Yale Researchers Charting Role of Individual Cells in Rice Plants
Yale researchers are building a community atlas that provides the expression patterns of every gene in every cell type in rice – one of the first cereals cultivated on earth, and the principal food source for half of the world’s population.
The four-year project is funded with a $4.5 million National Science Foundation (NSF) grant and is part of a $100 million NSF commitment to plant genome research.
“Rice has huge economic and cultural importance in the world,” said Timothy Nelson, professor of molecular, cellular and developmental biology at Yale and principal investigator of the study. “Rice is closely related to other important cereal grasses, such as corn, rye, barley and wheat. It has a simpler genome, but it’s close enough that much of what we learn in rice can be applied to these other species.”
He said the project combines his laboratory’s interest in plant developmental biology with the emergence of specialized tools – laser capture microdissection (LCM), whole-genome microarrrays, and bioinformatics computation, in particular – that will enable researchers to analyze the expression of the entire rice genome of 50,000-60,000 genes with a cellular resolution.
Nelson and his colleagues, Xing-Wang Deng, professor of molecular, cellular and developmental biology, and Hongyu Zhao, associate professor, epidemiology and public health and genetics, will be collecting data for each of the several dozen cell types in rice under a variety of developmental and environmental conditions. They are currently collecting their first data sets and developing the informatics tools needed to analyze the enormous amounts of information they contain. The open community nature of the project makes it possible for researchers and agricultural specialists around the world to access the resulting cellular gene expression information, and to contribute additional data to the atlas database.
The findings could potentially lead to everything from boosting crop size and quality to enabling scientists to conduct computerized experiments on virtual rice plants.