A Computational Genotyping System for Improved Influenza Surveillance

DESCRIPTION (provided by applicant): The influenza A virus causes moderate to severe epidemics annually and catastrophic pandemics sporadically. Identifying genetic changes to the viral genome and subsequently determining corresponding genotypes are crucial steps in influenza surveillance. Because of the unique structure of influenza A viral genome, which consists of eight segregated gene segments, the genotyping methods developed for other viruses cannot be applied to the influenza virus. As a result, a complete knowledge of influenza A viral genotypes remains unavailable. The long-term goal of this research is to better understand how influenza A viruses evolve, spread, and cause disease, so that enhanced diagnoses and ultimately control strategies for influenza epidemics and pandemics can be developed. The objective in this project is to develop a computational genotyping system to improve influenza surveillance through early detection of influenza A viral genotypes. The proposed research will be accomplished by pursuing the following specific aims: 1. Develop novel statistical methods and computer software for the genotyping analysis of influenza A viruses. A Markov chain-based method will be developed to represent influenza A virus sequences, and a mixture model-based clustering method will be developed to identify genotypes of influenza A viruses. The performance of the new genotyping method will be evaluated in comparison with various existing methods. New methods will be implemented into open source software for influenza A viral genotyping analysis. 2. Identify genotypes of all known influenza A viruses and infer evolutionary relationships among influenza A viral genotypes. Comprehensive genotyping and genome reassortment (i.e., reshuffling of gene segments from different viral strains) analyses will be performed for all known influenza A viral genomes, using the newly developed methods, as well as conventional methods. Phylogenetic tree approaches and phylogenetic network approaches will be used to infer evolutionary relationships among influenza A genotypes. 3. Develop a web-based genotyping system for accurate and sensitive prediction of newly emerging influenza A viral genotypes. A consolidated genotype database for influenza A viruses will be created, and the database will be integrated with the developed genotyping methods into a web-based system for rapid detection of new influenza A viral genotypes. User-friendly web interfaces will be developed to facilitate use of the genotyping tool, provide efficient access to the database, and disseminate research products. This research is potentially innovative, because of the novelty of the genotyping methods as well as the originality of the genotype database and the online genotyping system. The proposed research is significant, because the products generated in this project will be made publically available, including a genotype database and a genotype prediction system for influenza A viruses. With the genotyping database system, newly emerging influenza A viral genotypes can be identified in a timely and cost-effective manner.