BACKGROUND: Pathogenic variants in BRCA genes play a crucial role in the pathogenesis of ovarian cancer. Intronic variants of uncertain significance (VUS) may contribute to pathogenicity by affecting splicing. Currently, the significance of many intronic variants in BRCA has not been clarified, impacting patient treatment strategies and the management of familial cases.
METHODS: A retrospective study was conducted to analyze BRCA intronic VUS in a cohort of 707 unrelated ovarian cancer patients at a single institution from 2018 to 2023. Three splicing predictors were employed to analyze detected intronic VUS. Variants predicted to have splicing alterations were selected for further validation through minigene assays. Patient and familial investigations were conducted to comprehend cancer incidence within pedigrees and the application of poly (ADP-ribose) polymerase inhibitors (PARPi) by the patients. In accordance with the guidelines of the American College of Medical Genetics and Genomics (ACMG), the intronic VUS were reclassified based on minigene assay results and clinical evidence.
RESULTS: Approximately 9.8% (69/707) of patients were identified as carriers of 67 different VUS in BRCA1/2, with four intronic variants accounting for 6% (4/67) of all VUS. Splicing predictors indicated potential splicing alterations in splicing for BRCA1 c.4358-2A>G and BRCA2 c.475+5G>C variants. Minigene assays utilizing the pSPL3 exon trapping vector revealed that these variants induced changes in splicing sites and frameshift, resulting in premature termination of translation (p. Ala1453Glyfs and p. Pro143Glyfs). According to ACMG guidelines, BRCA1 c.4358-2A>G and BRCA2 c.475+5G>C were reclassified as pathogenic variants. Pedigree investigations were conducted on patients with BRCA1 c.4358-2A>G variant, and the detailed utilization of PARPi provided valuable insights into research on PARPi resistance.
CONCLUSIONS: Two intronic VUS were reclassified as pathogenic variants. A precise classification of variants is crucial for the effective treatment and management of both patients and healthy carriers.

BACKGROUND: Antenatal Bartter syndrome is a life-threatening disease caused by a mutation in the MAGED2 gene located on chromosome Xp11. It is characterized by severe polyhydramnios and extreme prematurity. While most reported mutations are located in the exon region, variations in the intron region are rarely reported.
METHODS: In our study, we employed whole exome sequencing and Sanger sequencing to genotype members of this family. Additionally, a minigene assay was conducted to evaluate the impact of genetic variants on splicing.
RESULTS: Our findings reveal a novel intronic variant (NM_177433.3:c.1271 + 4_1271 + 7delAGTA) in intron 10 of the MAGED2 gene. Further analysis using the minigene assay demonstrated that this variant activated an intronic cryptic splice site, resulting in a 96 bp insertion in mature mRNA.
CONCLUSIONS: Our results indicate that the novel intronic variant (c.1271 + 4_1271 + 7delAGTA) in intron 10 of the MAGED2 gene is pathogenic. This expands the mutation spectrum of MAGED2 and highlights the significance of intronic sequence analysis.

Human genetic variants that introduce an AG into the intronic region between the branchpoint (BP) and the canonical splice acceptor site (ACC) of protein-coding genes can disrupt pre-mRNA splicing. Using our genome-wide BP database, we delineated the BP-ACC segments of all human introns and found extreme depletion of AG/YAG in the [BP+8, ACC-4] high-risk region. We developed AGAIN as a genome-wide computational approach to systematically and precisely pinpoint intronic AG-gain variants within the BP-ACC regions. AGAIN identified 350 AG-gain variants from the Human Gene Mutation Database, all of which alter splicing and cause disease. Among them, 74% created new acceptor sites, whereas 31% resulted in complete exon skipping. AGAIN also predicts the protein-level products resulting from these two consequences. We performed AGAIN on our exome/genomes database of patients with severe infectious diseases but without known genetic etiology and identified a private homozygous intronic AG-gain variant in the antimycobacterial gene SPPL2A in a patient with mycobacterial disease. AGAIN also predicts a retention of six intronic nucleotides that encode an in-frame stop codon, turning AG-gain into stop-gain. This allele was then confirmed experimentally to lead to loss of function by disrupting splicing. We further showed that AG-gain variants inside the high-risk region led to misspliced products, while those outside the region did not, by two case studies in genes STAT1 and IRF7. We finally evaluated AGAIN on our 14 paired exome-RNAseq samples and found that 82% of AG-gain variants in high-risk regions showed evidence of missplicing. AGAIN is publicly available from https://hgidsoft.rockefeller.edu/AGAIN and https://github.com/casanova-lab/AGAIN.

We present the case of a male patient who was ultimately diagnosed with Becker muscular dystrophy (BMD; MIM# 300376) after the onset of muscle weakness in his teens progressively led to significant walking difficulties in his twenties. A genetic diagnosis was pursued but initial investigation revealed no aberrations in the dystrophin gene (DMD), although immunohistochemistry and Western blot analysis suggested the diagnosis of dystrophinopathy. Eventually, after more than 10 years, an RNA analysis captured abnormal splicing where 154 nucleotides from intron 43 were inserted between exon 43 and 44 resulting in a frameshift and a premature stop codon. Normal splicing of the DMD gene was also observed. Additionally, a novel variant c.6291-13537A>G in DMD was confirmed in the genomic DNA of the patient. The predicted function of the variant aligns with the mRNA results. To conclude, we here demonstrate that mRNA analysis can guide the diagnosis of non-coding genetic variants in DMD.

Objective: Variants of the polycystic kidney and hepatic disease 1 (PKHD1) gene are associated with autosomal recessive polycystic kidney disease (ARPKD). This study aimed to identify the genetic causes in a Chinese pedigree with ARPKD and design a minigene construct of the PKHD1 gene to investigate the impact of its variants on splicing. Methods: Umbilical cord samples from the proband and peripheral blood samples from his parents were collected, and genomic DNA was extracted for whole-exome sequencing (WES). Bioinformatic analysis was used to identify potential genetic causes, and Sanger sequencing confirmed the existence of variants within the pedigree. A minigene assay was performed to validate the effects of an intronic variant on mRNA splicing. Results: Two variants, c.9455del (p.N3152Tfs*10) and c.2408-13C>G, were identified in the PKHD1 gene (NM_138694.4) by WES; the latter has not been previously reported. In silico analysis predicted that this intronic variant is potentially pathogenic. Bioinformatic splice prediction tools revealed that the variant is likely to strongly impact splice site function. An in vitro minigene assay revealed that c.2408-13C>G can cause aberrant splicing, resulting in the retention of 12 bp of intron 23. Conclusion: A novel pathogenic variant of PKHD1, c.2408-13C>G, was found in a fetus with ARPKD, which enriches the variant spectrum of the PKHD1 gene and provides a basis for genetic counseling and the diagnosis of ARPKD. Minigenes are optimal to determine whether intron variants can cause aberrant splicing.

Predicting the impact of coding and noncoding variants on splicing is challenging, particularly in non-canonical splice sites, leading to missed diagnoses in patients. Existing splice prediction tools are complementary but knowing which to use for each splicing context remains difficult. Here, we describe Introme, which uses machine learning to integrate predictions from several splice detection tools, additional splicing rules, and gene architecture features to comprehensively evaluate the likelihood of a variant impacting splicing. Through extensive benchmarking across 21,000 splice-altering variants, Introme outperformed all tools (auPRC: 0.98) for the detection of clinically significant splice variants. Introme is available at https://github.com/CCICB/introme .

Background: Because CHARGE syndrome is characterized by high clinical variability, molecular confirmation of the clinical diagnosis is of pivotal importance. Most patients have a pathogenic variant in the CHD7 gene; however, variants are distributed throughout the gene and most cases are due to de novo mutations. Often, assessing the pathogenetic effect of a variant can be challenging, requiring the design of a unique assay for each specific case. Method: Here we describe a new CHD7 intronic variant, c.5607+17A>G, identified in two unrelated patients. In order to characterize the molecular effect of the variant, minigenes were constructed using exon trapping vectors. Results: The experimental approach pinpoints the pathogenetic effect of the variant on CHD7 gene splicing, subsequently confirmed using cDNA synthetized from RNA extracted from patient lymphocytes. Our results were further corroborated by the introduction of other substitutions at the same nucleotide position, showing that c.5607+17A>G specifically alters splicing possibly due to the generation of a recognition motif for the recruitment of a splicing effector. Conclusion: Here we identify a novel pathogenetic variant affecting splicing, and we provide a detailed molecular characterization and possible functional explanation.

Non-coding regions are areas of the genome that do not directly encode protein and were initially thought to be of little biological relevance. However, subsequent identification of pathogenic variants in these regions indicates there are exceptions to this assertion. With the increasing availability of next generation sequencing, variants in non-coding regions are often considered when no causative exonic changes have been identified. There is still a lack of understanding of normal human variation in non-coding areas. As a result, potentially pathogenic non-coding variants are initially classified as variants of uncertain significance or are even overlooked during genomic analysis. In most cases where the phenotype is non-specific, clinical suspicion is not sufficient to warrant further exploration of these changes, partly due to the magnitude of non-coding variants identified. In contrast, inborn errors of metabolism (IEMs) are one group of genetic disorders where there is often high phenotypic specificity. The clinical and biochemical features seen often result in a narrow list of diagnostic possibilities. In this context, there have been numerous cases in which suspicion of a particular IEM led to the discovery of a variant in a non-coding region. We present four patients with IEMs where the molecular aetiology was identified within non-coding regions. Confirmation of the molecular diagnosis is often aided by the clinical and biochemical specificity associated with IEMs. Whilst the clinical severity associated with a non-coding variant can be difficult to predict, obtaining a molecular diagnosis is crucial as it ends diagnostic odysseys and assists in management.

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

N6-methyladenosine (m6A) is essential in the regulation of the immune system, but the role that its single nucleotide polymorphisms (SNPs) play in the pathogenesis of type 1 diabetes (T1D) remains unknown. This study demonstrated the association between genetic variants in m6A regulators and T1D risk based on a case-control study in a Chinese population.
The tagging SNPs in m6A regulators were genotyped in 1005 autoantibody-positive patients with T1D and 1257 controls using the Illumina Human OmniZhongHua-8 platform. Islet-specific autoantibodies were examined by radioimmunoprecipitation in all the patients. The mixed-meal glucose tolerance test was performed on 355 newly diagnosed patients to evaluate their residual islet function. The functional annotations for the identified SNPs were performed in silico. Using 102 samples from a whole-genome expression microarray, key signaling pathways associated with m6A regulators in T1D were comprehendingly evaluated.
Under the additive model, we observed three tag SNPs in the noncoding region of the PRRC2A (rs2260051, rs3130623) and YTHDC2 (rs1862315) gene are associated with T1D risk. Although no association was found between these SNPs and islet function, patients carrying risk variants had a higher positive rate for ZnT8A, GADA, and IA-2A. Further analyses showed that rs2260051[T] was associated with increased expression of PRRC2A mRNA (P = 7.0E-13), and PRRC2A mRNA was significantly higher in peripheral blood mononuclear cell samples from patients with T1D compared to normal samples (P = 0.022). Enrichment analyses indicated that increased PRRC2A expression engages in the most significant hallmarks of cytokine-cytokine receptor interaction, cell adhesion and chemotaxis, and neurotransmitter regulation pathways. The potential role of increased PRRC2A in disrupting immune homeostasis is through the PI3K/AKT pathway and neuro-immune interactions.
This study found intronic variants in PRRC2A and YTHDC2 associated with T1D risk in a Chinese Han population. PRRC2A rs2260051[T] may be implicated in unbalanced immune homeostasis by affecting the expression of PRRC2A mRNA. These findings enriched our understanding of m6A regulators and their intronic SNPs that underlie the pathogenesis of T1D.