Cancer-associated mesothelial cells are regulated by the anti-Müllerian hormone axis.

Cancer-associated mesothelial cells (CAMCs) in the tumor microenvironment are thought to promote growth and immune evasion. We find that, in mouse and human ovarian tumors, cancer cells express anti-Müllerian hormone (AMH) while CAMCs express its receptor AMHR2, suggesting a paracrine axis. Factors secreted by cancer cells induce AMHR2 expression during their reprogramming into CAMCs in mouse and human in vitro models. Overexpression of AMHR2 in the Met5a mesothelial cell line is sufficient to induce expression of immunosuppressive cytokines and growth factors that stimulate ovarian cancer cell growth in an AMH-dependent way. Finally, syngeneic cancer cells implanted in transgenic mice with Amhr2-/- CAMCs grow significantly slower than in wild-type hosts. The cytokine profile of Amhr2-/- tumor-bearing mice is altered and their tumors express less immune checkpoint markers programmed-cell-death 1 (PD1) and cytotoxic T lymphocyte-associated protein 4 (CTLA4). Taken together, these data suggest that the AMH/AMHR2 axis plays a critical role in regulating the pro-tumoral function of CAMCs in ovarian cancer.

Mouse models of NADK2 deficiency analyzed for metabolic and gene expression changes to elucidate pathophysiology.

NADK2 encodes the mitochondrial form of nicotinamide adenine dinucleotide (NAD) kinase, which phosphorylates NAD. Rare recessive mutations in human NADK2 are associated with a syndromic neurological mitochondrial disease that includes metabolic changes, such as hyperlysinemia and 2,4 dienoyl CoA reductase (DECR) deficiency. However, the full pathophysiology resulting from NADK2 deficiency is not known. Here, we describe two chemically induced mouse mutations in Nadk2-S326L and S330P-which cause severe neuromuscular disease and shorten lifespan. The S330P allele was characterized in detail and shown to have marked denervation of neuromuscular junctions by 5 weeks of age and muscle atrophy by 11 weeks of age. Cerebellar Purkinje cells also showed progressive degeneration in this model. Transcriptome profiling on brain and muscle was performed at early and late disease stages. In addition, metabolomic profiling was performed on the brain, muscle, liver and spinal cord at the same ages and on plasma at 5 weeks. Combined transcriptomic and metabolomic analyses identified hyperlysinemia, DECR deficiency and generalized metabolic dysfunction in Nadk2 mutant mice, indicating relevance to the human disease. We compared findings from the Nadk model to equivalent RNA sequencing and metabolomic datasets from a mouse model of infantile neuroaxonal dystrophy, caused by recessive mutations in Pla2g6. This enabled us to identify disrupted biological processes that are common between these mouse models of neurological disease, as well as those processes that are gene-specific. These findings improve our understanding of the pathophysiology of neuromuscular diseases and describe mouse models that will be useful for future preclinical studies.

A unified gene catalog for the laboratory mouse reference genome.

We report here a semi-automated process by which mouse genome feature predictions and curated annotations (i.e., genes, pseudogenes, functional RNAs, etc.) from Ensembl, NCBI and Vertebrate Genome Annotation database (Vega) are reconciled with the genome features in the Mouse Genome Informatics (MGI) database (http://www.informatics.jax.org) into a comprehensive and non-redundant catalog. Our gene unification method employs an algorithm (fjoin--feature join) for efficient detection of genome coordinate overlaps among features represented in two annotation data sets. Following the analysis with fjoin, genome features are binned into six possible categories (1:1, 1:0, 0:1, 1:n, n:1, n:m) based on coordinate overlaps. These categories are subsequently prioritized for assessment of annotation equivalencies and differences. The version of the unified catalog reported here contains more than 59,000 entries, including 22,599 protein-coding coding genes, 12,455 pseudogenes, and 24,007 other feature types (e.g., microRNAs, lincRNAs, etc.). More than 23,000 of the entries in the MGI gene catalog have equivalent gene models in the annotation files obtained from NCBI, Vega, and Ensembl. 12,719 of the features are unique to NCBI relative to Ensembl/Vega; 11,957 are unique to Ensembl/Vega relative to NCBI, and 3095 are unique to MGI. More than 4000 genome features fall into categories that require manual inspection to resolve structural differences in the gene models from different annotation sources. Using the MGI unified gene catalog, researchers can easily generate a comprehensive report of mouse genome features from a single source and compare the details of gene and transcript structure using MGI's mouse genome browser.

High-precision genetic mapping of behavioral traits in the diversity outbred mouse population.

Historically our ability to identify genetic variants underlying complex behavioral traits in mice has been limited by low mapping resolution of conventional mouse crosses. The newly developed Diversity Outbred (DO) population promises to deliver improved resolution that will circumvent costly fine-mapping studies. The DO is derived from the same founder strains as the Collaborative Cross (CC), including three wild-derived strains. Thus the DO provides more allelic diversity and greater potential for discovery compared to crosses involving standard mouse strains. We have characterized 283 male and female DO mice using open-field, light-dark box, tail-suspension and visual-cliff avoidance tests to generate 38 behavioral measures. We identified several quantitative trait loci (QTL) for these traits with support intervals ranging from 1 to 3 Mb in size. These intervals contain relatively few genes (ranging from 5 to 96). For a majority of QTL, using the founder allelic effects together with whole genome sequence data, we could further narrow the positional candidates. Several QTL replicate previously published loci. Novel loci were also identified for anxiety- and activity-related traits. Half of the QTLs are associated with wild-derived alleles, confirming the value to behavioral genetics of added genetic diversity in the DO. In the presence of wild-alleles we sometimes observe behaviors that are qualitatively different from the expected response. Our results demonstrate that high-precision mapping of behavioral traits can be achieved with moderate numbers of DO animals, representing a significant advance in our ability to leverage the mouse as a tool for behavioral genetics.

The Mouse Tumor Biology Database (MTB): a central electronic resource for locating and integrating mouse tumor pathology data.

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.

From information to understanding: the role of model organism databases in comparative and functional genomics.

Data integration is key to functional and comparative genomics because integration allows diverse data types to be evaluated in new contexts. To achieve data integration in a scalable and sensible way, semantic standards are needed, both for naming things (standardized nomenclatures, use of key words) and also for knowledge representation. The Mouse Genome Informatics database and other model organism databases help to close the gap between information and understanding of biological processes because these resources enforce well-defined nomenclature and knowledge representation standards. Model organism databases have a critical role to play in ensuring that diverse kinds of data, especially genome-scale data sets and information, remain useful to the biological community in the long-term. The efforts of model organism database groups ensure not only that organism-specific data are integrated, curated and accessible but also that the information is structured in such a way that comparison of biological knowledge across model organisms is facilitated.

Systems biology of the 2-cell mouse embryo.

The transcriptome of the 2-cell mouse embryo was analyzed to provide insight into the molecular networks at play during nuclear reprogramming and embryonic genome activation. Analysis of ESTs from a 2-cell cDNA library identified nearly 4,000 genes, over half of which have not been previously studied. Transcripts of mobile elements, especially those of LTR retrotransposons, are abundantly represented in 2-cell embryos, suggesting their possible role in introducing genomic variation, and epigenetic restructuring of the embryonic genome. Analysis of Gene Ontology of the 2-cell-stage expressed genes outlines the major biological processes that guide the oocyte-to-embryo transition. These results provide a foundation for understanding molecular control at the onset of mammalian development.

The Gene Ontology (GO) database and informatics resource.

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.

Analysis of the mouse transcriptome based on functional annotation of 60,770 full-length cDNAs.

Only a small proportion of the mouse genome is transcribed into mature messenger RNA transcripts. There is an international collaborative effort to identify all full-length mRNA transcripts from the mouse, and to ensure that each is represented in a physical collection of clones. Here we report the manual annotation of 60,770 full-length mouse complementary DNA sequences. These are clustered into 33,409 'transcriptional units', contributing 90.1% of a newly established mouse transcriptome database. Of these transcriptional units, 4,258 are new protein-coding and 11,665 are new non-coding messages, indicating that non-coding RNA is a major component of the transcriptome. 41% of all transcriptional units showed evidence of alternative splicing. In protein-coding transcripts, 79% of splice variations altered the protein product. Whole-transcriptome analyses resulted in the identification of 2,431 sense-antisense pairs. The present work, completely supported by physical clones, provides the most comprehensive survey of a mammalian transcriptome so far, and is a valuable resource for functional genomics.

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.

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.

Mouse tumor biology database (MTB): enhancements and current status.

The Mouse Tumor Biology Database (MTB) is a Web-based resource that provides access to information on tumor frequency and latency, genetics and pathology in genetically defined mice (transgenics, targeted mutations and inbred strains). MTB is designed to serve as an information resource for cancer genetics researchers who use the laboratory mouse as a model system for understanding human disease processes. Data in MTB are obtained from the primary scientific literature and direct submissions by the research community. MTB is accessible from the Mouse Genome Informatics Web site (http://www. informatics.jax.org). User support is available for MTB via Email at mgi-help@informatics.jax.org

Electronic access to mouse tumor data: the Mouse Tumor Biology Database (MTB) project.

The Mouse Tumor Biology (MTB) Database supports the use of the mouse as a model system of hereditary and induced cancers by providing electronic access to: (i) tumor names and classifications, (ii) tumor incidence and latency data in different strains of mice, (iii) tumor pathology reports and images, (iv) information on genetic factors associated with tumors and tumor development, and (v) references (published and unpublished data). This resource has been designed to aid researchers in such areas as choosing experimental models, reviewing patterns of mutations in specific cancers, and identifying genes that are commonly mutated across a spectrum of cancers. MTB also provides hypertext links to related on-line resources and databases. MTB is accessible via the World Wide Web at http://tumor.informatics.jax.org. User support is available for MTB by Email at mgi-help@informatics.jax.org

A molecular phylogeny of the bivalve mollusks.

A phylogenetic reconstruction based on 506 nucleotides near the 5' end of the 18S subunit of ribosomal DNA (rDNA) in 2 gastropod, 3 chiton and 28 bivalve mollusks supported the monophyly and sister group relationship of the subclasses Heterodonta and Palaeoheterodonta but could not confidently establish either the monophyly or the phylogenetic relationships of the morphologically well defined subclasses Pteriomorphia, Protobranchia, and Anomalodesmata. When both gastropods and chitons were included in the analysis, one or the other invariably emerged within Bivalvia. Some evidence indicates that this apparent polyphyly may be the consequence of unequal rates of evolution and of rapid changes in the protobranch and anomalodesmatan lineages. The taxa usually included in Pteriomorpha emerge as a grade rather than a clade, although in a sequence that differs from morphologically based phylogenies.

Phylogeny and relationships of pleurotomariid gastropods (Mollusca: Gastropoda): an assessment based on partial 18S rDNA and cytochrome c oxidase I sequences.

The phylogenetic position of the ancient family Pleurotomariidae within the Molluscan class Gastropoda, as well as the relationships of its Recent genera and species, were assessed using an iterative, two-gene (18S rDNA and cytochrome c oxidase I) approach to phylogeny reconstruction. In order to orient the Pleurotomariidae within Gastropoda, partial 18S rDNA sequences were determined for 7 pleurotomariid and 22 other gastropods that span the major groups within the class as well as for one cephalopod and two polyplacophorans, which serve as outgroups. Cladistic analyses of a sequence of approximately 450 base pairs (bp) near the 5' end of the 18S rDNA support the monophyly of the following higher gastropod taxa: Patellogastropoda, Vetigastropoda, Neritopsina, Apogastropoda, and its subclades Caenogastropoda and Heterobranchia. The 18S rDNA sequences and 579 bp of cytochrome c oxidase I (COI) analyzed separately and together, indicate that Pleurotomariidae are included within Vetigastropoda but comprise a clade that is the sister group to the other families referred to this order. Monophyly of the Pleurotomariidae is also supported by the unique presence of seven separate inserts (ranging in length from 1 to 68 bp) within the V2 variable region of the 18S RNA. Relationships of the genera and species within Pleurotomariidae are fully resolved using "total molecular evidence" consisting of partial sequences of 18S rDNA and COI and including data on length variation within the inserts.

Complete genome sequence of the methanogenic archaeon, Methanococcus jannaschii.

The complete 1.66-megabase pair genome sequence of an autotrophic archaeon, Methanococcus jannaschii, and its 58- and 16-kilobase pair extrachromosomal elements have been determined by whole-genome random sequencing. A total of 1738 predicted protein-coding genes were identified; however, only a minority of these (38 percent) could be assigned a putative cellular role with high confidence. Although the majority of genes related to energy production, cell division, and metabolism in M. jannaschii are most similar to those found in Bacteria, most of the genes involved in transcription, translation, and replication in M. jannaschii are more similar to those found in Eukaryotes.

The minimal gene complement of Mycoplasma genitalium.

The complete nucleotide sequence (580,070 base pairs) of the Mycoplasma genitalium genome, the smallest known genome of any free-living organism, has been determined by whole-genome random sequencing and assembly. A total of only 470 predicted coding regions were identified that include genes required for DNA replication, transcription and translation, DNA repair, cellular transport, and energy metabolism. Comparison of this genome to that of Haemophilus influenzae suggests that differences in genome content are reflected as profound differences in physiology and metabolic capacity between these two organisms.

Initial assessment of human gene diversity and expression patterns based upon 83 million nucleotides of cDNA sequence.

In an effort to identify new genes and analyse their expression patterns, 174,472 partial complementary DNA sequences (expressed sequence tags (ESTs)), totalling more than 52 million nucleotides of human DNA sequence, have been generated from 300 cDNA libraries constructed from 37 distinct organs and tissues. These ESTs have been combined with an additional 118,406 ESTs from the database dbEST, for a total of 83 million nucleotides, and treated as a shotgun sequence assembly project. The assembly process yielded 29,599 distinct tentative human consensus (THC) sequences and 58,384 non-overlapping ESTs. Of these 87,983 distinct sequences, 10,214 further characterize previously known genes based on statistically significant similarity to sequences in the available databases; the remainder identify previously unknown genes. Thirty tissues were sampled by over 1,000 ESTs each; only eight genes were matched by ESTs from all 30 tissues, and 227 genes were represented in 20 or more of the tissues sampled with more than 1,000 ESTs. Approximately 40% of identified human genes appear to be associated with basic energy metabolism, cell structure, homeostasis and cell division, 22% with RNA and protein synthesis and processing, and 12% with cell signalling and communication.