Small-scale high-throughput sequencing-based identification of new therapeutic tools in cystic fibrosis

Although 97-99% of CFTR mutations have been identified, great efforts must be made to detect yet-unidentified mutations.

We developed a small-scale next-generation sequencing approach for reliably and quickly scanning the entire gene, including noncoding regions, to identify new mutations. We applied this approach to 18 samples from patients suffering from cystic fibrosis (CF) in whom only one mutation had hitherto been identified.

Using an in-house bioinformatics pipeline, we could rapidly identify a second disease-causing CFTR mutation for 16 of 18 samples. Of them, c.1680-883A>G was found in three unrelated CF patients. Analysis of minigenes and patients' transcripts showed that this mutation results in aberrantly spliced transcripts because of the inclusion of a pseudoexon. It is located only three base pairs from the c.1680-886A>G mutation (1811+1.6kbA>G), the fourth most frequent mutation in southwestern Europe. We next tested the effect of antisense oligonucleotides targeting splice sites on these two mutations on pseudoexon skipping. Oligonucleotide transfection resulted in the restoration of the full-length, in-frame CFTR transcript, demonstrating the effect of antisense oligonucleotide-induced pseudoexon skipping in CF.

Our data confirm the importance of analyzing noncoding regions to find unidentified mutations, which is essential to designing targeted therapeutic approaches.