A model for viral assembly around an explicit RNA sequence generates an Implicit fitness landscape

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Previously, a stochastic model of ssRNA virus assembly was created to model the cooperative effects between
capsid proteins and genomic RNA that would occur in a packaging signal-mediated assembly process. In such a assembly
scenario, multiple secondary structural elements from within the RNA, termed packaging signals (PS), contact coat proteins
and facilitate efficient capsid assembly. In this work, the assembly model is extended to incorporate explicit
nucleotide sequence information as well as simple aspects of RNA folding which would be occurring during the RNA/capsid
co-assembly process. Applying this new paradigm to a dodecahedral viral capsid, a computer derived nucleotide sequence is
evolved de novo that is optimal for packaging the RNA into capsids, while also containing capacity for coding for
a viral protein. Analysis of the effects of mutations on the ability of the RNA sequence to successfully package
into a viral capsid reveals a complex fitness landscape where the majority of mutations are neutral with respect to
packaging efficiency with a small number of mutations resulting in a near complete loss of RNA packaging. Moreover, the
model shows how attempts to ablate PSs in the viral RNA sequence may result in redundant PSs already present in the genome
fulfilling their packaging role. This explains why recent experiments that attempt to ablate putative PSs may not see an
effect on packaging. This modelling framework presents an example of how an implicit mapping can be made from genotype to
a fitness parameter important for viral biology, i.e. viral capsid yield, with potential applications to theoretical models
of viral evolution.
Original languageEnglish
Pages (from-to)506-516
Number of pages11
JournalBiophysical Journal
Issue number3
Publication statusPublished - 8 Aug 2017

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