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Related Concept Videos

Viral Mutations00:36

Viral Mutations

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A mutation is a change in the sequence of bases of DNA or RNA in a genome. Some mutations occur during replication of the genome due to errors made by the polymerase enzymes that replicate DNA or RNA. Unlike DNA polymerase, RNA polymerase is prone to errors because it is not capable of “proofreading” its work. Viruses with RNA-based genomes, like HIV, therefore accrue mutations faster than viruses with DNA-based genomes. Because mutation and recombination provide the raw material...
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Viral Recombination00:57

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Cells are sometimes infected by more than one virus at once. When two viruses disassemble to expose their genomes for replication in the same cell, similar regions of their genomes can pair together and exchange sequences in a process called recombination. Alternatively, viruses with segmented genomes can swap segments in a process called reassortment.
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An Affordable HIV-1 Drug Resistance Monitoring Method for Resource Limited Settings
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VIPERA: Viral Intra-Patient Evolution Reporting and Analysis.

Miguel Álvarez-Herrera1, Jordi Sevilla1, Paula Ruiz-Rodriguez1

  • 1Institute for Integrative Systems Biology (I2SysBio, University of Valencia-CSIC), FISABIO Joint Research Unit 'Infection and Public Health', C/Agustín Escardino, 9, Paterna 46980, Spain.

Virus Evolution
|March 21, 2024
PubMed
Summary

Viral mutations in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can lead to new variants. VIPERA software analyzes intra-patient viral evolution, tracking SARS-CoV-2 genetic changes during chronic infections to understand variant development.

Keywords:
SARS-CoV-2bioinformaticsintra-patient diversityserially sampled infectionsnakemake workflowwithin-host evolution

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Area of Science:

  • Virology
  • Computational Biology
  • Genomics

Background:

  • Intra-patient viral mutations in SARS-CoV-2 contribute to the emergence of variants of concern during chronic infections.
  • Existing frameworks lack integrated analysis for intra-patient SARS-CoV-2 evolutionary trajectories from serial samples.

Purpose of the Study:

  • To introduce Viral Intra-Patient Evolution Reporting and Analysis (VIPERA), a novel software tool.
  • To enable integrated evolutionary analysis of SARS-CoV-2 serial samples within individual patients.
  • To investigate intra-patient viral ancestry and evolutionary dynamics.

Main Methods:

  • Development of the VIPERA software for sequence analysis.
  • Integration of intra-patient ancestry evaluation and evolutionary trajectory analysis.
  • Validation using control datasets and application to a real-world case study.

Main Results:

  • VIPERA successfully validated on control datasets.
  • Application to a case study revealed viral population dynamics.
  • Evidence of adaptive evolution within a chronic SARS-CoV-2 infection was identified.

Conclusions:

  • VIPERA provides a comprehensive framework for analyzing intra-patient SARS-CoV-2 evolution.
  • The software aids in understanding the origins of viral variants.
  • Facilitates research into viral adaptation during persistent infections.