DIVERGE is available free of charge from http://xgu1.zool.iastate.edu/. Distribution packages for both Linux and Microsoft Windows operating systems are available, including manual and example files.

As a first step in establishing a proteome database for maize, we have embarked on the identification of the leaf proteins resolved on two-dimensional (2-D) gels. We detected nearly 900 spots on the gels with a pH 4-7 gradient and over 200 spots on the gels with a pH 6-11 gradient when the proteins were visualized with colloidal Coomassie blue. Peptide mass fingerprints for 300 protein spots were obtained with matrix assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectrometer and 149 protein spots were identified using the protein databases. We also searched the pdbEST databases to identify the leaf proteins and verified 66% of the protein spots that had been identified using the protein databases. Sixty-seven additional protein spots were identified from expressed sequence tags (ESTs). Many abundant leaf proteins are present in multiple spots. Functions of over 50% of the abundant leaf proteins are either unknown or hypothetical. Our results show that EST databases in conjunction with peptide mass fingerprints can be used for identifying proteins from organisms with incomplete genome sequence information.

Classical quantitative genetics has applied linear modeling to the problem of mapping genotypic to phenotypic variation. Much of this theory was developed prior to the availability of molecular biology. The current understanding of the mechanisms of gene expression indicates the importance of nonlinear effects resulting from gene interactions. We provide a bridge between genetics and gene network theories by relating key concepts from quantitative genetics to the parameters, variables, and performance functions of genetic networks. We illustrate this methodology by simulating the genetic switch controlling galactose metabolism in yeast and its response to selection for a population of individuals. Results indicate that genes have heterogeneous contributions to phenotypes and that additive and nonadditive effects are context dependent. Early cycles of selection suggest strong additive effects attributed to some genes. Later cycles suggest the presence of strong context-dependent nonadditive effects that are conditional on the outcomes of earlier selection cycles. A single favorable allele cannot be consistently identified for most loci. These results highlight the complications that can arise with the presence of nonlinear effects associated with genes acting in networks when selection is conducted on a population of individuals segregating for the genes contributing to the network. R ECENTLY there has been interest in interpretinganalyze the epistatic interactions between the genes conthe quantitative genetic properties of gene nettrolling this pathway and their impact on the selection works at the population level (Frank 1999; Omholt et process. al. 2000). This is warranted on at least three grounds:Fundamental to genetics is the relationship between (i) much of the molecular genetic evidence points to the genotype of an individual, the environment where the roles of genes in nonlinear networks in the determiit lives, and its resulting phenotype. This relationship is nation of gene-to-phenotype relationships, (ii) we have often referred to as genotype-to-phenotype (GP) mapa growing body of data on the structural and functional ping. Since the true mechanisms of gene expression properties of the genomes of organisms and as this pool have historically been poorly understood, geneticists of data continues to expand it is becoming more feasible have derived such mappings from the joint distributions to construct models of gene networks, and (iii) for many of genotypic and phenotypic data. The simplest mapaspects of basic and applied genetics it is necessary to ping, Mendelian genetics, considers traits that are deterstudy the properties of allelic variation for genes at the mined completely by individual genes. Many traits, howlevel of phenotypic effects and variation within populaever, are more complex than that; they are quantitative tions. Bridging the molecular and population-level views in nature and are influenced by contributions from of gene-to-phenotype relationships is a challenging area alleles...

Functional divergence after gene duplications is a fundamental issue for functional innovations in many organisms. As gene family proliferation (gene duplication) may have provided the raw materials for the origin of new genes, the details of how duplicate genes have preserved through functional divergence remain largely unknown. In this review paper, we discuss some recent developments about this important issue, with special references to the implication for functional genomics. With a combination of large-scale genome sequencing and powerful computational analysis, we show a great deal of functional information can be obtained from the evolutionary perspective, which can in turn be used to facilitate high throughput functional assays. The software DIVERGE can be obtained form http://xgu.gdcb.iastate.edu.

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