ECOFOR: Biodiversity and ecosystem functioning in degraded and recovering Amazonia...
| Grant number: | 11/52065-3 |
| Support type: | Research Grants - Research Partnership for Technological Innovation - PITE |
| Duration: | October 01, 2012 - March 31, 2017 |
| Field of knowledge: | Biological Sciences - Botany |
| Cooperation agreement: | Microsoft Research |
| Principal Investigator: | Marcos Silveira Buckeridge |
| Grantee: | Marcos Silveira Buckeridge |
| Home Institution: | Instituto de Biociências (IB). Universidade de São Paulo (USP). São Paulo , SP, Brazil |
| Company: | Microsoft |
| City: | São Paulo |
| Partner institutions: | Microsoft |
| Associated grant(s): | 13/50316-4 - Impact of elevated CO2 and drought on metabolism of Sorghum, AP.R |
| Associated scholarship(s): | 15/13479-8 - Using systems biology approach to develop a model for whole plant functioning,
BP.PD 13/24205-0 - Development of a bioinformatic tool for integration of transcriptomics, proteomics and physiology using sorghum and sugarcane as model systems, BP.DR |
Abstract
The advance of the sciences of the global climate changes and bioenergy require deep understanding of how plants work in a changing environment. Although model and native plants have been studied from the viewpoint of their ecophysiology, biochemistry and molecular biology, these levels of organization have not been approached in an integrated way. The limitation is the enormous amounts of data produced. This proposal aims at understanding the interaction among the different organizational levels through analysis of a data set from a C4 model plant (sorghum) cultivated at elevated CO2 combined with water deficit. We intend to obtain data on the physiology, metabolism and gene expression of sorghum grown in four different conditions: 1) ambient [CO2] well watered; 2) elevated [CO2] well watered; 3) ambient [CO2] with water deficit and 4) elevated [CO2] with water deficit. Two groups of plant sciences, will interact with one group of mathematics and computing sciences to reach the following goals: 1) test and refine tools for network analysis in biology; 2) develop tools for the integration of data from different experiments: 3) develop data visualization tools; 4) attempts to extrapolate to other species. (AU)