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DC Field | Value | Language |
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dc.contributor.author | FARHEEN, NIDA | en_US |
dc.contributor.author | Thattai, Mukund | en_US |
dc.date.accessioned | 2020-01-31T04:40:09Z | |
dc.date.available | 2020-01-31T04:40:09Z | |
dc.date.issued | 2019-11 | en_US |
dc.identifier.citation | Journal of the Royal Society Interface, 16(160). | en_US |
dc.identifier.issn | 1742-5689 | en_US |
dc.identifier.issn | 1742-56891742-5662 | en_US |
dc.identifier.uri | http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/4393 | - |
dc.identifier.uri | https://doi.org/10.1098/rsif.2019.0411 | en_US |
dc.description.abstract | The genome of the influenza virus consists of eight distinct single-stranded RNA segments, each encoding proteins essential for the viral life cycle. When the virus infects a host cell, these segments must be replicated and packaged into new budding virions. The viral genome is assembled with remarkably high fidelity: experiments reveal that most virions contain precisely one copy of each of the eight RNA segments. Cell-biological studies suggest that genome assembly is mediated by specific reversible and irreversible interactions between the RNA segments and their associated proteins. However, the precise inter-segment interaction network remains unresolved. Here, we computationally predict that tree-like irreversible interaction networks guarantee high-fidelity genome assembly, while cyclic interaction networks lead to futile or frustrated off-pathway products. We test our prediction against multiple experimental datasets. We find that tree-like networks capture the nearest-neighbour statistics of RNA segments in packaged virions, as observed by electron tomography. Just eight tree-like networks (of a possible 262 144) optimally capture both the nearest-neighbour data and independently measuredRNA-RNAbinding and co-localization propensities. These eight do not include the previously proposed hub-and-spoke and linear networks. Rather, each predicted network combines hub-like and linear features, consistent with evolutionary models of interaction gain and loss. | en_US |
dc.language.iso | en | en_US |
dc.publisher | The Royal Society | en_US |
dc.subject | Segmented virus | en_US |
dc.subject | Influenza | en_US |
dc.subject | Self-assembly | en_US |
dc.subject | Network evolution | en_US |
dc.subject | TOC-JAN-2020 | en_US |
dc.subject | 2019 | en_US |
dc.title | Frustration and fidelity in influenza genome assembly | en_US |
dc.type | Article | en_US |
dc.contributor.department | Dept. of Biology | en_US |
dc.identifier.sourcetitle | Journal of the Royal Society Interface | en_US |
dc.publication.originofpublisher | Foreign | en_US |
Appears in Collections: | JOURNAL ARTICLES |
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