OrthoDisease


21565935	OrthoDisease: tracking disease gene orthologs across 100 species. [PMID: 21565935] Forslund K, Schreiber F, Thanintorn N, Sonnhammer EL. Abstract Orthology is one of the most important tools available to modern biology, as it allows making inferences from easily studied model systems to much less tractable systems of interest, such as ourselves. This becomes important not least in the study of genetic diseases. We here review work on the orthology of disease-associated genes and also present an updated version of the InParanoid-based disease orthology database and web site OrthoDisease, with 14-fold increased species coverage since the previous version. Using this resource, we survey the taxonomic distribution of orthologs of human genes involved in different disease categories. The hypothesis that paralogs can mask the effect of deleterious mutations predicts that known heritable disease genes should have fewer close paralogs. We found large-scale support for this hypothesis as significantly fewer duplications were observed for disease genes in the OrthoDisease ortholog groups. Brief Bioinform. 2011:12(5) \| 10 Citations (from Europe PMC, 2025-04-05)
15241792	OrthoDisease: a database of human disease orthologs. [PMID: 15241792] O'Brien KP, Westerlund I, Sonnhammer EL. Abstract One of the greatest promises of genome sequencing projects is to further the understanding of human diseases and to develop new therapies. Model organism genomes have been sequenced in parallel to human genomes to provide effective tools for the investigation of human gene function. Many of their genes share a common ancestry and function with human genes, and this is particularly true for orthologous genes. Here we present OrthoDisease, a comprehensive database of model organism genes that are orthologous to human disease genes. OrthoDisease was constructed by applying the Inparanoid ortholog detection algorithm to disease genes derived from the Online Mendelian Inheritance in Man database (OMIM). Pairwise whole genome/proteome comparisons between Homo sapiens and six other organisms were performed to identify ortholog clusters. OMIM numbers were extracted from the OMIM Morbid Map and were converted to gene sequences using the Locuslink mim2loc and loc2acc tables. These were mapped to Inparanoid ortholog clusters using Blast. The number of ortholog clusters in OrthoDisease with each respective species is currently: M. musculus, 1,354; D. melanogaster, 724; C. elegans, 533; A. thaliana, 398; S. cerevisiae, 290; and E. coli, 153. The database is accessible online at http://orthodisease.cgb.ki.se, and can be searched with disease or protein names. The web interface presents all ortholog clusters that include a selected disease gene. A capability to download the entire dataset is also provided. Copyright 2004 Wiley-Liss, Inc. Hum Mutat. 2004:24(2) \| 37 Citations (from Europe PMC, 2025-04-05)

OrthoDisease: tracking disease gene orthologs across 100 species. [PMID: 21565935]

Forslund K, Schreiber F, Thanintorn N, Sonnhammer EL.

Orthology is one of the most important tools available to modern biology, as it allows making inferences from easily studied model systems to much less tractable systems of interest, such as ourselves. This becomes important not least in the study of genetic diseases. We here review work on the orthology of disease-associated genes and also present an updated version of the InParanoid-based disease orthology database and web site OrthoDisease, with 14-fold increased species coverage since the previous version. Using this resource, we survey the taxonomic distribution of orthologs of human genes involved in different disease categories. The hypothesis that paralogs can mask the effect of deleterious mutations predicts that known heritable disease genes should have fewer close paralogs. We found large-scale support for this hypothesis as significantly fewer duplications were observed for disease genes in the OrthoDisease ortholog groups.

Brief Bioinform. 2011:12(5) | 10 Citations (from Europe PMC, 2025-04-05)

OrthoDisease: a database of human disease orthologs. [PMID: 15241792]

O'Brien KP, Westerlund I, Sonnhammer EL.

Abstract

One of the greatest promises of genome sequencing projects is to further the understanding of human diseases and to develop new therapies. Model organism genomes have been sequenced in parallel to human genomes to provide effective tools for the investigation of human gene function. Many of their genes share a common ancestry and function with human genes, and this is particularly true for orthologous genes. Here we present OrthoDisease, a comprehensive database of model organism genes that are orthologous to human disease genes. OrthoDisease was constructed by applying the Inparanoid ortholog detection algorithm to disease genes derived from the Online Mendelian Inheritance in Man database (OMIM). Pairwise whole genome/proteome comparisons between Homo sapiens and six other organisms were performed to identify ortholog clusters. OMIM numbers were extracted from the OMIM Morbid Map and were converted to gene sequences using the Locuslink mim2loc and loc2acc tables. These were mapped to Inparanoid ortholog clusters using Blast. The number of ortholog clusters in OrthoDisease with each respective species is currently: M. musculus, 1,354; D. melanogaster, 724; C. elegans, 533; A. thaliana, 398; S. cerevisiae, 290; and E. coli, 153. The database is accessible online at http://orthodisease.cgb.ki.se, and can be searched with disease or protein names. The web interface presents all ortholog clusters that include a selected disease gene. A capability to download the entire dataset is also provided. Copyright 2004 Wiley-Liss, Inc.

Hum Mutat. 2004:24(2) | 37 Citations (from Europe PMC, 2025-04-05)

URL:	http://orthodisease.cgb.ki.se
Full name:	Tracking Disease Gene Orthologs Across 100 Species
Description:	OrthoDisease, a comprehensive database of model organism genes that are orthologous to human disease genes. OrthoDisease was constructed by applying the Inparanoid ortholog detection algorithm to disease genes derived from the Online Mendelian Inheritance in Man database (OMIM). Pairwise whole genome/proteome comparisons between Homo sapiens and six other organisms were performed to identify ortholog clusters.
Year founded:	2004
Last update:	2011-02-01
Version:	v2.0
Accessibility:	Accessible
Country/Region:	Sweden

Data type:	Protein
Data object:
Database category:	Health and medicine
Major species:	Arabidopsis thaliana Caenorhabditis elegans Drosophila melanogaster Escherichia coli Homo sapiens Mus musculus Saccharomyces cerevisiae
Keywords:	OMIM ortholog

University/Institution:	Stockholm University
Address:	Albanova, 10691 Stockholm, Sweden
City:	Stockholm
Province/State:
Country/Region:	Sweden
Contact name (PI/Team):	Kevin P.O’Brien
Contact email (PI/Helpdesk):	kevobr@mbox.ki.se

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Database Commons a catalog of worldwide biological databases