Error rates, PCR recombination, and sampling depth in HIV-1 Whole Genome Deep Sequencing

Abstract

Deep sequencing is a powerful and cost-effective tool to characterize the genetic diversity and evolution of virus populations. While modern sequencing instruments readily cover viral genomes many thousand fold and very rare variants can in principle be detected, sequencing errors, amplification biases, and other artifacts can limit sensitivity and complicate data interpretation. Here, we describe several control experiments and error correction methods for whole-genome deep sequencing of viral genomes. We developed many of these in the course of a large scale whole genome deep sequencing study of HIV-1 populations. We measured the substitution and indel errors that arose during sequencing and PCR and quantified PCR-mediated recombination. We find that depending on the viral load in the samples, rare mutations down to 0.2% can be reproducibly detected. PCR recombination can be avoided by consistently working at low amplicon concentrations.