ArticleBMC evolutionary biology2020
Floral signals evolve in a predictable way under artificial and pollinator selection in Brassica rapa.
Article in BMC evolutionary biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- The Convergent Evolution of Hummingbird Pollination Results in Repeated Floral Scent Loss Through Gene Downregulation.Molecular biology and evolution · 2025Article
- Drought drives selection for earlier flowering, while pollinators drive selection for larger flowers in annualAoB PLANTS · 2025Article
- Environmental effects on genetic variance are likely to constrain adaptation in novel environments.Evolution letters · 2024Article
- Genetic and spatial variation in vegetative and floral traits across a hybrid zone.American journal of botany · 2022Article
- The influence of genetic architecture on responses to selection under drought in rice.Evolutionary applications · 2022Article
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6 authors.
Funding
Abstract
backgroundAngiosperms employ an astonishing variety of visual and olfactory floral signals that are generally thought to evolve under natural selection. Those morphological and chemical traits can form highly correlated sets of traits. It is not always clear which of these are used by pollinators as primary targets of selection and which would be indirectly selected by being linked to those primary targets. Quantitative genetics tools for predicting multiple traits response to selection have been developed since long and have advanced our understanding of evolution of genetically correlated traits in various biological systems. We use these tools to predict the evolutionary trajectories of floral traits and understand the selection pressures acting on them.
resultsWe used data from an artificial selection and a pollinator (bumblebee, hoverfly) evolution experiment with fast cycling Brassica rapa plants to predict evolutionary changes of 12 floral volatiles and 4 morphological floral traits in response to selection. Using the observed selection gradients and the genetic variance-covariance matrix (G-matrix) of the traits, we showed that the observed responses of most floral traits including volatiles were predicted in the right direction in both artificial- and bumblebee-selection experiment. Genetic covariance had a mix of constraining and facilitating effects on evolutionary responses. We further revealed that G-matrices also evolved in the selection processes.
conclusionsOverall, our integrative study shows that floral signals, especially volatiles, evolve under selection in a mostly predictable way, at least during short term evolution. Evolutionary constraints stemming from genetic covariance affected traits evolutionary trajectories and thus it is important to include genetic covariance for predicting the evolutionary changes of a comprehensive suite of traits. Other processes such as resource limitation and selfing also need to be considered for a better understanding of floral trait evolution.
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