Reticulate Evolution Helps Explain Apparent Homoplasy in Floral Biology and Pollination in Baobabs (Adansonia; Bombacoideae; Malvaceae)

Abstract

Baobabs (Adansonia) are a cohesive group of tropical trees with a disjunct distribution in Australia, Madagascar, and continental Africa, and diverse flowers associated with two pollination modes. We used custom-targeted sequence capture in conjunction with new and existing phylogenetic comparative methods to explore the evolution of floral traits and pollination systems while allowing for reticulate evolution. Our analyses suggest that relationships in Adansonia are confounded by reticulation, with network inference methods supporting at least one reticulation event. The best supported hypothesis involves introgression between Adansonia rubrostipa and core Longitubae, both of which are hawkmoth pollinated with yellow/red flowers, but there is also some support for introgression between the African lineage and Malagasy Brevitubae, which are both mammal-pollinated with white flowers. New comparative methods for phylogenetic networks were developed that allow maximum-likelihood inference of ancestral states and were applied to study the apparent homoplasy in floral biology and pollination mode seen in Adansonia. This analysis supports a role for introgressive hybridization in morphological evolution even in a clade with highly divergent and geographically widespread species. Our new comparative methods for discrete traits on species networks are implemented in the software PhyloNetworks. [Comparative methods; Hyb-Seq; introgression; network inference; population trees; reticulate evolution; species tree inference; targeted sequence capture.]

Polyploid phylogenetics

“…A wide range of studies, such as the application of sophisticated hidden‐state state‐dependent diversification models to infer the relationships among polyploidy, breeding system evolution, and diversification (Zenil‐Ferguson et al ., 2019), or the investigation of the time‐dependency of polyploid diversification in a model like that of Freyman & Höhna (2018b), testing whether polyploids, if they survive an initial period of high extinction, tend to then diversify at elevated rates (Mayrose et al ., 2011; Tank et al ., 2015; Landis et al ., 2018), would all gain a greater biological realism and precision by the adoption of a polyploid phylogenetics approach. Some of these applications are already available, such as character state reconstruction on networks (Bastide et al ., 2018), which has resulted in novel insights that would not have been attainable if the researchers based their reconstructions on bifurcating trees (Karimi et al ., 2019). Others, however, including the inference of allopolyploidisation in a BiSSE‐like framework, await the development of a fully integrated tree model that models polyploidisations alongside speciation and extinction (some components of this model are available, e.g.…”

Phylogenomic Assessment of the Role of Hybridization and Introgression in Trait Evolution

“…Several computational methods for inferring phylogenetic networks based on this model were then developed, many of which are reviewed in [7]. Hybridization and introgression could impact and help explain trait evolution [20], and methods for tracing the evolution of a trait on a phylogenetic network were introduced in [19,2]. However, these methods do not take a "phylogenomic view" on trait evolution, i.e., they do not account for gene tree incongruence to tease apart homoplasy and hemiplasy.…”

Determining the probability of hemiplasy in the presence of incomplete lineage sorting and introgression

“…More recently,Bastide et al (2018) andKarimi et al (2020) developed extensions to comparative methods that allow quantitative trait likelihoods to be calculated on phylogenetic networks. However, while phylogenetic network inference methods are often robust to the effects of ILS (Solís-Lemus & Ané 2016, Wen et al 2018), the estimated networks themselves do not contain the necessary information to simultaneously capture the effects of ILS and introgression on trait probabilities (cf.…”