Unraveling the key molecular events of Pinot noir berry ripening under varying crop load

Abstract

Aligned to exploring the physiological and molecular complexity of grape berry development, there is a need to characterize the influence of the source:sink relationships on the genetic regulation of fruit composition. Crop load, as defined by the amount of fruit produced per unit vegetative growth at dormancy, is a common measure of source:sink relationships used to evaluate vineyard production efficiency. We studied the impact of varying crop load on the transcriptome and metabolome of Pinot noir grape berries by comparing the development and ripening of fruit grown on vines with either 50 % or 75 % of their grape clusters removed immediately following fruit set compared to unthinned vines for three consecutive vintages. A clear impact on the general phenylpropanoid pathway resulting in a redistribution between stilbenes and anthocyanins was revealed under varying crop loads and consistent with the transcriptomic profiles of the corresponding branches. Moreover, we identified genes, such as LBDIa3 and AG2, modulated by crop load around veraison, representing putative transcriptional key triggers of the berry ripening phase responding to differences in the vine source:sink ratio generated by the application of cluster thinning. Genes, specifically EXPA1 and EXPA18, involved in softening and other crucial events of ripening initiation responded to crop load and likely influenced the progression of the ripening process. Beyond the major impacts represented by a shift of the onset and completion of ripening, we were able to highlight more subtle effects of the crop load, related to the rate at which the molecular and metabolic changes occur. This study asserts that grape metabolism and transcriptome are remarkably flexible, and that manipulations such as cluster thinning induce extensive, genome-wide changes in expression during berry development. The insights gained here pave the way to progress towards the construction of robust models depicting the molecular network that characterizes berry development and the impact of crop load on its molecular regulation.