BACKGROUND: Cystic fibrosis is a life-threatening genetic disorder that has been associated with mutations in the CFTR [cystic fibrosis transmembrane conductance regulator (ATP-binding cassette sub-family C, member 7)] gene. Hundreds of CFTR mutations have been detected to date. Current CFTR genotyping assays target a subset of these mutations, particularly a mutation panel recommended by the American College of Medical Genetics for carrier screening of the general population. Fast sequencing of the entire coding sequence in a scalable manner could expand the detection of CFTR mutations and facilitate management of costs and turnaround times in the clinical laboratory. METHODS: We describe a proof-of-concept CFTR assay that uses PCR target enrichment and next-generation sequencing on the Ion Torrent Personal Genome Machine™ (PGM™) platform. RESULTS: The scalability of the assay was demonstrated, with an average mean depth of coverage ranging from 500× to 3500×, depending on the number of multiplexed patient samples and the Ion Torrent chip used. In a blinded study of 79 previously genotyped patient DNA samples and cell lines, our assay detected most of the mutations, including single-nucleotide variants, small insertions and deletions, and large copy-number variants. The reproducibility was 100% for detecting mutations in independent runs. Our assay demonstrated high specificity, with only 2 false-positive calls (at 2184delA) found in 2 samples caused by a sequencing error in a homopolymer stretch of sequence. The detection rate for variants of unknown significance was very low in the targeted region. CONCLUSIONS: With continued optimization and system refinements, PGM sequencing promises to be a powerful, rapid, and scalable means of clinical diagnostic sequencing.
BACKGROUND:Cystic fibrosis is a life-threatening genetic disorder that has been associated with mutations in the CFTR [cystic fibrosis transmembrane conductance regulator (ATP-binding cassette sub-family C, member 7)] gene. Hundreds of CFTR mutations have been detected to date. Current CFTR genotyping assays target a subset of these mutations, particularly a mutation panel recommended by the American College of Medical Genetics for carrier screening of the general population. Fast sequencing of the entire coding sequence in a scalable manner could expand the detection of CFTR mutations and facilitate management of costs and turnaround times in the clinical laboratory. METHODS: We describe a proof-of-concept CFTR assay that uses PCR target enrichment and next-generation sequencing on the Ion Torrent Personal Genome Machine™ (PGM™) platform. RESULTS: The scalability of the assay was demonstrated, with an average mean depth of coverage ranging from 500× to 3500×, depending on the number of multiplexed patient samples and the Ion Torrent chip used. In a blinded study of 79 previously genotyped patient DNA samples and cell lines, our assay detected most of the mutations, including single-nucleotide variants, small insertions and deletions, and large copy-number variants. The reproducibility was 100% for detecting mutations in independent runs. Our assay demonstrated high specificity, with only 2 false-positive calls (at 2184delA) found in 2 samples caused by a sequencing error in a homopolymer stretch of sequence. The detection rate for variants of unknown significance was very low in the targeted region. CONCLUSIONS: With continued optimization and system refinements, PGM sequencing promises to be a powerful, rapid, and scalable means of clinical diagnostic sequencing.
Authors: Erin Rooney Riggs; Karen E Wain; Darlene Riethmaier; Melissa Savage; Bethanny Smith-Packard; Erin B Kaminsky; Heidi L Rehm; Christa Lese Martin; David H Ledbetter; W Andrew Faucett Journal: Hum Mutat Date: 2013-04-02 Impact factor: 4.878
Authors: T Dörk; M Macek; F Mekus; B Tümmler; J Tzountzouris; T Casals; A Krebsová; M Koudová; I Sakmaryová; M Macek; V Vávrová; D Zemková; E Ginter; N V Petrova; T Ivaschenko; V Baranov; M Witt; A Pogorzelski; J Bal; C Zékanowsky; K Wagner; M Stuhrmann; I Bauer; H H Seydewitz; T Neumann; S Jakubiczka Journal: Hum Genet Date: 2000-03 Impact factor: 4.132
Authors: Charles M Strom; Beryl Crossley; Arlene Buller-Buerkle; Michael Jarvis; Franklin Quan; Mei Peng; Kasinathan Muralidharan; Victoria Pratt; Joy B Redman; Weimin Sun Journal: Genet Med Date: 2011-02 Impact factor: 8.822
Authors: Michael S Watson; Garry R Cutting; Robert J Desnick; Deborah A Driscoll; Katherine Klinger; Michael Mennuti; Glenn E Palomaki; Bradley W Popovich; Victoria M Pratt; Elizabeth M Rohlfs; Charles M Strom; C Sue Richards; David R Witt; Wayne W Grody Journal: Genet Med Date: 2004 Sep-Oct Impact factor: 8.822
Authors: Martina I Lefterova; Peidong Shen; Justin I Odegaard; Eula Fung; Tsoyu Chiang; Gang Peng; Ronald W Davis; Wenyi Wang; Martin Kharrazi; Iris Schrijver; Curt Scharfe Journal: J Mol Diagn Date: 2016-02-01 Impact factor: 5.568
Authors: Emma L Williams; Eleanor A L Bagg; Michael Mueller; Jana Vandrovcova; Timothy J Aitman; Gill Rumsby Journal: Mol Genet Genomic Med Date: 2015-01 Impact factor: 2.183
Authors: Vincenza Precone; Valentina Del Monaco; Maria Valeria Esposito; Fatima Domenica Elisa De Palma; Anna Ruocco; Francesco Salvatore; Valeria D'Argenio Journal: Biomed Res Int Date: 2015-11-19 Impact factor: 3.411