Drought induced yield losses can be substantial and researchers have been attempting to improve the tolerance of crops to limiting supplies of water for decades. Physiologists, breeders, biochemists, agronomists, and molecular biologists have all used specific tools from their disciplines to unravel the complexities of the drought response. Their efforts have resulted in improved knowledge of drought tolerance; however, predictable improvement remains elusive. We believe that one key to improving drought tolerance is the identification of critical genes whose expression controls the plant phenotype. This effort has been aided recently by the identification of chromosomal segments associated with drought tolerance via quantitative trait loci (QTL) analysis. Unfortunately, large numbers of genes fall within these chromosomal segments and the identification of key genes within QTL responsible for drought tolerance have not yet been identified. With the advent of genomic technologies, it is now possible to efficiently analyze thousands of genes simultaneously and, hopefully, identify drought responsive genes in maize. Genomic technologies can be divided into structural and functional categories. Structural genomics categories. Structural genomics entails some aspect of sequencing genomes and this activity has been ongoing for some time in many species, including maize. At Pioneer, we have been sequencing the maize genome since 1996, and we currently have over 200, 000 ESTs in our database, which we estimate represents 60% of the genes in the genome. We are applying these sequenced genes to various functional genomic tools. Functional genomics involves using various technology platforms to determine transcript levels of sequenced genes. In our case, we are using these tools to better understand the molecular mechanisms of maize plants growing under water deficits. We are using both open and closed expression profiling technologies. By definition, an open system allows one to survey all transcripts and compare their levels between two different RNA pools, but the identity of the genes may not be known a priori. In contrast, with the closed system one can analyze only those genes that one has isolated a priori; however, once the analysis is complete the genes showing differential expression are immediately know.
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