Rice Genetics IV - IRRI books - International Rice Research Institute

Functional genomicsThe field of functional genomics has emerged to address the function of genes discoveredby genome sequencing. In contrast to the previously prevalent gene-by-geneapproaches, new high-throughput methods are being developed for expression analysisas well as for the recovery and identification of mutants. The experimentalapproach is consequently changing from hypothesis-driven to nonbiased data collectionand an archiving methodology that makes these data available for analysis bybioinformatics tools. The functional genomics methodology is also changing the experimentalstrategy from a forward genetics (or mutant to gene) approach to a reversegenetics (or sequenced gene to mutant and function) approach. It is expected that thefunctional genomics of model plants will contribute to the understanding of basicplant biology as well as the exploitation of genomic information for crop improvement.This is because a large number of gene functions for generic traits will be functionalacross species, either directly or after identifying the functional homologues.With its relatively small genome (450 Mb), rice has been selected to be the modelmonocot plant to be first sequenced. Although the other cereal genomes will not besequenced completely soon, the synteny between the monocots (Gale and Devos 1998)will help decipher the structure and function of the more complex genomes.The major developments in whole-genome analysis have been in the field of transcriptexpression analysis using a variety of high-throughput methods. In plants, differenttechnologies have been employed (Baldwin et al 1999) based on high-densitynylon filters, microarrays, various gel systems, and even a sequencing-based method,SAGE, that has been employed for rice (Matsumura et al 1999). With gene chips ormicroarrays, the representative genes of an organism can be placed on a solid supportsuch as glass and used in hybridization experiments with different RNA samples toreveal gene expression patterns and help identify pathways by association. However,the expression patterns of genes supply correlative information and do not necessarilyprove a causal relationship between gene sequence and function. As mRNA levelalone does not reflect the actual expression of the gene product, additional means areprovided by proteomics (Dove 1999), which addresses the protein expression of a celltype, and metabolomics, which reveals the metabolite profile (Trethewey et al 1999)of the cell/tissue type revealing the active biochemical processes. A combination ofdifferent expression analysis tools and mutant or overexpression analysis of geneswill be able to provide a unique multidimensional picture of genetic circuits and pathways.Knockout mutagenesisThe phenotype associated with a gene function is often the best clue to its role in theplant. Phenotype of mutants can be broadly defined at the morphological, biochemical,or physiological level and it provides information on the interactions among differentprocesses. Classically, chemical and physical mutagens have provided loss-offunctionmutants and have helped define genes involved in specific pathways or pro-264 Greco et al