bioRxivEvolutionary Biology
Ecological diversification in an adaptive radiation of plants: the role of de novo mutation and introgression
Abstract
Adaptive radiations are characterized by rapid ecological diversification and speciation events, leading to fuzzy species boundaries between ecologically differentiated species. Adaptive radiations are therefore key systems for understanding how species are formed and maintained, including the role of de novo mutations vs. pre-existing variation in ecological adaptation and the genome-wide consequences of hybridization events. For example, adaptive introgression, where beneficial alleles are transferred between lineages through hybridization, may fuel diversification in adaptive radiations and facilitate adaptation to new environments. In this study, we employed whole-genome resequencing data to investigate the evolutionary origin of hummingbird-pollinated flowers and to characterize genome-wide patterns of phylogenetic discordance and introgression in Penstemon subgenus Dasanthera, a small and diverse adaptive radiation of plants. We found that magenta hummingbird-adapted flowers have apparently evolved twice from ancestral blue-violet bee-pollinated flowers within this radiation. These shifts in flower color are accompanied by a variety of inactivating mutations to a key anthocyanin pathway enzyme, suggesting that independent de novo loss-of-function mutations underlie parallel evolution of this trait. Although patterns of introgression and phylogenetic discordance were heterogenous across the genome, a strong effect of gene density suggests that, in general, natural selection opposes introgression and maintains genetic differentiation in gene-rich genomic regions. Our results highlight the importance of both de novo mutation and introgression as sources of evolutionary change and indicate a role for de novo mutation in driving parallel evolution in adaptive radiations.
- organism: plant (other)
- assay: whole-genome sequencing
- research focus: ecology & biodiversity
- approach: statistical model
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