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Transcription Factors Evolve Faster Than Their Structural Gene Targets in the Flavonoid Pigment Pathway
Abstract
Dissecting the relationship between gene function and substitution rates is key to understanding genome-wide patterns of molecular evolution. Biochemical pathways provide powerful systems for investigating this relationship because the functional role of each gene is often well characterized. Here, we investigate the evolution of the flavonoid pigment pathway in the colorful Petunieae clade of the tomato family (Solanaceae). This pathway is broadly conserved in plants, both in terms of its structural elements and its MYB, basic helix–loop–helix, and WD40 transcriptional regulators, and its function has been extensively studied, particularly in model species of petunia. We built a phylotranscriptomic data set for 69 species of Petunieae to infer patterns of molecular evolution across pathway genes and across lineages. We found that transcription factors exhibit faster rates of molecular evolution (dN/dS) than their targets, with the highly specialized MYB genes evolving fastest. Using the largest comparative data set to date, we recovered little support for the hypothesis that upstream enzymes evolve slower than those occupying more downstream positions, although expression levels do predict molecular evolutionary rates. Although shifts in floral pigmentation were only weakly related to changes affecting coding regions, we found a strong relationship with the presence/absence patterns of MYB transcripts. Intensely pigmented species express all three main MYB anthocyanin activators in petals, whereas pale or white species express few or none. Our findings reinforce the notion that pathway regulators have a dynamic history, involving higher rates of molecular evolution than structural components, along with frequent changes in expression during color transitions.
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If a replicated change in phenotype has been achieved through changes in different genetic elements, PhyloG2P methods will fail to identify them unless considerable prior knowledge of the genetic elements involved can be leveraged to identify genetic replication at the network or pathway level.
“If a replicated change in phenotype has been achieved through changes in different genetic elements, then PhyloG2P methods will fail to identify them unless considerable prior knowledge of the genetic elements involved can be leveraged to identify genetic replication at the network or pathway level (Lamichhaney et al. 2019; Wheeler et al. 2022; Eastment et al. 2024; Shakya et al. 2025).”
From From Trees to Traits: A Review of Advances in PhyloG2P Methods and Future Directions (2025) · cites this paper as Wheeler et al. 2022
Studies using only a single PhyloG2P method limit the scope of conclusions they can draw and risk missing important genetic elements associated with the trait.
“Such studies limit the scope of the conclusions they can draw, and risk missing important genetic elements associated with the trait (Wheeler et al. 2022).”
From From Trees to Traits: A Review of Advances in PhyloG2P Methods and Future Directions (2025) · cites this paper as Wheeler et al. 2022
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Sorted by citations
From Trees to Traits: A Review of Advances in PhyloG2P Methods and Future Directions
Macdonald, A. R., James, M. E., Mitchell, J. D., & Holland, B. R. (2025) · Genome Biology and Evolution · doi:10.1093/gbe/evaf150 · Cited by 5
Metadata
- Authors
- Wheeler, L. C., Walker, J. F., Ng, J., Deanna, R., Dunbar-Wallis, A., Backes, A., Pezzi, P. H., Palchetti, M. V., Robertson, H. M., Monaghan, A., de Freitas, L. B., Barboza, G. E., Moyroud, E., & Smith, S. D.
- Affiliations
- Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, CO, USA
- Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom
- Laboratory of Molecular Evolution, Department of Genetics, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Instituto Multidisciplinario de Biología Vegetal (IMBIV), CONICET and Universidad Nacional de Córdoba, Córdoba, Argentina
- Research Computing, University of Colorado, Boulder, CO, USA
- Venue
- Molecular Biology and Evolution
- Publisher
- Oxford University Press (OUP)
- Published
- 2022-02-25
- Volume
- 39
- Issue
- 3
- ISSN
- 0737-4038
- 1537-1719
- PMC
- PMC8911815
- Cited by
- 63
- References
- 4
- Language
- en
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