- Award ID(s):
- 1758912
- Publication Date:
- NSF-PAR ID:
- 10309073
- Journal Name:
- Virus Evolution
- Volume:
- 6
- Issue:
- 2
- ISSN:
- 2057-1577
- Sponsoring Org:
- National Science Foundation
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Natural selection acts on cellular organisms by ensuring the genes responsible for an advantageous phenotype consistently reap the phenotypic advantage. This is possible because reproductive cells of these organisms are almost always haploid, separating the beneficial gene from its rival allele at every generation. How natural selection acts on plus-strand RNA viruses is unclear because these viruses frequently load host cells with numerous genome copies and replicate thousands of progeny genomes in each cell. Recent studies suggest that these viruses encode the Bottleneck, Isolate, Amplify, Select (BIAS) mechanism that blocks all but a few viral genome copies from replication, thus creating the environment in which the bottleneck-escaping viral genome copies are isolated from each other, allowing natural selection to reward beneficial mutations and purge lethal errors. This BIAS mechanism also blocks the genomes of highly homologous superinfecting viruses, thus explaining cellular-level superinfection exclusion.
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Abstract Long-range ribonucleic acid (RNA)–RNA interactions (RRI) are prevalent in positive-strand RNA viruses, including Beta-coronaviruses, and these take part in regulatory roles, including the regulation of sub-genomic RNA production rates. Crosslinking of interacting RNAs and short read-based deep sequencing of resulting RNA–RNA hybrids have shown that these long-range structures exist in severe acute respiratory syndrome coronavirus (SARS-CoV)-2 on both genomic and sub-genomic levels and in dynamic topologies. Furthermore, co-evolution of coronaviruses with their hosts is navigated by genetic variations made possible by its large genome, high recombination frequency and a high mutation rate. SARS-CoV-2’s mutations are known to occur spontaneously during replication, and thousands of aggregate mutations have been reported since the emergence of the virus. Although many long-range RRIs have been experimentally identified using high-throughput methods for the wild-type SARS-CoV-2 strain, evolutionary trajectory of these RRIs across variants, impact of mutations on RRIs and interaction of SARS-CoV-2 RNAs with the host have been largely open questions in the field. In this review, we summarize recent computational tools and experimental methods that have been enabling the mapping of RRIs in viral genomes, with a specific focus on SARS-CoV-2. We also present available informatics resources to navigate the RRI maps andmore »
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