This is a Preprint and has not been peer reviewed.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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Abstract
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.
DOI
https://doi.org/10.32942/X2759X
Subjects
Biology, Evolution, Life Sciences
Keywords
flavonoids, flower color, canonical correlation analysis, pathway evolution, phylo-transcriptomics, Petunieae, Solanaceae, molecular evolution, phenotypic evolution
Dates
Published: 2023-02-03 11:35
Last Updated: 2023-07-07 18:09
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License
CC-BY Attribution-NonCommercial 4.0 International
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Conflict of interest statement:
None
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.
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