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  Section: Molecular Biology of Plant Pathways » Genetic Engineering for Salinity Stress Tolerance
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The present focus on genomics-type plant biology has been ushered in by the generation of the Arabidopsis sequencing project initiated in the end of 1980s, mirrored on the coincidental focus on bacterial, yeast, and animal, human in particular, genome sequencing projects. Genome sequences have become essential requisites for anchoring ESTs and expression profiles, and even more significantly, for determining which protein and pathways are present in an organism. The recognition of syntenic relationships between species is increasingly exploited for comparative genomics analyses (Bennetzen, 2002). Similar comprehensive data collection methods have emerged for proteins and metabolites, with improvements in tools and technologies continuous or accelerating. Sequences and dynamic expression profiles are only a starting point: the number of predicted reading frames is continuously increasing as predictive bioinformatics tools improve, as additional reading frames, dismissed or not recognized in the past, are confirmed by their presence, and as the siRNAs, RNA genes that selectively silence particular transcripts, are now being added as novel, important components of gene expression regulation. The number of splicing variants, leading to different protein sequences from one gene, can be expected to increase as well. Within this multitude of genes will be many functions relevant for ion and metabolic homeostasis under saline conditions, as well as specialized pathways for other abiotic stresses; functions that underlie the multigenic trait that is stress tolerance or resistance. In S. cerevisiae, the model that has most crucially contributed to our understanding of salt stress tolerance, more than 500 genes confer a ‘‘severe salt phenotype’’ to the cells when deleted (http://www.yeastgenome. org/cache/genome-wide-analysis.html) (Hohmann, 2002; Serrano et al., 1999). More than 400 of these genes have homologues in Arabidopsis. Even when trivial causes, for example, the deletion of a ribosomal protein gene or an essential RNA polymerase subunit, are excluded, the genes that are essential for yeast cell survival identify many different functional categories, most likely in any cell.

The most promising way forward will, most likely, be to identify the stressrelevant genes in model species through mutagenesis and forward screens and tilling methods (Henikoff et al., 2004; Tani et al., 2004). This strategy will be especially useful when the population of tagged mutants carries a reporter gene that reports altered responses to stress (Ishitani et al., 1997). A second opportunity is to become more aware of evolutionarily related naturally stress tolerant species that are relatives of established glycophytic model species. In comparisons of gene and protein expression patterns, and by determining divergent gene numbers (paralogues of ubiquitous genes), we can learn about the underlying functions that determine different plant life styles (Bressan et al., 2002; Inan et al., 2004; Taji et al., 2004).

Additionally, the immediate future will be characterized by high throughput localization studies for all or most of the
salinity stress-related transcripts and proteins, using, for example, cell ablation techniques combined with microarray analysis, and cellular and subcellular painting of transcripts and proteins by highthroughput in situ and real-time, in vivo fluorescence detection and localization methods. Eventually, we will have a virtual representation of all transcripts, proteins, and major metabolites during the life of a number of model species from seed to seed under optimal conditions, and when challenged by abiotic stresses.

This information when combined with classical and marker-assisted breeding and correlating quantitative trati loci (QTL) regions with genome information may enable us to generate stress tolerant species and lines of crops that rely on the immense genetic variability that exists in plants (Koyama et al., 2001; Loudet et al., 2003; Tuberosa et al., 2002).

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