Abstract
An Influenza Probe Set (IPS) consisting in 1,249 9-mer probes for genomic fingerprinting of closely and distantly related Influenza Virus strains was designed and tested in silico. The IPS was derived from alignments of Influenza genomes. The RNA segments of 5,133 influenza strains having diverse degree of relatedness were concatenated and aligned. After alignment, 9-mer sites having high Shannon entropy were searched. Additional criteria such as: G+C content between 35 to 65%, absence of dimer or trimer consecutive repeats, a minimum of 2 differences between 9mers and selecting only sequences with Tm values between 34.5 and 36.5oC were applied for selecting probes with high sequential entropy. Virtual Hybridization was used to predict Genomic Fingerprints to assess the capability of the IPS to discriminate between influenza and related strains. Distance scores between pairs of Influenza Genomic Fingerprints were calculated, and used for estimating Taxonomic Trees. Visual examination of both Genomic Fingerprints and Taxonomic Trees suggest that the IPS is able to discriminate between distant and closely related Influenza strains. It is proposed that the IPS can be used to investigate, by virtual or experimental hybridization, any new, and potentially virulent, strain.