Using networks to analyze and visualize the distribution of overlapping genes in virus genomes.
Gene overlap occurs when two or more genes are encoded by the same nucleotides. This phenomenon is found in all taxonomic domains, but is particularly common in viruses, where it may increase the information content of compact genomes or influence the creation of new genes. Here we report a global c...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2022-02-01
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| Series: | PLoS Pathogens |
| Online Access: | https://doi.org/10.1371/journal.ppat.1010331 |
| _version_ | 1818258844853207040 |
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| author | Laura Muñoz-Baena Art F Y Poon |
| author_facet | Laura Muñoz-Baena Art F Y Poon |
| author_sort | Laura Muñoz-Baena |
| collection | DOAJ |
| description | Gene overlap occurs when two or more genes are encoded by the same nucleotides. This phenomenon is found in all taxonomic domains, but is particularly common in viruses, where it may increase the information content of compact genomes or influence the creation of new genes. Here we report a global comparative study of overlapping open reading frames (OvRFs) of 12,609 virus reference genomes in the NCBI database. We retrieved metadata associated with all annotated open reading frames (ORFs) in each genome record to calculate the number, length, and frameshift of OvRFs. Our results show that while the number of OvRFs increases with genome length, they tend to be shorter in longer genomes. The majority of overlaps involve +2 frameshifts, predominantly found in dsDNA viruses. Antisense overlaps in which one of the ORFs was encoded in the same frame on the opposite strand (-0) tend to be longer. Next, we develop a new graph-based representation of the distribution of overlaps among the ORFs of genomes in a given virus family. In the absence of an unambiguous partition of ORFs by homology at this taxonomic level, we used an alignment-free k-mer based approach to cluster protein coding sequences by similarity. We connect these clusters with two types of directed edges to indicate (1) that constituent ORFs are adjacent in one or more genomes, and (2) that these ORFs overlap. These adjacency graphs not only provide a natural visualization scheme, but also a novel statistical framework for analyzing the effects of gene- and genome-level attributes on the frequencies of overlaps. |
| first_indexed | 2024-12-12T18:06:00Z |
| format | Article |
| id | doaj.art-66d9c00919564226bc190594146b85c4 |
| institution | Directory Open Access Journal |
| issn | 1553-7366 1553-7374 |
| language | English |
| last_indexed | 2024-12-12T18:06:00Z |
| publishDate | 2022-02-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Pathogens |
| spelling | doaj.art-66d9c00919564226bc190594146b85c42022-12-22T00:16:29ZengPublic Library of Science (PLoS)PLoS Pathogens1553-73661553-73742022-02-01182e101033110.1371/journal.ppat.1010331Using networks to analyze and visualize the distribution of overlapping genes in virus genomes.Laura Muñoz-BaenaArt F Y PoonGene overlap occurs when two or more genes are encoded by the same nucleotides. This phenomenon is found in all taxonomic domains, but is particularly common in viruses, where it may increase the information content of compact genomes or influence the creation of new genes. Here we report a global comparative study of overlapping open reading frames (OvRFs) of 12,609 virus reference genomes in the NCBI database. We retrieved metadata associated with all annotated open reading frames (ORFs) in each genome record to calculate the number, length, and frameshift of OvRFs. Our results show that while the number of OvRFs increases with genome length, they tend to be shorter in longer genomes. The majority of overlaps involve +2 frameshifts, predominantly found in dsDNA viruses. Antisense overlaps in which one of the ORFs was encoded in the same frame on the opposite strand (-0) tend to be longer. Next, we develop a new graph-based representation of the distribution of overlaps among the ORFs of genomes in a given virus family. In the absence of an unambiguous partition of ORFs by homology at this taxonomic level, we used an alignment-free k-mer based approach to cluster protein coding sequences by similarity. We connect these clusters with two types of directed edges to indicate (1) that constituent ORFs are adjacent in one or more genomes, and (2) that these ORFs overlap. These adjacency graphs not only provide a natural visualization scheme, but also a novel statistical framework for analyzing the effects of gene- and genome-level attributes on the frequencies of overlaps.https://doi.org/10.1371/journal.ppat.1010331 |
| spellingShingle | Laura Muñoz-Baena Art F Y Poon Using networks to analyze and visualize the distribution of overlapping genes in virus genomes. PLoS Pathogens |
| title | Using networks to analyze and visualize the distribution of overlapping genes in virus genomes. |
| title_full | Using networks to analyze and visualize the distribution of overlapping genes in virus genomes. |
| title_fullStr | Using networks to analyze and visualize the distribution of overlapping genes in virus genomes. |
| title_full_unstemmed | Using networks to analyze and visualize the distribution of overlapping genes in virus genomes. |
| title_short | Using networks to analyze and visualize the distribution of overlapping genes in virus genomes. |
| title_sort | using networks to analyze and visualize the distribution of overlapping genes in virus genomes |
| url | https://doi.org/10.1371/journal.ppat.1010331 |
| work_keys_str_mv | AT lauramunozbaena usingnetworkstoanalyzeandvisualizethedistributionofoverlappinggenesinvirusgenomes AT artfypoon usingnetworkstoanalyzeandvisualizethedistributionofoverlappinggenesinvirusgenomes |