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- Title
pSONIC: Ploidy-aware Syntenic Orthologous Networks Identified via Collinearity.
- Authors
Conover, Justin L.; Sharbrough, Joel; Wendel, Jonathan F.
- Abstract
With the rapid rise in availability of high-quality genomes for closely related species, methods for orthology inference that incorporate synteny are increasingly useful. Polyploidy perturbs the 1:1 expected frequencies of orthologs between two species, complicating the identification of orthologs. Here we present a method of ortholog inference, Ploidy-aware Syntenic Orthologous Networks Identified via Collinearity (pSONIC). We demonstrate the utility of pSONIC using four species in the cotton tribe (Gossypieae), including one allopolyploid, and place between 75% and 90% of genes from each species into nearly 32,000 orthologous groups, 97% of which consist of at most singletons or tandemly duplicated genes--58.8% more than comparable methods that do not incorporate synteny. We show that 99% of singleton gene groups follow the expected tree topology and that our ploidy-aware algorithm recovers 97.5% identical groups when compared to splitting the allopolyploid into its two respective subgenomes, treating each as separate "species."
- Subjects
POLYPLOIDY; ALGORITHMS; SPECIES; GENOMES
- Publication
G3: Genes | Genomes | Genetics, 2021, Vol 11, Issue 8, p1
- ISSN
2160-1836
- Publication type
Article
- DOI
10.1093/g3journal/jkab170