skip to main content

SciTech ConnectSciTech Connect

Title: Characterization of genetic variability of Venezuelan equine encephalitis viruses

Venezuelan equine encephalitis virus (VEEV) is a mosquito-borne alphavirus that has caused large outbreaks of severe illness in both horses and humans. New approaches are needed to rapidly infer the origin of a newly discovered VEEV strain, estimate its equine amplification and resultant epidemic potential, and predict human virulence phenotype. We performed whole genome single nucleotide polymorphism (SNP) analysis of all available VEE antigenic complex genomes, verified that a SNP-based phylogeny accurately captured the features of a phylogenetic tree based on multiple sequence alignment, and developed a high resolution genome-wide SNP microarray. We used the microarray to analyze a broad panel of VEEV isolates, found excellent concordance between array- and sequence-based SNP calls, genotyped unsequenced isolates, and placed them on a phylogeny with sequenced genomes. The microarray successfully genotyped VEEV directly from tissue samples of an infected mouse, bypassing the need for viral isolation, culture and genomic sequencing. Lastly, we identified genomic variants associated with serotypes and host species, revealing a complex relationship between genotype and phenotype.
 [1] ;  [1] ;  [1] ;  [1] ;  [2] ;  [2] ;  [2] ;  [1]
  1. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
  2. Univ. of Texas, Galveston, TX (United States)
Publication Date:
OSTI Identifier:
Report Number(s):
Journal ID: ISSN 1932-6203
Grant/Contract Number:
Accepted Manuscript
Journal Name:
Additional Journal Information:
Journal Volume: 11; Journal Issue: 4; Journal ID: ISSN 1932-6203
Public Library of Science
Research Org:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
Sponsoring Org:
Country of Publication:
United States
59 BASIC BIOLOGICAL SCIENCES Venezuelan equine encephalitis virus; microarray; single nucleotide polymorphism; genotype; phenotype; pathogen; phylogenetic analysis; genome complexity; decision trees; mammalian genomics; microarrays; sequence alignment; multiple alignment calculation; genome analysis