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.

ABSTRACT:

Background

Viral 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.

Results

We present a bioinformatics approach that enables in silico evaluation of primers a

SUBMITTER: Vanneste K 

PROVIDER: S-EPMC6123964 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature