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Xenbase (https://www.xenbase.org/), the Xenopus model organism knowledgebase, is a web-accessible resource that integrates the diverse genomic and biological data from research on the laboratory frogs Xenopus laevis and Xenopus tropicalis. The goal of Xenbase is to accelerate discovery and empower Xenopus research, to enhance the impact of Xenopus research data, and to facilitate the dissemination of these data. Xenbase also enhances the value of Xenopus data through high-quality curation, data integration, providing bioinformatics tools optimized for Xenopus experiments, and linking Xenopus data to human data, and other model organisms. Xenbase also plays an indispensable role in making Xenopus data interoperable and accessible to the broader biomedical community in accordance with FAIR principles. Xenbase provides annotated data updates to organizations such as NCBI, UniProtKB, Ensembl, the Gene Ontology consortium, and most recently, the Alliance of Genomic Resources, a common clearing house for data from humans and model organisms. This article provides a brief overview of key and recently added features of Xenbase. New features include processing of Xenopus high-throughput sequencing data from the NCBI Gene Expression Omnibus; curation of anatomical, physiological, and expression phenotypes with the newly created Xenopus Phenotype Ontology; Xenopus Gene Ontology annotations; new anatomical drawings of the Normal Table of Xenopus development; and integration of the latest Xenopus laevis v10.1 genome annotations. Finally, we highlight areas for future development at Xenbase as we continue to support the Xenopus research community.

BackgroundOntologies of precisely defined, controlled vocabularies are essential to curate the results of biological experiments such that the data are machine searchable, can be computationally analyzed, and are interoperable across the biomedical research continuum. There is also an increasing need for methods to interrelate phenotypic data easily and accurately from experiments in animal models with human development and disease.ResultsHere we present the Xenopus Phenotype Ontology (XPO) to annotate phenotypic data from experiments in Xenopus, one of the major vertebrate model organisms used to study gene function in development and disease. The XPO implements design patterns from the Unified Phenotype Ontology (uPheno), and the principles outlined by the Open Biological and Biomedical Ontologies (OBO Foundry) to maximize interoperability with other species and facilitate ongoing ontology management. Constructed in Web Ontology Language (OWL) the XPO combines the existing uPheno library of ontology design patterns with additional terms from the Xenopus Anatomy Ontology (XAO), the Phenotype and Trait Ontology (PATO) and the Gene Ontology (GO). The integration of these different ontologies into the XPO enables rich phenotypic curation, whilst the uPheno bridging axioms allows phenotypic data from Xenopus experiments to be related to phenotype data from other model organisms and human disease. Moreover, the simple post-composed uPheno design patterns facilitate ongoing XPO development as the generation of new terms and classes of terms can be substantially automated.ConclusionsThe XPO serves as an example of current best practices to help overcome many of the inherent challenges in harmonizing phenotype data between different species. The XPO currently consists of approximately 22,000 terms and is being used to curate phenotypes by Xenbase, the Xenopus Model Organism Knowledgebase, forming a standardized corpus of genotype-phenotype data that can be directly related to other uPheno compliant resources.

FLT3 mutations are prevalent in AML patients and confer poor prognosis. Crenolanib, a potent type I pan-FLT3 inhibitor, is effective against both internal tandem duplications and resistance-conferring tyrosine kinase domain mutations. While crenolanib monotherapy has demonstrated clinical benefit in heavily pretreated relapsed/refractory AML patients, responses are transient and relapse eventually occurs. Here, to investigate the mechanisms of crenolanib resistance, we perform whole exome sequencing of AML patient samples before and after crenolanib treatment. Unlike other FLT3 inhibitors, crenolanib does not induce FLT3 secondary mutations, and mutations of the FLT3 gatekeeper residue are infrequent. Instead, mutations of NRAS and IDH2 arise, mostly as FLT3-independent subclones, while TET2 and IDH1 predominantly co-occur with FLT3-mutant clones and are enriched in crenolanib poor-responders. The remaining patients exhibit post-crenolanib expansion of mutations associated with epigenetic regulators, transcription factors, and cohesion factors, suggesting diverse genetic/epigenetic mechanisms of crenolanib resistance. Drug combinations in experimental models restore crenolanib sensitivity. FLT3 is commonly mutated in acute myeloid leukaemia and treatment with FLT3 inhibitors often ends with relapse. Here, the authors perform exome sequencing of samples from patients treated with the FLT3 inhibitor, crenolanib, to show that resistance occurs due to diverse molecular mechanisms, not primarily due to secondary FLT3 mutations.

The implementation of targeted therapies for acute myeloid leukaemia (AML) has been challenging because of the complex mutational patterns within and across patients as well as a dearth of pharmacologic agents for most mutational events. Here we report initial findings from the Beat AML programme on a cohort of 672 tumour specimens collected from 562 patients. We assessed these specimens using whole-exome sequencing, RNA sequencing and analyses of ex vivo drug sensitivity. Our data reveal mutational events that have not previously been detected in AML. We show that the response to drugs is associated with mutational status, including instances of drug sensitivity that are specific to combinatorial mutational events. Integration with RNA sequencing also revealed gene expression signatures, which predict a role for specific gene networks in the drug response. Collectively, we have generated a dataset—accessible through the Beat AML data viewer (Vizome)—that can be leveraged to address clinical, genomic, transcriptomic and functional analyses of the biology of AML. Analyses of samples from patients with acute myeloid leukaemia reveal that drug response is associated with mutational status and gene expression; the generated dataset provides a basis for future clinical and functional studies of this disease.

In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven’t been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics.

Ocular toxoplasmosis is the commonest clinical manifestation of infection with obligate intracellular parasite, Toxoplasma gondii. Active ocular toxoplasmosis is characterized by replication of T. gondii tachyzoites in the retina, with reactive inflammation. The multifunctional retinal pigment epithelium is a key target cell population for T. gondii. Since the global gene expression profile is germane to understanding molecular involvements of retinal pigment epithelial cells in ocular toxoplasmosis, we performed RNA-Sequencing (RNA-Seq) of human cells following infection with T. gondii tachyzoites. Primary cell isolates from eyes of cadaveric donors (n = 3), and the ARPE-19 human retinal pigment epithelial cell line, were infected for 24 h with GT-1 strain T. gondii tachyzoites (multiplicity of infection = 5) or incubated uninfected as control. Total and small RNA were extracted from cells and sequenced on the Illumina NextSeq 500 platform; results were aligned to the human hg19 reference sequence. Multidimensional scaling showed good separation between transcriptomes of infected and uninfected primary cell isolates, which were compared in edgeR software. This differential expression analysis revealed a sizeable response in the total RNA transcriptome—with significantly differentially expressed genes totaling 7,234 (28.9% of assigned transcripts)—but very limited changes in the small RNA transcriptome—totaling 30 (0.35% of assigned transcripts) and including 8 microRNA. Gene ontology and pathway enrichment analyses of differentially expressed total RNA in CAMERA software, identified a strong immunologic transcriptomic signature. We conducted RT-qPCR for 26 immune response-related protein-coding and long non-coding transcripts in epithelial cell isolates from different cadaveric donors (n = 3), extracted by a different isolation protocol but similarly infected with T. gondii, to confirm immunological activity of infected cells. For microRNA, increases in miR-146b and miR-212 were detected by RT-qPCR in 2 and 3 of these independent cell isolates. Biological network analysis in the InnateDB platform, including 735 annotated differentially expressed genes plus 2,046 first-order interactors, identified 10 contextural hubs and 5 subnetworks in the transcriptomic immune response of cells to T. gondii. Our observations provide a solid base for future studies of molecular and cellular interactions between T. gondii and the human retinal pigment epithelium to illuminate mechanisms of ocular toxoplasmosis.

Xenbase is the Xenopus model organism database ( www.xenbase.org ), a web-accessible resource that integrates the diverse genomic and biological data for Xenopus research. It hosts a variety of content including current and archived genomes for both X. laevis and X. tropicalis, bioinformatic tools for comparative genetic analyses including BLAST and GBrowse, annotated Xenopus literature, and catalogs of reagents including antibodies, ORFeome clones, morpholinos, and transgenic lines. Xenbase compiles gene-specific pages which include manually curated gene expression images, functional information including gene ontology (GO), disease associations, and links to other major data sources such as NCBI:Entrez, UniProtKB, and Ensembl. We also maintain the Xenopus Anatomy Ontology (XAO) which describes anatomy throughout embryonic development. This chapter provides a full description of the many features of Xenbase, and offers a guide on how to use various tools to perform a variety of common tasks such as identifying nucleic acid or protein sequences, finding gene expression patterns for specific genes, stages or tissues, identifying literature on a specific gene or tissue, locating useful reagents and downloading our extensive content, including Xenopus gene-Human gene disease mapping files.

Anti-apoptotic BCL-2 family proteins contribute to AML pathogenesis and chemotherapy resistance. Venetoclax (VEN) monotherapy has limited activity in relapsed/refractory AML with a 19% overall response rate. PI3K pathway is constitutively active in 50-80% of AML pts and is tightly linked to the apoptotic pathway. Using clinical, genomic and ex vivo drug sensitivity (IC50) data from 802 AML pts from the multi-institutional Beat AML 1.0 collaboration, we tested the hypothesis that aberrant activation of the PI3K/FLT3 pathway is a mechanism of VEN resistance, with potential utility for identifying pt subsets likely to respond to novel drug combinations. IC50 values were determined by ex vivo drug sensitivity assay, and RNAseq analysis was performed on Illumina HiSeq 2500. To identify pts with activated PI3K signaling, we derived a novel 24-gene expression signature from genes enriched among PIK3CA-mutant tumors, and calculated a PI3K signaling score by applying singular value decomposition to the expression value matrix. Drug response biomarkers were evaluated using a student's t-test without adjustments for multiple comparisons. 45.2% (161/356) of AML pt samples were sensitive to VEN (median IC50, 1.64μM), 70% (190/272) to taselisib (tas), a selective PI3Kα and δ but β-sparing inhibitor (median IC50, 0.06μM) and 95.8% (115/120) to VEN-tas combination (median IC50, 0.02μM). Response to PI3K inhibition varied; 23% (150/659) of AML samples were sensitive to PI3Kδ inhibitor idelalisib (idela; median IC50, 7.23μM) and 63% (337/533) to pan-PI3K inhibitor pictilisib (pic; median IC50, 0.45μM; p=0.03 vs tas). 92% (47/51) of VEN-resistant AML samples tested were sensitive to VEN-tas. VEN sensitivity correlated with high BCL-2 expression, and was greatest among pts with both high BCL-2 and low MCL-1 expression or low PI3K signature. Low expression of PIK3CD (but not PIK3CA/B/G) and the PI3K signature were associated with VEN sensitivity. High BCL-2 expression was associated with resistance to pic, idela and FLT3 inhibitor quizartinib (quiz), with a weaker trend for tas that did not reach statistical significance. Activities of tas, pic and quiz were significantly greater among AML samples with FLT3-ITD mutations, a previously reported VEN resistant subgroup. Expression of activated PI3K signature was higher among AML samples sensitive to pic and quiz. Among 30 AML samples refractory to tas, 18 (60%) were sensitive to VEN and 28 (93%) to VEN-tas. In summary, we identified novel AML subsets characterized by either high gene expression of an activated PI3K gene signature that are refractory to BCL-2 inhibitors or by high BCL-2 expression associated with resistance to PI3K/FLT3 inhibitors. 95.8% of AML pt samples were sensitive to combined inhibition of PI3K and BCL-2. Dual inhibition of PI3K and BCL-2 apoptotic pathways may be a promising combination and should be evaluated in clinical trials. Citation Format: Teiko Sumiyoshi, Chris Bolen, Jeff Tyner, Steve Kurtz, Uma Borate, Shannon McWeeney, Beth Wilmot, Dan Bottomly, Erik Segerdell, Monique Dail, Timothy R. Wilson, Wan-Jen Hong, Jeffrey M. Venstrom. Novel and established acute myeloid leukemia (AML) subsets correlate with ex vivo sensitivity to BCL-2 and PI3K inhibition [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3599.

The Zebrafish Information Network (ZFIN) is a web based community resource that serves as a centralized location for the curation and integration of zebrafish genetic, genomic and developmental data. ZFIN is publicly accessible at http://zfin.org. ZFIN provides an integrated representation of mutants, genes, genetic markers, mapping panels, publications and community contact data. Recent enhancements to ZFIN include: (i) an anatomical dictionary that provides a controlled vocabulary of anatomical terms, grouped by developmental stages, that may be used to annotate and query gene expression data; (ii) gene expression data; (iii) expanded support for genome sequence; (iv) gene annotation using the standardized vocabulary of Gene Ontology (GO) terms that can be used to elucidate relationships between gene products in zebrafish and other organisms; and (v) collaborations with other databases (NCBI, Sanger Institute and SWISS-PROT) to provide standardization and interconnections based on shared curation.

The systematic assignment of gene function to a sequenced genome is one of the outstanding challenges in the post-genomic era. Large-scale systematic mutagenesis screens are important tools for reaching this goal. Here we describe GSD, a software package that allows storage and integration of data from genetic screens. GSD was initially developed for a large-scale F3 mutagenesis screen for developmental mutants of medaka (Oryzias latipes). The version presented here supports a wide range of different screens (mutagenesis, RNAi, morpholinos, transgenesis and others) using different organisms. Data are stored in a relational database and can be made accessible through web interfaces. Researchers can enter data describing their screened embryos: They can track statistics, submit images and describe the resulting phenotypes using a phenotype classification ontology. We developed a fish phenotype classification ontology of medaka and zebrafish for this software package and made it available to the public. In addition, a list of genetic lines resulting from each screen can be generated. These lines (mutant alleles, transgenic lines) can be described and categorized in the same ways as the screened individuals. Raw data from the screen can be integrated to describe these lines. A query module that searches this list can be used to publish the screen results on the Internet. A test version is available at and the software can be downloaded from this site.

Imagine if we could compute across phenotype data as easily as genomic data; this article calls for efforts to realize this vision and discusses the potential benefits., Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility.

Purpose: Chronic neutrophilic leukemia (CNL), chronic myelomonocytic leukemia (CMML), atypical chronic myeloid leukemia (aCML), and unclassified myeloproliferative neoplasms (MPN-U) are a group of heterogeneous disorders belonging to rare entities of myeloproliferative or myelodysplastic/myeloproliferative (MDS/MPN) syndromes. Due to lack of specific molecular markers and the limited understanding of pathogenesis, the treatment of these diseases remains empirical, resulting in poor outcomes. Recently, recurrent mutations in ASXL1, TET2, SRSF2 and cell signaling genes have been identified in these diseases. In this study we aim to analyze the co-occurrence patterns of these gene mutations, as well as the association of different mutations with disease subtypes and treatment outcomes. Methods and results: We performed whole exome sequence and RNA-Seq on primary patient samples. Consistent with previous studies, high frequencies of ASXL1, SRSF2, TET2, SETBP1 and signaling pathway mutations were observed; whereas mutations of MPL, CEBPa, IDH1/2, and TP53 were rare. Further variant allelic frequency analysis demonstrated that mutations of the chromatin modifiers, epigenetic markers and splicing factors are mostly present in the major clones indicating early acquisition of these mutations. In addition, ASXL1/2, splicing factor and signaling pathway mutations co-occur in around 45% of all patients with these mutations, indicating that they drive these diseases in a cooperative manner. RNA-seq analysis demonstrated two major gene expression clusters with high levels of either RAS or JAK-STAT signaling alterations respectively, indicating a potential need for distinct therapeutic targeting of specific subgroups of these diseases. In addition, we observed that 17% of patients have more than one signaling pathway mutation, possibly in distinct subclones, providing rationale for drug combination treatment. Furthermore, we observed that mutations related to RAS signaling pathway are prevalent in CMML; CSF3R and JAK2 mutations are enriched in CNL; whereas, RAS and JAK-STAT pathway double mutations are more frequent in aCML. Similar incidence of ASXL1, splicing factor and epidemics mutations are observed across all these diseases. Conclusions: CNL/aCML/MPN-U/CMML is a group of heterogeneous diseases associated with chromatin modifier, epigenetic, splicing factor and signaling pathway mutations in concomitant manner. We propose future studies of rational drug combinations with agents, targeting epigenetic and splicing factors, together with the appropriate signaling pathway inhibitors. Our study represents a large-scale comprehensive genomic analysis of these diseases, which reveals novel insight into patterns of mutation co-occurrence which could translate into new treatment paradigms for these difficult to treat hematologic malignancies. Citation Format: Haijiao Zhang, Beth Wilmot, Daniel Bottomly, Libbey White, Erik Segerdell, Shannon K. McWeeney, Vishesh Khanna, Angela Rofelty, Sophie Means, Brian Junio, Samantha Savage, Emily Stevens, Kim-Hien Dao, Julia E. Maxson, Jeffrey W. Tyner. Detailed genomic characterization of CNL/aCML/MPN-U/CMML reveals disease subgroups that may benefit from rationally-designed combination therapies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2452. doi:10.1158/1538-7445.AM2017-2452

Background Porifera (sponges) are ancient basal metazoans that lack organs. They provide insight into key evolutionary transitions, such as the emergence of multicellularity and the nervous system. In addition, their ability to synthesize unusual compounds offers potential biotechnical applications. However, much of the knowledge of these organisms has not previously been codified in a machine-readable way using modern web standards. Results The Porifera Ontology is intended as a standardized coding system for sponge anatomical features currently used in systematics. The ontology is available from http://purl.obolibrary.org/obo/poro.owl, or from the project homepage http://porifera-ontology.googlecode.com/. The version referred to in this manuscript is permanently available from http://purl.obolibrary.org/obo/poro/releases/2014-03-06/. Conclusions By standardizing character representations, we hope to facilitate more rapid description and identification of sponge taxa, to allow integration with other evolutionary database systems, and to perform character mapping across the major clades of sponges to better understand the evolution of morphological features. Future applications of the ontology will focus on creating (1) ontology-based species descriptions; (2) taxonomic keys that use the nested terms of the ontology to more quickly facilitate species identifications; and (3) methods to map anatomical characters onto molecular phylogenies of sponges. In addition to modern taxa, the ontology is being extended to include features of fossil taxa.

Development of biocuration processes and guidelines for new data types or projects is a challenging task. Each project finds its way toward defining annotation standards and ensuring data consistency with varying degrees of planning and different tools to support and/or report on consistency. Further, this process may be data type specific even within the context of a single project. This article describes our experiences with eagle-i, a 2-year pilot project to develop a federated network of data repositories in which unpublished, unshared or otherwise ‘invisible’ scientific resources could be inventoried and made accessible to the scientific community. During the course of eagle-i development, the main challenges we experienced related to the difficulty of collecting and curating data while the system and the data model were simultaneously built, and a deficiency and diversity of data management strategies in the laboratories from which the source data was obtained. We discuss our approach to biocuration and the importance of improving information management strategies to the research process, specifically with regard to the inventorying and usage of research resources. Finally, we highlight the commonalities and differences between eagle-i and similar efforts with the hope that our lessons learned will assist other biocuration endeavors. Database URL: www.eagle-i.net

The skeleton is of fundamental importance in research in comparative vertebrate morphology, paleontology, biomechanics, developmental biology, and systematics. Motivated by research questions that require computational access to and comparative reasoning across the diverse skeletal phenotypes of vertebrates, we developed a module of anatomical concepts for the skeletal system, the Vertebrate Skeletal Anatomy Ontology (VSAO), to accommodate and unify the existing skeletal terminologies for the species-specific (mouse, the frog Xenopus, zebrafish) and multispecies (teleost, amphibian) vertebrate anatomy ontologies. Previous differences between these terminologies prevented even simple queries across databases pertaining to vertebrate morphology. This module of upper-level and specific skeletal terms currently includes 223 defined terms and 179 synonyms that integrate skeletal cells, tissues, biological processes, organs (skeletal elements such as bones and cartilages), and subdivisions of the skeletal system. The VSAO is designed to integrate with other ontologies, including the Common Anatomy Reference Ontology (CARO), Gene Ontology (GO), Uberon, and Cell Ontology (CL), and it is freely available to the community to be updated with additional terms required for research. Its structure accommodates anatomical variation among vertebrate species in development, structure, and composition. Annotation of diverse vertebrate phenotypes with this ontology will enable novel inquiries across the full spectrum of phenotypic diversity.

The eagle-i Consortium ("http://www.eagle-i.org/home":www.eagle-i.org/home) comprises nine geographically and ethnically diverse universities across America working to build a federated network of research resources. Biomedical research generates many resources that are rarely shared or published, including: reagents, protocols, instruments, expertise, organisms, training opportunities, software, human studies, and biological specimens. The goal of eagle-i is to improve biomedical research by helping researchers more easily find scientific resources that are difficult to discover, reducing time-consuming and expensive duplication of resources. Now in early development, the system will ultimately expand to include research resources at other universities following the end of the two-year pilot phase. An application ontology is being developed to enable representation of core facility and research lab resources in the eagle-i repository, leading to more effective searches and better linkage between data types. The eagle-i ontology will guide users to valid queries via auto-suggestion, ontology browsing, concept-based search, and synonym expansion. The ontology development effort is being guided by active discussions within the ontology community and brings together relevant preexisting ontologies in a logical framework. Components of the data entry and search interfaces are generated directly from the ontology, which allows rapid change in response to user needs and ontology evolution. Each eagle-i institution will populate and manage a local repository using data collection and curation tools. To enhance the quantity and quality of data, the data tools will take advantage of the ontology to support semi-automated annotation of resources. NIH/NCRR ARRA award U24RR029825.

RP-134

Xenbase (www.xenbase.org), the model organism database for Xenopus laevis and X. (Silurana) tropicalis, is the principal centralized resource of genomic, development data and community information for Xenopus research. Recent improvements include the addition of the literature and interaction tabs to gene catalog pages. New content has been added including a section on gene expression patterns that incorporates image data from the literature, large scale screens and community submissions. Gene expression data are integrated into the gene catalog via an expression tab and is also searchable by multiple criteria using an expression search interface. The gene catalog has grown to contain over 15 000 genes. Collaboration with the European Xenopus Research Center (EXRC) has resulted in a stock center section with data on frog lines supplied by the EXRC. Numerous improvements have also been made to search and navigation. Xenbase is also the source of the Xenopus Anatomical Ontology and the clearinghouse for Xenopus gene nomenclature.

Xenbase (www.xenbase.org) is a model organism database integrating a diverse array of biological and genomic data on the frogs, Xenopus laevis and Xenopus (Silurana) tropicalis. Data is collected from other databases, high-throughput screens and the scientific literature and integrated into a number of database modules covering subjects such as community, literature, gene and genomic analysis. Gene pages are automatically assembled from data piped from the Entrez Gene, Gurdon Institute, JGI, Metazome, MGI, OMIM, PubMed, Unigene, Zfin, commercial suppliers and others. These data are then supplemented with in-house annotation. Xenbase has implemented the Gbrowse genome browser and also provides a BLAST service that allows users to specifically search either laevis or tropicalis DNA or protein targets. A table of Xenopus gene synonyms has been implemented and allows the genome, genes, publications and high-throughput gene expression data to be seamlessly integrated with other Xenopus data and to external database resources, making the wealth of developmental and functional data from the frog available to the broader research community.

Understanding the developmental and genetic underpinnings of particular evolutionary changes has been hindered by inadequate databases of evolutionary anatomy and by the lack of a computational approach to identify underlying candidate genes and regulators. By contrast, model organism studies have been enhanced by ontologies shared among genomic databases. Here, we suggest that evolutionary and genomics databases can be developed to exchange and use information through shared phenotype and anatomy ontologies. This would facilitate computing on evolutionary questions pertaining to the genetic basis of evolutionary change, the genetic and developmental bases of correlated characters and independent evolution, biomedical parallels to evolutionary change, and the ecological and paleontological correlates of particular types of change in genes, gene networks and developmental pathways.