A molecular phenology scale of fruit development

Abstract

Fruit growth and development consists of a continuous succession of physical, biochemical, and physiological changes driven by a genetic program that dynamically responds to environmental cues. Establishing recognizable stages over the whole fruit lifetime represents a fundamental requirement for research and fruit crop cultivation. This is especially relevant in perennial crops like the grapevine to scale the development of its fruit across genotypes and growing conditions. In this work, molecular-based information from several grape berry transcriptomic datasets was exploited to build a molecular phenology scale (MPhS) and to map the ontogenic development of the fruit. The proposed statistical pipeline consisted in an unsupervised learning procedure yielding an innovative combination of semiparametric, smoothing and dimensionality reduction tools. The transcriptomic distance between fruit samples was precisely quantified by means of the MPhS that also enabled to highlight the winding dynamics of the transcriptional program over berry development through the calculation of the rate of variation of MPhS stages by time. The MPhS allowed the alignment of time-series fruit samples proving to be a step forward in mapping the progression of grape berry development with higher precision compared to classic time- or phenotype-based approaches and inspiring the use of the transcriptional information to scale the developmental progression of any organ in any plant species.