HAU16008-05-7 - Naturwissenschaften(2002 89:235249 DOI...

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Abstract Functional genome analysis of plants has en- tered the high-throughput stage. The complete genome information from key species such as Arabidopsis thali- ana and rice is now available and will further boost the application of a range of new technologies to functional plant gene analysis. To broadly assign functions to un- known genes, different fast and multiparallel approaches are currently used and developed. These new technolo- gies are based on known methods but are adapted and improved to accommodate for comprehensive, large- scale gene analysis, i.e. such techniques are novel in the sense that their design allows researchers to analyse many genes at the same time and at an unprecedented pace. Such methods allow analysis of the different con- stituents of the cell that help to deduce gene function, namely the transcripts, proteins and metabolites. Similar- ly the phenotypic variations of entire mutant collections can now be analysed in a much faster and more efficient way than before. The different methodologies have de- veloped to form their own fields within the functional genomics technological platform and are termed tran- scriptomics, proteomics, metabolomics and phenomics. Gene function, however, cannot solely be inferred by us- ing only one such approach. Rather, it is only by bring- ing together all the information collected by different functional genomic tools that one will be able to un- equivocally assign functions to unknown plant genes. This review focuses on current technical developments and their impact on the field of plant functional geno- mics. The lower plant Physcomitrella is introduced as a new model system for gene function analysis, owing to its high rate of homologous recombination. Introduction Large-scale genome projects have greatly changed the face of biology. Genomics has often been referred to as a new field that has led to a paradigm shift in the way sci- ence is performed. Meanwhile the post-genomic era has emerged by taking full advantage of the vast amount of genome sequence data. It has become possible to look at biology in a different way in the sense that nowadays re- searchers do not need to approach biological questions in a hypothesis-driven way but instead can collect and ana- lyse data in a more non-biased and broader fashion (Rounsley and Briggs 1999; Brent 2000). New types of scientific questions can be asked and new kinds of exper- iments can be performed at an unprecedented pace. Re- cent technological advances and the rapid development of novel tools now permit the interrogation of a complete genome all at once and in a single experiment. Currently the mass of genome data is being converted into gene- function data, meaning that value is added to the nucleo- tide sequence collections. Knowing the exact sequence and location of all the genes of a given organism is only the first step towards understanding how all the parts of a biological system work together. In this respect functional genomics is the key approach to transforming quantity in- to quality. Functional genomics is a general approach to-
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