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Amplification of Near Full-length HIV-1 Proviruses for Next-Generation Sequencing

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Published on: October 16, 2018

A safe an easy method for building consensus HIV sequences from 454 massively parallel sequencing data.

Jose Ángel Fernández-Caballero Rico¹, Natalia Chueca Porcuna¹, Marta Álvarez Estévez¹

¹Servicio de Microbiología Clínica, Hospital Universitario San Cecilio, Complejo Hospitalario Universitario Granada e Instituto de Investigación IBS, Granada, España.

Enfermedades Infecciosas Y Microbiologia Clinica (English Ed.)

|October 8, 2016

Summary

This study presents a method for generating HIV consensus sequences from next-generation sequencing data. A 20% threshold is recommended for accurate molecular epidemiology studies.

Keywords:

Filogenia Human immunodeficiency virus Next generation sequencing Phylogeny Thresholds Umbrales Virus de la inmunodeficiencia humana

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Published on: October 16, 2018

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An Affordable HIV-1 Drug Resistance Monitoring Method for Resource Limited Settings

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Published on: March 30, 2014

Area of Science:

Virology
Genetics
Bioinformatics

Background:

HIV drug resistance studies generate massive parallel sequencing data.
Accurate consensus sequences are crucial for molecular epidemiology.
Next-generation sequencing (NGS) offers potential for HIV sequence analysis.

Purpose of the Study:

To establish a reliable method for generating HIV consensus sequences from NGS data.
To evaluate the suitability of NGS-derived consensus sequences for molecular epidemiology.
To determine the optimal threshold for consensus sequence generation from NGS data.

Main Methods:

Paired Sanger and NGS HIV sequences from 62 patients were analyzed.
NGS consensus sequences were generated using Mesquite software at 10%, 15%, and 20% thresholds.
Phylogenetic analyses were performed using Molecular Evolutionary Genetics Analysis (MEGA).

Main Results:

Phylogenetic association between NGS and Sanger sequences improved with increasing thresholds.
At a 10% threshold, 17/62 patients showed related sequences (median bootstrap 88%).
At a 15% threshold, 36/62 patients were associated (median bootstrap 94%).
At a 20% threshold, 61/62 patients were associated with a high median bootstrap value of 99%.

Conclusions:

A robust method for generating HIV consensus sequences from NGS data using a 20% threshold is presented.
This method enhances the utility of NGS data for HIV molecular epidemiology.
The findings support the use of NGS for routine HIV resistance and epidemiological studies.