Title |
Newborn Screening Quality Assurance Program for CFTR Mutation Detection and Gene Sequencing to Identify Cystic Fibrosis
|
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Published in |
Journal of Inborn Errors of Metabolism and Screening, October 2016
|
DOI | 10.1177/2326409816661358 |
Pubmed ID | |
Authors |
Miyono M. Hendrix, Stephanie L. Foster, Suzanne K. Cordovado |
Abstract |
All newborn screening laboratories in the United States and many worldwide screen for cystic fibrosis. Most laboratories use a second-tier genotyping assay to identify a panel of mutations in the CF transmembrane regulator (CFTR) gene. Centers for Disease Control and Prevention's Newborn Screening Quality Assurance Program houses a dried blood spot repository of samples containing CFTR mutations to assist newborn screening laboratories and ensure high-quality mutation detection in a high-throughput environment. Recently, CFTR mutation detection has increased in complexity with expanded genotyping panels and gene sequencing. To accommodate the growing quality assurance needs, the repository samples were characterized with several multiplex genotyping methods, Sanger sequencing, and 3 next-generation sequencing assays using a high-throughput, low-concentration DNA extraction method. The samples performed well in all of the assays, providing newborn screening laboratories with a resource for complex CFTR mutation detection and next-generation sequencing as they transition to new methods. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 29 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Bachelor | 4 | 14% |
Other | 4 | 14% |
Student > Master | 3 | 10% |
Student > Ph. D. Student | 3 | 10% |
Researcher | 2 | 7% |
Other | 5 | 17% |
Unknown | 8 | 28% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 10 | 34% |
Medicine and Dentistry | 4 | 14% |
Agricultural and Biological Sciences | 3 | 10% |
Computer Science | 1 | 3% |
Unspecified | 1 | 3% |
Other | 2 | 7% |
Unknown | 8 | 28% |