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Data_Sheet_2_Sex-Dependent Variation of Pumpkin (Cucurbita maxima cv. Big Max) Nectar and Nectaries as Determined by Proteomics and Metabolomics.XLSX (15.45 kB)

Data_Sheet_2_Sex-Dependent Variation of Pumpkin (Cucurbita maxima cv. Big Max) Nectar and Nectaries as Determined by Proteomics and Metabolomics.XLSX

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posted on 2018-06-29, 08:56 authored by Elizabeth C. Chatt, Patrick von Aderkas, Clay J. Carter, Derek Smith, Monica Elliott, Basil J. Nikolau

Nectar is a floral reward that sustains mutualisms with pollinators, which in turn, improves fruit set. While it is known that nectar is a chemically complex solution, extensive identification and quantification of this complexity has been lacking. Cucurbita maxima cv. Big Max, like many cucurbits, is monoecious with separate male and female flowers. Attraction of bees to the flowers through the reward of nectar is essential for reproductive success in this economically valuable crop. In this study, the sex-dependent variation in composition of male and female nectar and the nectaries were defined using a combination of GC-MS based metabolomics and LC-MS/MS based proteomics. Metabolomics analysis of nectar detected 88 metabolites, of which 40 were positively identified, and includes sugars, sugar alcohols, aromatics, diols, organic acids, and amino acids. There are differences in 29 metabolites between male and female nectar. The nectar proteome consists of 45 proteins, of which 70% overlap between nectar types. Only two proteins are unique to female nectar, and 10 are specific to male nectar. The nectary proteome data, accessible at ProteomeXchange with identifier PXD009810, contained 339 identifiable proteins, 71% of which were descriptively annotatable by homology to Plantae. The abundance of 45 proteins differs significantly between male and female nectaries, as determined by iTRAQ labeling. This rich dataset significantly expands the known complexity of nectar composition, supports the hypothesis of H+-driven nectar solute export, and provides genetic and chemical targets to understand plant–pollinator interactions.

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