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Updated: Feb 22, 2026

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

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

Published on: October 16, 2018

Decoding noises in HIV computational genotyping.

MingRui Jia¹, Timothy Shaw², Xing Zhang³

¹Department of Pain Management, Shandong Provincial Hospital Affiliated to Shandong University, 324 Jingwu Road, Jinan, Shandong Province 250021, China; Department of Epidemiology and Biostatistics, University of Georgia, GA 30602, USA.

|September 18, 2017

Summary

This summary is machine-generated.

Mis-genotyping in HIV genetic data affects research and surveillance. This study found 4.6% of global HIV cases were mis-genotyped, highlighting the need for standardized quality control in HIV genotyping.

Keywords:

Epidemic surveillance HIV Molecular genotyping

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Last Updated: Feb 22, 2026

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

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

Published on: October 16, 2018

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

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Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3

Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3

Published on: December 27, 2010

Area of Science:

Genomics
Molecular Biology
Epidemiology

Background:

Reliable human immunodeficiency virus (HIV) genotyping is crucial for understanding pathogenesis, drug resistance, and treatment.
The impact of mis-genotyping, or errors in molecular genotyping, on HIV epidemic surveillance remains unclear.

Purpose of the Study:

To conduct a comprehensive assessment of HIV genotyping quality globally.
To identify patterns and prevalence of mis-genotyping in published HIV sequence data.

Main Methods:

Systematic assessment pipeline applied to HIV sequence data from worldwide published records.
Analysis of mis-genotyping rates, regional variations, and specific genetic patterns.

Main Results:

Globally, 4.6% of assessed HIV cases exhibited mis-genotyping, with regional and population-specific heterogeneities.
A consistent mis-genotyping pattern was observed in the gp120 region across most populations.
Novel viral diversities were suggested in mis-genotyped cases.

Conclusions:

Standardized genotyping pipelines are essential to mitigate disparities and improve the accuracy of HIV genomic research.
Accurate HIV genotyping is vital for advancing the understanding of virus evolution and informing public health strategies.