Reassortment networks and the evolution of pandemic H1N1 swine-origin influenza

Shahid H. Bokhari*, Laura W. Pomeroy, Daniel A. Janies

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

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

Original languageEnglish
Article number5871586
Pages (from-to)214-227
Number of pages14
JournalIEEE/ACM Transactions on Computational Biology and Bioinformatics
Volume9
Issue number1
DOIs
Publication statusPublished - 2012
Externally publishedYes

Bibliographical note

Funding Information:
The authors wish to thank Jeffrey Parvin for his encouragement of this research. They also thank David Mizell and Kristyn Maschhoff for providing access to “Egret,” the XMT at Cray Inc. and for assistance with performance and programming issues on the machine. All of the reassortment networks discussed in this paper were run on “Cougar,” the XMT at the Center for Adaptive Supercomputing Software (CASS), Pacific Northwest Laboratory (PNL). We thank John Feo and Andrés Marquez for their support and Michael Peterson for his efforts in assuring uninterrupted access to the machine. The lavish computational resources provided by Ohio Supercomputer Center (OSC) and by the Department of Biomedical Informatics (BMI) at The Ohio State University are gratefully acknowledged. Hideaki Kikuchi provided valuable advice on the BMI “Bucki” cluster. We thank Ambreen Bokhari for her help with the figures. We are grateful to Saniyah Bokhari and Saba Bokhari for their careful editing of the manuscript. This work was supported by Pacific Northwest National Laboratory [Contract 97499 to Shahid H. Bokhari]; Ohio Supercomputer Center [allocation of time to Shahid H. Bokhari and Daniel A. Janies]; US Army Research Laboratory and Office [Grants W911NF-05-1-0271 and HR-0011-09-2-009 to Daniel A. Janies].

Keywords

  • Cray XMT
  • graph theory
  • influenza
  • multithreading
  • networks
  • pandemic
  • reassortment
  • S-OIV
  • shortest paths
  • swine flu

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