A deep sequencing approach to identify and quantify subgenomic RNA of dengue virus

Abstract

Dengue virus (DENV) is a mosquito-borne flavivirus that causes frequent epidemics globally with an estimated 390 million infections each year. Over the years, epidemiological studies have described the association between genetic changes within the same DENV serotype with epidemic emergence, but the underlying mechanism remains unknown. We have recently examined Puerto Rican DENV-2 isolates that caused a major outbreak in 1994. Preliminary studies have identified three nucleotide changes in the 3' untranslated region (UTR) altering the viral fitness through the production of subgenomic flavivirus RNA (sfRNA) that inhibits interferon (IFN) expression. To further understand the significance of the point mutations in the 3' UTR on the epidemic potential of DENV-2, we have proposed to identify and quantify sfRNA by deep sequencing. In this project, we described a method to improve the 5' ligation efficiency of sfRNA as the adapter ligation step was proven to be inefficient in total RNA conditions. Hence, we investigated the effects of adapter concentration and incubation time of T4 RNA ligase 1 on the 5' ligation efficiency. As a result, we managed to successfully ligate an adapter to the 5' end of sfRNA with the optimized protocol, which was confirmed with Sanger sequencing.