Therefore, to ensure accuracy, comprehensive validation of deep sequencing approaches should accompany diversity measures from biological samples. ![]() PCR amplification of virus nucleic acid is a common approach to overcome this challenge, although it can introduce biases by altering the composition of intrahost genetic variants. This is especially true for Zika virus, where low viremias (< 1000 copies/μL of RNA) are often detected during natural and experimental infections. Moreover, for many clinical samples, low ratios of viral to host RNA often necessitate enrichment of viral nucleic acid to recover sufficient templates for deep sequencing. ![]() Multiple factors, such as virus titer, sample preparation, sequencing errors, and computational inferences, can bias measures of genetic diversity. In many cases, however, accurately measuring intrahost RNA virus diversity using deep sequencing remains a significant challenge. Studying virus populations, both within naturally infected hosts and during experimental evolution, can therefore lead to breakthroughs in our understanding of virus-host interactions and novel approaches for outbreak response. Generation of intrahost genetic diversity allows virus populations to evade host immune responses, alter the severity of disease, and adapt to changing environments. Part of this burden stems from their ability to rapidly evolve within hosts. ![]() RNA viruses, including HIV, influenza, West Nile, and Zika, pose significant threats to public health worldwide.
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