in Mendelian disease

Variable levels of gene expression between tissues complicates the use of RNA sequencing of patient biosamples to delineate the impact of genomic variants. Here, we describe a gene- and tissue-specific metric to inform the feasibility of RNA sequencing. This overcomes limitations of using expression values alone as a metric to predict RNA-sequencing utility. We have derived a metric, minimum required sequencing depth (MRSD), that estimates the depth of sequencing required from RNA sequencing to achieve user-specified sequencing coverage of a gene, transcript, or group of genes. We applied MRSD across four human biosamples: whole blood, lymphoblastoid cell lines (LCLs), skeletal muscle, and cultured fibroblasts. MRSD has high precision (90.1%-98.2%) and overcomes transcript region-specific sequencing biases. Applying MRSD scoring to established disease gene panels shows that fibroblasts, of these four biosamples, are the optimum source of RNA for 63.1% of gene panels. Using this approach, up to 67.8% of the variants of uncertain significance in ClinVar that are predicted to impact splicing could be assayed by RNA sequencing in at least one of the biosamples. We demonstrate the utility and benefits of MRSD as a metric to inform functional assessment of splicing aberrations, in particular in the context of Mendelian genetic disorders to improve diagnostic yield.

The splicing effect of variants at branchpoint elements in cancer genes

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSION

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

What Has the Undiagnosed Diseases Network Taught Us About the Clinical Applications of Genomic Testing?

Genetic testing has undergone a revolution in the last decade, particularly with the advent of next-generation sequencing and its associated reductions in costs and increases in efficiencies. The Undiagnosed Diseases Network (UDN) has been a leader in the application of such genomic testing for rare disease diagnosis. This review discusses the current state of genomic testing performed within the UDN, with a focus on the strengths and limitations of whole-exome and whole-genome sequencing in clinical diagnostics and the importance of ongoing data reanalysis. The role of emerging technologies such as RNA and long-read sequencing to further improve diagnostic rates in the UDN is also described. This review concludes with a discussion of the challenges faced in insurance coverage of comprehensive genomic testing as well as the opportunities for a larger role of testing in clinical medicine.

Identification of a Novel Canonical Splice Site Variant TSC2 c.2967-1G>T That is Not Associated With Tuberous Sclerosis Pathogenesis

Tuberous sclerosis, also known as tuberous sclerosis complex (TSC), is an autosomal dominant defect characterized by hamartomas in multiple organ systems. Inactivating variants cause this defect in either the TSC1 gene or the TSC2 gene, leading to hamartin or tuberin protein dysfunction, thus resulting in TSC. The diagnostic criteria for TSC suggest that it can be diagnosed by identifying a heterozygous pathogenic variant of TSC1 or TSC2, even in the absence of clinical signs. In a 4-year-old girl, we identified a splicing variant (NM_000548.4: c.2967-1G>T) that she inherited from her father. Neither the girl (patient) nor her father showed typical features of TSC. This variant is located in a NAGNAG acceptor, which can produce mRNA isoforms that differ by a three-nucleotide indel. Reverse transcription polymerase chain reaction analysis of the patient and both parents' blood RNA samples suggested two different splicing patterns, and these two splicing patterns differed in the presence or absence of the first codon of exon 27, thus providing two splicing products designated as isoforms A and B, respectively. Furthermore, the proportions of these two patterns varied between the patient and either parent. A minigene assay further confirmed that the c.2967-1G>T variant led to the absence of isoform A (including the first codon of exon 27). The finding of our study demonstrates this variant, c.2967-1G>T, disrupts the balance of an alternative splice event which involves the use of two tandem alternatives acceptors and is not associated with typical symptoms of tuberous sclerosis. Our finding is of importance for genetic counseling and suggests that we need to be vigilant to avoid misdiagnosis when we encounter such a site.

Silent variant in F8:c.222G>T (p.Thr74Thr) causes a partial exon skipping in a patient with mild hemophilia A

One of the challenges of genetic testing in patients with hemophilia A is the interpretation of sequence variants. Here we report a silent variant found in exon 2 in the F8 gene in a 47‐year‐old patient with a previous von Willebrand disease (VWD) type 1 diagnosis. Clinically he had mild bleeding symptoms restricted to prolonged bleeding from minor wounds. Sanger sequencing of F8 gene using genomic DNA showed a hemizygous silent variant in exon 2: c.222G>T, p.Thr74Thr. When applying ACMG criteria, the variant was predicted to be “likely benign” in the analyzing software or VUS after curating. Sanger sequencing of the patient's cDNA after nested polymerase chain reaction showed that the patient had both a normal transcript containing exons 1–4 and a defect transcript lacking exon 2. These findings explain the patient's low FVIII:C level and led to the diagnosis of mild hemophilia A instead of VWD type 1. This case illustrates that mRNA work‐up may be needed to clarify a patient's phenotype–genotype.

Case Report: Functional Investigation of an Undescribed Missense Variant Affecting Splicing in a Patient With Dravet Syndrome

Pathogenic variants in the SCN1A gene are associated with a spectrum of epileptic disorders ranging in severity from familial febrile seizures to Dravet syndrome. Large proportions of reported pathogenic variants in SCN1A are annotated as missense variants and are often classified as variants of uncertain significance when no functional data are available. Although loss-of-function variants are associated with a more severe phenotype in SCN1A, the molecular mechanism of single nucleotide variants is often not clear, and genotype-phenotype correlations in SCN1A-related epilepsy remain uncertain. Coding variants can affect splicing by creating novel cryptic splicing sites in exons or by disrupting exonic cis-regulation elements crucial for proper pre-mRNA splicing. Here, we report a novel case of Dravet syndrome caused by an undescribed missense variant, c.4852G>A (p.(Gly1618Ser)). By midigene splicing assay, we demonstrated that the identified variant is in fact splice-affecting. To our knowledge, this is the first report on the functional investigation of a missense variant affecting splicing in Dravet syndrome.

Hereditary spastic paraplegia associated with a novel homozygous intronic noncanonical splice site variant in the AP4B1 gene

Pathogenic variants in the AP4B1 gene lead to a rare form of hereditary spastic paraplegia (HSP) known as SPG47. We report on a patient with a clinical suspicion of complicated HSP of the lower limbs with intellectual disability, as well as a novel homozygous noncanonical splice site variant in the AP4B1 gene, in which the effect on splicing was validated by RNA analysis. We sequenced 152 genes associated with HSP using Next-Generation Sequencing (NGS). We isolated total RNA from peripheral blood and generated cDNA using reverse transcription-polymerase chain reaction (RT-PCR). A region of AP4B1 mRNA was amplified by PCR and the fragments obtained were purified from the agarose gel and sequenced. We found a homozygous variant of uncertain significance in the AP4B1 gene NM_006594.4: c.1511-6C>G in the proband. Two different AP4B1 mRNA fragments were obtained in the patient and his carrier parents. The shorter fragment was the predominant fragment in the patient and revealed a deletion with skipping of the AP4B1 exon 10. The patient's longer fragment corresponded to an insertion of the last five nucleotides of AP4B1 intron 9. We confirmed that this variant affects the normal splicing of RNA, sustaining the molecular diagnosis of SPG47 in the patient.

Standardized practices for RNA diagnostics using clinically accessible specimens reclassifies 75% of putative splicing variants

PURPOSE

Genetic variants causing aberrant premessenger RNA splicing are increasingly being recognized as causal variants in genetic disorders. In this study, we devise standardized practices for polymerase chain reaction (PCR)-based RNA diagnostics using clinically accessible specimens (blood, fibroblasts, urothelia, biopsy).

METHODS

A total of 74 families with diverse monogenic conditions (31% prenatal-congenital onset, 47% early childhood, and 22% teenage-adult onset) were triaged into PCR-based RNA testing, with comparative RNA sequencing for 19 cases.

RESULTS

Informative RNA assay data were obtained for 96% of cases, enabling variant reclassification for 75% variants that can be used for genetic counseling (71%), to inform clinical care (32%) and prenatal counseling (41%). Variant-associated mis-splicing was highly reproducible for 28 cases with samples from ≥2 affected individuals or heterozygotes and 10 cases with ≥2 biospecimens. PCR amplicons encompassing another segregated heterozygous variant was vital for clinical interpretation of 22 of 79 variants to phase RNA splicing events and discern complete from partial mis-splicing.

CONCLUSION

RNA diagnostics enabled provision of a genetic diagnosis for 64% of recruited cases. PCR-based RNA diagnostics has capacity to analyze 81.3% of clinically significant genes, with long amplicons providing an advantage over RNA sequencing to phase RNA splicing events. The Australasian Consortium for RNA Diagnostics (SpliceACORD) provide clinically-endorsed, standardized protocols and recommendations for interpreting RNA assay data.

Prenatal phenotype of PNKP-related primary microcephaly associated with variants affecting both the FHA and phosphatase domain

Biallelic PNKP variants cause heterogeneous disorders ranging from neurodevelopmental disorder with microcephaly/seizures to adult-onset Charcot–Marie–Tooth disease. To date, only postnatal descriptions exist. We present the first prenatal diagnosis of PNKP-related primary microcephaly. Pathological examination of a male fetus in the 18th gestational week revealed micrencephaly with extracerebral malformations and thus presumed syndromic microcephaly. A recessive disorder was suspected because of previous pregnancy termination for similar abnormalities. Prenatal trio-exome sequencing identified compound heterozygosity for the PNKP variants c.498G>A, p.[(=),0?] and c.302C>T, p.(Pro101Leu). Segregation confirmed both variants in the sister fetus. Through RNA analyses, we characterized exon 4 skipping affecting the PNKP forkhead-associated (FHA) and phosphatase domains (p.Leu67_Lys166del) as the predominant effect of the paternal c.498G>A variant. We retrospectively investigated two unrelated individuals diagnosed with biallelic PNKP-variants to compare prenatal/postnatal phenotypes. Both carry the splice donor variant c.1029+2T>C intrans with a variant in the FHA domain (c.311T>C, p.(Leu104Pro); c.151G>C, p.(Val51Leu)). RNA-seq showed complex splicing for c.1029+2T>C and c.151G>C. Structural modeling revealed significant clustering of missense variants in the FHA domain with variants generating structural damage. Our clinical description extends the PNKP-continuum to the prenatal stage. Investigating possible PNKP-variant effects using RNA and structural modeling, we highlight the mutational complexity and exemplify a PNKP-variant characterization framework.

Comparison of in silico strategies to prioritize rare genomic variants impacting RNA splicing for the diagnosis of genomic disorders

The development of computational methods to assess pathogenicity of pre-messenger RNA splicing variants is critical for diagnosis of human disease. We assessed the capability of eight algorithms, and a consensus approach, to prioritize 249 variants of uncertain significance (VUSs) that underwent splicing functional analyses. The capability of algorithms to differentiate VUSs away from the immediate splice site as being 'pathogenic' or 'benign' is likely to have substantial impact on diagnostic testing. We show that SpliceAI is the best single strategy in this regard, but that combined usage of tools using a weighted approach can increase accuracy further. We incorporated prioritization strategies alongside diagnostic testing for rare disorders. We show that 15% of 2783 referred individuals carry rare variants expected to impact splicing that were not initially identified as 'pathogenic' or 'likely pathogenic'; one in five of these cases could lead to new or refined diagnoses.

A discarded synonymous variant in NPHP3 explains nephronophthisis and congenital hepatic fibrosis in several families

Half of patients with a ciliopathy syndrome remain unsolved after initial analysis of whole exome sequencing (WES) data, highlighting the need for improved variant filtering and annotation. By candidate gene curation of WES data, combined with homozygosity mapping, we detected a homozygous predicted synonymous allele in NPHP3 in two children with hepatorenal fibrocystic disease from a consanguineous family. Analyses on patient-derived RNA shows activation of a cryptic mid-exon splice donor leading to frameshift. Remarkably, the same rare variant was detected in four additional families with hepatorenal disease from UK, US, and Saudi patient cohorts and in addition, another synonymous NPHP3 variant was identified in an unsolved case from the Genomics England 100,000 Genomes data set. We conclude that synonymous NPHP3 variants, not reported before and discarded by pathogenicity pipelines, solved several families with a ciliopathy syndrome. These findings prompt careful reassessment of synonymous variants, especially if they are rare and located in candidate genes.

Whole genome sequencing in the diagnosis of primary ciliary dyskinesia

BACKGROUND

It is estimated that 1-13% of cases of bronchiectasis in adults globally are attributable to primary ciliary dyskinesia (PCD) but many adult patients with bronchiectasis have not been investigated for PCD. PCD is a disorder caused by mutations in genes required for motile cilium structure or function, resulting in impaired mucociliary clearance. Symptoms appear in infancy but diagnosis is often late or missed, often due to the lack of a "gold standard" diagnostic tool and non-specific symptoms. Mutations in > 50 genes account for around 70% of cases, with additional genes, and non-coding, synonymous, missense changes or structural variants (SVs) in known genes presumed to account for the missing heritability.

METHODS

UK patients with no identified genetic confirmation for the cause of their PCD or bronchiectasis were eligible for whole genome sequencing (WGS) in the Genomics England Ltd 100,000 Genomes Project. 21 PCD probands and 52 non-cystic fibrosis (CF) bronchiectasis probands were recruited in Wessex Genome Medicine Centre (GMC). We carried out analysis of single nucleotide variants (SNVs) and SVs in all families recruited in Wessex GMC.

RESULTS

16/21 probands in the PCD cohort received confirmed (n = 9), probable (n = 4) or possible (n = 3) diagnosis from WGS, although 13/16 of these could have been picked up by current standard of care gene panel testing. In the other cases, SVs were identified which were missed by panel testing. We identified variants in novel PCD candidate genes (IFT140 and PLK4) in 2 probands in the PCD cohort. 3/52 probands in the non-CF bronchiectasis cohort received a confirmed (n = 2) or possible (n = 1) diagnosis of PCD. We identified variants in novel PCD candidate genes (CFAP53 and CEP164) in 2 further probands in the non-CF bronchiectasis cohort.

CONCLUSIONS

Genetic testing is an important component of diagnosing PCD, especially in cases of atypical disease history. WGS is effective in cases where prior gene panel testing has found no variants or only heterozygous variants. In these cases it may detect SVs and is a powerful tool for novel gene discovery.

Performance Evaluation of SpliceAI for the Prediction of Splicing of NF1 Variants

Neurofibromatosis type 1, characterized by neurofibromas and café-au-lait macules, is one of the most common genetic disorders caused by pathogenic NF1 variants. Because of the high proportion of splicing mutations in NF1, identifying variants that alter splicing may be an essential issue for laboratories. Here, we investigated the sensitivity and specificity of SpliceAI, a recently introduced in silico splicing prediction algorithm in conjunction with other in silico tools. We evaluated 285 NF1 variants identified from 653 patients. The effect on variants on splicing alteration was confirmed by complementary DNA sequencing followed by genomic DNA sequencing. For in silico prediction of splicing effects, we used SpliceAI, MaxEntScan (MES), and Splice Site Finder-like (SSF). The sensitivity and specificity of SpliceAI were 94.5% and 94.3%, respectively, with a cut-off value of Δ Score > 0.22. The area under the curve of SpliceAI was 0.975 (p < 0.0001). Combined analysis of MES/SSF showed a sensitivity of 83.6% and specificity of 82.5%. The concordance rate between SpliceAI and MES/SSF was 84.2%. SpliceAI showed better performance for the prediction of splicing alteration for NF1 variants compared with MES/SSF. As a convenient web-based tool, SpliceAI may be helpful in clinical laboratories conducting DNA-based NF1 sequencing.

Splicing Outcomes of 5' Splice Site GT>GC Variants That Generate Wild-Type Transcripts Differ Significantly Between Full-Length and Minigene Splicing Assays

Combining data derived from a meta-analysis of human disease-associated 5' splice site GT>GC (i.e., +2T>C) variants and a cell culture-based full-length gene splicing assay (FLGSA) of forward engineered +2T>C substitutions, we recently estimated that ∼15-18% of +2T>C variants can generate up to 84% wild-type transcripts relative to their wild-type counterparts. Herein, we analyzed the splicing outcomes of 20 +2T>C variants that generate some wild-type transcripts in two minigene assays. We found a high discordance rate in terms of the generation of wild-type transcripts, not only between FLGSA and the minigene assays but also between the different minigene assays. In the pET01 context, all 20 wild-type minigene constructs generated the expected wild-type transcripts; of the 20 corresponding variant minigene constructs, 14 (70%) generated wild-type transcripts. In the pSPL3 context, only 18 of the 20 wild-type minigene constructs generated the expected wild-type transcripts whereas 8 of the 18 (44%) corresponding variant minigene constructs generated wild-type transcripts. Thus, in the context of a particular type of variant, we raise awareness of the limitations of minigene splicing assays and emphasize the importance of sequence context in regulating splicing. Whether or not our findings apply to other types of splice-altering variant remains to be investigated.

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

Simple Summary

There is a significant percentage of hereditary breast and ovarian cancer (HBOC) cases that remain undiagnosed, because no pathogenic variant is detected through massively parallel sequencing of coding exons and exon-intron boundaries of high-moderate susceptibility risk genes. Deep intronic regions may contain variants affecting RNA splicing, leading ultimately to disease, and hence they may explain several cases where the genetic cause of HBOC is unknown. This study aims to characterize intronic regions to identify a landscape of “exonizable” zones and test the efficiency of two in silico tools to detect deep intronic variants affecting the mRNA splicing process.

Abstract

The contribution of deep intronic splice-altering variants to hereditary breast and ovarian cancer (HBOC) is unknown. Current computational in silico tools to predict spliceogenic variants leading to pseudoexons have limited efficiency. We assessed the performance of the SpliceAI tool combined with ESRseq scores to identify spliceogenic deep intronic variants by affecting cryptic sites or splicing regulatory elements (SREs) using literature and experimental datasets. Our results with 233 published deep intronic variants showed that SpliceAI, with a 0.05 threshold, predicts spliceogenic deep intronic variants affecting cryptic splice sites, but is less effective in detecting those affecting SREs. Next, we characterized the SRE profiles using ESRseq, showing that pseudoexons are significantly enriched in SRE-enhancers compared to adjacent intronic regions. Although the combination of SpliceAI with ESRseq scores (considering ∆ESRseq and SRE landscape) showed higher sensitivity, the global performance did not improve because of the higher number of false positives. The combination of both tools was tested in a tumor RNA dataset with 207 intronic variants disrupting splicing, showing a sensitivity of 86%. Following the pipeline, five spliceogenic deep intronic variants were experimentally identified from 33 variants in HBOC genes. Overall, our results provide a framework to detect deep intronic variants disrupting splicing.

Splicing in the Diagnosis of Rare Disease: Advances and Challenges

Mutations which affect splicing are significant contributors to rare disease, but are frequently overlooked by diagnostic sequencing pipelines. Greater ascertainment of pathogenic splicing variants will increase diagnostic yields, ending the diagnostic odyssey for patients and families affected by rare disorders, and improving treatment and care strategies. Advances in sequencing technologies, predictive modeling, and understanding of the mechanisms of splicing in recent years pave the way for improved detection and interpretation of splice affecting variants, yet several limitations still prohibit their routine ascertainment in diagnostic testing. This review explores some of these advances in the context of clinical application and discusses challenges to be overcome before these variants are comprehensively and routinely recognized in diagnostics.

Benchmarking deep learning splice prediction tools using functional splice assays

Hereditary disorders are frequently caused by genetic variants that affect pre-messenger RNA splicing. Though genetic variants in the canonical splice motifs are almost always disrupting splicing, the pathogenicity of variants in the noncanonical splice sites (NCSS) and deep intronic (DI) regions are difficult to predict. Multiple splice prediction tools have been developed for this purpose, with the latest tools employing deep learning algorithms. We benchmarked established and deep learning splice prediction tools on published gold standard sets of 71 NCSS and 81 DI variants in the ABCA4 gene and 61 NCSS variants in the MYBPC3 gene with functional assessment in midigene and minigene splice assays. The selection of splice prediction tools included CADD, DSSP, GeneSplicer, MaxEntScan, MMSplice, NNSPLICE, SPIDEX, SpliceAI, SpliceRover, and SpliceSiteFinder-like. The best-performing splice prediction tool for the different variants was SpliceRover for ABCA4 NCSS variants, SpliceAI for ABCA4 DI variants, and the Alamut 3/4 consensus approach (GeneSplicer, MaxEntScacn, NNSPLICE and SpliceSiteFinder-like) for NCSS variants in MYBPC3 based on the area under the receiver operator curve. Overall, the performance in a real-time clinical setting is much more modest than reported by the developers of the tools.

Strategies to Uplift Novel Mendelian Gene Discovery for Improved Clinical Outcomes

Rare genetic disorders, while individually rare, are collectively common. They represent some of the most severe disorders affecting patients worldwide with significant morbidity and mortality. Over the last decade, advances in genomic methods have significantly uplifted diagnostic rates for patients and facilitated novel and targeted therapies. However, many patients with rare genetic disorders still remain undiagnosed as the genetic etiology of only a proportion of Mendelian conditions has been discovered to date. This article explores existing strategies to identify novel Mendelian genes and how these discoveries impact clinical care and therapeutics. We discuss the importance of data sharing, phenotype-driven approaches, patient-led approaches, utilization of large-scale genomic sequencing projects, constraint-based methods, integration of multi-omics data, and gene-to-patient methods. We further consider the health economic advantages of novel gene discovery and speculate on potential future methods for improved clinical outcomes.

Unraveling synonymous and deep intronic variants causing aberrant splicing in two genetically undiagnosed epilepsy families

BACKGROUND

Variants identified through parent-child trio-WES yield up to 28-55% positive diagnostic rate across a variety of Mendelian disorders, there remain numerous patients who do not receive a genetic diagnosis. Studies showed that some aberrant splicing variants, which are either not readily detectable by WES or could be miss-interpreted by regular detecting pipelines, are highly relevant to human diseases.

METHODS

We retrospectively investigated the negative molecular diagnostics through trio-WES for 15 genetically undiagnosed patients whose clinical manifestations were highly suspected to be genetic disorders with well-established genotype-phenotype relationships. We scrutinized the synonymous variants from WES data and Sanger sequenced the suspected intronic region for deep intronic variants. The functional consequences of variants were analyzed by in vitro minigene experiments.

RESULTS

Here, we report two abnormal splicing events, one of which caused exon truncating due to the activation of cryptic splicing site by a synonymous variant; the other caused partial intron retention due to the generation of splicing sites by a deep intronic variant.

CONCLUSIONS

We suggest that, despite initial negative genetic test results in clinically highly suspected genetic diseases, the combination of predictive bioinformatics and functional analysis should be considered to unveil the genetic etiology of undiagnosed rare diseases.

A novel synonymous variant in exon 1 of GNAS gene results in a cryptic splice site and causes pseudohypoparathyroidism type 1A and pseudo-pseudohypoparathyroidism in a French family

INTRODUCTION

Pseudohypoparathyroidism type 1A (PHP1A) and pseudopseudohypoparathyroidism (PPHP) (Inactivating PTH/PTHrP Signaling Disorders type 2, IPPSD2) are two rare autosomal disorders caused by loss-of-function mutations on either maternal or paternal allele, respectively, in the imprinted GNAS gene, which encodes the α subunit of the ubiquitously-expressed stimulatory G protein (Gαs).

CASE PRESENTATION

We investigated a synonymous GNAS variant NM_001077488.2: c.108C>A / p.(Val36=) identified in a family presenting with IPPSD2 phenotype. In silico splicing prediction algorithms were in favor of a deleterious effect of this variant, by creating a new donor splicing site. The GNAS expression studies in blood suggested haploinsufficiency and showed an alternate splice product demonstrating the unmasking of a cryptic site, leading to a 34 base pairs deletion and the creation of a probable unstable RNA.We present the first familial case of IPPSD2 caused by a pathogenic synonymous variant in GNAS gene.

Clinical Utility of Functional RNA Analysis for the Reclassification of Splicing Gene Variants in Hereditary Cancer

BACKGROUND

Classification of splicing variants (SVs) in genes associated with hereditary cancer is often challenging. The aim of this study was to investigate the occurrence of SVs in hereditary cancer genes and the clinical utility of RNA analysis.

MATERIAL AND METHODS

1518 individuals were tested for cancer predisposition, using a Next Generation Sequencing (NGS) panel of 36 genes. Splicing variant analysis was performed using RT-PCR and Sanger Sequencing.

RESULTS

In total, 34 different SVs were identified, 53% of which were classified as pathogenic or likely pathogenic. The remaining 16 variants were initially classified as Variant of Uncertain Significance (VUS). RNA analysis was performed for 3 novel variants.

CONCLUSION

The RNA analysis assisted in the reclassification of 20% of splicing variants from VUS to pathogenic. RNA analysis is essential in the case of uncharacterized splicing variants, for proper classification and personalized management of these patients.

Spectrum of splicing variants in disease genes and the ability of RNA analysis to reduce uncertainty in clinical interpretation

The complexities of gene expression pose challenges for the clinical interpretation of splicing variants. To better understand splicing variants and their contribution to hereditary disease, we evaluated their prevalence, clinical classifications, and associations with diseases, inheritance, and functional characteristics in a 689,321-person clinical cohort and two large public datasets. In the clinical cohort, splicing variants represented 13% of all variants classified as pathogenic (P), likely pathogenic (LP), or variants of uncertain significance (VUSs). Most splicing variants were outside essential splice sites and were classified as VUSs. Among all individuals tested, 5.4% had a splicing VUS. If RNA analysis were to contribute supporting evidence to variant interpretation, we estimated that splicing VUSs would be reclassified in 1.7% of individuals in our cohort. This would result in a clinically significant result (i.e., P/LP) in 0.1% of individuals overall because most reclassifications would change VUSs to likely benign. In ClinVar, splicing VUSs were 4.8% of reported variants and could benefit from RNA analysis. In the Genome Aggregation Database (gnomAD), splicing variants comprised 9.4% of variants in protein-coding genes; most were rare, precluding unambiguous classification as benign. Splicing variants were depleted in genes associated with dominant inheritance and haploinsufficiency, although some genes had rare variants at essential splice sites or had common splicing variants that were most likely compatible with normal gene function. Overall, we describe the contribution of splicing variants to hereditary disease, the potential utility of RNA analysis for reclassifying splicing VUSs, and how natural variation may confound clinical interpretation of splicing variants.

Applying genomic and transcriptomic advances to mitochondrial medicine

Next-generation sequencing (NGS) has increased our understanding of the molecular basis of many primary mitochondrial diseases (PMDs). Despite this progress, many patients with suspected PMD remain without a genetic diagnosis, which restricts their access to in-depth genetic counselling, reproductive options and clinical trials, in addition to hampering efforts to understand the underlying disease mechanisms. Although they represent a considerable improvement over their predecessors, current methods for sequencing the mitochondrial and nuclear genomes have important limitations, and molecular diagnostic techniques are often manual and time consuming. However, recent advances in genomics and transcriptomics offer realistic solutions to these challenges. In this Review, we discuss the current genetic testing approach for PMDs and the opportunities that exist for increased use of whole-genome NGS of nuclear and mitochondrial DNA (mtDNA) in the clinical environment. We consider the possible role for long-read approaches in sequencing of mtDNA and in the identification of novel nuclear genomic causes of PMDs. We examine the expanding applications of RNA sequencing, including the detection of cryptic variants that affect splicing and gene expression and the interpretation of rare and novel mitochondrial transfer RNA variants.

Identification of Deep-Intronic Splice Mutations in a Large Cohort of Patients With Inherited Retinal Diseases

High throughput sequencing technologies have revolutionized the identification of mutations responsible for a diverse set of Mendelian disorders, including inherited retinal disorders (IRDs). However, the causal mutations remain elusive for a significant proportion of patients. This may be partially due to pathogenic mutations located in non-coding regions, which are largely missed by capture sequencing targeting the coding regions. The advent of whole-genome sequencing (WGS) allows us to systematically detect non-coding variations. However, the interpretation of these variations remains a significant bottleneck. In this study, we investigated the contribution of deep-intronic splice variants to IRDs. WGS was performed for a cohort of 571 IRD patients who lack a confident molecular diagnosis, and potential deep intronic variants that affect proper splicing were identified using SpliceAI. A total of six deleterious deep intronic variants were identified in eight patients. An in vitro minigene system was applied to further validate the effect of these variants on the splicing pattern of the associated genes. The prediction scores assigned to splice-site disruption positively correlated with the impact of mutations on splicing, as those with lower prediction scores demonstrated partial splicing. Through this study, we estimated the contribution of deep-intronic splice mutations to unassigned IRD patients and leveraged in silico and in vitro methods to establish a framework for prioritizing deep intronic variant candidates for mechanistic and functional analyses.

Functional characterization of ABCC8 variants of unknown significance based on bioinformatics predictions, splicing assays, and protein analyses: Benefits for the accurate diagnosis of congenital hyperinsulinism

ABCC8 encodes the SUR1 subunit of the β-cell ATP-sensitive potassium channel whose loss of function causes congenital hyperinsulinism (CHI). Molecular diagnosis is critical for optimal management of CHI patients. Unfortunately, assessing the impact of ABCC8 variants on RNA splicing remains very challenging as this gene is poorly expressed in leukocytes. Here, we performed bioinformatics analysis and cell-based minigene assays to assess the impact on splicing of 13 ABCC8 variants identified in 20 CHI patients. Next, channel properties of SUR1 proteins expected to originate from minigene-detected in-frame splicing defects were analyzed after ectopic expression in COSm6 cells. Out of the analyzed variants, seven induced out-of-frame splicing defects and were therefore classified as recessive pathogenic, whereas two led to skipping of in-frame exons. Channel functional analysis of the latter demonstrated their pathogenicity. Interestingly, the common rs757110 SNP increased exon skipping in our system suggesting that it may act as a disease modifier factor. Our strategy allowed determining the pathogenicity of all selected ABCC8 variants, and CHI-inheritance pattern for 16 out of the 20 patients. This study highlights the value of combining RNA and protein functional approaches in variant interpretation and reveals the minigene splicing assay as a new tool for CHI molecular diagnostics.

Transcriptome-directed analysis for Mendelian disease diagnosis overcomes limitations of conventional genomic testing

BACKGROUNDTranscriptome sequencing (RNA-seq) improves diagnostic rates in individuals with suspected Mendelian conditions to varying degrees, primarily by directing the prioritization of candidate DNA variants identified on exome or genome sequencing (ES/GS). Here we implemented an RNA-seq-guided method to diagnose individuals across a wide range of ages and clinical phenotypes.METHODSOne hundred fifteen undiagnosed adult and pediatric patients with diverse phenotypes and 67 family members (182 total individuals) underwent RNA-seq from whole blood and skin fibroblasts at the Baylor College of Medicine (BCM) Undiagnosed Diseases Network clinical site from 2014 to 2020. We implemented a workflow to detect outliers in gene expression and splicing for cases that remained undiagnosed despite standard genomic and transcriptomic analysis.RESULTSThe transcriptome-directed approach resulted in a diagnostic rate of 12% across the entire cohort, or 17% after excluding cases solved on ES/GS alone. Newly diagnosed conditions included Koolen-de Vries syndrome (KANSL1), Renpenning syndrome (PQBP1), TBCK-associated encephalopathy, NSD2- and CLTC-related intellectual disability, and others, all with negative conventional genomic testing, including ES and chromosomal microarray (CMA). Skin fibroblasts exhibited higher and more consistent expression of clinically relevant genes than whole blood. In solved cases with RNA-seq from both tissues, the causative defect was missed in blood in half the cases but none from fibroblasts.CONCLUSIONSFor our cohort of undiagnosed individuals with suspected Mendelian conditions, transcriptome-directed genomic analysis facilitated diagnoses, primarily through the identification of variants missed on ES and CMA.TRIAL REGISTRATIONNot applicable.FUNDINGNIH Common Fund, BCM Intellectual and Developmental Disabilities Research Center, Eunice Kennedy Shriver National Institute of Child Health & Human Development.

When phenotype does not match genotype: importance of "real-time" refining of phenotypic information for exome data interpretation

PURPOSE

Clinical data provided to genetic testing laboratories are frequently scarce. Our purpose was to evaluate clinical scenarios where phenotypic refinement in proband's family members might impact exome data interpretation.

METHODS

Of 614 exomes, 209 were diagnostic and included in this study. Phenotypic information was gathered by the variant interpretation team from genetic counseling letters and images. If a discrepancy between reported clinical findings and presumably disease-causing variant segregation was observed, referring clinicians were contacted for phenotypic clarification.

RESULTS

In 16/209 (7.7%) cases, phenotypic refinement was important due to (1) lack of cosegregation of disease-causing variant with the reported phenotype; (2) identification of different disorders with overlapping symptoms in the same family; (3) similar features in proband and family members, but molecular cause identified in proband only; and (4) previously unrecognized maternal condition causative of child's phenotype. As a result of phenotypic clarification, in 12/16 (75%) cases definition of affected versus unaffected status in one of the family members has changed, and in one case variant classification has changed.

CONCLUSION

Detailed description of phenotypes in family members including differences in clinical presentations, even if subtle, are important in exome interpretation and should be communicated to the variant interpretation team.

Phenotype Driven Analysis of Whole Genome Sequencing Identifies Deep Intronic Variants that Cause Retinal Dystrophies by Aberrant Exonization

Purpose

To demonstrate the effectiveness of combining retinal phenotyping and focused variant filtering from genome sequencing (GS) in identifying deep intronic disease causing variants in inherited retinal dystrophies.

Methods

Affected members from three pedigrees with classical enhanced S-cone syndrome (ESCS; Pedigree 1), congenital stationary night blindness (CSNB; Pedigree 2), and achromatopsia (ACHM; Pedigree 3), respectively, underwent detailed ophthalmologic evaluation, optical coherence tomography, and electroretinography. The probands underwent panel-based genetic testing followed by GS analysis. Minigene constructs (NR2E3, GPR179 and CNGB3) and patient-derived cDNA experiments (NR2E3 and GPR179) were performed to assess the functional effect of the deep intronic variants.

Results

The electrophysiological findings confirmed the clinical diagnosis of ESCS, CSNB, and ACHM in the respective pedigrees. Panel-based testing revealed heterozygous pathogenic variants in NR2E3 (NM_014249.3; c.119-2A>C; Pedigree 1) and CNGB3 (NM_019098.4; c.1148delC/p.Thr383Ilefs*13; Pedigree 3). The GS revealed heterozygous deep intronic variants in Pedigrees 1 (NR2E3; c.1100+1124G>A) and 3 (CNGB3; c.852+4751A>T), and a homozygous GPR179 variant in Pedigree 2 (NM_001004334.3; c.903+343G>A). The identified variants segregated with the phenotype in all pedigrees. All deep intronic variants were predicted to generate a splice acceptor gain causing aberrant exonization in NR2E3 [89 base pairs (bp)], GPR179 (197 bp), and CNGB3 (73 bp); splicing defects were validated through patient-derived cDNA experiments and/or minigene constructs and rescued by antisense oligonucleotide treatment.

Conclusions

Deep intronic mutations contribute to missing heritability in retinal dystrophies. Combining results from phenotype-directed gene panel testing, GS, and in silico splice prediction tools can help identify these difficult-to-detect pathogenic deep intronic variants.

Identification of a deep intronic POLR3A variant causing inclusion of a pseudoexon derived from an Alu element in Pol III-related leukodystrophy

Pseudoexon inclusion caused by deep intronic variants is an important genetic cause for various disorders. Here, we present a case of a hypomyelinating leukodystrophy with developmental delay, intellectual disability, autism spectrum disorder, and hypodontia, which are consistent with autosomal recessive POLR3-related leukodystrophy. Whole-exome sequencing identified only a heterozygous missense variant (c.1451G>A) in POLR3A. To explore possible involvement of a deep intronic variant in another allele, we performed whole-genome sequencing of the patient with variant annotation by SpliceAI, a deep-learning-based splicing prediction tool. A deep intronic variant (c.645 + 312C>T) in POLR3A, which was predicted to cause inclusion of a pseudoexon derived from an Alu element, was identified and confirmed by mRNA analysis. These results clearly showed that whole-genome sequencing, in combination with deep-learning-based annotation tools such as SpliceAI, will bring us further benefits in detecting and evaluating possible pathogenic variants in deep intronic regions.

Genetics of mitochondrial diseases: Identifying mutations to help diagnosis

Mitochondrial diseases are amongst the most genetically and phenotypically diverse groups of inherited diseases. The vast phenotypic overlap with other disease entities together with the absence of reliable biomarkers act as driving forces for the integration of unbiased methodologies early in the diagnostic algorithm, such as whole exome sequencing (WES) and whole genome sequencing (WGS). Such approaches are used in variant discovery and in combination with high-throughput functional assays such as transcriptomics in simultaneous variant discovery and validation. By capturing all genes, they not only increase the diagnostic rate in heterogenous mitochondrial disease patients, but accelerate novel disease gene discovery, and are valuable in side-stepping the risk of overlooking unexpected or even treatable genetic disease diagnoses.