ABI Innovation: A New Framework to Analyze Plant Energy-Related Phenomics Data

Large-scale phenotyping (phenomics) promises to bridge the gap between genomics, gene functions and traits. Specifically, to meet our growing needs for food and fuel, new bio]imaging approaches were developed to allow high]throughput, detailed plant phenotyping, with a focus on improving the efficiency of photosynthesis. We aim to identify genes and processes that control photosynthesis efficiency in response to fluctuating environmental conditions, which are critical for understanding and improving plant energy storage and improving crop productivity. To achieve this, we must resolve a wide range of interacting factors that respond to environmental factors over very wide dynamic ranges of frequency, duration and intensity of conditions. Recently, we have developed the Dynamic Environmental Phenotype Imager (DEPI), a novel platform for monitoring responses of plant phenotypes under dynamic conditions. Initial data from DEPI reveals previously unseen effects attributable to genes formerly thought to have no known function. One of those discoveries will be elaborated here in Aim 4. While these developments on plant phenotyping are exciting, we are limited by the tools to analyze fully the phenomics data. Removing that limitation is the proposed goal of this project.