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Interaction among ploidy, breeding system and lineage diversification
Author(s) -
ZenilFerguson Rosana,
Burleigh J. Gordon,
Freyman William A.,
Igić Boris,
Mayrose Itay,
Goldberg Emma E.
Publication year - 2019
Publication title -
new phytologist
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.742
H-Index - 244
eISSN - 1469-8137
pISSN - 0028-646X
DOI - 10.1111/nph.16184
Subject(s) - biology , polyploid , ploidy , evolutionary biology , genetic algorithm , diversification (marketing strategy) , trait , phylogenetic tree , extinction (optical mineralogy) , phylogenetics , lineage (genetic) , macroevolution , genetics , gene , paleontology , marketing , computer science , business , programming language
Summary If particular traits consistently affect rates of speciation and extinction, broad macroevolutionary patterns can be interpreted as consequences of selection at high levels of the biological hierarchy. Identifying traits associated with diversification rates is difficult because of the wide variety of characters under consideration and the statistical challenges of testing for associations from comparative phylogenetic data. Ploidy (diploid vs polyploid states) and breeding system (self‐incompatible vs self‐compatible states) are both thought to be drivers of differential diversification in angiosperms. We fit 29 diversification models to extensive trait and phylogenetic data in Solanaceae and investigate how speciation and extinction rate differences are associated with ploidy, breeding system, and the interaction between these traits. We show that diversification patterns in Solanaceae are better explained by breeding system and an additional unobserved factor, rather than by ploidy. We also find that the most common evolutionary pathway to polyploidy in Solanaceae occurs via direct breakdown of self‐incompatibility by whole genome duplication, rather than indirectly via breakdown followed by polyploidization. Comparing multiple stochastic diversification models that include complex trait interactions alongside hidden states enhances our understanding of the macroevolutionary patterns in plant phylogenies.