Time-series oligonucleotide count to assign antiviral siRNAs with long utility fit in the big data era

Abstract

Oligonucleotides are key elements of nucleic acid therapeutics such as small interfering RNAs (siRNAs). Influenza and Ebolaviruses are zoonotic RNA viruses mutating very rapidly, and their sequence changes must be characterized intensively to design therapeutic oligonucleotides with long utility. Focusing on a total of 182 experimentally validated siRNAs for influenza A, B and Ebolaviruses compiled by the siRNA database, we conducted time-series analyses of occurrences of siRNA targets in these viral genomes. Reflecting their high mutation rates, occurrences of target oligonucleotides evidently fluctuate in viral populations and often disappear. Time-series analysis of the one-base changed sequences derived from each original target identified the oligonucleotide that shows a compensatory increase and will potentially become the 'awaiting-Type oligonucleotide'; the combined use of this oligonucleotide with the original can provide therapeutics with long utility. This strategy is also useful for assigning diagnostic reverse transcription-PCR primers with long utility.