Hosted by: Ben Babst

Main Research Interests — Dr. Coruzzi's lab initiated systems biology approaches in Arabidopsis and other species to study gene regulatory networks. Using network integration and machine-learning approaches, her lab generated the first dynamic and predictive regulatory networks in plants, a hallmark of Systems Biology. These networks uncovered novel hypotheses including nutrient control of the clock, and a Hit-and-Run transcription model. These informatic tools are embodied in a systems-biology enabling software platform VirtualPlantv1.3 (www.virtualplant.org), developed with NYU's Courant Inst. of Mathematical Sci. Dr. Coruzzi also leads a collaborative NSF Plant Genome Project - "Comparative Genomics of Seed Evolution" with co-PIs at the NY Botanical Garden, the American Museum of Natural History, and CSHL. This generated the largest genome-scale phylogeny of 150 seed plants, the BigPlantv1.0 matrix (http://nypg.bio.nyu.edu/bp/) available as an interactive browser, "PhyloBrowser." This resource enables researchers to explore the genomic underpinnings of plant diversification across a wide range of species. Selection of four major recent publications: [1]Para A, Li Y, Marshall-Colon A, et al., and Coruzzi GM (2014) Hit-and-run transcriptional control by bZIP1 mediates rapid nutrient signaling in Arabidopsis. PNAS 111(28):10371-6. [2]Ruffel S, Krouk G, Ristova D, et al., and Coruzzi GM (2011) Nitrogen economics of root foraging: Transitive closure of the nitrate-cytokinin relay and distinct systemic signals for N supply vs. demand. PNAS 108(45):18524-9. [3]Lee EK, Cibrian-Jaramillo A, Kolokotronis S-O, et al., Coruzzi G, and DeSalle R (2011) A functional phylogenomic view of the seed plants. PLoS Genetics 7(12):e1002411. [4]Krouk G, Mirowski P, et al., and Coruzzi GM (2010) Predictive network modeling of the high-resolution dynamic plant transcriptome in response to nitrate. Genome Biology 11(12):R123.