Environmental Gene Regulatory Interaction Networks in Rice

01 Sep 2011 31 Aug 2017

Michael Purugganan (PI) , Richard Bonneau (CoPI)


PI: Michael Purugganan [New York University (NYU)]

CoPI: Richard Bonneau (NYU)

Key Collaborator: Endang Septiningsih (International Rice Research Institute, the Philippines)

Plants in the real world are continuously exposed to multiple environmental signals and must respond appropriately to the dynamic conditions found in nature. Environmental signals can fluctuate during an individual's life cycle with varying degrees of predictability, and complex natural environments are the norm. This project will analyze public data and undertake time-series microarray experiments to infer Environmental Gene Regulatory Interaction Networks (EGRINs) in the rice leaf associated with fluctuating environmental signals. The research focus will be on temperature and water availability, and examine genomic networks for these environmental signals in four different landraces adapted to rainfed upland versus paddy field lowland environments. This research will adapt and scale-up computational methods for biclustering and network inference for use with plant transcriptome data, including the use of data from multiple genotypes. Rice global gene expression patterns in natural seasonal environments will be studied by carrying out transcriptome analyses in different agricultural field conditions. This study provides a systematic determination of genomic networks associated with environmental signals and their behavior in ecologically relevant field conditions. This work lays the foundation for a broader dissection of plant responses to both normal environmental fluctuations as well as extreme environmental conditions that lead to plant stress, and develop systems biological approaches to understanding plant-environmental interactions. These results will be especially useful in understanding plant response to climate fluctuations, as well as develop cultivars that can tolerate temperature and water stress in agricultural environments.

This project will develop software packages for gene network inference in plants, and provide inferred gene biclusters and networks to the plant science community through Gramene (www.gramene.org). As part of the outreach efforts, graduate-level science journalism students from the NYU Science, Health and Environment Reporting Program will also be trained in plant genomics and systems biology. Finally, plant biologists from both the US and the International Rice Research Institute (IRRI) will also be trained in systems biology by developing a Rice Systems Biology training workshop to be held at IRRI.