Alternative RNA splicing greatly increases proteome diversity and may thereby contribute to tissue-specific functions. We carried out genome-wide quantitative analysis of alternative splicing using a custom Affymetrix microarray to assess the role of the neuronal splicing factor Nova in the brain. We used a stringent algorithm to identify 591 exons that were differentially spliced in the brain relative to immune tissues, and 6.6% of these showed major splicing defects in the neocortex of Nova2-/- mice. We tested 49 exons with the largest predicted Nova-dependent splicing changes and validated all 49 by RT-PCR. We analyzed the encoded proteins and found that all those with defined brain functions acted in the synapse (34 of 40, including neurotransmitter receptors, cation channels, adhesion and scaffold proteins) or in axon guidance (8 of 40). Moreover, of the 35 proteins with known interaction partners, 74% (26) interact with each other. Validating a large set of Nova RNA targets has led us to identify a multi-tiered network in which Nova regulates the exon content of RNAs encoding proteins that interact in the synapse.

We have developed GoMiner, a program package that organizes lists of 'interesting' genes (for example, under-and overexpressed genes from a microarray experiment) for biological interpretation in the context of the Gene Ontology. GoMiner provides quantitative and statistical output files and two useful visualizations. The first is a tree-like structure analogous to that in the AmiGO browser and the second is a compact, dynamically interactive 'directed acyclic graph'. Genes displayed in GoMiner are linked to major public bioinformatics resources. RationaleGene-expression profiling and other forms of high-throughput genomic and proteomic studies are revolutionizing biology. That much is universally agreed. But the new technologies pose new challenges. The first is the experiment itself, the second is statistical analysis of results, the third is biological interpretation. That third challenge is often the most vexing and time-consuming. In gene-expression microarray studies, for example, one generally obtains a list of dozens or hundreds of genes that differ in expression between samples and then asks: 'What does all of this mean biologically?' The work of the Gene Ontology (GO) Consortium [1] provides a way to address that question. GO organizes genes into hierarchical categories based on biological process, molecular function and subcellular localization. In the past, this GO information was queried one gene at a time. Recently, batch processing has been introduced [2], but with a flat-format output that does not communicate the richness of GO's hierarchical structure.We have developed, and present here, the program package GoMiner as a freely available computer resource that fully incorporates the hierarchical structure of the Gene Ontology to automate the functional categorization of gene lists of any length. GoMiner is downloadable free of charge from [3] or [4]. GoMiner was developed particularly for biological interpretation of microarray data; one can input a list of underand overexpressed genes and a list of all genes on the array, and then calculate enrichment or depletion of categories with genes that have changed expression. GoMiner thus facilitates analysis and organization of the results for rapid interpretation of 'omic' [5,6] data. For concreteness, the descriptions in

The National Institutes of Health Mammalian Gene Collection (MGC) Program is a multiinstitutional effort to identify and sequence a cDNA clone containing a complete ORF for each human and mouse gene. ESTs were generated from libraries enriched for full-length cDNAs and analyzed to identify candidate full-ORF clones, which then were sequenced to high accuracy. The MGC has currently sequenced and verified the full ORF for a nonredundant set of >9,000 human and >6,000 mouse genes. Candidate full-ORF clones for an additional 7,800 human and 3,500 mouse genes also have been identified. All MGC sequences and clones are available without restriction through public databases and clone distribution networks (see http:͞͞mgc.nci.nih.gov).T he gene content of the mammalian genome is a topic of great interest. While draft sequences are now available for the human (1, 2), mouse (www.ensembl.org͞Mus musculus), and rat (http:͞͞hgsc.bcm.tmc.edu͞projects͞rat) genomes, the challenge remains to correctly identify all of the encoded genes. Difficulty in deciphering the anatomy of mammalian genes is due to several factors, including large amounts of intervening (noncoding) sequence, the imperfection of gene-prediction algorithms (3), and the incompleteness of cDNA-sequence resources, many of which consist of gene tags of variable length and quality. Full-length cDNA sequences are extremely useful for determining the genomic structure of genes, especially when analyzed within the context of genomic sequence. To facilitate geneidentification efforts and to catalyze experimental investigation, the National Institutes of Health (NIH) launched the Mammalian Gene Collection (MGC) program (4) with the aim of providing freely accessible, high-quality sequences for validated, complete ORF cDNA clones. In this article, we describe our progress toward the goal of identifying and accurately sequencing at least one full ORF-containing cDNA clone for each human and mouse gene, as well as making these fully sequenced clones available without restriction. Materials and MethodscDNA Library Production. MGC cDNA libraries were prepared from a diverse set of tissues and cell lines, in several different vector systems, by using a variety of methods. Vector maps and details of library construction are available at http:͞͞mgc. nci.nih.gov͞Info͞VectorMaps. The complete sequences for each of the MGC vectors can be found at http:͞͞image.llnl.gov͞ image͞html͞vectors.shtml. The catalog of MGC cDNA libraries can be accessed at http:͞͞mgc.nci.nih.gov.

32P labeling of microtubular protein by endogenous protein kinase activity is shown to result from a net increase in protein-bound phosphate and is not the result of a phosphate exchange reaction between ATP and phosphoprotein. Protein phosphorylation is maximal in the presence of 0.5 mM Mg2+ and 0.25 mM ATP, resulting in approximately 2.8 nmol of phosphate/mg of protein. However, phosphorylation can be increased two-to threefold by cAMP. The protein substrates for phosphorylation either the absence or presence of cAMP are the microtubule-associated proteins which copurify with tubulin and promote microtubule assembly. Phosphorylation of microtubule-associated proteins inhibits both the rate and extent of microtubule assembly when the protein is exposed to conditions which result in dissociation of rings. These results are taken to indicate that phosphorylation modifies MAPs so that they have a reduced ability to form an assembly-competent complex with tubulin.

Background: We previously developed GoMiner, an application that organizes lists of 'interesting' genes (for example, under-and overexpressed genes from a microarray experiment) for biological interpretation in the context of the Gene Ontology. The original version of GoMiner was oriented toward visualization and interpretation of the results from a single microarray (or other highthroughput experimental platform), using a graphical user interface. Although that version can be used to examine the results from a number of microarrays one at a time, that is a rather tedious task, and original GoMiner includes no apparatus for obtaining a global picture of results from an experiment that consists of multiple microarrays. We wanted to provide a computational resource that automates the analysis of multiple microarrays and then integrates the results across all of them in useful exportable output files and visualizations.

BackgroundMicroarray experiments generate vast amounts of data. The functional context of differentially expressed genes can be assessed by querying the Gene Ontology (GO) database via GoMiner. Directed acyclic graph representations, which are used to depict GO categories enriched with differentially expressed genes, are difficult to interpret and, depending on the particular analysis, may not be well suited for formulating new hypotheses. Additional graphical methods are therefore needed to augment the GO graphical representation.ResultsWe present an alternative visualization approach, area-proportional Euler diagrams, showing set relationships with semi-quantitative size information in a single diagram to support biological hypothesis formulation. The cardinalities of sets and intersection sets are represented by area-proportional Euler diagrams and their corresponding graphical (circular or polygonal) intersection areas. Optimally proportional representations are obtained using swarm and evolutionary optimization algorithms.ConclusionVennMaster's area-proportional Euler diagrams effectively structure and visualize the results of a GO analysis by indicating to what extent flagged genes are shared by different categories. In addition to reducing the complexity of the output, the visualizations facilitate generation of novel hypotheses from the analysis of seemingly unrelated categories that share differentially expressed genes.

Activation of the p53 network plays a central role in the inflammatory stress response associated with ulcerative colitis and may modulate cancer risk in patients afflicted with this chronic disease. Here, we describe the gene expression profiles associated with four microenvironmental components of the inflammatory response (NO .

Sequencing of full-insert clones from full-length cDNA libraries from both Xenopus laevis and Xenopus tropicalis has been ongoing as part of the Xenopus Gene Collection Initiative. Here we present 10,967 full ORF verified cDNA clones (8049 from X. laevis and 2918 from X. tropicalis) as a community resource. Because the genome of X. laevis, but not X. tropicalis, has undergone allotetraploidization, comparison of coding sequences from these two clawed (pipid) frogs provides a unique angle for exploring the molecular evolution of duplicate genes. Within our clone set, we have identified 445 gene trios, each comprised of an allotetraploidization-derived X. laevis gene pair and their shared X. tropicalis ortholog. Pairwise d N /d S, comparisons within trios show strong evidence for purifying selection acting on all three members. However, d N /d S ratios between X. laevis gene pairs are elevated relative to their X. tropicalis ortholog. This difference is highly significant and indicates an overall relaxation of selective pressures on duplicated gene pairs. We have found that the paralogs that have been lost since the tetraploidization event are enriched for several molecular functions, but have found no such enrichment in the extant paralogs. Approximately 14% of the paralogous pairs analyzed here also show differential expression indicative of subfunctionalization.