Genes expressed in corn under drought conditions
Identification of differentially expressed genes in roots of maize lines contrasting for drought tolerance. Water deficit is one of the most critical environmental stress plants can be submitted to during their life cycle. The evolutionary and the economic performances of the plant are affected directly by reducing its survival in the natural environment and its productivity in agriculture. Plants respond to water stress by biochemical and physiological modifications that may be involved in tolerance or adaptation mechanisms. The molecular bases of water stress tolerance remains unknown. Candidate genes induced by water-deficit stress in plants relatively sensitive to cellular dehydration have been identified and characterized, mainly in the model plant Arabidopsis thaliana (Vinocur and Altman, 2005; Verslues et al., 2006). The investigated plant systems have been shown to have common molecular and physiological components in a wide range of tolerance levels, indicating a major role for spatial and temporal gene expression regulation in water stress resistance (Ramanjulu and Bartels, 2002; Taji et al., 2004). Sequencing projects are producing large quantities of genomic and cDNA sequences for a number of organisms. In the model plant Arabidopsis, the complete genomic sequences of two chromosomes have been determined (Lin et al., 1999; Mayer et al., 1999), and the entire genomic sequence was completed by the end of 2000. Expressed sequence tag (EST) projects have also provided a major contribution with the discovery of expressed genes (Höfte et al., 1993; Newman et al., 1994; Cooke et al., 1996; Asamizu et al., 2000). A recent release of dbEST (the EST database of the National Center for Biotechnology Information, http:// www.ncbi.nlm.nih.gov) contained partial cDNA sequences. Recently, microarray technology has become a useful tool for the analysis of genome-scale gene expression (Schena et al., 1995; Eisen and Brown, 1999). This DNA chip-based technology arrays cDNA sequences on a glass slide at a density 1000 genes/cm2. These arrayed sequences are hybridized simultaneously to a two-color fluorescently labeled cDNA probe pair prepared from RNA samples of different cell or tissue types, allowing direct and large-scale comparative analysis of gene expression. This technology was first demonstrated by analyzing 48 Arabidopsis genes for differential expression in roots and shoots (Schena et al., 1995). Microarrays were used to study 1000 randomly chosen clones from a human cDNA library for identification of novel genes responding to heat shock and protein kinase C activation (Schena et al., 1996). In another study, expression profiles of inflammatory disease-related genes were analyzed under various induction conditions by this chip-based method (Heller et al., 1997). Furthermore, the yeast genome of 6000 coding sequences has been analyzed for dynamic expression by the use of microarrays (DeRisi et al., 1997; Wodicka et al., 1997). However, in plant science, only several reports of microarray analyses have been published (Schena et al., 1995; Ruan et al., 1998; Aharoni et al., 2000; Reymond et al., 2000). Microarrays are conceptually very simple, but their production and analysis can be technically demanding. Another name for such technology might be “reverse northern-dot blots.” DNA representing thousands of genes is deposited on a solid surface at high density (1,000–10,000 “spots”/cm2). These DNA samples are then hybridized with labeled probes derived from the mRNA population present in plant sample(s). When two mRNA samples are compared (for example, from control and treated plants) the intensity of the signal from label bound to each spot reflects the relative mRNA abundance for each gene represented on the array. Therefore, information on gene expression can be obtained simultaneously for thousands of genes (Schaffer et al., 2000). The probes are usually labeled with fluorescent nucleotide derivatives and the arrays scanned by confocal microscopy. mRNA species present at very low levels (a few copies per cell) can be detected and the dynamic range over which expression can be monitored is several orders of magnitude. Microarrays can also be produced using oligonucleotides deposited by a photolithographic process (Fodor et al., 1993; Lipshutz et al., 1999) and such Arabidopsis arrays representing about 8,000 genes are commercially available from Affymetrix (Table I). Although cDNA-based and oligonucleotide-based arrays are well-proven technologies that provide reliable data on expression patterns of thousands of genes, each type of array has distinct advantages. For example, oligonucleotide arrays can in many cases more easily distinguish between closely related members of gene families. The arrays offered by AFGC, which are based on spotting PCR products of cDNA or genomic DNA, also have several advantages, which include lower costs, the ability to provide data on different Arabidopsis ecotypes or closely related species such as Brassica, and the ability to cohybridize probes from two or more mRNA samples simultaneously on the same array (Wismann and Ohlrogge 2000) The objective of this project is to identify differentially expressed genes in roots of maize lines contrasting for drought stress tolerance. To achieve this objective RNA extracted from theses maize lines tolerant to drought in the presence and absence of the stress with labeled and hybridized to maize oligo microarray. Maize long oligonucleotide arrays are available to researchers at academic and non profit institutions. Approximately 58,000 maize oligos are printed over two slides. Each slide contains both positive and negative controls. In addition to oligos designed to the maize EST Unigene set and selected Assembled Zea mays (AZM) genomic sequences not represented in the maize EST set, the array contains oligos to 465 organellar genes, 400 retrotransposon repeats (in both oligo orientations), 297 "community requested" genes, and 11 genes typically used in transgenes. References Aharoni, A., et al. (2000). Identification of the SAAT gene involved in strawberry flavor biogenesis by use of DNA microarrays. Plant Cell 12, 647–661. Asamizu, E., Nakamura, Y., Sato, S., and Tabata, S. (2000). 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