In this study we evaluate the capacity of Virtual Hybridization to identify between highly related bacterial strains. Eight genomic fingerprints were obtained by virtual hybridization for the Bacillus anthracis genome set, and a set of 15,264 13-nucleotide short probes designed to produce genomic fingerprints unique for each organism. The data obtained from each genomic fingerprint were used to obtain hybridization patterns simulating a DNA microarray. Two virtual hybridization methods were used: the Direct and the Extended method to identify the number of potential hybridization sites and thus determine the minimum sensitivity value to discriminate between genomes with 99.9% similarity. Genomic fingerprints were compared using both methods and phylogenomic trees were constructed to verify that the minimum detection value is 0.000017. Results obtained from the genomic fingerprints suggest that the distribution in the trees is correct, as compared to other taxonomic methods. Specific virtual hybridization sites for each of the genomes studied were also identified.
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.
Background: Commercial kits for Human Identification (HID) purposes, based on 15 short tandem repeat (STR) regions, allow the resolution of most forensic and paternity cases. However, some pitfalls arise in situations such as identification of missing persons, disaster victims, and in motherless paternities. We describe nine fortuitous matches found during the inclusion of new DNA profiles and/or searching for missing persons within a Mexican STR database (N = 2000). For these cases, we estimated both the likelihood ratio (LR) and the modified LR according to National Research Council (NRC) recommendations (i.e., LR NRC ).
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