Xenbase: Facilitating the Use of Xenopus to Model Human Disease

At a fundamental level most genes, signaling pathways, biological functions and organ systems are highly conserved between man and all vertebrate species. Leveraging this conservation, researchers are increasingly using the experimental advantages of the amphibian Xenopus to model human disease. The online Xenopus resource, Xenbase, enables human disease modeling by curating the Xenopus literature published in PubMed and integrating these Xenopus data with orthologous human genes, anatomy, and more recently with links to the Online Mendelian Inheritance in Man resource (OMIM) and the Human Disease Ontology (DO). Here we review how Xenbase supports disease modeling and report on a meta-analysis of the published Xenopus research providing an overview of the different types of diseases being modeled in Xenopus and the variety of experimental approaches being used. Text mining of over 50,000 Xenopus research articles imported into Xenbase from PubMed identified approximately 1,000 putative disease- modeling articles. These articles were manually assessed and annotated with disease ontologies, which were then used to classify papers based on disease type. We found that Xenopus is being used to study a diverse array of disease with three main experimental approaches: cell-free egg extracts to study fundamental aspects of cellular and molecular biology, oocytes to study ion transport and channel physiology and embryo experiments focused on congenital diseases. We integrated these data into Xenbase Disease Pages to allow easy navigation to disease information on external databases. Results of this analysis will equip Xenopus researchers with a suite of experimental approaches available to model or dissect a pathological process. Ideally clinicians and basic researchers will use this information to foster collaborations necessary to interrogate the development and treatment of human diseases

Data from: Seasonal temperature, the lunar cycle and diurnal rhythms interact in a combinatorial manner to modulate genomic responses to the environment in a reef-building coral

Rhythms of various periodicities drive cyclical processes in organisms ranging from single cells to the largest mammals on earth, and on scales from cellular physiology to global migrations. Molecular mechanisms that generate circadian behaviours in model organisms are well studied, but longer phase cycles and interactions between cycles with different periodicities are not well understood. Broadcast spawning corals are one of the best examples of an organism integrating inputs from multiple environmental parameters including seasonal temperature, the lunar phase, and hour of the day, to calibrate their annual reproductive event. We present a deep RNA-seq experiment utilizing multiple analyses to differentiate transcriptomic responses modulated by the interactions between the three aforementioned environmental parameters. Acropora millepora was sampled over multiple 24-hour periods throughout a full lunar month and at two seasonal temperatures. Temperature, lunar and diurnal cycles produce distinct transcriptomic responses, with interactions between all three variables identifying a core set of genes. These core genes include mef2, a developmental master regulator, and two hnRNPs, one of which is known to post-transcriptionally interact with mef2 and with biological clock regulating mRNAs. Interactions between diurnal and temperature differences impacted a range of core processes ranging from biological clocks to stress responses. Genes involved with developmental processes and transcriptional regulation were impacted by the lunar phase and seasonal temperature differences. Lastly, there was a diurnal and lunar phase interaction where genes involved with RNA-processing and translational regulation were differentially regulated. These data illustrate the extraordinary levels of transcriptional variation across time in a simple radial cnidarian in response to the environment under normal conditions

The Xenopus phenotype ontology: bridging model organism phenotype data to human health and development

Abstract Background Ontologies 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. Results Here 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. Conclusions The 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