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.
CONCLUSIONS: 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.

For more than three decades, researchers have known that consensus splice sites alone are not sufficient regulatory elements to provide complex splicing regulation. Other regulators, so-called splicing regulatory elements (SREs) are needed. Most importantly, their sequence variants often underlie the development of various human disorders. However, due to their variable location and high degeneracy, these regulatory sequences are also very difficult to recognize and predict. Many different approaches aiming to identify SREs have been tried, often leading to the development of in silico prediction tools. While these tools were initially expected to be helpful to identify splicing-affecting mutations in genetic diagnostics, we are still quite far from meeting this goal. In fact, most of these tools are not able to accurately discern the SRE-affecting pathological variants from those not affecting splicing. Nonetheless, several recent evaluations have given appealing results (namely for EX-SKIP, ESRseq and Hexplorer predictors). In this review, we aim to summarize the history of the different approaches to SRE prediction, and provide additional validation of these tools based on patients\' clinical data. Finally, we evaluate their usefulness for diagnostic settings and discuss the challenges that have yet to be met.