The Xenopus Phenotype Ontology: bridging model organism phenotype data to human health and development.

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.

Download Full-text

How much do model organism phenotypes contribute to the computational identification of human disease genes?

10.1101/2021.12.24.474099 ◽

2021 ◽

Author(s):

Sarah M Alghamdi ◽

Paul N Schofield ◽

Robert Hoehndorf

Keyword(s):

Human Gene ◽

Model Organism ◽

Model Organisms ◽

Disease Genes ◽

Loss Of Function ◽

Relative Contribution ◽

Phenotype Data ◽

Disease Associations ◽

Disease Associated Genes ◽

Human Disease Genes

Computing phenotypic similarity has been shown to be useful in identification of new disease genes and for rare disease diagnostic support. Genotype--phenotype data from orthologous genes in model organisms can compensate for lack of human data to greatly increase genome coverage. Work over the past decade has demonstrated the power of cross-species phenotype comparisons, and several cross-species phenotype ontologies have been developed for this purpose. The relative contribution of different model organisms to identifying disease-associated genes using computational approaches is not yet fully explored. We use methods based on phenotype ontologies to semantically relate phenotypes resulting from loss-of-function mutations in different model organisms to disease-associated phenotypes in humans. Semantic machine learning methods are used to measure how much different model organisms contribute to the identification of known human gene--disease associations. We find that only mouse phenotypes can accurately predict human gene--disease associations. Our work has implications for the future development of integrated phenotype ontologies, as well as for the use of model organism phenotypes in human genetic variant interpretation.

Download Full-text

An automated feeding system for the African killifish reveals effects of dietary restriction on lifespan and allows scalable assessment of associative learning

10.1101/2021.03.30.437790 ◽

2021 ◽

Author(s):

Andrew McKay ◽

Chi-Kuo Hu ◽

Sharon Chen ◽

Claire Nicole Bedbrook ◽

Mike Thielvoldt ◽

...

Keyword(s):

Associative Learning ◽

Dietary Restriction ◽

Model Organism ◽

Video Camera ◽

Food Delivery ◽

Automated System ◽

Model Organisms ◽

Feeding Time ◽

Feeding System ◽

Vertebrate Model

AbstractThe African turquoise killifish is an exciting new vertebrate model for aging studies. A significant challenge for any model organism is control over its diet in space and time. To address this challenge, we created an automated and networked fish feeding system. Our automated feeder is designed to be open-source, easily transferable, and built from widely available components. Compared to manual feeding, our automated system is highly precise and flexible. As a proof-of-concept for the feeding schedule flexibility of these automated feeders, we define a favorable regimen for growth and fertility for the African killifish and a dietary restriction regimen where both feeding time and quantity are reduced. We show that this dietary restriction regimen extends lifespan in males. Moreover, combining our automated feeding system with a video camera, we establish an associative learning assay for the killifish. This learning assay provides an integrative measure of cognitive decline during aging. The ability to precisely control food delivery in the killifish opens new areas to assess lifespan and cognitive behavior dynamics and to screen for dietary interventions and drugs in a high-throughput manner previously impossible with traditional vertebrate model organisms.

Download Full-text

Zebrafish as an animal model for the antiviral RNA interference pathway

Journal of General Virology ◽

10.1099/jgv.0.001552 ◽

2021 ◽

Author(s):

Yanxin Ren ◽

Xueyu Li ◽

Zhonghui Tian ◽

Yan Xu ◽

Ruilin Zhang ◽

...

Keyword(s):

Rna Interference ◽

Sindbis Virus ◽

Rna Virus ◽

Model Organism ◽

Model Organisms ◽

Rnai Pathway ◽

Small Interfering Rnas ◽

Argonaute 2 ◽

Larval Zebrafish ◽

Vertebrate Model

The zebrafish (Danio rerio) possesses evolutionarily conserved innate and adaptive immunity as a mammal and has recently become a popular vertebrate model to exploit infection and immunity. Antiviral RNA interference (RNAi) has been illuminated in various model organisms, including Arabidopsis thaliana, Drosophila melanogaster, Caenorhabditis elegans and mice. However, to date, there is no report on the antiviral RNAi pathway of zebrafish. Here, we have evaluated the possible use of zebrafish to study antiviral RNAi with Sindbis virus (SINV), vesicular stomatitis virus (VSV) and Nodamura virus (NoV). We find that SINVs and NoVs induce the production of virus-derived small interfering RNAs (vsiRNAs), the hallmark of antiviral RNAi, with a preference for a length of 22 nucleotides, after infection of larval zebrafish. Meanwhile, the suppressor of RNAi (VSR) protein, NoV B2, may affect the accumulation of the NoV in zebrafish. Furthermore, taking advantage of the fact that zebrafish argonaute-2 (Ago2) protein is naturally deficient in cleavage compared with that of mammals, we provide evidence that the slicing activity of human Ago2 can virtually inhibit the accumulation of RNA virus after being ectopically expressed in larval zebrafish. Thus, zebrafish may be a unique model organism to study the antiviral RNAi pathway.

Download Full-text

The Vertebrate Taxonomy Ontology: A framework for reasoning across model organism and species phenotypes

10.7287/peerj.preprints.28 ◽

2013 ◽

Author(s):

Peter E Midford ◽

T Alex Dececchi ◽

James P Balhoff ◽

Wasila M Dahdul ◽

Nizar Ibrahim ◽

...

Keyword(s):

Large Scale ◽

Model Organism ◽

Primary Source ◽

Semantic Integration ◽

Biodiversity Data ◽

Phenotypic Data ◽

Creative Commons ◽

Phenotype Data ◽

Large Scale Integration ◽

Scale Integration

Background: A hierarchical taxonomy of organisms is a prerequisite for semantic integration of biodiversity data. Ideally, there would be a single, expansive, authoritative taxonomy that includes extinct and extant taxa, information on synonyms and common names, and monophyletic supraspecific taxa that reflect our current understanding of phylogenetic relationships. Description: As a step towards development of such a resource, and to enable large-scale integration of phenotypic data across the vertebrates, we created the Vertebrate Taxonomy Ontology (VTO), a semantically defined taxonomic resource derived from the integration of existing taxonomic compilations, and freely distributed under a Creative Commons Zero (CC0) public domain waiver. The VTO includes both extant and extinct vertebrates and currently contains 106,927 taxonomic terms, 23 taxonomic ranks, 104,506 synonyms, and 162,132 taxonomic cross-references. Key challenges in constructing the VTO included (1) extracting and merging names, synonyms, and identifiers from heterogeneous sources; (2) replacing subgroups with more authoritative local taxonomies; and (3) automating this process as much as possible to accommodate updates in source taxonomies. Conclusions: The VTO is the primary source of taxonomic information used by the Phenoscape Knowledgebase (http://phenoscape.org/), which integrates genetic and evolutionary phenotype data across both model and nonmodel vertebrates. The VTO is useful for crudely inferring phenotypic changes on the vertebrate tree of life, which enables queries for candidate genes for different episodes in vertebrate evolution.

Download Full-text

The Vertebrate Taxonomy Ontology: A framework for reasoning across model organism and species phenotypes

10.7287/peerj.preprints.28v1 ◽

2013 ◽

Author(s):

Peter E Midford ◽

T Alex Dececchi ◽

James P Balhoff ◽

Wasila M Dahdul ◽

Nizar Ibrahim ◽

...

Keyword(s):

Large Scale ◽

Model Organism ◽

Primary Source ◽

Semantic Integration ◽

Biodiversity Data ◽

Phenotypic Data ◽

Creative Commons ◽

Phenotype Data ◽

Large Scale Integration ◽

Scale Integration

Download Full-text

The rat genome database (RGD) facilitates genomic and phenotypic data integration across multiple species for biomedical research

Mammalian Genome ◽

10.1007/s00335-021-09932-x ◽

2021 ◽

Author(s):

M. L. Kaldunski ◽

J. R. Smith ◽

G. T. Hayman ◽

K. Brodie ◽

J. L. De Pons ◽

...

Keyword(s):

Sequence Similarity ◽

Single Gene ◽

Model Organism ◽

Human Diseases ◽

Model Organisms ◽

Phenotypic Data ◽

Genome Database ◽

Bioinformatic Tools ◽

Multiple Species ◽

Rat Genome

AbstractModel organism research is essential for discovering the mechanisms of human diseases by defining biologically meaningful gene to disease relationships. The Rat Genome Database (RGD, (https://rgd.mcw.edu)) is a cross-species knowledgebase and the premier online resource for rat genetic and physiologic data. This rich resource is enhanced by the inclusion and integration of comparative data for human and mouse, as well as other human disease models including chinchilla, dog, bonobo, pig, 13-lined ground squirrel, green monkey, and naked mole-rat. Functional information has been added to records via the assignment of annotations based on sequence similarity to human, rat, and mouse genes. RGD has also imported well-supported cross-species data from external resources. To enable use of these data, RGD has developed a robust infrastructure of standardized ontologies, data formats, and disease- and species-centric portals, complemented with a suite of innovative tools for discovery and analysis. Using examples of single-gene and polygenic human diseases, we illustrate how data from multiple species can help to identify or confirm a gene as involved in a disease and to identify model organisms that can be studied to understand the pathophysiology of a gene or pathway. The ultimate aim of this report is to demonstrate the utility of RGD not only as the core resource for the rat research community but also as a source of bioinformatic tools to support a wider audience, empowering the search for appropriate models for human afflictions.

Download Full-text

Representing glycophenotypes: semantic unification of glycobiology resources for disease discovery

Database ◽

10.1093/database/baz114 ◽

2019 ◽

Vol 2019 ◽

Cited By ~ 4

Author(s):

Jean-Philippe F Gourdine ◽

Matthew H Brush ◽

Nicole A Vasilevsky ◽

Kent Shefchek ◽

Sebastian Köhler ◽

...

Keyword(s):

Rare Diseases ◽

Semantic Analysis ◽

Model Organism ◽

Disease Diagnosis ◽

Knowledge Bases ◽

Phenotype Ontology ◽

Human Phenotype ◽

Biological Ontologies ◽

Phenotype Data ◽

Structuring Knowledge

Abstract While abnormalities related to carbohydrates (glycans) are frequent for patients with rare and undiagnosed diseases as well as in many common diseases, these glycan-related phenotypes (glycophenotypes) are not well represented in knowledge bases (KBs). If glycan-related diseases were more robustly represented and curated with glycophenotypes, these could be used for molecular phenotyping to help to realize the goals of precision medicine. Diagnosis of rare diseases by computational cross-species comparison of genotype–phenotype data has been facilitated by leveraging ontological representations of clinical phenotypes, using Human Phenotype Ontology (HPO), and model organism ontologies such as Mammalian Phenotype Ontology (MP) in the context of the Monarch Initiative. In this article, we discuss the importance and complexity of glycobiology and review the structure of glycan-related content from existing KBs and biological ontologies. We show how semantically structuring knowledge about the annotation of glycophenotypes could enhance disease diagnosis, and propose a solution to integrate glycophenotypes and related diseases into the Unified Phenotype Ontology (uPheno), HPO, Monarch and other KBs. We encourage the community to practice good identifier hygiene for glycans in support of semantic analysis, and clinicians to add glycomics to their diagnostic analyses of rare diseases.

Download Full-text

In Search of Species-Specific SNPs in a Non-Model Animal (European Bison (Bison bonasus))—Comparison of De Novo and Reference-Based Integrated Pipeline of STACKS Using Genotyping-by-Sequencing (GBS) Data

Animals ◽

10.3390/ani11082226 ◽

2021 ◽

Vol 11 (8) ◽

pp. 2226

Author(s):

Sazia Kunvar ◽

Sylwia Czarnomska ◽

Cino Pertoldi ◽

Małgorzata Tokarska

Keyword(s):

Reference Genome ◽

De Novo ◽

Bos Taurus ◽

Model Organism ◽

Genotyping By Sequencing ◽

Model Organisms ◽

European Bison ◽

Model Animal ◽

Pcr Duplicates ◽

Species Specific

The European bison is a non-model organism; thus, most of its genetic and genomic analyses have been performed using cattle-specific resources, such as BovineSNP50 BeadChip or Illumina Bovine 800 K HD Bead Chip. The problem with non-specific tools is the potential loss of evolutionary diversified information (ascertainment bias) and species-specific markers. Here, we have used a genotyping-by-sequencing (GBS) approach for genotyping 256 samples from the European bison population in Bialowieza Forest (Poland) and performed an analysis using two integrated pipelines of the STACKS software: one is de novo (without reference genome) and the other is a reference pipeline (with reference genome). Moreover, we used a reference pipeline with two different genomes, i.e., Bos taurus and European bison. Genotyping by sequencing (GBS) is a useful tool for SNP genotyping in non-model organisms due to its cost effectiveness. Our results support GBS with a reference pipeline without PCR duplicates as a powerful approach for studying the population structure and genotyping data of non-model organisms. We found more polymorphic markers in the reference pipeline in comparison to the de novo pipeline. The decreased number of SNPs from the de novo pipeline could be due to the extremely low level of heterozygosity in European bison. It has been confirmed that all the de novo/Bos taurus and Bos taurus reference pipeline obtained SNPs were unique and not included in 800 K BovineHD BeadChip.

Download Full-text

Alliance of Genome Resources Portal: unified model organism research platform

Nucleic Acids Research ◽

10.1093/nar/gkz813 ◽

2019 ◽

Vol 48 (D1) ◽

pp. D650-D658 ◽

Cited By ~ 36

Author(s):

◽

Julie Agapite ◽

Laurent-Philippe Albou ◽

Suzi Aleksander ◽

Joanna Argasinska ◽

...

Keyword(s):

Gene Ontology ◽

Model Organism ◽

Model Organisms ◽

Data Types ◽

Primary Model ◽

Genomic Studies ◽

Health And Disease ◽

Extensive Body ◽

Access To Data ◽

Model Organism Databases

Abstract The Alliance of Genome Resources (Alliance) is a consortium of the major model organism databases and the Gene Ontology that is guided by the vision of facilitating exploration of related genes in human and well-studied model organisms by providing a highly integrated and comprehensive platform that enables researchers to leverage the extensive body of genetic and genomic studies in these organisms. Initiated in 2016, the Alliance is building a central portal (www.alliancegenome.org) for access to data for the primary model organisms along with gene ontology data and human data. All data types represented in the Alliance portal (e.g. genomic data and phenotype descriptions) have common data models and workflows for curation. All data are open and freely available via a variety of mechanisms. Long-term plans for the Alliance project include a focus on coverage of additional model organisms including those without dedicated curation communities, and the inclusion of new data types with a particular focus on providing data and tools for the non-model-organism researcher that support enhanced discovery about human health and disease. Here we review current progress and present immediate plans for this new bioinformatics resource.

Download Full-text