INSERM U827, Laboratoire de Génétique de Maladies Rares, Montpellier, France.
Université Montpellier I, UFR de Médecine, Montpellier, France.
Genet Med. 2015 Oct;17(10):796-806. doi: 10.1038/gim.2014.194. Epub 2015 Jan 8.
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.
尽管已经鉴定出 97%-99%的 CFTR 突变，但仍需努力发现尚未鉴定出的突变。
我们开发了一种小规模的下一代测序方法，可可靠且快速地扫描整个基因，包括非编码区，以鉴定新的突变。我们将该方法应用于 18 名患有囊性纤维化 (CF) 的患者的样本，这些患者此前仅鉴定出一种突变。
使用内部生物信息学管道，我们能够快速鉴定出 18 个样本中的 16 个样本中的第二个致病 CFTR 突变。其中，在三个无关联的 CF 患者中发现了 c.1680-883A>G 突变。对小基因和患者转录本的分析表明，该突变导致异常剪接转录本，因为包含了假外显子。它仅位于 c.1680-886A>G 突变（1811+1.6kbA>G）的三个碱基对内，这是在西欧第四个最常见的突变。我们接下来测试了针对这两个突变的针对剪接位点的反义寡核苷酸的效果，在假性外显子跳过。寡核苷酸转染导致全长、框架内 CFTR 转录本的恢复，证明了反义寡核苷酸诱导假性外显子跳过在 CF 中的作用。
我们的数据证实了分析非编码区以发现未鉴定突变的重要性，这对于设计靶向治疗方法至关重要。
