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Front Microbiol. 2015 Nov 12;6:1258. doi: 10.3389/fmicb.2015.01258. eCollection 2015.

Quasispecies Analyses of the HIV-1 Near-full-length Genome With Illumina MiSeq.

Frontiers in microbiology

Hirotaka Ode, Masakazu Matsuda, Kazuhiro Matsuoka, Atsuko Hachiya, Junko Hattori, Yumiko Kito, Yoshiyuki Yokomaku, Yasumasa Iwatani, Wataru Sugiura

Affiliations

  1. Department of Infectious Diseases and Immunology, Clinical Research Center, National Hospital Organization Nagoya Medical Center Nagoya, Japan.
  2. Department of Infectious Diseases and Immunology, Clinical Research Center, National Hospital Organization Nagoya Medical Center Nagoya, Japan ; Department of AIDS Research, Graduate School of Medicine, Nagoya University Nagoya, Japan.

PMID: 26617593 PMCID: PMC4641896 DOI: 10.3389/fmicb.2015.01258

Abstract

Human immunodeficiency virus type-1 (HIV-1) exhibits high between-host genetic diversity and within-host heterogeneity, recognized as quasispecies. Because HIV-1 quasispecies fluctuate in terms of multiple factors, such as antiretroviral exposure and host immunity, analyzing the HIV-1 genome is critical for selecting effective antiretroviral therapy and understanding within-host viral coevolution mechanisms. Here, to obtain HIV-1 genome sequence information that includes minority variants, we sought to develop a method for evaluating quasispecies throughout the HIV-1 near-full-length genome using the Illumina MiSeq benchtop deep sequencer. To ensure the reliability of minority mutation detection, we applied an analysis method of sequence read mapping onto a consensus sequence derived from de novo assembly followed by iterative mapping and subsequent unique error correction. Deep sequencing analyses of aHIV-1 clone showed that the analysis method reduced erroneous base prevalence below 1% in each sequence position and discarded only < 1% of all collected nucleotides, maximizing the usage of the collected genome sequences. Further, we designed primer sets to amplify the HIV-1 near-full-length genome from clinical plasma samples. Deep sequencing of 92 samples in combination with the primer sets and our analysis method provided sufficient coverage to identify >1%-frequency sequences throughout the genome. When we evaluated sequences of pol genes from 18 treatment-naïve patients' samples, the deep sequencing results were in agreement with Sanger sequencing and identified numerous additional minority mutations. The results suggest that our deep sequencing method would be suitable for identifying within-host viral population dynamics throughout the genome.

Keywords: HIV-1; consensus sequence estimation; deep sequencing; drug resistance; error correction; quasispecies

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