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. 1999;13(4):318-27.
doi: 10.1002/(SICI)1098-1004(1999)13:4<318::AID-HUMU9>3.0.CO;2-F.

High-throughput single-strand conformation polymorphism analysis by automated capillary electrophoresis: robust multiplex analysis and pattern-based identification of allelic variants

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High-throughput single-strand conformation polymorphism analysis by automated capillary electrophoresis: robust multiplex analysis and pattern-based identification of allelic variants

L A Larsen et al. Hum Mutat. 1999.

Abstract

Genetic diagnosis of an inherited disease or cancer often involves analysis for unknown point mutations in several genes; therefore, rapid and automated techniques that can process a large number of samples are needed. We describe a method for high-throughput single-strand conformation polymorphism (SSCP) analysis using automated capillary electrophoresis. The operating temperature of a commercially available capillary electrophoresis instrument (ABI PRISM 310) was expanded by installation of a cheap in-house designed cooling system, thereby allowing us to perform automated SSCP analysis at 14-45 degrees C. We have used the method for detection of point mutations associated with the inherited cardiac disorders long QT syndrome (LQTS) and hypertrophic cardiomyopathy (HCM). The sensitivity of the method was 100% when 34 different point mutations were analyzed, including two previously unpublished LQTS-associated mutations (F157C in KVLQT1 and G572R in HERG), as well as eight novel normal variants in HERG and MYH7. The analyzed polymerase chain reaction (PCR) fragments ranged in size from 166 to 1,223 bp. Seventeen different sequence contexts were analyzed. Three different electrophoresis temperatures were used to obtain 100% sensitivity. Two mutants could not be detected at temperatures greater than 20 degrees C. The method has a high resolution and good reproducibility and is very robust, making multiplex SSCP analysis and pattern-based identification of known allelic variants as single nucleotide polymorphisms (SNPs) possible. These possibilities, combined with automation and short analysis time, make the method suitable for high-throughput tasks, such as genetic screening.

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