A New Set of Algorithms for Designing Ultra-Specific Probes for High-Throughput Allele Detection

M. Zhang, C. Putonti, and Y. Fofanov (USA)


Allele detection, ultra-specific genomic signatures, and optimal combinations of probes.


Genetic variations within the human genomic sequence can affect an individual’s susceptibility to disease as well as his/her response to pathogens, drug treatment and vaccines. Such variations are often introduced through single nucleotide polymorphisms or SNPs, resulting in the presence of different combinations of SNPs or alleles throughout the population. Identification of these variations in a high-throughput, high-resolution and cost effective manner is imperative for various applications such as population-scale epidemiological studies. To meet such a challenge, a new approach was developed to design microarray probe sets for identification of an allele in which the probe sequences are specific to the targeted SNP and the minimum number of probes are employed. Using recently developed algorithms, the specificity of all candidate probes is measured by calculating the distance or the number of base changes necessary in order to convert the sequence to the nearest non-target sequence (likely contaminants of a sample, the remainder of the human genome, etc.). Through the implementation of an evolutionary programming approach, one can then determine the minimum number of these ultra-specific probes which can be used to provide the highest resolution of typing.

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