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Predicted rat interactome database and gene set linkage analysis

Rattus norvegicus, or the rat, has been widely used as animal models for a diversity of human diseases in the last 150 years. The rat, as a disease model, has the advantage of relatively large body size and highly similar physiology to humans. In drug discovery, rat models are routinely used in drug...

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Autores principales: Tao, Yu-Tian, Ding, Xiao-Bao, Jin, Jie, Zhang, Hai-Bo, Guo, Wen-Ping, Ruan, Li, Yang, Qiao-Lei, Chen, Peng-Cheng, Yao, Heng, Chen, Xin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7678787/
https://www.ncbi.nlm.nih.gov/pubmed/33216897
http://dx.doi.org/10.1093/database/baaa086
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author Tao, Yu-Tian
Ding, Xiao-Bao
Jin, Jie
Zhang, Hai-Bo
Guo, Wen-Ping
Ruan, Li
Yang, Qiao-Lei
Chen, Peng-Cheng
Yao, Heng
Chen, Xin
author_facet Tao, Yu-Tian
Ding, Xiao-Bao
Jin, Jie
Zhang, Hai-Bo
Guo, Wen-Ping
Ruan, Li
Yang, Qiao-Lei
Chen, Peng-Cheng
Yao, Heng
Chen, Xin
author_sort Tao, Yu-Tian
collection PubMed
description Rattus norvegicus, or the rat, has been widely used as animal models for a diversity of human diseases in the last 150 years. The rat, as a disease model, has the advantage of relatively large body size and highly similar physiology to humans. In drug discovery, rat models are routinely used in drug efficacy and toxicity assessments. To facilitate molecular pharmacology studies in rats, we present the predicted rat interactome database (PRID), which is a database of high-quality predicted functional gene interactions with balanced sensitivity and specificity. PRID integrates functional gene association data from 10 public databases and infers 305 939 putative functional associations, which are expected to include 13.02% of all rat protein interactions, and 52.59% of these function associations may represent protein interactions. This set of functional interactions may not only facilitate hypothesis formulation in molecular mechanism studies, but also serve as a reference interactome for users to perform gene set linkage analysis (GSLA), which is a web-based tool to infer the potential functional impacts of a set of changed genes observed in transcriptomics analyses. In a case study, we show that GSLA based on PRID may provide more precise and informative annotations for investigators to understand the physiological mechanisms underlying a phenotype and lead investigators to testable hypotheses for further studies. Widely used functional annotation tools such as Gene Ontology (GO) analysis, and Database for Annotation, Visualization and Integrated Discovery (DAVID) did not provide similar insights. Database URL: http://rat.biomedtzc.cn
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spelling pubmed-76787872020-11-25 Predicted rat interactome database and gene set linkage analysis Tao, Yu-Tian Ding, Xiao-Bao Jin, Jie Zhang, Hai-Bo Guo, Wen-Ping Ruan, Li Yang, Qiao-Lei Chen, Peng-Cheng Yao, Heng Chen, Xin Database (Oxford) Original Article Rattus norvegicus, or the rat, has been widely used as animal models for a diversity of human diseases in the last 150 years. The rat, as a disease model, has the advantage of relatively large body size and highly similar physiology to humans. In drug discovery, rat models are routinely used in drug efficacy and toxicity assessments. To facilitate molecular pharmacology studies in rats, we present the predicted rat interactome database (PRID), which is a database of high-quality predicted functional gene interactions with balanced sensitivity and specificity. PRID integrates functional gene association data from 10 public databases and infers 305 939 putative functional associations, which are expected to include 13.02% of all rat protein interactions, and 52.59% of these function associations may represent protein interactions. This set of functional interactions may not only facilitate hypothesis formulation in molecular mechanism studies, but also serve as a reference interactome for users to perform gene set linkage analysis (GSLA), which is a web-based tool to infer the potential functional impacts of a set of changed genes observed in transcriptomics analyses. In a case study, we show that GSLA based on PRID may provide more precise and informative annotations for investigators to understand the physiological mechanisms underlying a phenotype and lead investigators to testable hypotheses for further studies. Widely used functional annotation tools such as Gene Ontology (GO) analysis, and Database for Annotation, Visualization and Integrated Discovery (DAVID) did not provide similar insights. Database URL: http://rat.biomedtzc.cn Oxford University Press 2020-11-20 /pmc/articles/PMC7678787/ /pubmed/33216897 http://dx.doi.org/10.1093/database/baaa086 Text en © The Author(s) 2020. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Tao, Yu-Tian
Ding, Xiao-Bao
Jin, Jie
Zhang, Hai-Bo
Guo, Wen-Ping
Ruan, Li
Yang, Qiao-Lei
Chen, Peng-Cheng
Yao, Heng
Chen, Xin
Predicted rat interactome database and gene set linkage analysis
title Predicted rat interactome database and gene set linkage analysis
title_full Predicted rat interactome database and gene set linkage analysis
title_fullStr Predicted rat interactome database and gene set linkage analysis
title_full_unstemmed Predicted rat interactome database and gene set linkage analysis
title_short Predicted rat interactome database and gene set linkage analysis
title_sort predicted rat interactome database and gene set linkage analysis
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7678787/
https://www.ncbi.nlm.nih.gov/pubmed/33216897
http://dx.doi.org/10.1093/database/baaa086
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