Arabidopsis 2010: Nitrogen Networks in Plants

New York University, New York NY

Investigators

Abstract

This project involves the determination of functional gene networks regulated by nitrogen status. Targets for functional analysis will be the key nodes controlling N-regulation of metabolic and developmental networks associated with growth and seed development- key agronomic traits. Regulatory hubs of these N-networks will be identified using "multinetwork" analysis in which "edges" connecting gene "nodes" are supported by multiple data/evidence including; metabolic pathways, protein:protein, protein:DNA, and microRNA:target datasets. Microarray data from leaves, roots, root cell-types and seeds of nitrogen-treated Arabidopsis will be analzed using this multinetwork to determine. Machine learning techniques will be used to predict mechanisms of N-regulation of networks and to identify putative regulatory nodes. Predictions of key regulatory nodes will be based on expression data, number, types, and weight of edges linked to a node, and will implicate transcription factors, signal transducers or genes encoding microRNAs as potential regulators. This analysis will be iterative, to refine predictions using kinetic microarray and growth data from wild-type and mutants in putative regulators. Specific aims of this project are: Aim 1. Integrate network responses to N-sources and interactions between nitrogen, carbon and light signaling. Aim 2. Integrate N-regulatory networks and development. Aim 3: Integrate omic-datasets and identify regulatory nodes in multinetworks. Aim 4. In vivo testing of N-network models and putative regulatory nodes. Long term, these systems-based models can be used in a predictive mode to target regulatory nodes that may be modified in transgenic plants to alter N-use efficiency for agronomic purposes. As such, the aims of this project are therefore directly in line with the 2010 goals to "Identify and analyze function of networks of genes; dissect nodes, and integrate computational modeling with experimentation". Broader Impacts: This project involves a number of collaborations with other plant genome groups including Arabidopsis small RNAs, Medicago and Lotus genome groups. The functional information on the components of these gene networks and regulatory nodes controlling them will be published and deposited in The Arabidopsis Information Resource Database (TAIR) using structured vocabularies to facilitate future bioinformatic analysis of the data. The expression data generated will also be made available to the community through public repositories such as ArrayExpress, and also on our N2010 website http://www.nyu.edu/fas/dept/biology/n2010/. The Arabidopsis transgenic/mutant lines generated in these studies will be deposited in the ABRC. The project will provide an excellent mechanism for training students and post-doctoral fellows in interdisciplinary research.