The Gene Ontology (GO) project (http://www. geneontology.org/) provides structured, controlled vocabularies and classifications that cover several domains of molecular and cellular biology and are freely available for community use in the annotation of genes, gene products and sequences. Many model organism databases and genome annotation groups use the GO and contribute their annotation sets to the GO resource. The GO database integrates the vocabularies and contributed annotations and provides full access to this information in several formats. Members of the GO Consortium continually work collectively, involving outside experts as needed, to expand and update the GO vocabularies. The GO Web resource also provides access to extensive documentation about the GO project and links to applications that use GO data for functional analyses.

The mouse is a prime organism of choice for modelling human disease. Over 450 inbred strains of mice have been described, providing a wealth of different genotypes and phenotypes for genetic and other studies. As new strains are generated and others become extinct, it is useful to review periodically what strains are available and how they are related to each other, particularly in the light of available DNA polymorphism data from microsatellite and other markers. We describe the origins and relationships of inbred mouse strains, 90 years after the generation of the first inbred strain. Given the large collection of inbred strains available, and that published information on these strains is incomplete, we propose that all genealogical and genetic data on inbred strains be submitted to a common electronic database to ensure this valuable information resource is preserved and used efficiently.

We established two mouse interspecific backcross DNA panels, one containing 94 N2 animals from the cross (C57BL/6J x Mus spretus)F1 x C57BL/6J, and another from 94 N2 animals from the reciprocal backcross (C57BL/6J x SPRET/Ei)F1 x SPRET/Ei. We prepared large quantities of DNA from most tissues of each animal to create a community resource of interspecific backcross DNA for use by laboratories interested in mapping loci in the mouse. Initial characterization of the genetic maps of both panels has been completed. We used MIT SSLP markers, proviral loci, and several other sequence-defined genes to anchor our maps to other published maps. The BSB panel map (from the backcross to C57BL/6J) contains 215 loci and is anchored by 45 SSLP and 32 gene sequence loci. The BSS panel map (from the backcross to SPRET/Ei) contains 451 loci and is anchored by 49 SSLP loci, 43 proviral loci, and 60 gene sequence loci. To obtain a high density of markers, we used motif-primed PCR to "fingerprint" the panel DNAs. We constructed two maps, each representing one of the two panels. All new loci can be located with a high degree of certainty on the maps at current marker density. Segregation patterns in these data reveal several examples of transmission ratio distortion and permit analysis of the distribution of crossovers on individual chromosomes.

Technological advances have made possible the development of high-resolution genetic linkage maps for the mouse. These maps in turn offer exciting prospects for understanding mammalian genome evolution through comparative mapping, for developing mouse models of human disease, and for identifying the function of all genes in the organism.

A community-wide effort to establish baseline phenotypic data on commonly used and genetically diverse inbred mouse strains and to provide the information through a publicly accessible database.

Cytological analysis of the mouse Y* chromosome revealed a complex rearrangement involving acquisition of a functional centromere and centromeric heterochromatin and attachment of this chromosomal segment to the distal end of a normal Y* chromosome. This rearrangement positioned the Y* short-arm region at the distal end of the Y* chromosome and the pseudoautosomal region interstitially, just distal to the newly acquired centromere. In addition, the majority of the pseudoautosomal region was inverted. Recombination between the X and the Y* chromosomes generates two new sex chromosomes: (1) a large chromosome comprised of the X chromosome attached at its distal end to all of the Y* chromosome but missing the centromeric region (XY*) and (2) a small chromosome containing the centromeric portion of the Y* chromosome attached to G-band-negative material from the X chromosome (YX). Mice that inherit the XY* chromosome develop as sterile males, whereas mice that inherit the Y*X chromosome develop as fertile females. Recovery of equal numbers of recombinant and nonrecombinant offspring from XY* males supports the hypothesis that recombination between the mammalian X and Y chromosomes is necessary for primary spermatocytes to successfully complete spermatogenesis and form functional sperm.

High-throughput sequencing of miRNAs has revealed the diversity and variability of mature and functional short noncoding RNAs, including their genomic origins, biogenesis pathways, sequence variability, and newly identified products such as miRNA-offset RNAs (moRs). Here we review known cases of alternative mature miRNA-like RNA fragments and propose a revised definition of miRNAs to encompass this diversity. We then review nomenclature guidelines for miRNAs and propose to extend nomenclature conventions to align with those for protein-coding genes established by international consortia. Finally, we suggest a system to encompass the full complexity of sequence variations (i.e., isomiRs) in the analysis of small RNA sequencing experiments.

The Mouse Genome Database (MGD) is a comprehensive public database of mouse genomic, genetic and phenotypic information (http://www. informatics.jax.org). This community database provides information about genes, serves as a mapping resource of the mouse genome, details mammalian orthologs, integrates experimental data, represents standardized mouse nomenclature for genes and alleles, incorporates links to other genomic resources such as sequence data, and includes a variety of additional information about the laboratory mouse. MGD scientists and annotators work cooperatively with the research community to provide an integrated, consensus view of the mouse genome while also providing experimental data including data conflicting with the consensus representation. Recent improvements focus on the representation of phenotypic information and the enhancement of gene and allele descriptions.

For the study of biological phenomena influenced by multiple genes in mice, the Recombinant Congenic Strains (RCS) have been developed. An RCS series comprises approximately 20 homozygous strains, each of which contains on average 87.5% genes of a common background strain and 12.5% of a common donor strain. In an RCS series, non-linked genes involved in the control of a multigenic trait become distributed into different recombinant congenic strains. In this way a multigenic trait is transformed into a series of single gene traits in which each gene can be studied individually. For the ability to use the strength of the recombinant congenic strains system to its full extent, a thorough genetic characterization is indispensable. We have typed the CcS/Dem and OcB/Dem series for 611 and 550 markers, respectively. This results in a genetic characterization sufficient to detect most donor strain genes. In addition, we report the genetic characterization of the HcB/Dem and HcB(N4)/Dem series. Strains of the latter series contain on average 6.25% of the donor strain genome. Both series have been typed for 130 markers. All the typing data have been deposited in the Mouse Genome Database at The Jackson Laboratory.

The Gene Expression Database (GXD) is a community resource of gene expression information for the laboratory mouse. By combining the different types of expression data, GXD aims to provide increasingly complete information about the expression profiles of genes in different mouse strains and mutants, thus enabling valuable insights into the molecular networks that underlie normal development and disease. GXD is integrated with the Mouse Genome Database (MGD). Extensive interconnections with sequence databases and with databases from other species, and the development and use of shared controlled vocabularies extend GXD's utility for the analysis of gene expression information. GXD is accessible through the Mouse Genome Informatics web site at http://www.informatics.jax.org/ or directly at http://www.informatics.jax.org/menus/expression_menu. shtml.

Murine ovarian teratomas were used to determine recombination percentages for gene-gene and centromere-gene intervals. Data were obtained utilizing a recombinant inbred strain, LTXBJ, and a number of newly developed LT/SvEi congenic strains.--Centromere-gene recombination was measured at 11.3 +/- 1.2% for the centromere of chromosome 7 - Gpi-1 interval and 15.8 +/- 2.4% for the centromere of chromosome 14 - Np-1 interval using the ovarian teratoma method. The centromere - Np-1 interval was measured at 26.5 +/- 3.6% using a standard backcross involving the Rb6Bnr Robertsonian translocation as a centromere marker.--To assess the accuracy of the ovarian teratoma mapping method, we compared the recombination frequency obtained for the Mpi-1-Mod-1 interval on chromosome 9 using the ovarian teratoma method to that obtained using a standard backcross. The recombination percentage was 22.9 +/- 5.4 using the ovarian teratoma method and 18.6 +/- 3.3 using the backcross method, indicating that the two methods produce equivalent estimates of recombination. In addition, for centromere-gene intervals known to be more than 30 cM in length, the ovarian teratoma method was consistent with classical recombination methods, yielding high recombination percentages. We conclude from these results that the ovarian teratoma mapping method is a reliable method for estimating recombination frequencies and the most accurate method available for estimating centromere-gene recombination frequency in the mouse.

The Gene Expression Database (GXD) is a community resource that stores and integrates expression information for the laboratory mouse, with a particular emphasis on mouse development, and makes these data freely available in formats appropriate for comprehensive analysis. GXD is implemented as a relational database and integrated with the Mouse Genome Database (MGD) to enable global analysis of genotype, expression and phenotype information. Interconnections with sequence databases and with databases from other species further extend GXD's utility for the analysis of gene expression data. GXD is available through the Mouse Genome Informatics Web Site at http://www.informatics.jax.org/

The Mouse Genome Database (MGD) focuses on the integration of mapping, homology, polymorphism and molecular data about the laboratory mouse. Detailed descriptions of genes including their chromosomal location, gene function, disease associations, mutant phenotypes, molecular polymorphisms and links to representative sequences including ESTs are integrated within MGD. The association of information from experiment to gene to genome requires careful coordination and implementation of standardized vocabularies, unique nomenclature constructions, and detailed information derived from multiple sources. This information is linked to other public databases that focus on additional information such as expression patterns, sequences, bibliographic details and large mapping panel data. Scientists participate in the curation of MGD data by generating the Chromosome Committee Reports, consulting on gene family nomenclature revisions, and providing descriptions of mouse strain characteristics and of new mutant phenotypes. MGD is accessible at http://www.informatics.jax.org

The Mouse Genome Database (MGD) is the community database resource for the laboratory mouse, a key model organism for interpreting the human genome and for understanding human biology and disease (http://www.informatics.jax.org). MGD provides standard nomenclature and consensus map positions for mouse genes and genetic markers; it provides a curated set of mammalian homology records, user-defined chromosomal maps, experimental data sets and the definitive mouse 'gene to sequence' reference set for the research community. The integration and standardization of these data sets facilitates the transition between mouse DNA sequence, gene and phenotype annotations. A recent focus on allele and phenotype representations enhances the ability of MGD to organize and present data for exploring the relationship between genotype and phenotype. This link between the genome and the biology of the mouse is especially important as phenotype information grows from large mutagenesis projects and genotype information grows from large-scale sequencing projects.

The Mouse Genome Database (MGD) is a comprehensive community resource of mouse genetic and biological information populated both with data from published literature and with data electronically submitted from the research community. MGD stores genetic, physical and comparative mapping data, clones/probes/PCR information, and phenotype descriptions for genes, mutations and mouse strains. Supporting software for importation, analysis, display and distribution of mouse genetic data have been developed. User support is provided through dedicated staff providing documentation, training, and response to individual user queries. MGD is accessible over the Internet at URL http://www.informatics.jax.org.

The Mouse Tumor Biology Database (MTB) is designed to provide an electronic data storage, search, and analysis system for information on mouse models of human cancer. The MTB includes data on tumor frequency and latency, strain, germ line, and somatic genetics, pathologic notations, and photomicrographs. The MTB collects data from the primary literature, other public databases, and direct submissions from the scientific community. The MTB is a community resource that provides integrated access to mouse tumor data from different scientific research areas and facilitates integration of molecular, genetic, and pathologic data. Current status of MTB, search capabilities, data types, and future enhancements are described in this article.