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Application of whole genome data for in silico evaluation of primers and probes routinely employed for the detection of viral species by RT-qPCR using dengue virus as a case study

机译:全基因组数据在计算机上评估常规用于通过登革热病毒进行RT-qPCR检测病毒种类的引物和探针的计算机模拟研究

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摘要

BackgroundViral infection by dengue virus is a major public health problem in tropical countries. Early diagnosis and detection are increasingly based on quantitative reverse transcriptase real-time polymerase chain reaction (RT-qPCR) directed against genomic regions conserved between different isolates. Genetic variation can however result in mismatches of primers and probes with their targeted nucleic acid regions. Whole genome sequencing allows to characterize and track such changes, which in turn enables to evaluate, optimize, and (re-)design novel and existing RT-qPCR methods. The immense amount of available sequence data renders this however a labour-intensive and complex task.
机译:背景登革病毒的病毒感染是热带国家的主要公共卫生问题。早期诊断和检测越来越多地基于针对不同分离株之间保守的基因组区域的定量逆转录酶实时聚合酶链反应(RT-qPCR)。然而,遗传变异会导致引物和探针与其靶向的核酸区域不匹配。全基因组测序可以表征和跟踪此类变化,从而可以评估,优化和(重新)设计新颖的和现有的RT-qPCR方法。大量可用的序列数据使这项工作变得十分繁重且复杂。

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