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Plant Systems Biology. Our goal is to identify gene regulatory networks in plants using a combination of genetic, genomic, bioinformatic, and systems biology approaches. Our lab has two main areas of inquiry: 1. A systems approach to nitrogen networks & the Virtual Plant. 2. Comparative genomics of seed evolution. All published experiments can be accessed by clicking here A Systems Approach to Nitrogen Networks & the VirtualPlant. The long-term goal of this project is to
understand how internal and external perturbations affect gene
regulatory networks that link plant metabolism and development.
Succeeding in this endeavor will allow us to (1) explain
mechanistically how changes in gene networks evoke systems-wide
responses to external treatments such as nitrogen, and (2) to predict
network states under untested conditions or in response to
modifications. In the long term, this systems biology approach to gene
networks should enable researchers to test the effects of
biotechnological strategies for gene modifications in silico, prior to
implementation in transgenic plants. Our approach starts with
the integration of all available information on Arabidopsis genomic
data into a "multinetwork" where the "edges" connecting gene "nodes"
are supported by multiple evidence including: metabolic pathway
connections, protein:protein and protein:DNA interactions, microarray
data, microRNA:target datasets, and literature-based
interactions. At present, the Arabidopsis multinetwork we
have created contains approximately 7,000 gene nodes and
230,000 interactions between them. As proof-of-principle, we
have used this Arabidopsis multinetwork to identify the gene networks
controlled by light, carbon and nitrogen signals.
In selected cases, the networks identified in wild-type plants have
been validated using microarray data from Arabidopsis signaling
mutants. Our studies include analysis of gene networks in
specific organs (leaves, roots or seeds) or in specific cell-types
based on analysis of microarray data obtained from cell-sorted samples
of roots.
The VirtualPlant Project. In order to go beyond data integration to conceptual integration of genomic data, we recognize that scientists pattern recognition skills often lead to the most enduring qualitative biological insights. To support those skills in a data-rich environment, have implemented a set of data integration, analysis and visualization tools into a system called the "VirtualPlant" (www.virtualplant.org). This system encompasses visualization techniques that render the multivariate genomic information in visual formats that facilitate the extraction of biological concepts and enable a "Systems Biology" view of the genomic data. While our project relates specifically to Arabidopsis, the data structures, algorithms, and visualization tools we have developed have been designed in a species-independent fashion. Thus, with the proper data uploads, the system can be used to visualize and model the molecular basis and underlying genomic responses in any organism for which genomic data is available. Comparative Genomics of Seed Evolution. This NSF Plant Genome project (NSF DBI-0421604) involves the comparative
genomic analysis of non-model, non-crop species, to uncover genes
important to the evolution of seeds, an important agronomic trait. This
project is being conducted with our partners in the NY Plant Genomic
Consortium that include coPIs from NYU Biology (Coruzzi), NYU Courant
(Shasha), NYBG (Stevenson), AMNH (DeSalle) and CSHL (McCombie &
Martienssen). Our approach is to generate and mine
EST data from the the most primitive living-seed plants, the nodal
Gymnosperms and the heterosporous lycophyte, Selaginella (as an
outgroup), to resolve their phylogenetic relationship and to uncover
novel genes and characters associated with the evolution and
development of seeds. This project is being conducted collaboratively
by scientists at three NY area institutions specializing in evolution,
genomics and bioinformatics, who comprise The New York Plant Genomics
Consortium (www.nypgenomics.org). Participants in this project include
PIs who collaborate in the training of post docs and graduate students
from New York University, The New York Botanical Garden, Cold Spring
Harbor, and The American Museum of Natural History.
We aim to achieve four goals:
1. Evolutionary Genomics: We have
generated 18,437 ESTs from three "nodal" Gymnosperm species which have
enabled us to create genome-scale phylogenies to resolve evolutionary
relationships in the Gymnosperms and identify putative genes involved
in the evolution of seeds. |