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Bioinformatics Advance Access published online on November 15, 2005

Bioinformatics, doi:10.1093/bioinformatics/bti781
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© The Author (2005). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received July 27, 2005
Revised October 27, 2005
Accepted November 11, 2005

Discovery note

Highly consistent patterns for inherited human diseases at the molecular level

Núria López-Bigas 1 *, Benjamin J. Blencowe 2, and Christos A. Ouzounis 3

1 Genome Bioinformatics Laboratory, Center for Genomic Regulation, Universitat Pompeu Fabra, Pg. Maritim de la Barceloneta 37-49, E-08003, Barcelona, Spain
2 Banting and Best Department of Medical Research, C. H. Best Institute, University of Toronto, 112 College Street, Toronto, Ontario MG5 1L6, Canada
3 Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK

* To whom correspondence should be addressed.
Núria López-Bigas, E-mail: nuria.lopez{at}crg.es


   Abstract

Over 1600 mammalian genes are known to cause an inherited disorder, when subjected to one or more mutations. These disease genes represent a unique resource for the identification and quantification of relationships between phenotypic attributes of a disease and the molecular features of the associated disease genes, including their ascribed annotated functional classes and expression patterns. Such analyses can provide a more global perspective and a deeper understanding of the probable causes underlying human hereditary diseases. In this perspective and critical view of disease genomics, we present a comparative analysis of genes reported to cause inherited diseases in humans in terms of their causative effects on physiology, their genetics and inheritance modes, the functional processes they are involved in, and their expression profiles across a wide spectrum of tissues. Our analysis reveals that there are more extensive correlations between these attributes of genetic disease genes than previously appreciated. For instance, the functional pattern of genes causing dominant and recessive diseases are markedly different. Also, the function of the genes and their expression correlate with the type of disease they cause when mutated. The results further indicate that a comparative genomics approach for the analysis of genes linked to human genetic diseases will facilitate the elucidation of the underlying molecular and cellular mechanisms.


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