Identification of a splicing enhancer in MLH1 using COMPARE, a new assay for determination of relative RNA splicing efficiencies

Genetic and Clinical Analyses of the KIZ-c.226C>T Variant Resulting in a Dual Mutational Mechanism

Retinitis pigmentosa (RP) is a heterogeneous inherited retinal disorder. Mutations in KIZ cause autosomal recessive (AR) RP. We aimed to characterize the genotype, expression pattern, and phenotype in a large cohort of KIZ cases. Sanger and whole exome sequencing were used to identify the KIZ variants. Medical records were reviewed and analyzed. Thirty-one patients with biallelic KIZ mutations were identified: 28 homozygous for c.226C>T (p.R76*), 2 compound heterozygous for p.R76* and c.3G>A (p.M1?), and one homozygous for c.247C>T (p.R83*). c.226C>T is a founder mutation among patients of Jewish descent. The clinical parameters were less severe in KIZ compared to DHDDS and FAM161A cases. RT-PCR analysis in fibroblast cells revealed the presence of four different transcripts in both WT and mutant samples with a lower percentage of the WT transcript in patients. Sequence analysis identified an exonic sequence enhancer (ESE) that includes the c.226 position which is affected by the mutation. KIZ mutations are an uncommon cause of IRD worldwide but are not rare among Ashkenazi Jews. Our data indicate that p.R76* affect an ESE which in turn results in the pronounced skipping of exon 3. Therefore, RNA-based therapies might show low efficacy since the mutant transcripts are spliced.

In silico and in vivo splicing analysis of MLH1 and MSH2 missense mutations shows exon- and tissue-specific effects

BACKGROUND

Abnormalities of pre-mRNA splicing are increasingly recognized as an important mechanism through which gene mutations cause disease. However, apart from the mutations in the donor and acceptor sites, the effects on splicing of other sequence variations are difficult to predict. Loosely defined exonic and intronic sequences have been shown to affect splicing efficiency by means of silencing and enhancement mechanisms. Thus, nucleotide substitutions in these sequences can induce aberrant splicing. Web-based resources have recently been developed to facilitate the identification of nucleotide changes that could alter splicing. However, computer predictions do not always correlate with in vivo splicing defects. The issue of unclassified variants in cancer predisposing genes is very important both for the correct ascertainment of cancer risk and for the understanding of the basic mechanisms of cancer gene function and regulation. Therefore we aimed to verify how predictions that can be drawn from in silico analysis correlate with results obtained in an in vivo splicing assay.

RESULTS

We analysed 99 hMLH1 and hMSH2 missense mutations with six different algorithms. Transfection of three different cell lines with 20 missense mutations, showed that a minority of them lead to defective splicing. Moreover, we observed that some exons and some mutations show cell-specific differences in the frequency of exon inclusion.

CONCLUSION

Our results suggest that the available algorithms, while potentially helpful in identifying splicing modulators especially when they are located in weakly defined exons, do not always correspond to an obvious modification of the splicing pattern. Thus caution must be used in assessing the pathogenicity of a missense or silent mutation with prediction programs. The variations observed in the splicing proficiency in three different cell lines suggest that nucleotide changes may dictate alternative splice site selection in a tissue-specific manner contributing to the widely observed phenotypic variability in inherited cancers.