Ventilatory Phenotypes among Four Strains of Adult Rats.

Our purpose in this study was to identify different ventilatory phenotypes among four different strains of rats. We examined 114 rats from three in-house, inbred strains and one outbred strain: Brown Norway (BN;n = 26), Dahl salt-sensitive (n = 24), Fawn-hooded Hypertensive (FHH: n = 27), and outbred Sprague-Dawley rats (SD; n = 37). We measured eupneic (room air) breathing and the ventilatory responses to hypoxia (12% O2-88% N2), hypercapnia (7% CO2), and two levels of submaximal exercise. Primary strain differences were between BN and the other strains. BN rats had a relatively attenuated ventilatory response to CO2 (P \u3c 0.001), an accentuated ventilatory response to exercise (P \u3c 0.05), and an accentuated ventilatory roll-off during hypoxia (P \u3c 0.05). Ventilation during hypoxia was lower than other strains, but hyperventilation during hypoxia was equal to the other strains (P \u3e 0.05), indicating that the metabolic rate during hypoxia decreased more in BN rats than in other strains. Another strain difference was in the frequency and timing components of augmented breaths, where FHH rats frequently differed from the other strains, and the BN rats had the longest expiratory time of the augmented breaths (probably secondary to the blunted CO2 sensitivity). These strain differences not only provide insight into physiological mechanisms but also indicate traits (such as CO2 sensitivity) that are genetically regulated. Finally, the data establish a foundation for physiological genomic studies aimed at elucidating the genetics of these ventilatory control mechanisms

Three Ontologies to Define Phenotype Measurement Data

Background: There is an increasing need to integrate phenotype measurement data across studies for both human studies and those involving model organisms. Current practices allow researchers to access only those data involved in a single experiment or multiple experiments utilizing the same protocol. Results: Three ontologies were created: Clinical Measurement Ontology, Measurement Method Ontology and Experimental Condition Ontology. These ontologies provided the framework for integration of rat phenotype data from multiple studies into a single resource as well as facilitated data integration from multiple human epidemiological studies into a centralized repository. Conclusion: An ontology based framework for phenotype measurement data affords the ability to successfully integrate vital phenotype data into critical resources, regardless of underlying technological structures allowing the user to easily query and retrieve data from multiple studies

Lung Injury Pathways: Adenosine Receptor 2B Signaling Limits Development of Ischemic Bronchiolitis Obliterans Organizing Pneumonia

Purpose/Aim of the Study: Adenosine signaling was studied in bronchiolitis obliterans organizing pneumonia (BOOP) resulting from unilateral lung ischemia. Materials and Methods: Ischemia was achieved by either left main pulmonary artery or complete hilar ligation. Sprague–Dawley (SD) rats, Dahl salt sensitive (SS) rats and SS mutant rat strains containing a mutation in the A2B adenosine receptor gene (Adora2b) were studied. Adenosine concentrations were measured in bronchoalveolar lavage (BAL) by HPLC. A2A (A2AAR) and A2B adenosine receptor (A2BAR) mRNA and protein were quantified. Results: Twenty-four hours after unilateral PA ligation, BAL adenosine concentrations from ischemic lungs were increased relative to contralateral lungs in SD rats. A2BAR mRNA and protein concentrations were increased after PA ligation while miR27a, a negatively regulating microRNA, was decreased in ischemic lungs. A2AAR mRNA and protein concentrations remained unchanged following ischemia. A2BAR protein was increased in PA ligated lungs of SS rats after 7 days, and 4 h after complete hilar ligation in SD rats. SS-Adora2b mutants showed a greater extent of BOOP relative to SS rats, and greater inflammatory changes. Conclusion: Increased A2BAR and adenosine following unilateral lung ischemia as well as more BOOP in A2BAR mutant rats implicate a protective role for A2BAR signaling in countering ischemic lung injury

Rat Strain Ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD

BACKGROUND: The Rat Genome Database (RGD) ( http://rgd.mcw.edu/) is the premier site for comprehensive data on the different strains of the laboratory rat (Rattus norvegicus). The strain data are collected from various publications, direct submissions from individual researchers, and rat providers worldwide. Rat strain, substrain designation and nomenclature follow the Guidelines for Nomenclature of Mouse and Rat Strains, instituted by the International Committee on Standardized Genetic Nomenclature for Mice. While symbols and names aid in identifying strains correctly, the flat nature of this information prohibits easy search and retrieval, as well as other data mining functions. In order to improve these functionalities, particularly in ontology-based tools, the Rat Strain Ontology (RS) was developed. RESULTS: The Rat Strain Ontology (RS) reflects the breeding history, parental background, and genetic manipulation of rat strains. This controlled vocabulary organizes strains by type: inbred, outbred, chromosome altered, congenic, mutant and so on. In addition, under the chromosome altered category, strains are organized by chromosome, and further by type of manipulations, such as mutant or congenic. This allows users to easily retrieve strains of interest with modifications in specific genomic regions. The ontology was developed using the Open Biological and Biomedical Ontology (OBO) file format, and is organized on the Directed Acyclic Graph (DAG) structure. Rat Strain Ontology IDs are included as part of the strain report (RS: ######). CONCLUSIONS: As rat researchers are often unaware of the number of substrains or altered strains within a breeding line, this vocabulary now provides an easy way to retrieve all substrains and accompanying information. Its usefulness is particularly evident in tools such as the PhenoMiner at RGD, where users can now easily retrieve phenotype measurement data for related strains, strains with similar backgrounds or those with similar introgressed regions. This controlled vocabulary also allows better retrieval and filtering for QTLs and in genomic tools such as the GViewer. The Rat Strain Ontology has been incorporated into the RGD Ontology Browser ( http://rgd.mcw.edu/rgdweb/ontology/view.html?acc_id=RS:0000457#s) and is available through the National Center for Biomedical Ontology ( http://bioportal.bioontology.org/ontologies/1150) or the RGD ftp site ( ftp://rgd.mcw.edu/pub/ontology/rat_strain/)

A Revamped Rat Reference Genome Improves the Discovery of Genetic Diversity in Laboratory Rats

The seventh iteration of the reference genome assembly for Rattus norvegicus-mRatBN7.2-corrects numerous misplaced segments and reduces base-level errors by approximately 9-fold and increases contiguity by 290-fold compared with its predecessor. Gene annotations are now more complete, improving the mapping precision of genomic, transcriptomic, and proteomics datasets. We jointly analyzed 163 short-read whole-genome sequencing datasets representing 120 laboratory rat strains and substrains using mRatBN7.2. We defined ∼20.0 million sequence variations, of which 18,700 are predicted to potentially impact the function of 6,677 genes. We also generated a new rat genetic map from 1,893 heterogeneous stock rats and annotated transcription start sites and alternative polyadenylation sites. The mRatBN7.2 assembly, along with the extensive analysis of genomic variations among rat strains, enhances our understanding of the rat genome, providing researchers with an expanded resource for studies involving rats

The Gene Ontology knowledgebase in 2023

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project