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Updated: May 9, 2025

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

Predicting Potential PRRSV-2 Variant Emergence through Phylogenetic Inference.

Nakarin Pamornchainavakul¹, Mariana Kikuti¹, Igor A D Paploski¹

¹College of Veterinary Medicine, University of Minnesota, St. Paul, MN, USA.

Transboundary and Emerging Diseases

|April 30, 2025

Summary

Predicting new Porcine reproductive and respiratory syndrome virus type 2 (PRRSV-2) variants is crucial for disease control. This study identified phylogenetic indicators for PRRSV-2 emergence, aiding future prevention strategies.

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Area of Science:

Veterinary Virology
Molecular Epidemiology
Disease Prediction Modeling

Background:

Porcine reproductive and respiratory syndrome (PRRS) causes significant economic losses in the US pork industry, exceeding $500 million annually.
The emergence of genetically diverse Porcine reproductive and respiratory syndrome virus type 2 (PRRSV-2) strains complicates disease control and vaccine development.
Predictive tools for emerging viral variants, successful for other diseases, are lacking for PRRSV-2 despite available data.

Purpose of the Study:

To identify phylogenetic-based early indicators for predicting short-term (12 months) and long-term (24 months) PRRSV-2 variant emergence.
To analyze PRRSV-2 Lineage 1, the predominant US lineage, using a decade of ORF5 sequence data.
To evaluate population expansion, spatial distribution, and genetic diversity as key metrics for variant emergence.

Main Methods:

Analysis of 20,700 PRRSV-2 ORF5 sequences and associated metadata from the past decade.
Phylogenetic analysis to identify indicators of variant emergence.
Conditional logistic regression to assess predictive power of indicators for population expansion, spatial distribution, and genetic diversity.

Main Results:

Successful PRRSV-2 variants exhibited population expansion and wide geographical spread with limited genetic diversification.
The local branching index predicted population expansion (BA=0.75), while ancestral branch length predicted genetic diversity (BA=0.79).
Branch length and putative antigenic difference predicted spatial dispersion (BA=0.67); models captured 58-81% of variants but had low PPV (9-16%).

Conclusions:

Phylogenetic indicators can provide early warnings for PRRSV-2 variant emergence.
Predictive models show promise in identifying potential future variants, aiding proactive disease management.
This study represents a crucial first step towards developing precise PRRSV-2 prevention strategies.