Introduction
In the diagnosis of X-Linked Alport Syndrome (XLAS), functionally validating intronic splicing variants is challenging due to difficulties in obtaining patient samples (e.g., skin fibroblasts or urine cells), which is both time-consuming and invasive. An innovative study established a non-invasive, efficient detection system (PHA-induced lymphoblastoid cells) and combined it with the predictive power of the RDDC RNA Splicing Prediction Model. In this research, RDDC successfully predicted the pathogenic splicing effect of a novel intronic variant in the COL4A5 gene. This prediction was subsequently validated by multiple assays (lymphoblastoid cells, iPSCs, and minigene), providing a crucial "prediction-validation" paradigm for the molecular diagnosis of XLAS.
Research Challenge: WES Identifies in cis Intronic VUSs
The challenge in this study originated from a 5-year-old XLAS patient. Whole Exome Sequencing (WES) identified two intronic variants located on the same chromosome (in cis) in his COL4A5 gene: c.465+29T>G and c.4822-12T>C. Both variants are located in non-coding regions, are absent from public databases, and were classified as "Variants of Uncertain Significance" (VUS). To determine which variant was pathogenic and how it caused the disease, bioinformatic prediction and functional validation were essential.
RDDC's Precise Prediction: Pinpointing the Causal Variant
To assess the potential pathogenic mechanisms of these two VUSs, researchers used the RDDC RNA Splicing Prediction Model. The RDDC AI model provided distinctly different predictions for the two variants:
Prediction Results
- For
c.465+29T>G: RDDC predicted no significant impact on splicing signals. - For
c.4822-12T>C: RDDC predicted the variant would likely activate a cryptic splice site, leading to aberrant splicing.
RDDC's predictions clearly directed the research focus onto c.4822-12T>C as the critical pathogenic variant and provided a specific hypothesis for its mechanism (activation of a cryptic site).
Multi-Assay Validation: Confirming RDDC's Accuracy
The research team then validated RDDC's predictions using three different experimental approaches:
Lymphoblastoid and iPSC Validation
By inducing patient PBMCs into lymphoblastoid cells and Induced Pluripotent Stem Cells (iPSCs) (both valid models for COL4A5 expression), RT-PCR analysis showed that the c.4822-12T>C variant indeed caused the skipping of exon 52, producing a truncated protein (p.M1601fsTer1). Conversely, the c.465+29T>G variant caused no splicing abnormalities.
Minigene Assay
Minigene assay: The mutant vector (containing c.4822-12T>C) produced a 331 bp aberrant transcript (representing exon 52 deletion), while the wild-type vector produced the 504 bp normal transcript.
Validation Conclusion
The results from all three experimental methods were in perfect agreement with the predictions made by the RDDC RNA Splicing Prediction Model (RNA Splicer). This concordance between in silico prediction and in vitro validation successfully identified c.4822-12T>C as the pathogenic variant and confirmed c.465+29T>G as benign.
Case Implications
This case powerfully demonstrates that RDDC RNA Splicer is a robust tool for identifying and assessing the pathogenicity of intronic VUSs in WES data. It can accurately distinguish "pathogenic" from "benign" signals within complex variant patterns (like in cis variants), and its predictions can effectively guide subsequent functional validation. This "RDDC prediction + cell model/Minigene validation" pathway not only reduced the diagnostic turnaround time from 15 days to just 3 days but also identified a clear target (c.4822-12T>C induced exon skipping) for potential Antisense Oligonucleotide (ASO) therapies, serving as a critical tool in advancing the translation from genetic discovery to clinical intervention for rare diseases.
Content Source and Disclaimer
This article is a compilation and interpretation of the scientific study cited below, intended to highlight the application of RDDC bioinformatics tools. All research data and conclusions belong to the original authors and publication.
Original Article
Li Y, Tian R, Hei Y, et al. Detection of Pathogenic Intronic Variants for COL4A5 Gene in X-Linked Alport Syndrome: Developing a Novel Methodology. Human Mutation. 2025.
Article Link: https://onlinelibrary.wiley.com/doi/full/10.1155/humu/1443580
