Response diversity of Arabidopsis thaliana ecotypes in elevated [CO2] in the field
- 609 Downloads
Free Air [CO2] Enrichment (FACE) allows for plant growth under fully open-air conditions of elevated [CO2] at concentrations expected to be reached by mid-century. We used Arabidopsis thaliana ecotypes Col-0, Cvi-0, and WS to analyze changes in gene expression and metabolite profiles of plants grown in “SoyFACE” (http://www.soyface.uiuc.edu/), a system of open-air rings within which [CO2] is elevated to ~550 ppm. Data from multiple rings, comparing plants in ambient air and elevated [CO2], were analyzed by mixed model ANOVA, linear discriminant analysis (LDA) and data-mining tools. In elevated [CO2], decreases in the expression of genes related to chloroplast functions characterized all lines but individual members of distinct multi-gene families were regulated differently between lines. Also, different strategies distinguished the lines with respect to the␣regulation of genes related to carbohydrate biosynthesis and partitioning, N-allocation and amino acid metabolism, cell wall biosynthesis, and hormone responses, irrespective of the plants’ developmental status. Metabolite results paralleled reactions seen at the level of transcript expression. Evolutionary adaptation of species to their habitat and intrinsic genetic plasticity seem to determine the nature of responses to elevated [CO2]. Irrespective of their underlying genetic diversity, and evolutionary adaptation to different habitats, a small number of common, predominantly stress-responsive, signature transcripts appear to characterize responses of the Arabidopsis ecotypes in FACE.
KeywordsArabidopsis thaliana ecotypes Elevated [CO2] FACE Transcript profiling Metabolite profiling
Unable to display preview. Download preview PDF.
We thank the people at UIUC SoyFACE for their help and encouragement, and Drs. Vera Lozovaya and Keith Cadwallader (UIUC) for help with metabolite analyses, Dr. Oliver Fiehn (UC Davis) for metabolite library information, and Valeriy Poroyko (UIUC) for help in primer design. The permission to cite unpublished data on physiological responses of Arabidopsis ecotypes grown in SoyFACE by Drs. Elizabeth A. Ainsworth and Andrew D. B. Leakey (UIUC) is gratefully acknowledged. The work has been supported by NSF DBI 0223905 and IBN0219322 and by UIUC and VT institutional grants.
- Catchpole GS, Beckmann M, Enot DP, Mondhe M, Zywicki B, Taylor J, Hardy N, Smith A, King RD, Kell DB, Fiehn O, Draper J (2005) Hierarchical metabolomics demonstrates substantial compositional similarity between genetically modified and conventional potato crops. Proc Natl Acad Sci USA 102:14458–14462PubMedCrossRefGoogle Scholar
- Heath LS, Ramakrishnan N, Sederoff RR, Whetten RW, Chevone BI, Struble CA, Jouenne VY, Chen DW, van Zyl L, Grene R (2002) Studying the functional genomics of stress responses in loblolly pine with the Expresso microarray experiment management system. Comp Functional Genomics 3:226–243CrossRefGoogle Scholar
- Hirai MY, Yano M, Goodenowe DB, Kanaya S, Kimura T, Awazuhara M, Arita M, Fujiwara T, Saito K (2004) Integration of transcriptomics and metabolomics for understanding of global responses to nutritional stresses in Arabidopsis thaliana. Proc Natl Acad Sci USA 101:10205–10210PubMedCrossRefGoogle Scholar
- Jobson JD (1992) Applied multivariate data analysis. Volume II: Categorical and Multivariate Methods. Springer Verlag, New York, pp 483–568Google Scholar
- Kruckeberg AL, Neuhaus HE, Feil R, Gottlieb LD, Stitt M (1989) Decreased-activity mutants of phosphoglucose isomerase in the cytosol and chloroplast of Clarkia xantiana. Impact on mass-action ratios and fluxes to sucrose and starch, and estimation of Flux Control Coefficients and Elasticity Coefficients. Biochem J 261:457–467PubMedGoogle Scholar
- Miglietta F, Hoosbeek MR, Foot J, Gigon F, Hassinen A, Heijmans M, Peressotti A, Saarinen T, van Breemen N, Wallen B (2001) Spatial and temporal performance of the MiniFACE (Free Air CO2 Enrichment) system on bog ecosystems in northern and central Europe. Environ Monitoring Assessment 66:107–127CrossRefGoogle Scholar
- Pritchard S, Amthor J (2005) Crops and environmental change: an introduction to effects of global warming, rising Co2 and O3 concentrations, and soil salinization on crop physiology and yield. Haworth Press, Binghamton, NYGoogle Scholar
- Roessner U, Willmitzer L, Fernie AR (2001) High-resolution metabolic phenotyping of genetically and environmentally diverse potato tuber systems. Identification of phenocopies. Plant Physiol 127:749–764Google Scholar
- Sharma S (1996) Applied multivariate techniques. John Wiley & Sons, New York, pp 90–143Google Scholar
- Sioson A, Watkinson JI, Vasquez-Robinet C, Ellis M, Shukla M, Kumar D, Ramakrishnan N, Heath LS, Grene R, Chevone BI, Kadafar K, Watson LT (2003) Expresso and Chips: Creating a Next Generation Microarray Experiment Management System, In 17th International Parallel and Distributed Processing Symposium (IPDPS’03), Nice, France, p 209Google Scholar
- Usadel B, Nagel A, Thimm O, Redestig H, Blaesing OE, Palacios-Rojas N, Selbig J, Hannemann J, Piques MC, Steinhauser D, Scheible WR, Gibon Y, Morcuende R, Weicht D, Meyer S, Stitt M (2005) Extension of the visualization tool MapMan to allow statistical analysis of arrays, display of corresponding genes, and comparison with known responses. Plant Physiol 138:1195–1204PubMedCrossRefGoogle Scholar
- Watkinson JI, Sioson AA, Vasquez-Robinet C, Shukla M, Kumar D, Ellis M, Heath LS, Ramakrishnan N, Chevone B, Watson LT, van Zyl L, Egertsdotter U, Sederoff RR, Grene R (2003) Photosynthetic acclimation is reflected in specific patterns of gene expression in drought-stressed loblolly pine. Plant Physiol 133:1702–1716PubMedCrossRefGoogle Scholar