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Functional Profiling and Evolutionary Analysis of a Marine Microalgal Virus Pangenome

Phycodnaviridae are large double-stranded DNA viruses, which facilitate studies of host–virus interactions and co-evolution due to their prominence in algal infection and their role in the life cycle of algal blooms. However, the genomic interpretation of these viruses is hampered by a lack of funct...

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Detalles Bibliográficos
Autores principales: Lobb, Briallen, Shapter, Anson, Doxey, Andrew C., Nissimov, Jozef I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10222054/
https://www.ncbi.nlm.nih.gov/pubmed/37243202
http://dx.doi.org/10.3390/v15051116
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author Lobb, Briallen
Shapter, Anson
Doxey, Andrew C.
Nissimov, Jozef I.
author_facet Lobb, Briallen
Shapter, Anson
Doxey, Andrew C.
Nissimov, Jozef I.
author_sort Lobb, Briallen
collection PubMed
description Phycodnaviridae are large double-stranded DNA viruses, which facilitate studies of host–virus interactions and co-evolution due to their prominence in algal infection and their role in the life cycle of algal blooms. However, the genomic interpretation of these viruses is hampered by a lack of functional information, stemming from the surprising number of hypothetical genes of unknown function. It is also unclear how many of these genes are widely shared within the clade. Using one of the most extensively characterized genera, Coccolithovirus, as a case study, we combined pangenome analysis, multiple functional annotation tools, AlphaFold structural modeling, and literature analysis to compare the core and accessory pangenome and assess support for novel functional predictions. We determined that the Coccolithovirus pangenome shares 30% of its genes with all 14 strains, making up the core. Notably, 34% of its genes were found in at most three strains. Core genes were enriched in early expression based on a transcriptomic dataset of Coccolithovirus EhV-201 algal infection, were more likely to be similar to host proteins than the non-core set, and were more likely to be involved in vital functions such as replication, recombination, and repair. In addition, we generated and collated annotations for the EhV representative EhV-86 from 12 different annotation sources, building up information for 142 previously hypothetical and putative membrane proteins. AlphaFold was further able to predict structures for 204 EhV-86 proteins with a modelling accuracy of good–high. These functional clues, combined with generated AlphaFold structures, provide a foundational framework for the future characterization of this model genus (and other giant viruses) and a further look into the evolution of the Coccolithovirus proteome.
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spelling pubmed-102220542023-05-28 Functional Profiling and Evolutionary Analysis of a Marine Microalgal Virus Pangenome Lobb, Briallen Shapter, Anson Doxey, Andrew C. Nissimov, Jozef I. Viruses Article Phycodnaviridae are large double-stranded DNA viruses, which facilitate studies of host–virus interactions and co-evolution due to their prominence in algal infection and their role in the life cycle of algal blooms. However, the genomic interpretation of these viruses is hampered by a lack of functional information, stemming from the surprising number of hypothetical genes of unknown function. It is also unclear how many of these genes are widely shared within the clade. Using one of the most extensively characterized genera, Coccolithovirus, as a case study, we combined pangenome analysis, multiple functional annotation tools, AlphaFold structural modeling, and literature analysis to compare the core and accessory pangenome and assess support for novel functional predictions. We determined that the Coccolithovirus pangenome shares 30% of its genes with all 14 strains, making up the core. Notably, 34% of its genes were found in at most three strains. Core genes were enriched in early expression based on a transcriptomic dataset of Coccolithovirus EhV-201 algal infection, were more likely to be similar to host proteins than the non-core set, and were more likely to be involved in vital functions such as replication, recombination, and repair. In addition, we generated and collated annotations for the EhV representative EhV-86 from 12 different annotation sources, building up information for 142 previously hypothetical and putative membrane proteins. AlphaFold was further able to predict structures for 204 EhV-86 proteins with a modelling accuracy of good–high. These functional clues, combined with generated AlphaFold structures, provide a foundational framework for the future characterization of this model genus (and other giant viruses) and a further look into the evolution of the Coccolithovirus proteome. MDPI 2023-05-05 /pmc/articles/PMC10222054/ /pubmed/37243202 http://dx.doi.org/10.3390/v15051116 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Lobb, Briallen
Shapter, Anson
Doxey, Andrew C.
Nissimov, Jozef I.
Functional Profiling and Evolutionary Analysis of a Marine Microalgal Virus Pangenome
title Functional Profiling and Evolutionary Analysis of a Marine Microalgal Virus Pangenome
title_full Functional Profiling and Evolutionary Analysis of a Marine Microalgal Virus Pangenome
title_fullStr Functional Profiling and Evolutionary Analysis of a Marine Microalgal Virus Pangenome
title_full_unstemmed Functional Profiling and Evolutionary Analysis of a Marine Microalgal Virus Pangenome
title_short Functional Profiling and Evolutionary Analysis of a Marine Microalgal Virus Pangenome
title_sort functional profiling and evolutionary analysis of a marine microalgal virus pangenome
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10222054/
https://www.ncbi.nlm.nih.gov/pubmed/37243202
http://dx.doi.org/10.3390/v15051116
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