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Application of Transient Intervention and Live-Imaging Methods to Resolve Cellular and Molecular Networks Regulating Stem-Cell Homeostatis in Arabidopsis Shoot Apex

$1,014,002FY2007BIONSF

University Of California-Riverside, Riverside CA

Investigators

Abstract

Venugopala Reddy Gonehal 0718046 Application of transient intervention and live-imaging methods to resolve cellular and molecular networks regulating stem-cell homeostasis in Arabidopsis shoot apex Cell division of stem-cells is critical to ensure proper development, maintenance and repair of tissues and organs of both animals and plants. In plants, the shoot tip (shoot apical meristem; SAM) harbors a set of stem-cells that are surrounded by differentiating cells. The stem-cell number remains constant, even though the stem-cell progeny are being continually diverted to differentiating cells. Thus, the SAM represents a dynamic network of different cell types in which growth and differentiation are dynamically regulated through a cell-cell communication network that precisely controls spatial and temporal patterns of gene expression. Understanding how cells interpret this complex mixture of signals to regulate cell division requires the development of new methods that identify network components and elucidate their regulatory dynamics and function. In this proposal, the PI will apply transient genetic and physical manipulations with live-imaging technologies to explore the function and regulation of key regulators of stem-cell maintenance. The PI also will combine transient gene manipulation and stem-cell enrichment methods with microarray technology to develop a dynamic map of cellular and molecular interactions in actively growing SAMs with the ultimate objective of developing predictive models of cell-cell communication that mediate stem cell homeostasis. Training will be provided for a post-doctoral fellow, graduate student and under-graduate students in designing new methods of transient gene manipulation, expression profiling and live-imaging. They will be exposed to state-of-the art imaging systems and image processing platforms for visualization, rendering and analysis of microscopic data. Early exposure of a new generation of scientists to dynamic methods of data acquisition and data handling would prepare them for future challenges of quantitative imaging.

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