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, bHLH and WD40 transcriptional regulators, and its function has been extensively studied, particularly in model species of petunia. We built a phylotranscriptomic dataset 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 dataset 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. While 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, while 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.
Urban areas are increasingly affected by extreme heat in the face of climate change, while the size and vulnerability of exposed populations are shifting due to economic development, demographic change, and urbanization. In addition to the need to assess future urban heat-related health risks, there is also an increasing need to design adaptation strategies that will be effective under varying levels of socioeconomic development and climate change. We use the case study of Houston, Texas, to develop and demonstrate a scenario-based approach to explore the effectiveness of both autonomous and planned heat-related adaptations under multiple plausible futures. We couple a heat risk model with urban climate projections (under the Representative Concentration Pathways) and vulnerability projections (under locally extended Shared Socioeconomic Pathways) to investigate the impact of different adaptation strategies under multiple scenario combinations. We demonstrate that, in the context of Houston, community-based adaptation strategies aiming to reduce social isolation are the most effective and the least challenging to implement across all plausible futures. Scenario-based approaches can provide local policymakers with context-specific assessments of possible adaptation strategies that account for uncertain futures.
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