Literature DB >> 25632109

PhenoMiner: a quantitative phenotype database for the laboratory rat, Rattus norvegicus. Application in hypertension and renal disease.

Shur-Jen Wang1, Stanley J F Laulederkind2, G Thomas Hayman2, Victoria Petri2, Weisong Liu2, Jennifer R Smith2, Rajni Nigam2, Melinda R Dwinell2, Mary Shimoyama3.   

Abstract

Rats have been used extensively as animal models to study physiological and pathological processes involved in human diseases. Numerous rat strains have been selectively bred for certain biological traits related to specific medical interests. Recently, the Rat Genome Database (http://rgd.mcw.edu) has initiated the PhenoMiner project to integrate quantitative phenotype data from the PhysGen Program for Genomic Applications and the National BioResource Project in Japan as well as manual annotations from biomedical literature. PhenoMiner, the search engine for these integrated phenotype data, facilitates mining of data sets across studies by searching the database with a combination of terms from four different ontologies/vocabularies (Rat Strain Ontology, Clinical Measurement Ontology, Measurement Method Ontology and Experimental Condition Ontology). In this study, salt-induced hypertension was used as a model to retrieve blood pressure records of Brown Norway, Fawn-Hooded Hypertensive (FHH) and Dahl salt-sensitive (SS) rat strains. The records from these three strains served as a basis for comparing records from consomic/congenic/mutant offspring derived from them. We examined the cardiovascular and renal phenotypes of consomics derived from FHH and SS, and of SS congenics and mutants. The availability of quantitative records across laboratories in one database, such as these provided by PhenoMiner, can empower researchers to make the best use of publicly available data. Database URL: http://rgd.mcw.edu.
© The Author(s) 2015. Published by Oxford University Press.

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Year:  2015        PMID: 25632109      PMCID: PMC4309021          DOI: 10.1093/database/bau128

Source DB:  PubMed          Journal:  Database (Oxford)        ISSN: 1758-0463            Impact factor:   3.451


  25 in total

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Authors:  Richard J Roman; Kimberly M Hoagland; Bernardo Lopez; Anne E Kwitek; Michael R Garrett; John P Rapp; Josef Lazar; Howard J Jacob; Albert Sarkis
Journal:  Am J Physiol Renal Physiol       Date:  2006-01-05

2.  Multiple blood pressure QTL on rat chromosome 1 defined by Dahl rat congenic strains.

Authors:  Y Saad; M R Garrett; J P Rapp
Journal:  Physiol Genomics       Date:  2001-01-19       Impact factor: 3.107

3.  Modularization and epistatic hierarchy determine homeostatic actions of multiple blood pressure quantitative trait loci.

Authors:  Cristina Chauvet; Kimberley Crespo; Annie Ménard; Julie Roy; Alan Y Deng
Journal:  Hum Mol Genet       Date:  2013-06-28       Impact factor: 6.150

4.  Chromosome substitution reveals the genetic basis of Dahl salt-sensitive hypertension and renal disease.

Authors:  David L Mattson; Melinda R Dwinell; Andrew S Greene; Anne E Kwitek; Richard J Roman; Howard J Jacob; Allen W Cowley
Journal:  Am J Physiol Renal Physiol       Date:  2008-07-23

5.  Three ontologies to define phenotype measurement data.

Authors:  Mary Shimoyama; Rajni Nigam; Leslie Sanders McIntosh; Rakesh Nagarajan; Treva Rice; D C Rao; Melinda R Dwinell
Journal:  Front Genet       Date:  2012-05-28       Impact factor: 4.599

6.  Identifying multiple causative genes at a single GWAS locus.

Authors:  Michael J Flister; Shirng-Wern Tsaih; Caitlin C O'Meara; Bradley Endres; Matthew J Hoffman; Aron M Geurts; Melinda R Dwinell; Jozef Lazar; Howard J Jacob; Carol Moreno
Journal:  Genome Res       Date:  2013-09-04       Impact factor: 9.043

7.  Mycophenolate mofetil prevents high-fat diet-induced hypertension and renal glomerular injury in Dahl SS rats.

Authors:  Frank T Spradley; Carmen De Miguel; Janet Hobbs; David M Pollock; Jennifer S Pollock
Journal:  Physiol Rep       Date:  2013-11-05

8.  The clinical measurement, measurement method and experimental condition ontologies: expansion, improvements and new applications.

Authors:  Jennifer R Smith; Carissa A Park; Rajni Nigam; Stanley Jf Laulederkind; G Thomas Hayman; Shur-Jen Wang; Timothy F Lowry; Victoria Petri; Jeff De Pons; Marek Tutaj; Weisong Liu; Elizabeth A Worthey; Mary Shimoyama; Melinda R Dwinell
Journal:  J Biomed Semantics       Date:  2013-10-08

9.  Role of Nox4 in murine models of kidney disease.

Authors:  Andrea Babelova; Despina Avaniadi; Oliver Jung; Christian Fork; Janet Beckmann; Judith Kosowski; Norbert Weissmann; Narayana Anilkumar; Ajay M Shah; Liliana Schaefer; Katrin Schröder; Ralf P Brandes
Journal:  Free Radic Biol Med       Date:  2012-06-27       Impact factor: 7.376

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

Authors:  Rajni Nigam; Diane H Munzenmaier; Elizabeth A Worthey; Melinda R Dwinell; Mary Shimoyama; Howard J Jacob
Journal:  J Biomed Semantics       Date:  2013-11-22
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  5 in total

1.  Comprehensive coverage of cardiovascular disease data in the disease portals at the Rat Genome Database.

Authors:  Shur-Jen Wang; Stanley J F Laulederkind; G Thomas Hayman; Victoria Petri; Jennifer R Smith; Marek Tutaj; Rajni Nigam; Melinda R Dwinell; Mary Shimoyama
Journal:  Physiol Genomics       Date:  2016-06-10       Impact factor: 3.107

Review 2.  From engineering to editing the rat genome.

Authors:  Stephen Meek; Tomoji Mashimo; Tom Burdon
Journal:  Mamm Genome       Date:  2017-07-27       Impact factor: 2.957

Review 3.  Rat Genome and Model Resources.

Authors:  Mary Shimoyama; Jennifer R Smith; Elizabeth Bryda; Takashi Kuramoto; Laura Saba; Melinda Dwinell
Journal:  ILAR J       Date:  2017-07-01

4.  Integrated curation and data mining for disease and phenotype models at the Rat Genome Database.

Authors:  Shur-Jen Wang; Stanley J F Laulederkind; Yiqing Zhao; G Thomas Hayman; Jennifer R Smith; Monika Tutaj; Jyothi Thota; Marek A Tutaj; Matthew J Hoffman; Elizabeth R Bolton; Jeffrey De Pons; Melinda R Dwinell; Mary Shimoyama
Journal:  Database (Oxford)       Date:  2019-01-01       Impact factor: 3.451

5.  Disease, Models, Variants and Altered Pathways-Journeying RGD Through the Magnifying Glass.

Authors:  Victoria Petri; G Thomas Hayman; Marek Tutaj; Jennifer R Smith; Stan Laulederkind; Shur-Jen Wang; Rajni Nigam; Jeff De Pons; Mary Shimoyama; Melinda R Dwinell
Journal:  Comput Struct Biotechnol J       Date:  2015-11-26       Impact factor: 7.271

  5 in total

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