Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Viral Mutations

Viral Mutations

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...

Viral Recombination

Viral Recombination

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.

Retroviruses

Retroviruses

Retroviruses and retrotransposons both insert copies of their genetic elements into the genome of the host cell. Thus, the viral genes are passed on when the host genome is replicated or translated. A typical retroviral DNA sequence contains 3-4 genes that encode the different proteins required for its structural assembly and function as a molecular parasite. This DNA is transcribed into a single mRNA, which is very similar in structure to conventional mRNAs, i.e., it is capped at the 5’...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

A distant brown dwarf coplanar to a warm Jupiter and a hot super-Earth.

Nature·2026

Same author

Nomenclature for Tracking of Genetic Variation of Seasonal Influenza Viruses.

Influenza and other respiratory viruses·2026

Same author

Pre-existing neutralizing antibodies against cattle-transmitted influenza A virus H5N1 are detectable in unexposed individuals.

Immunity·2026

Same author

Concepts and Methods for Predicting Viral Evolution.

Methods in molecular biology (Clifton, N.J.)·2025

Same author

Energy landscapes of peptide-MHC binding.

PLoS computational biology·2024

Same author

Concepts and methods for predicting viral evolution.

ArXiv·2024

Same journal

Layered social competition coordinates reproductive hierarchy formation in ants.

bioRxiv : the preprint server for biology·2026

Same journal

Combination epigenetic-targeted therapy increases the immunogenicity of poorly immunogenic sarcomas.

bioRxiv : the preprint server for biology·2026

Same journal

Loss of LanC-like proteins delays post-injury regeneration of aging skeletal muscles.

bioRxiv : the preprint server for biology·2026

Same journal

Integrative Transfer Network: Deep Transfer Learning Across Populations and Prediction Targets.

bioRxiv : the preprint server for biology·2026

Same journal

Confidence-supported label-free metabolic imaging with FPhaS phase autofluorescence microscopy.

bioRxiv : the preprint server for biology·2026

Same journal

Sequence-encoded autoinhibition couples mRNA decapping activity to phase separation.

bioRxiv : the preprint server for biology·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jun 26, 2025

Reverse Genetics to Engineer Positive-Sense RNA Virus Variants

Reverse Genetics to Engineer Positive-Sense RNA Virus Variants

Published on: June 9, 2022

Concepts and methods for predicting viral evolution.

Matthijs Meijers¹, Denis Ruchnewitz¹, Jan Eberhardt¹

¹Institute for Biological Physics, University of Cologne, Zülpicherstr. 77, 50937, Köln, Germany.

Biorxiv : the Preprint Server for Biology

|May 15, 2024

Summary

This summary is machine-generated.

Predicting seasonal influenza virus evolution is crucial for vaccine strain selection. This study presents a data-driven pipeline integrating diverse data for accurate viral evolution predictions and vaccine efficacy assessments.

Keywords:

antigenic evolution fitness models influenza vaccines population immunity

More Related Videos

Isolation of Fidelity Variants of RNA Viruses and Characterization of Virus Mutation Frequency

Isolation of Fidelity Variants of RNA Viruses and Characterization of Virus Mutation Frequency

Published on: June 16, 2011

Prediction of HIV-1 Coreceptor Usage Tropism by Sequence Analysis using a Genotypic Approach

Prediction of HIV-1 Coreceptor Usage Tropism by Sequence Analysis using a Genotypic Approach

Published on: December 1, 2011

Related Experiment Videos

Last Updated: Jun 26, 2025

Reverse Genetics to Engineer Positive-Sense RNA Virus Variants

Reverse Genetics to Engineer Positive-Sense RNA Virus Variants

Published on: June 9, 2022

Isolation of Fidelity Variants of RNA Viruses and Characterization of Virus Mutation Frequency

Isolation of Fidelity Variants of RNA Viruses and Characterization of Virus Mutation Frequency

Published on: June 16, 2011

Prediction of HIV-1 Coreceptor Usage Tropism by Sequence Analysis using a Genotypic Approach

Prediction of HIV-1 Coreceptor Usage Tropism by Sequence Analysis using a Genotypic Approach

Published on: December 1, 2011

Area of Science:

Virology and Epidemiology
Computational Biology and Bioinformatics
Immunology and Vaccine Development

Background:

Seasonal human influenza viruses evolve rapidly due to adaptive mutations, primarily in haemagglutinin antigenic epitopes.
Yearly changes in circulating viral strains necessitate continuous monitoring and prediction for effective public health interventions.
Existing methods may not fully integrate diverse data streams for comprehensive viral evolution forecasting.

Purpose of the Study:

To develop and present a consistent, data-driven methodology for predictive analysis of viral evolution.
To enable accurate forecasting of circulating viral strains and clade frequencies.
To provide a basis for pre-emptive vaccine strain selection by estimating protection against future viral populations.

Main Methods:

Integration of four key data types: global viral isolate sequence data, epidemiological incidence data, antigenic characterization, and intrinsic viral phenotypes.
Development of a computational pipeline for combined analysis of these integrated datasets.
Estimation of relative fitness for circulating strains and prediction of clade frequencies up to one year in advance.

Main Results:

The pipeline successfully estimates relative fitness of current influenza strains.
Accurate predictions of future clade frequencies are generated, enabling proactive monitoring.
Comparative estimates of vaccine strain protection against emerging viral populations are provided.

Conclusions:

The described data-driven pipeline offers a robust framework for predicting seasonal influenza virus evolution.
This approach facilitates informed, pre-emptive vaccine strain selection, enhancing global influenza preparedness.
Continuously updated predictions for influenza and SARS-CoV-2 are accessible via previr.app.