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Can Cis-Regulatory Elements Explain Differences in Petunia Pollination Syndromes?
Aléxia G Pereira1, João Pedro C Filgueiras1, Loreta B Freitas1
1Department of Genetics, Universidade Federal do Rio Grande do Sul, 9500 Bento Gonçalves, Av., Porto Alegre 91509-900, Brazil.
Abstract:
Background: Transcription factors have been linked to changes in various physiological processes, such as attractive and rewarding phenotypes during plant-pollinator interactions. In the genus Petunia, most species are pollinated by bees, but hawkmoth- and bird pollination are also observed. Here, we aimed to test the hypothesis that species with the same pollination syndrome evolved through convergence, while differences in pollinators indicate divergence. We selected six genes (MYB-FL, DFR, EOBII, ODO1, BPBT, and NEC1) involved in establishing pollination syndromes to explore the potential role of cis-regulatory elements in shifts among pollination syndromes, attracting and rewarding pollinators. Methods: We retrieved the genomic sequences of genes from the genomes of four Petunia species, which exhibit distinct pollination syndromes. We analyzed the cis-regulatory elements, focusing on the structure and composition of motifs, and inferred the functions of these transcription factors using Gene Ontology analysis. Results: All sequences were highly conserved among species, with variations in promoter motif structure and TF binding sites. The evolutionary relationships among the genes closely reflected the species' phylogeny. Likewise, regulatory elements and gene structure mostly followed the species' evolutionary history. However, different pollination syndromes are present, and there is an unexpected lack of convergence between the two bee-pollinated species. Conclusions: Our findings showed that the most recent common ancestor of these species better predicts relationships among gene regulatory elements than does the pollination syndrome. To fully understand the evolution of pollination syndromes in Petunia, additional studies are needed to analyze entire pathways and compare genomes and transcriptomes.
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