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Viruses 2019, 11(4), 320; https://doi.org/10.3390/v11040320

Protein Structure-Guided Hidden Markov Models (HMMs) as A Powerful Method in the Detection of Ancestral Endogenous Viral Elements

1
Department of Bioinformatics, University of Tartu, Tartu, 51010, Riia 23, Estonia
2
Institute of Technology, University of Tartu, Tartu, 50411, Nooruse 1, Estonia
*
Authors to whom correspondence should be addressed.
Received: 29 January 2019 / Revised: 23 March 2019 / Accepted: 27 March 2019 / Published: 2 April 2019
(This article belongs to the Special Issue Virus Bioinformatics)
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Abstract

It has been believed for a long time that the transfer and fixation of genetic material from RNA viruses to eukaryote genomes is very unlikely. However, during the last decade, there have been several cases in which “virus-to-host” gene transfer from various viral families into various eukaryotic phyla have been described. These transfers have been identified by sequence similarity, which may disappear very quickly, especially in the case of RNA viruses. However, compared to sequences, protein structure is known to be more conserved. Applying protein structure-guided protein domain-specific Hidden Markov Models, we detected homologues of the Virgaviridae capsid protein in Schizophora flies. Further data analysis supported “virus-to-host” transfer into Schizophora ancestors as a single transfer event. This transfer was not identifiable by BLAST or by other methods we applied. Our data show that structure-guided Hidden Markov Models should be used to detect ancestral virus-to-host transfers. View Full-Text
Keywords: endogenous viral elements; bioinformatics; horizontal gene transfer; virus-to-host gene transfer; HMM; tobacco mosaic virus; Drosophila; capsid protein endogenous viral elements; bioinformatics; horizontal gene transfer; virus-to-host gene transfer; HMM; tobacco mosaic virus; Drosophila; capsid protein
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Kirsip, H.; Abroi, A. Protein Structure-Guided Hidden Markov Models (HMMs) as A Powerful Method in the Detection of Ancestral Endogenous Viral Elements. Viruses 2019, 11, 320.

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