Evolutionary walks through flower color space driven by gene expression in Petunia and allies (Petunieae)

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1098/rspb.2023.0275. This is version 2 of this Preprint.

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Lucas C Wheeler, Amy Dunbar-Wallis, Kyle Schutz, Stacey D. Smith


The structure and function of biochemical and developmental pathways determine the range of accessible phenotypes, which are the substrate for evolutionary change. Accordingly, we expect that observed phenotypic variation across species is strongly influenced by pathway structure, with different phenotypes arising due to changes in activity along pathway branches. Here, we use flower colour as a model to investigate how the structure of pigment pathways shapes the evolution of phenotypic diversity. We focus on the phenotypically diverse Petunieae clade in the nightshade family, which contains ca 180 species of Petunia and related genera, as a model to understand how flavonoid pathway gene expression maps onto pigment production. We use multivariate comparative methods to estimate co-expression relationships between pathway enzymes and transcriptional regulators, and then assess how expression of these genes relates to the major axes of variation in floral pigmentation. Our results indicate that coordinated shifts in gene expression predict transitions in both total anthocyanin levels and pigment type, which, in turn, incur trade-offs with the production of UV-absorbing flavonol compounds. These findings demonstrate that the intrinsic structure of the flavonoid pathway and its regulatory architecture underlies the accessibility of pigment phenotypes and shapes evolutionary outcomes for floral pigment production.




Biology, Evolution, Life Sciences


flavonoids, flower color, canonical correlation analysis, pathway evolution, phylo-transcriptomics, Petunieae, Solanaceae, molecular evolution, phenotypic evolution


Published: 2023-02-03 07:35

Last Updated: 2023-07-07 12:09

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CC-BY Attribution-NonCommercial 4.0 International

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Conflict of interest statement:

Data and Code Availability Statement:
The transcriptome assemblies, scripts, and processed data files used to conduct the analyses are available in the supplementary OSF repo (https://osf.io/zg9cu/). The raw RNA-seq data files have been added to the existing SRA BioProject PRJNA746328.