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PLoS Comput Biol. 2012 Apr;8(4):e1002492. Epub 2012 Apr 19.
Inference of Genotype-Phenotype Relationships in the Antigenic Evolution of Human Influenza A (H3N2) Viruses.
Steinbr?ck L, McHardy AC.
Source
Department for Algorithmic Bioinformatics, Heinrich Heine University, D?sseldorf, Germany.
Abstract
Distinguishing mutations that determine an organism's phenotype from (near-) neutral 'hitchhikers' is a fundamental challenge in genome research, and is relevant for numerous medical and biotechnological applications. For human influenza viruses, recognizing changes in the antigenic phenotype and a strains' capability to evade pre-existing host immunity is important for the production of efficient vaccines. We have developed a method for inferring 'antigenic trees' for the major viral surface protein hemagglutinin. In the antigenic tree, antigenic weights are assigned to all tree branches, which allows us to resolve the antigenic impact of the associated amino acid changes. Our technique predicted antigenic distances with comparable accuracy to antigenic cartography. Additionally, it identified both known and novel sites, and amino acid changes with antigenic impact in the evolution of influenza A (H3N2) viruses from 1968 to 2003. The technique can also be applied for inference of 'phenotype trees' and genotype-phenotype relationships from other types of pairwise phenotype distances.
PMID:
22532796
[PubMed - in process]
PMCID:
PMC3330098
Free PMC Article
Inference of Genotype-Phenotype Relationships in the Antigenic Evolution of Human Influenza A (H3N2) Viruses.
Steinbr?ck L, McHardy AC.
Source
Department for Algorithmic Bioinformatics, Heinrich Heine University, D?sseldorf, Germany.
Abstract
Distinguishing mutations that determine an organism's phenotype from (near-) neutral 'hitchhikers' is a fundamental challenge in genome research, and is relevant for numerous medical and biotechnological applications. For human influenza viruses, recognizing changes in the antigenic phenotype and a strains' capability to evade pre-existing host immunity is important for the production of efficient vaccines. We have developed a method for inferring 'antigenic trees' for the major viral surface protein hemagglutinin. In the antigenic tree, antigenic weights are assigned to all tree branches, which allows us to resolve the antigenic impact of the associated amino acid changes. Our technique predicted antigenic distances with comparable accuracy to antigenic cartography. Additionally, it identified both known and novel sites, and amino acid changes with antigenic impact in the evolution of influenza A (H3N2) viruses from 1968 to 2003. The technique can also be applied for inference of 'phenotype trees' and genotype-phenotype relationships from other types of pairwise phenotype distances.
PMID:
22532796
[PubMed - in process]
PMCID:
PMC3330098
Free PMC Article
