Floral signals evolve in a predictable way under artificial and pollinator selection in Brassica rapa

Abstract

Background Angiosperms 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. Results We 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. Conclusions Overall, 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.

The convergent evolution of hummingbird pollination results in repeated floral scent loss through gene downregulation

“…Yet all three species produce little to no floral scent, suggesting there can be quick breakdown of floral scent production following pollinator transitions. This observation is consistent with previous studies that have shown that floral scent often evolves rapidly in response to selection (Ramos and Schiestl 2019;Zu et al 2020;Liu et al 2024).…”

The influence of genetic architecture on responses to selection under drought in rice

“…When genetic correlations oppose the direction of selection, evolutionary responses can be constrained (Conner, 2012;Etterson & Shaw, 2001;Lande & Arnold, 1983). Such constraints can be investigated through quantitative genetics using the G-matrix of additive genetic variances and covariances and the selection gradients, as has been done in a number of prior studies (Colautti & Barrett, 2011;Conner & Agrawal, 2005;Franks et al, 2012;Johnson et al, 2009;Smith & Rausher, 2008;Zu et al, 2020). Several different approaches have been used to quantify how much of a constraint would occur due to genetic correlations (Calsbeek & Goodnight, 2009), but a simple first approach is to compare direct and indirect selection, given that direct selection accounts for selection directly acting on a trait without accounting for correlations, while indirect selection includes selection driven by selection acting on other correlated traits (Conner & Hartl, 2004).…”

Environmental effects on genetic variance are likely to constrain adaptation in novel environments

“…These are often found by decomposing G into independent axes, akin to principal components, representing directions in which phenotypes vary genetically ( Lande, 1979 ; Walsh & Blows, 2009 ). The primary axis of G , known as g max , is the direction of the phenotype in which genetic variation is most abundant and the direction in which phenotypic evolution is expected to occur ( Costa e Silva et al, 2020 ; McGlothlin et al, 2018 ; Schluter, 1996 ; Walter, 2023 ; Zu et al, 2020 ).…”