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Ways to get from plant genomes to phenomes: via yeast

DOI: 10.1186/gb-2005-6-3-310

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Abstract:

Whole-genome sequencing, although not yet a routine laboratory technique, is certainly becoming more affordable, and increasing numbers of nearly complete eukaryote genomes are relentlessly being added to the list. Making sense of the resulting overwhelming amount of sequence may require an equal effort. Several high-throughput tools for automated identification of genes at the structural level are available, but functional annotation can only be tentatively inferred on the basis of sequence motifs or sequence similarity. 'Gold standard' structural and functional annotation still requires extensive human intervention to eliminate frequent errors. The next challenge is to investigate how a genome sequence determines the phenotype of the whole organism (sometimes referred to as the 'phenome'). The way in which each protein contributes to the phenotype depends on a variety of factors such as regulation of expression, interaction with other proteins or nucleic acids, response to small molecules, subcellular localization, and so on. Technologies for genome-wide analysis of gene expression such as microarray hybridization are now commonly used and genome-wide analyses of protein-protein or protein-DNA interactions (the 'interactome') are emerging. The complexity of higher eukaryotic genomes makes analysis difficult, however, particularly for interactomes. This was reflected in a meeting on the functional analysis of plant genomes held last December in Cold Spring Harbor, where most of the results presented on interactome analysis were in fact carried out on the less complex genome of yeast.A paradigm for this approach is a yeast synthetic genetic array (SGA) analysis described by Charles Boone (University of Toronto, Canada). Out of the 6,000 yeast genes, 5,000 have been shown to be non-essential in a genome-wide single-gene-knockout project, but double mutants of these non-essential genes often have lethal phenotypes (synthetic lethal phenotypes). SGA analysis allows the

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