ASSESSING THE IMPACT OF GLOBAL CLIMATE CHANGE FACTORS ON PLANTS USING GENE EXPRESSION PROFILING

This is a collaborative project with Chris Field (Director of the Department of Global Ecology, Carnegie Institution, Stanford, CA) and the Jasper Ridge Global Change Experiment (JRGCE).

Humans rely on ecosystems for critical goods and services. In the coming decades, ecosystems will be exposed to a novel range of human impacts, including altered climate. To anticipate the consequences of these changes on the biosphere, detailed knowledge of how various ecosystems respond to global change parameters is needed. This project is a component of a large, long-term, interdisciplinary study of an annual Mediterranean grassland ecosystem, the Jasper Ridge Global Change Experiment (JRGCE). The broad goals of the JRGCE are to develop a mechanistic understanding of ecosystem changes to realistic combinations of elevated CO2, precipitation, nitrogen and temperature, and to develop predictive models of future ecosystem change. The general goal of this gene expression profiling project is to provide some insight into the underlying physiological processes in plants that contribute to ecosystem change in this grassland.

To date, we have hybridized samples from A. barbata and G. dissectum to the Arabidopsis AFGC Y2001 microarrays (~14,313 genes; Wu et al. 2001) and found that 20% of the spots are hybridized to A. barbata, 60% to G. dissectum as compared to 81% with Arabidopsis leaf samples (percentage of spots with an intensity greater than background plus 1 standard deviation) (Fig. 1). There is good reproducibility between replicate samples collected in the plots. The data sets for two replicates of treatment 15 (i.e., ambient N and elevated CO2, water and heat) showed a correlation value of 0.934 (Fig. 2). Because a relatively high proportion of spotted DNAs on the arrays gave good intensity signals, we decided to use the Y2001 AFGC cDNA microarrays for the G. dissectum studies.

Fig. 1. One of 48 blocks from an Arabidopsis AFGC Y2001 array hybridized with Cy5-labeled G. dissectum samples (red) and Cy3-labeled Arabidopsis genomic DNA (green). Spiking controls occur in the top and bottom rows.	Fig. 2. Comparison of the microarray data from two replicates of G. dissectum samples from plots with ambient nitrogen, and elevated CO2, water and temperature. The 2 data sets were normalized, centered and converted to Log2 values, prior to plotting. Red spots are poorly measured values.

The microarray technology was selected as it is the best currently available method for surveying a very large number of parameters (genes) in a largely unbiased fashion (Brown and Botstein 1999). From these experiments, genes or groups of genes whose expression patterns closely reflect one or more of the global change factors, will be identified and genes that are diagnostic for some of the ecological and biochemical processes measured on the JRGCE plots will be determined. Specifically, we hope to identify leads to physiological processes that we may not have anticipated from our reading of the literature. Notably, analysis of NPP showed an unexpected suppressive effect of CO₂ enrichment when combined with the remaining global change parameters (Shaw et al. 2002). Although our colleagues have suggested several possible bases for this observation, the underlying mechanism(s) is not understood (Shaw et al. 2002). Thus, there is a need for more information about physiological and biochemical changes occurring in the organisms of this ecosystem. This exploratory project is expected to lead to a number of specific hypotheses about plant responses and ecosystem level changes to global change factors, which will be tested in future experiments.

References:

Brown PO, Botstein D (1999) Exploring the new world of the genome with DNA microarrays. Nature Genet supp 21: 33-37

Shaw MR, Zavaleta ES, Chiariello NR, Cleland EE, Mooney HA, Field CB (2002) Grassland responses to global environmental changes suppressed by elevated CO₂. Science 298: 1987-1990

Wu SH, Ramonell K, Gollub J, Somerville S (2001) Plant gene expression profiling with DNA microarrays. Plant Physiol Biochem 39: 917-926.