The distributions of three human ribosomal gene polymorphisms among individual chromosomes containing nucleolus organizers were analyzed by using mouse--human hybrid cells. Different nucleolus organizers can contain the same variant, suggesting the occurrence of genetic exchanges among ribosomal gene clusters on nonhomologous chromosomes. Such exchanges appear to occur less frequently in mice. This difference is discussed in terms of the nucleolar organization and chromosomal location of ribosomal gene clusters in humans and mice.
The Reactome dataset originates from the website https://reactome.org/ where it can be downloaded as Neo4j graph. This graph has been subsequently imported to Neo4j and in turn exported as RDF dump file in Turtle format which is now hosted on this site. The dataset is not yet RDFS-entailed and it utilizes the "http://dev.neo4j.owl.de/" base URI instead of "http://reacome.org/".
Treatment of mice with the carcinogen N-methylnitrosourea results in the development of thymic lymphomas with frequent involvement of the N-ras oncogene. The activated mouse N-ras gene was isolated from one of these lymphomas and, by transformation in concert with restriction digestion, a map of the gene was prepared and its approximate boundaries were determined. By means of somatic cell hybrids the normal N-ras gene was found to be unlinked to other members of the ras gene family.
MicroRNA regulation of developmental and cellular processes is a relatively new field of study, and the available research data have not been organized to enable its inclusion in pathway and network analysis tools. The association of gene products with terms from the Gene Ontology is an effective method to analyze functional data, but until recently there has been no substantial effort dedicated to applying Gene Ontology terms to microRNAs. Consequently, when performing functional analysis of microRNA data sets, researchers have had to rely instead on the functional annotations associated with the genes encoding microRNA targets. In consultation with experts in the field of microRNA research, we have created comprehensive recommendations for the Gene Ontology curation of microRNAs. This curation manual will enable provision of a high-quality, reliable set of functional annotations for the advancement of microRNA research. Here we describe the key aspects of the work, including development of the Gene Ontology to represent this data, standards for describing the data, and guidelines to support curators making these annotations. The full microRNA curation guidelines are available on the GO Consortium wiki (http://wiki.geneontology.org/index.php/MicroRNA_GO_annotation_manual).
To determine the chromosomal localization of murine lambda light (L) chain structural genes, DNA from a panel of 11 mouse x hamster somatic cell hybrids was scored for the presence of sequences homologous to cloned lambda DNA probe molecules. Six of the hybrids had detectable lambda I and lambda II gene sequences. In all six, the full complement of murine sequences was present, and in its germline configuration. The remaining hybrids lacked any detectable murine lambda L chain gene sequences. The only mouse chromosome present in all of the positive hybrids and absent from the negative ones was number 16, allowing the assignment of lambda L chain structural genes to this chromosome. Together with the previous assignments of the kappa L chain genes to chromosome 6 and heavy chain genes to chromosome 12, this finding completes the mapping of Ig structural genes in the mouse at the chromosomal level.
The soil nematodes Caenorhabditis briggsae and Caenorhabditis elegans diverged from a common ancestor roughly 100 million years ago and yet are almost indistinguishable by eye. They have the same chromosome number and genome sizes, and they occupy the same ecological niche. To explore the basis for this striking conservation of structure and function, we have sequenced the C. briggsae genome to a high-quality draft stage and compared it to the finished C. elegans sequence. We predict approximately 19,500 protein-coding genes in the C. briggsae genome, roughly the same as in C. elegans. Of these, 12,200 have clear C. elegans orthologs, a further 6,500 have one or more clearly detectable C. elegans homologs, and approximately 800 C. briggsae genes have no detectable matches in C. elegans. Almost all of the noncoding RNAs (ncRNAs) known are shared between the two species. The two genomes exhibit extensive colinearity, and the rate of divergence appears to be higher in the chromosomal arms than in the centers. Operons, a distinctive feature of C. elegans, are highly conserved in C. briggsae, with the arrangement of genes being preserved in 96% of cases. The difference in size between the C. briggsae (estimated at approximately 104 Mbp) and C. elegans (100.3 Mbp) genomes is almost entirely due to repetitive sequence, which accounts for 22.4% of the C. briggsae genome in contrast to 16.5% of the C. elegans genome. Few, if any, repeat families are shared, suggesting that most were acquired after the two species diverged or are undergoing rapid evolution. Coclustering the C. elegans and C. briggsae proteins reveals 2,169 protein families of two or more members. Most of these are shared between the two species, but some appear to be expanding or contracting, and there seem to be as many as several hundred novel C. briggsae gene families. The C. briggsae draft sequence will greatly improve the annotation of the C. elegans genome. Based on similarity to C. briggsae, we found strong evidence for 1,300 new C. elegans genes. In addition, comparisons of the two genomes will help to understand the evolutionary forces that mold nematode genomes.
The mammalian Rho family GTPases TC10 and Cdc42 share many properties. Activated forms of both proteins stimulate transcription mediated by nuclear factor kappaB, serum response factor, and the cyclin D1 promoter; activate c-Jun NH2-terminal kinase; cooperate with activated Raf to transform NIH-3T3 cells; and, by a mechanism independent of all of these effects, induce filopodia formation. In contrast, previously reported differences between TC10 and Cdc42 are not striking. We now present studies of TC10 and Cdc42 in cell culture that reveal clear functional differences: (a) wild-type TC10 localizes predominantly to the plasma membrane and less extensively to a perinuclear membranous compartment, whereas wild-type Cdc42 localizes predominantly to this compartment and less extensively to the plasma membrane; (b) expression of Rho guanine nucleotide dissociation inhibitor alpha results in a redistribution of wild-type Cdc42 to the cytosol but has no effect on the plasma membrane localization of wild-type TC10; (c) TC10 fails to rescue a Saccharomyces cerevisiae cdc42 mutation, unlike mammalian Cdc42; (d) dominant negative Cdc42, but not dominant negative TC10, inhibits neurite outgrowth in PC12 cells stimulated by nerve growth factor; and (e) activation of nuclear factor kappaB-dependent transcription by Cdc42, but not by TC10, is inhibited by sodium salicylate. These findings point to distinct pathways in which TC10 and Cdc42 may act and distinct modes of regulation of these proteins.
Abstract Gene inactivation can affect the process(es) in which that gene acts and causally downstream ones, yielding diverse mutant phenotypes. Identifying the genetic pathways resulting in a given phenotype helps us understand how individual genes interact in a functional network. Computable representations of biological pathways include detailed process descriptions in the Reactome Knowledgebase and causal activity flows between molecular functions in Gene Ontology-Causal Activity Models (GO-CAMs). A computational process has been developed to convert Reactome pathways to GO-CAMs. Laboratory mice are widely used models of normal and pathological human processes. We have converted human Reactome GO-CAMs to orthologous mouse GO-CAMs, as a resource to transfer pathway knowledge between humans and model organisms. These mouse GO-CAMs allowed us to define sets of genes that function in a causally connected way. To demonstrate that individual variant genes from connected pathways result in similar but distinguishable phenotypes, we used the genes in our pathway models to cross-query mouse phenotype annotations in the Mouse Genome Database (MGD). Using GO-CAM representations of 2 related but distinct pathways, gluconeogenesis and glycolysis, we show that individual causal paths in gene networks give rise to discrete phenotypic outcomes resulting from perturbations of glycolytic and gluconeogenic genes. The accurate and detailed descriptions of gene interactions recovered in this analysis of well-studied processes suggest that this strategy can be applied to less well-understood processes in less well-studied model systems to predict phenotypic outcomes of novel gene variants and to identify potential gene targets in altered processes.
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