An amplicon-based sequencing framework for accurately measuring intrahost virus diversity using PrimalSeq and iVar

Nathan D Grubaugh,Kristian G Andersen,Karthik Gangavarapu,Amanda L Tan,Scott F Michael,Bradley J Main,Lauren M Paul,Lark L Coffey,Doug E Brackney,Joshua Quick,Nathaniel L Matteson,Sharon Isern,Nicholas J Loman,Koen K A Van Rompay,Nikos Gurfield,Jaqueline Goes De Jesus,Saran Grewal

doi:10.1186/s13059-018-1618-7

Abstract

How viruses evolve within hosts can dictate infection outcomes; however, reconstructing this process is challenging. We evaluate our multiplexed amplicon approach, PrimalSeq, to demonstrate how virus concentration, sequencing coverage, primer mismatches, and replicates influence the accuracy of measuring intrahost virus diversity. We develop an experimental protocol and computational tool, iVar, for using PrimalSeq to measure virus diversity using Illumina and compare the results to Oxford Nanopore sequencing. We demonstrate the utility of PrimalSeq by measuring Zika and West Nile virus diversity from varied sample types and show that the accumulation of genetic diversity is influenced by experimental and biological systems.

Highlights

RNA viruses, including HIV, influenza, West Nile, and Zika, pose significant threats to public health worldwide
Given the potential biases that may be introduced during PCR amplification, we sought to assess the accuracy of PrimalSeq for intrahost single-nucleotide variants (iSNVs) detection
We found that PCR amplification leads to more variable true iSNV frequency measurements, but that the overall accuracy of PrimalSeq is comparable to metagenomic sequencing (Fig. 4)

Summary

Introduction

RNA viruses, including HIV, influenza, West Nile, and Zika, pose significant threats to public health worldwide Part of this burden stems from their ability to rapidly evolve within hosts [1]. 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 [17]. This is especially true for Zika virus, where low viremias (< 1000 copies/μL of RNA) are often detected during natural and experimental infections [18,19,20,21]. To ensure accuracy, comprehensive validation of deep sequencing approaches should accompany diversity measures from biological samples

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Discussion

Conclusion