Issue No. 01 - January/February (2012 vol. 9)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TCBB.2011.95
Shahid H. Bokhari , The Ohio State University, Columbus
Laura W. Pomeroy , The Ohio State University, Columbus
Daniel A. Janies , The Ohio State University, Columbus
Prior research developed Reassortment Networks to reconstruct the evolution of segmented viruses under both reassortment and mutation. We report their application to the swine-origin pandemic H1N1 virus (S-OIV). A database of all influenza A viruses, for which complete genome sequences were available in Genbank by October 2009, was created and dynamic programming was used to compute distances between all corresponding segments. A reassortment network was created to obtain the minimum cost evolutionary paths from all viruses to the exemplar S-OIV A/California/04/2009. This analysis took 35 hours on the Cray Extreme Multithreading (XMT) supercomputer, which has special hardware to permit efficient parallelization. Six specific H1N1/H1N2 bottleneck viruses were identified that almost always lie on minimum cost paths to S-OIV. We conjecture that these viruses are crucial to S-OIV evolution and worthy of careful study from a molecular biology viewpoint. In phylogenetics, ancestors are typically medians that have no functional constraints. In our method, ancestors are not inferred, but rather chosen from previously observed viruses along a path of mutation and reassortment leading to the target virus. This specificity and functional constraint render our results actionable for further experiments in vitro and in vivo
Cray XMT, graph theory, influenza, multithreading, networks, pandemic, reassortment, shortest paths, S-OIV, swine flu.
L. W. Pomeroy, D. A. Janies and S. H. Bokhari, "Reassortment Networks and the Evolution of Pandemic H1N1 Swine-Origin Influenza," in IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 9, no. , pp. 214-227, 2011.