Web-based access to mouse models of human cancers: the Mouse Tumor Biology (MTB) Database

The Mouse Tumor Biology (MTB) Database serves as a curated, integrated resource for information about tumor genetics and pathology in genetically defined strains of mice (i.e., inbred, transgenic and targeted mutation strains). Sources of information for the database include the published scientific literature and direct data submissions by the scientific community. Researchers access MTB using Web-based query forms and can use the database to answer such questions as 'What tumors have been reported in transgenic mice created on a C57BL/6J background?', 'What tumors in mice are associated with mutations in the Trp53 gene?' and 'What pathology images are available for tumors of the mammary gland regardless of genetic background?'. MTB has been available on the Web since 1998 from the Mouse Genome Informatics web site (http://www.informatics.jax.org). We have recently implemented a number of enhancements to MTB including new query options, redesigned query forms and results pages for pathology and genetic data, and the addition of an electronic data submission and annotation tool for pathology data.     

The Mouse Gene Expression Database (GXD)

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.     

GXD: a gene expression database for the laboratory mouse. The Gene Expression Database Group.

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/     

BioGPS and GXD: mouse gene expression data—the benefits and challenges of data integration

Mouse gene expression data are complex and voluminous. To maximize the utility of these data, they must be made readily accessible through databases, and those resources need to place the expression data in the larger biological context. Here we describe two community resources that approach these problems in different but complementary ways: BioGPS and the Mouse Gene Expression Database (GXD). BioGPS connects its large and homogeneous microarray gene expression reference data sets via plugins with a heterogeneous collection of external gene centric resources, thus casting a wide but loose net. GXD acquires different types of expression data from many sources and integrates these data tightly with other types of data in the Mouse Genome Informatics (MGI) resource, with a strong emphasis on consistency checks and manual curation. We describe and contrast the “loose” and “tight” data integration strategies employed by BioGPS and GXD, respectively, and discuss the challenges and benefits of data integration. BioGPS is freely available at http://biogps.org. GXD is freely available through the MGI web site (www.informatics.jax.org) or directly at www.informatics.jax.org/expression.shtml.     

MGD: the Mouse Genome Database

The Mouse Genome Database (MGD) (http://www.informatics.jax.org) one component of a community database resource for the laboratory mouse, a key model organism for interpreting the human genome and for understanding human biology. MGD strives to provide an extensively integrated information resource with experimental details annotated from both literature and on-line genomic data sources. MGD curates and presents the consensus representation of genotype (sequence) to phenotype information including highly detailed information about genes and gene products. Primary foci of integration are through representations of relationships between genes, sequences and phenotypes. MGD collaborates with other bioinformatics groups to curate a definitive set of information about the laboratory mouse. Recent developments include a general implementation of database structures for controlled vocabularies and the integration of a phenotype classification system.     

The Mouse Genome Database (MGD): integration nexus for the laboratory mouse

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.     

Rules and guidelines for genetic nomenclature in mice: excerpted version

The unique identification of genes and mouse strains is critical to their identification in research and in the scientific literature. Rules for genetic nomenclature in mice have existed since the 1940s. The latest complete revision of the rules was approved by the International Committee on Standardized Genetic Nomenclature for Mice in November, 1993. Minor revisions have occurred since. The complete, current rules are available on-line from The Jackson Laboratory's Mouse Genome Database (MGD), URL: http://www.informatics.jax.org. A printed version appeared in Mouse Genome 92 (2), June, 1994, and in Genetic Variants and Strains of the Laboratory Mouse, 3rd edition (Committee on Standardized Genetic Nomenclature for Mice, 1996a,b,c). The excerpted version below gives the general guidelines for naming and symbolizing mouse genes, transgenes and transgenic strains, targeted mutations and DNA markers. More detailed guidelines, including revisions as they are made, may be found at the MGD Web site given above. Subparagraphs are numbered as in the complete guidelines so that the user can refer easily from this excerpted version to the full text. Textual references to paragraphs not included here may be found in the full text as well     

A collaborative database of inbred mouse strain characteristics

A database and website (MPD: Mouse Phenome Database) have been developed to serve as a consolidated home for mouse strain characterization data being generated by the scientific community. Physiological, anatomical and behavioral data are being collected and integrated into a common framework for tabulation by strain and sex. Genotypic data are being collected as well. The current focus is on a set of 40 inbred strains. The MPD as of February 2004 contains approximately 500 phenotypic parameters relevant to human health, voluntarily contributed by several dozen investigators and laboratories. AVAILABILITY: www.jax.org/phenome     

New mouse genetic models for human contraceptive development

Genetic strategies for the post-genomic sequence age will be designed to provide information about gene function in a myriad of physiological processes. Here an ENU mutagenesis program (http://reprogenomics.jax.org) is described that is generating a large resource of mutant mouse models of infertility; male and female mutants with defects in a wide range of reproductive processes are being recovered. Identification of the genes responsible for these defects, and the pathways in which these genes function, will advance the fields of reproduction research and medicine. Importantly, this program has potential to reveal novel human contraceptive targets.     

Computational structural analysis of proteins of Mycobacterium tuberculosis and a resource for identifying off-targets

Advancement in technology has helped to solve structures of several proteins including M. tuberculosis (MTB) proteins. Identifying similarity between protein structures could not only yield valuable clues to their function, but can also be employed for motif finding, protein docking and off-target identification. The current study has undertaken analysis of structures of all MTB gene products with available structures was analyzed. Majority of the MTB proteins belonged to the α/β class. 23 different protein folds are used in the MTB protein structures. Of these, the TIM barrel fold was found to be highly conserved even at very low sequence identity. We identified 21 paralogs and 27 analogs of MTB based on domains and EC classification. Our analysis revealed that many of the current drug targets share structural similarity with other proteins within the MTB genome, which could probably be off-targets. Results of this analysis have been made available in the Mycobacterium tuberculosis Structural Database (http://bmi.icmr.org.in/mtbsd/MtbSD.php/search.php) which is a useful resource for current and novel drug targets of MTB.     

PACdb: PolyA Cleavage Site and 3'-UTR Database

SUMMARY: The PolyA Cleavage Site and 3'-UTR Database (PACdb) is a web-accessible database that catalogs putative 3'-processing sites and 3'-UTR sequences for multiple organisms. Sites have been identified primarily via expressed sequence tag-genome alignments, enabling delineation of both the specificities and heterogeneity of 3'-processing events. AVAILABILITY: By web browser or CGI: PACdb: http://harlequin.jax.org/pacdb/; AtPACdb: http://harlequin.jax.org/atpacdb/. SUPPLEMENTARY INFORMATION: Available online at http://harlequin.jax.org/pacdb/supplemental.php.     

An extensive list of genes that produce alternative transcripts in the mouse

SUMMARY: A single gene can generate multiple transcribed gene products. An extensive list of alternatively transcribed mouse genes has been generated, and is publicly available from http://www.informatics.jax.org/report.html. CONTACT: mgi-help@informatics.jax.org     

Multiple Merger Genealogies in Outbreaks of Mycobacterium tuberculosis

The Kingman coalescent and its developments are often considered among the most important advances in population genetics of the last decades. Demographic inference based on coalescent theory has been used to reconstruct the population dynamics and evolutionary history of several species, including Mycobacterium tuberculosis (MTB), an important human pathogen causing tuberculosis. One key assumption of the Kingman coalescent is that the number of descendants of different individuals does not vary strongly, and violating this assumption could lead to severe biases caused by model misspecification. Individual lineages of MTB are expected to vary strongly in reproductive success because 1) MTB is potentially under constant selection due to the pressure of the host immune system and of antibiotic treatment, 2) MTB undergoes repeated population bottlenecks when it transmits from one host to the next, and 3) some hosts show much higher transmission rates compared with the average (superspreaders).Here, we used an approximate Bayesian computation approach to test whether multiple-merger coalescents (MMC), a class of models that allow for large variation in reproductive success among lineages, are more appropriate models to study MTB populations. We considered 11 publicly available whole-genome sequence data sets sampled from local MTB populations and outbreaks and found that MMC had a better fit compared with the Kingman coalescent for 10 of the 11 data sets. These results indicate that the null model for analyzing MTB outbreaks should be reassessed and that past findings based on the Kingman coalescent need to be revisited.     

Direct and simultaneous identification of Mycobacterium tuberculosis complex (MTBC) and Mycobacterium tuberculosis (MTB) by rapid multiplex nested PCR-ICT assay

The Mycobacterium tuberculosis (MTB) shows different virulence and host infection range from other members of the M. tuberculosis complex (MTBC). Differential identification of MTB from MTBC is thus important in certain occasions. The currently commercially available molecular assays which use either IS6110 or 16S rDNA fragment as identification targets are mainly designed for identifying MTBC but not for MTB. Comparative genomic DNA analysis has provided valuable information on regions of difference (RD) present in MTB but not in other members of the MTBC. RD9 region is further suggested to be a potential target for differential identification of MTB from MTBC. In this study, using IS6110 and Rv3618 (belong to RD9) as the specific identification targets for MTBC and MTB, respectively, we developed and tested a multiplex nested PCR-ICT (immuno-chromatography test) assay for simultaneously and directly detecting not only MTBC but also MTB from 1500 clinical sputum specimens. The results were compared with traditional culture and biochemical identification results together with patients' clinical assessments. This assay showed a 95.5% sensitivity, 97.9% specificity, 2.1% false positive rate and 4.5% false negative rate towards detection of MTBC, and a 93.0% sensitivity, 99.8% specificity, 0.2% false positive rate and 7.0% false negative rate for detection of MTB. This detection system shows great potential in clinical application.     

Functional genomics complements quantitative genetics in identifying disease-gene associations

An ultimate goal of genetic research is to understand the connection between genotype and phenotype in order to improve the diagnosis and treatment of diseases. The quantitative genetics field has developed a suite of statistical methods to associate genetic loci with diseases and phenotypes, including quantitative trait loci (QTL) linkage mapping and genome-wide association studies (GWAS). However, each of these approaches have technical and biological shortcomings. For example, the amount of heritable variation explained by GWAS is often surprisingly small and the resolution of many QTL linkage mapping studies is poor. The predictive power and interpretation of QTL and GWAS results are consequently limited. In this study, we propose a complementary approach to quantitative genetics by interrogating the vast amount of high-throughput genomic data in model organisms to functionally associate genes with phenotypes and diseases. Our algorithm combines the genome-wide functional relationship network for the laboratory mouse and a state-of-the-art machine learning method. We demonstrate the superior accuracy of this algorithm through predicting genes associated with each of 1157 diverse phenotype ontology terms. Comparison between our prediction results and a meta-analysis of quantitative genetic studies reveals both overlapping candidates and distinct, accurate predictions uniquely identified by our approach. Focusing on bone mineral density (BMD), a phenotype related to osteoporotic fracture, we experimentally validated two of our novel predictions (not observed in any previous GWAS/QTL studies) and found significant bone density defects for both Timp2 and Abcg8 deficient mice. Our results suggest that the integration of functional genomics data into networks, which itself is informative of protein function and interactions, can successfully be utilized as a complementary approach to quantitative genetics to predict disease risks. All supplementary material is available at http://cbfg.jax.org/phenotype.     

Cryoconservation—archiving for the future

Mouse genetics is set to play a pivotal role in the key post-genome challenge—the study of mammalian gene function. Addressing this challenge will involve the development and application of systematic mutagenesis approaches. The expanding mouse mutant resource that will result threatens to overwhelm the currently available animal facility space. Cryopreservation of both mouse embryos and spermatozoa is currently widely employed for the efficient archiving of mouse stocks. Distribution and dissemination of new and existing mouse strains is simplified by the availability of extensive frozen archives. Also, the availability of archives of frozen spermatozoa provides a potential powerful route for the production of backcross progeny for rapid genetic mapping. Moreover, frozen oocytes and ovaries may offer a valuable addition to the current cryopreservation approaches. Comprehensive mouse mutant archives will provide an essential resource for mammalian genetics throughout the 21^st century. Received: 16 December 1999 / Accepted: 17 December 1999     

结核分枝杆菌的耐药基因及其相关分子机制

结核分枝杆菌原发性和继发性耐药是当前控帝】和治疗结核病面临的重要问题,随着分子遗传学的发展,已经阐明了结核分枝杆菌耐药的分子基础是染色体的突变,影响了药靶本身或激活了药物前体的细菌酶,造成MTB的耐药。本文主要就MTB对其常用药物的耐药机制展开讨论,以便正确认识MTB对不同药物的耐药机制,建立快速检测耐药结核分枝杆菌基因型的分子生物学方法。     

High-resolution gene expression atlases for adult and developing mouse brain and spinal cord

Knowledge of the structure, genetics, circuits, and physiological properties of the mammalian brain in both normal and pathological states is ever increasing as research labs worldwide probe the various aspects of brain function. Until recently, however, comprehensive cataloging of gene expression across the central nervous system has been lacking. The Allen Institute for Brain Science, as part of its mission to propel neuroscience research, has completed several large gene-mapping projects in mouse, nonhuman primate, and human brain, producing informative online public resources and tools. Here we present the Allen Mouse Brain Atlas, covering ~20,000 genes throughout the adult mouse brain; the Allen Developing Mouse Brain Atlas, detailing expression of approximately 2,000 important developmental genes across seven embryonic and postnatal stages of brain growth; and the Allen Spinal Cord Atlas, revealing expression for ~20,000 genes in the adult and neonatal mouse spinal cords. Integrated data-mining tools, including reference atlases, informatics analyses, and 3-D viewers, are described. For these massive-scale projects, high-throughput industrial techniques were developed to standardize and reliably repeat experimental goals. To verify consistency and accuracy, a detailed analysis of the 1,000 most viewed genes for the adult mouse brain (according to website page views) was performed by comparing our data with peer-reviewed literature and other databases. We show that our data are highly consistent with independent sources and provide a comprehensive compendium of information and tools used by thousands of researchers each month. All data and tools are freely available via the Allen Brain Atlas portal (www.brain-map.org).