Title
Genome-wide analysis of human disease alleles reveals that their locations are correlated in paralogous proteins.
Abstract
The millions of mutations and polymorphisms that occur in human populations are potential predictors of disease, of our reactions to drugs, of predisposition to microbial infections, and of age-related conditions such as impaired brain and cardiovascular functions. However, predicting the phenotypic consequences and eventual clinical significance of a sequence variant is not an easy task. Computational approaches have found perturbation of conserved amino acids to be a useful criterion for identifying variants likely to have phenotypic consequences. To our knowledge, however, no study to date has explored the potential of variants that occur at homologous positions within paralogous human proteins as a means of identifying polymorphisms with likely phenotypic consequences. In order to investigate the potential of this approach, we have assembled a unique collection of known disease-causing variants from OMIM and the Human Genome Mutation Database (HGMD) and used them to identify and characterize pairs of sequence variants that occur at homologous positions within paralogous human proteins. Our analyses demonstrate that the locations of variants are correlated in paralogous proteins. Moreover, if one member of a variant-pair is disease-causing, its partner is likely to be disease-causing as well. Thus, information about variant-pairs can be used to identify potentially disease-causing variants, extend existing procedures for polymorphism prioritization, and provide a suite of candidates for further diagnostic and therapeutic purposes.
Year
DOI
Venue
2008
10.1371/journal.pcbi.1000218
PLOS COMPUTATIONAL BIOLOGY
Keywords
Field
DocType
sequence alignment,computational biology,linkage disequilibrium,proteins,amino acid,genetic markers,polymorphism,alleles,phenotype,gene frequency,human genome,amino acid sequence
Sequence alignment,Genome,Linkage disequilibrium,Allele,Biology,Allele frequency,Human genome,Bioinformatics,Genetics,Genetic marker,Mutation
Journal
Volume
Issue
ISSN
4
11
1553-7358
Citations 
PageRank 
References 
1
0.40
4
Authors
7
Name
Order
Citations
PageRank
Mark Yandell1394.53
Barry Moore231.91
Fidel Salas3238.63
Chris Mungall431636.22
Andrew MacBride510.40
Charles White610.40
Martin G Reese724360.95