Elucidating Gene Networks Regulating Development in Tomato

University Of California-Davis, Davis CA

Investigators

Abstract

PI: Neelima R. Sinha (University of California, Davis) CoPI: Julin Maloof (University of California, Davis) CoPI: Jie Peng (University of California, Davis) Plants acquire the bulk of their energy from light capture by leaves, and leaf shape has direct consequences on the efficiency of light capture and photosynthetic carbon fixation. As a result, leaf shape must be optimized in response to variation in light quality. To understand the processes controlling these fundamental processes, genetic networks regulating both environmental response and morphological form must be integrated. This project uses a genomics approach to understand natural variation in leaf morphology and light response, and to investigate the mechanism by which these two genetic networks are integrated to ensure optimal plant form. These goals will be accomplished by characterizing the differences between tomato species varying in both light response and leaf complexity. Characterization of these differences will be made using genomic technologies to find differences in DNA sequence and gene expression. Statistical analyses will be used to reconstruct the web of interacting genes (genetic networks) that regulate leaf morphology and light responses. This analysis will allow identification of central regulators of development and developmental variation. Increased knowledge of the basis of phenotypic diversity in the developmental and environmental context should allow better manipulation of crop systems for improved agricultural productivity. Finally, a program will be developed to train future researchers and students from under-represented groups from UC Davis, Cal State University Sacramento, and Los Rios Community College in modern cross-disciplinary genomic biology. All data, gene chip data, BIN maps, QTL analysis and networks generated by this project will be made available to the public as soon as the data has passed quality control. All Solexa sequence data will be deposited in Genbank (http://www.ncbi.nlm.nih.gov/Genbank/). All microarray data will be deposited in the Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo/). In addition, community specific data will be made available via the SOLGENES website (http://www.sgn.cornell.edu/) and a project-specific web site that will be developed.