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Related Experiment Video

Updated: Jan 16, 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

Comprehensive Transcriptome Annotation of Thousands of HIV-1 Genomes.

Ales Varabyou^1,2,3, Mykhaylo Artamonov^4,5, Sophia Cheng^4,5

¹Department of Biomedical Engineering, Johns Hopkins University; Baltimore, MD.

Biorxiv : the Preprint Server for Biology

|October 3, 2025

Summary

Researchers created HIV Atlas, a comprehensive resource for HIV-1 and SIV transcriptional diversity. This tool supports advanced computational analysis of viral RNA sequencing data, improving research accuracy.

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Last Updated: Jan 16, 2026

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Determining 3'-Termini and Sequences of Nascent Single-Stranded Viral DNA Molecules during HIV-1 Reverse Transcription in Infected Cells

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Exploring m6A and m5C Epitranscriptomes upon Viral Infection: an Example with HIV

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Published on: March 5, 2022

Area of Science:

Virology
Computational Biology
Genomics

Background:

Alternative splicing in Human Immunodeficiency Virus type 1 (HIV-1) is crucial for viral gene regulation and immune evasion.
Existing resources lack comprehensive transcriptome-wide analysis support for HIV-1, hindering computational research.
Modern computational methods for analyzing viral transcriptomes are limited by the absence of a reference annotation.

Purpose of the Study:

To introduce HIV Atlas, the first reference-quality annotation resource for HIV-1 and SIV transcriptional diversity.
To provide a comprehensive dataset supporting transcriptome-wide analysis of viral RNA.
To enable advanced computational methods for HIV-1 research.

Main Methods:

Manual curation of transcriptomes for HIV-1_HXB2 and SIV_mac239.
Development of Vira, an automated annotation-transfer method tailored for viral genome biology.
Generation of high-quality annotations for 2,077 complete HIV-1 genomes.

Main Results:

HIV Atlas provides reference-quality annotations for HIV-1 and SIV transcriptional diversity.
Analysis revealed near-perfect conservation of major splice donor and acceptor sites in HIV-1.
HIV Atlas enhances RNA-seq analysis methodology, improving result quality and novelty.

Conclusions:

HIV Atlas is a valuable resource for the scientific community, supporting advanced computational analyses of HIV-1.
The resource facilitates more accurate and comprehensive studies using bulk, single-cell, and spatial RNA-seq.
HIV Atlas opens new avenues for research into HIV-1 gene regulation, immune evasion, and therapeutic responses.