| Title: | Floral signals evolve in a predictable way under artificial and pollinator selection in Brassica rapa |
| Author(s): | Zu P; Schiestl FP; Gervasi D; Li X; Runcie D; Guillaume F; |
| Address: | "Department of Systematic and Evolutionary Botany, University of Zurich, Zollikerstrasse 107, CH-8008, Zurich, Switzerland. Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA, 02139, USA. Department of Plant Sciences, University of California Davis, One Shields Avenue, Davis, CA, 95616, USA. Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, CH-8057, Zurich, Switzerland. frederic.guillaume@ieu.uzh.ch" |
| DOI: | 10.1186/s12862-020-01692-7 |
| ISSN/ISBN: | 1471-2148 (Electronic) 1471-2148 (Linking) |
| 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" |
| Keywords: | "Animals Bees *Brassica rapa/genetics Diptera Flowers/*genetics Phenotype *Pollination *Selection, Genetic Adaptive evolution Artificial selection Brassica rapa Experimental evolution Floral scent G-matrix Multivariate prediction Pollinator selection;" |
| Notes: | "MedlineZu, Pengjuan Schiestl, Florian P Gervasi, Daniel Li, Xin Runcie, Daniel Guillaume, Frederic eng PP00P3_144846/Schweizerischer Nationalfonds zur Forderung der Wissenschaftlichen Forschung/International 281093/FP7 Ideas: European Research Council/International Research Support, Non-U.S. Gov't England 2020/09/26 BMC Evol Biol. 2020 Sep 24; 20(1):127. doi: 10.1186/s12862-020-01692-7" |
