Abstract
A computational approach for identification and assessment of genomic sequence variability (GeneSV) is described. For a given nucleotide sequence, GeneSV collects information about the permissible nucleotide variability (changes that potentially preserve function) observed in corresponding regions in genomic sequences, and combines it with conservation/variability results from protein sequence and structure-based analyses of evaluated protein coding regions. GeneSV was used to predict effects (functional vs. non-functional) of 37 amino acid substitutions on the NS5 polymerase (RdRp) of dengue virus type 2 (DENV-2), 36 of which are not observed in any publicly available DENV-2 sequence. 32 novel mutants with single amino acid substitutions in the RdRp were generated using a DENV-2 reverse genetics system. In 81% (26 of 32) of predictions tested, GeneSV correctly predicted viability of introduced mutations. In 4 of 5 (80%) mutants with double amino acid substitutions proximal in structure to one another GeneSV was also correct in its predictions. Predictive capabilities of the developed system were illustrated on dengue RNA virus, but described in the manuscript a general approach to characterize real or theoretically possible variations in genomic and protein sequences can be applied to any organism.