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Isolation and Genome Analysis of Single Virions using 'Single Virus Genomics'
Published on: May 26, 2013
Evolutionary dynamics of genome segmentation in multipartite viruses
Jaime Iranzo1, Susanna C Manrubia
1Centro de Astrobiología, INTA-CSIC, 28850 Torrejón de Ardoz, Madrid, Spain.
Proceedings. Biological Sciences
|July 6, 2012
Summary
Multipartite viruses, with genomes split into multiple parts, require high infection numbers to spread. This study suggests genome stability, not replication speed, favors their evolution, particularly for viruses with few segments.
Area of Science:
- Virology
- Evolutionary Biology
- Genetics
Background:
- Multipartite viruses package their genomes into multiple independent capsids.
- Successful propagation necessitates a high multiplicity of infection (MOI).
- The evolutionary advantages and origins of multipartite viruses remain largely unclear.
Purpose of the Study:
- To determine the conditions favoring multipartite viral genome organization over non-segmented variants.
- To explore the evolutionary pathways leading to multipartite viruses from defective genome fragments.
- To investigate the role of differential stability and MOI in multipartite virus evolution.
Main Methods:
- Mathematical modeling of viral genome stability as a function of genome length.
- Calculation of conditions for competitive advantage of segmented genomes.
- Analysis of evolutionary scenarios involving defective viral genomes.
Main Results:
- Increased virion stability of incomplete genomes can compensate for the need for complementation.
- Differential stability and MOI are key parameters in the evolution of multipartite viruses.
- The model predicts that multipartite viruses with a small number of segments are more likely to evolve under the studied conditions.
Conclusions:
- Viral genome segmentation may be driven by enhanced virion stability rather than replication efficiency.
- The evolutionary origin of multipartite viruses, especially those with numerous segments, requires further investigation beyond the proposed model.
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