Gravitropic signal transduction: a network approach to identifying regulatory mechanisms

点击翻译按钮获取中文摘要

Gravity plays a fundamental role in plant growth and development, controlling the direction of shoot and root growth at germination, positioning of organs for light capture, nutrient absorption and to facilitate pollination and seed dispersal. Plants have interacted with, adapted to and modified their responses to gravity throughout evolution, and we, as humans, have selected plants for agriculture and horticulture based on these responses. For simplicity, the physiological response pathways have been separated into three sequential steps: perception, signal transduction, and response. The events of gravity perception and the mechanisms resulting in the gravity response are fairly well defined, but the events of signal transduction remain, for the most part, a "black box." Using a cold effect, dubbed the gravity persistent signal (GPS) response, a mutant screen has been developed toidentify specifically components of the signal transduction pathway. The gps mutants have already provided new insights into the gravity signal transduction pathway. This project combines the GPS response with gene expression microarrays, proteomics analysis, and continued mutant analysis to identified molecular networks that result in adaptations to changes in gravity. The data will be used to build a computer-generated model (a gravity signaling-specific interactome) to identify candidate genes/proteins for hypothesis development and testing. Besides providing new, fundamental information to supplement existing models of plant gravitropism, the outcomes of this research could lead to innovations to improve harvesting capability, post-harvest handling, or lead to new plant varieties that better suit human needs. The PI is dedicated to education and outreach and uses her research as a launching point for those interactions and anticipates that the current project will provide additional research and training opportunities for several undergraduates and graduate students. It will also provide the foundation for a novel, computer-game like, teaching tool on how genes interact.