Different orthology inference algorithms generate similar predicted orthogroups among Brassicaceae species
Abstract Premise Orthology inference is crucial for comparative genomics, and multiple algorithms have been developed to identify putative orthologs for downstream analyses. Despite the abundance of proposed solutions, including publicly available benchmarks, it is difficult to assess which tool is...
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| Format: | Article |
| Language: | English |
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Wiley
2025-01-01
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| Series: | Applications in Plant Sciences |
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| Online Access: | https://doi.org/10.1002/aps3.11627 |
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| author | Irene T. Liao Karen E. Sears Lena C. Hileman Lachezar A. Nikolov |
| author_facet | Irene T. Liao Karen E. Sears Lena C. Hileman Lachezar A. Nikolov |
| author_sort | Irene T. Liao |
| collection | DOAJ |
| description | Abstract Premise Orthology inference is crucial for comparative genomics, and multiple algorithms have been developed to identify putative orthologs for downstream analyses. Despite the abundance of proposed solutions, including publicly available benchmarks, it is difficult to assess which tool is most suitable for plant species, which commonly have complex genomic histories. Methods We explored the performance of four orthology inference algorithms—OrthoFinder, SonicParanoid, Broccoli, and OrthNet—on eight Brassicaceae genomes in two groups: one group comprising only diploids and another set comprising the diploids, two mesopolyploids, and one recent hexaploid genome. Results The composition of the orthogroups reflected the species' ploidy and genomic histories, with the diploid set having a higher proportion of identical orthogroups. While the diploid + higher ploidy set had a lower proportion of orthogroups with identical compositions, the average degree of similarity between the orthogroups was not different from the diploid set. Discussion Three algorithms—OrthoFinder, SonicParanoid, and Broccoli—are helpful for initial orthology predictions. Results produced using OrthNet were generally outliers but could still provide detailed information about gene colinearity. With our Brassicaceae dataset, slight discrepancies were found across the orthology inference algorithms, necessitating additional analyses such as tree inference to fine‐tune results. |
| format | Article |
| id | doaj-art-f90e5301c7ec484691b310f6be2fbf53 |
| institution | Kabale University |
| issn | 2168-0450 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Applications in Plant Sciences |
| spelling | doaj-art-f90e5301c7ec484691b310f6be2fbf532025-02-03T12:21:34ZengWileyApplications in Plant Sciences2168-04502025-01-01131n/an/a10.1002/aps3.11627Different orthology inference algorithms generate similar predicted orthogroups among Brassicaceae speciesIrene T. Liao0Karen E. Sears1Lena C. Hileman2Lachezar A. Nikolov3Department of Molecular, Cell, and Development Biology University of California – Los Angeles Los Angeles California USADepartment of Molecular, Cell, and Development Biology University of California – Los Angeles Los Angeles California USADepartment of Ecology and Evolutionary Biology University of Kansas Lawrence Kansas USADepartment of Biology Indiana University Bloomington 47405 Indiana USAAbstract Premise Orthology inference is crucial for comparative genomics, and multiple algorithms have been developed to identify putative orthologs for downstream analyses. Despite the abundance of proposed solutions, including publicly available benchmarks, it is difficult to assess which tool is most suitable for plant species, which commonly have complex genomic histories. Methods We explored the performance of four orthology inference algorithms—OrthoFinder, SonicParanoid, Broccoli, and OrthNet—on eight Brassicaceae genomes in two groups: one group comprising only diploids and another set comprising the diploids, two mesopolyploids, and one recent hexaploid genome. Results The composition of the orthogroups reflected the species' ploidy and genomic histories, with the diploid set having a higher proportion of identical orthogroups. While the diploid + higher ploidy set had a lower proportion of orthogroups with identical compositions, the average degree of similarity between the orthogroups was not different from the diploid set. Discussion Three algorithms—OrthoFinder, SonicParanoid, and Broccoli—are helpful for initial orthology predictions. Results produced using OrthNet were generally outliers but could still provide detailed information about gene colinearity. With our Brassicaceae dataset, slight discrepancies were found across the orthology inference algorithms, necessitating additional analyses such as tree inference to fine‐tune results.https://doi.org/10.1002/aps3.11627Brassicaceaecomparative genomicsorthogrouporthology inferencephylogenomicsYABBY gene family |
| spellingShingle | Irene T. Liao Karen E. Sears Lena C. Hileman Lachezar A. Nikolov Different orthology inference algorithms generate similar predicted orthogroups among Brassicaceae species Applications in Plant Sciences Brassicaceae comparative genomics orthogroup orthology inference phylogenomics YABBY gene family |
| title | Different orthology inference algorithms generate similar predicted orthogroups among Brassicaceae species |
| title_full | Different orthology inference algorithms generate similar predicted orthogroups among Brassicaceae species |
| title_fullStr | Different orthology inference algorithms generate similar predicted orthogroups among Brassicaceae species |
| title_full_unstemmed | Different orthology inference algorithms generate similar predicted orthogroups among Brassicaceae species |
| title_short | Different orthology inference algorithms generate similar predicted orthogroups among Brassicaceae species |
| title_sort | different orthology inference algorithms generate similar predicted orthogroups among brassicaceae species |
| topic | Brassicaceae comparative genomics orthogroup orthology inference phylogenomics YABBY gene family |
| url | https://doi.org/10.1002/aps3.11627 |
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