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A digital coding combination analysis for mutational genotyping using pyrosequencing.
Wei, Rongbin; Fei, Zhongjie; Liu, Yanrong; Fu, Bangwen; Chen, Ling; Wang, Liu; Xiao, Pengfeng.
Afiliación
  • Wei R; State Key Laboratory of Bioelectronics, National Demonstration Center for Experimental Biomedical Engineering Education, School of Biological Science and Medical Engineering, Southeast University, Nanjing, P. R. China.
  • Fei Z; State Key Laboratory of Bioelectronics, National Demonstration Center for Experimental Biomedical Engineering Education, School of Biological Science and Medical Engineering, Southeast University, Nanjing, P. R. China.
  • Liu Y; Heze Center for Disease Control and Prevention, Heze, P. R. China.
  • Fu B; State Key Laboratory of Bioelectronics, National Demonstration Center for Experimental Biomedical Engineering Education, School of Biological Science and Medical Engineering, Southeast University, Nanjing, P. R. China.
  • Chen L; State Key Laboratory of Bioelectronics, National Demonstration Center for Experimental Biomedical Engineering Education, School of Biological Science and Medical Engineering, Southeast University, Nanjing, P. R. China.
  • Wang L; State Key Laboratory of Bioelectronics, National Demonstration Center for Experimental Biomedical Engineering Education, School of Biological Science and Medical Engineering, Southeast University, Nanjing, P. R. China.
  • Xiao P; State Key Laboratory of Bioelectronics, National Demonstration Center for Experimental Biomedical Engineering Education, School of Biological Science and Medical Engineering, Southeast University, Nanjing, P. R. China.
Electrophoresis ; 42(11): 1262-1269, 2021 06.
Article en En | MEDLINE | ID: mdl-33641189
In the present study, we developed a novel digital coding combination analysis (DCCA) to analyze the gene mutation based on the sample combination principle. The principle is that any numerically named sample is divided into two groups, any two samples are not grouped in the same two groups, and any sample can be tested within the detection limit. Therefore, we proposed a specific combination that N samples were divided into M groups. Then N samples were analyzed, which could obtain the mutation results of M mixed groups. If only two groups showed positive (mutant type) signals, the same sample number from two positive signal groups would be the positive sample, and the remaining samples were negative (wild type). If three groups or more exhibited positive results, the same sample number from three positive signal groups would be the positive sample. If some samples remained uncertain, individual samples could be analyzed on a small scale. In the present study, we used the two genotypes of a mutation site (A5301G) to verify whether it was a useful and promising method. The results showed that we could quantitatively detect mutations and demonstrate 100% consistent results against a panel of defined mixtures with the detection limit using pyrosequencing. This method was suitable, sensitive, and reproducible for screening and analyzing low-frequency mutation samples, which could reduce reagent consumption and cost by approximately 70-80% compared with conventional clinical methods.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Secuenciación de Nucleótidos de Alto Rendimiento / Técnicas de Genotipaje Idioma: En Revista: Electrophoresis Año: 2021 Tipo del documento: Article

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Secuenciación de Nucleótidos de Alto Rendimiento / Técnicas de Genotipaje Idioma: En Revista: Electrophoresis Año: 2021 Tipo del documento: Article