We receive funding from the NSF for the project titled:

"Arabidopsis 2010: Identifying transcriptional networks at cellular resolution"

NSF Award Abstract #0618304

Scientific Goals:
The long-term goal of this project is to define the cellular states that occur during root development in Arabidopsis when subjected to different stimuli. As a tractable approach to defining cellular state, transcriptional networks active in different cell types when grown under a variety of environmental conditions will be identified. To describe a first-order transcriptional network three types of data are needed: 1) transcriptional profiles at cell-type specific resolution under normal lab conditions and when subjected to external stimuli; 2) knowledge of transcription factor localization at cellular resolution and 3) information about the targets of transcription factors. For the first, a technique that involves sorting of fluorescently marked cell populations followed by microarray analysis of the RNA from the marked cells will be used. For the second, comparisons will be made of the expression patterns of constructs containing the promoter regions of transcription factors driving fluorescent reporter genes with constructs containing the same promoter regions driving the coding sequences of transcription factors fused to fluorescent reporter genes. For the third, yeast one-hybrid and two-hybrid methods will be used with libraries of tissue-specific transcription factors. Analyses will initially be performed on plants growing under standard laboratory conditions. To determine how expression is perturbed by external stimuli, plants will be systematically subjected to a variety of external stimuli and the effects on transcriptional profiles determined at cell-type specific resolution. To determine the effect of external stimuli on expression at high spatial and temporal resolution a novel technology called the "RootArray" will be developed. The combination of results, from these different approaches, will provide information concerning the function of the identified genes. Results from these studies will be posted on the Arabidopsis Gene Expression Database, at www.arexdb.org.

Broader Impact:
To achieve continued improvement in plant traits while minimizing unwanted side effects will require a sophisticated understanding of the networks that control plant development and physiology. This research will provide a high-resolution dataset for the identification of transcriptional networks active during root development. It will also determine the effect on root transcriptional networks of stimuli relevant to plant growth in the field. Another outcome of the research will be detailed knowledge of the spatial and temporal expression patterns of large numbers of plant genes and the regulatory sequences able to confer specific expression patterns. These should be of immediate value in many plant research programs and are likely to be useful for agronomic purposes as well. Another important part of the project will be to train the next generation of plant scientists in Systems Biology, which integrates computational, engineering and experimental approaches. Postdoctoral fellows, graduate and undergraduate students will be trained in this research. The PIs also will participate actively in outreach efforts such as development of a Systems Biology curriculum at Duke. The research program will also leverage the currently funded NSF IGERT program in biologically inspired materials and material systems directed by Co-PI Clark. A significant focus of the IGERT program is placed upon recruitment and training of women and underrepresented minorities in engineering and the sciences.

Relevance to Arabidopsis 2010 goals:
The research activities will contribute to all three of the primary goals of the Arabidopsis 2010 program. Enhancing the resolution of the root expression map under normal laboratory conditions and producing expression profiles at cell-type specific resolution in response to different stimuli will substantially aid in "Benchmarking Gene Function." Developing computational tools for cis-element identification and automated image analysis as well as developing the RootArray should provide "genome wide experimental approaches and tools for analyzing gene function and regulation." Perhaps most directly, the research has as its aim to identify the transcriptional networks acting in root development and physiology, thus "exploring exemplary networks and systems."

Recent journal publications include:
Weitz, JS, Benfey, PN and NS Wingreen, "Evolution, Interactions, and Biological Networks", PloS Biology, p. e11, vol. 5, (2007). Published,

Brady SM, Song S, Dhugga KS, Rafalski JA, Benfey PN, "Combining expression and comparative evolutionary analysis. The COBRA gene
family.", Plant Physiology, p. 172, vol. 143, (2007). Published,

Brady SM, Long TA and Benfey PN, "Unraveling the dynamic transcriptome", Plant Cell, p. 2101, vol. 18, (2006). Published,

Researchers:
This work involves a large team of scientists, including 6 postdocs, 5 graduate students, 3 undergraduates, a computer programmer technician, and a lab technician. The postdocs are Siobhan Brady, Jose Dinneny, Terri Long, Hongchang Cui, Anjali Iyer-Pascuzzi, and Hironaka Tsukagoshi. The graduate students are Todd Twigg, David Orlando, Terry Jackson, Daniel Mace, and Greg Fricke. The undergraduates are Solomon Pointer, Eric Jiang, and Patricia Lo. Our computer programmer and statistician is Mikhail Kovtun, and our assisting lab technician has been Jean Wang.

Investigators:
Philip Benfey (Principal Investigator)
Robert Clark (Co-Principal Investigator)
Uwe Ohler (Co-Principal Investigator)

Contact:
philip.benfey@duke.edu

Last updated: July 10, 2007