Abstract

Cystic fibrosis (CF) is one of the most frequently diagnosed autosomal-recessive diseases in the Caucasian population. For general-population CF carrier screening, the American College of Medical Genetics (ACMG)/American College of Obstetricians and Gynecologists (ACOG) have recommended a core panel of 23 mutations that will identify 49-98% of carriers, depending on ethnic background. Using a genotyping technology that can rapidly identify disease-causing mutations is important for high-throughput general-population carrier screening, confirming clinical diagnosis, determining treatment options, and prenatal diagnosis. Here, we describe a proof-of-concept study to determine whether the Ion Torrent Personal Genome Machine (PGM) sequencer platform can reliably identify all ACMG/ACOG 23 CF transmembrane conductance regulator (CFTR) mutations. A WT CF specimen along with mutant DNA specimens representing all 23 CFTR mutations were sequenced bidirectionally on the Ion Torrent 314 chip to determine the accuracy of the PGM for CFTR variant detection. We were able to reliably identify all of the targeted mutations except for 2184delA, which lies in a difficult, 7-mer homopolymer tract. Based on our study, we believe PGM sequencing may be a suitable technology for identifying CFTR mutations in the future. However, as a result of the elevated rate of base-calling errors within homopolymer stretches, mutations within such regions currently need to be evaluated carefully using an alternative method.

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