rSNP_Guide: Meta-Tools Predicting of Regulatory DNA Signals Damaged/Appeared Due to Single Nucleotide Mutation by Alterations in Pattern of DNA Binding to Nuclear Proteins

摘要

A meta-tools adapting the Web-based system MATRIX, initially created for recognizing natural regulatory DNA signals during Genome annotation, to recognize the damaged/appeared signals due to single nucleotide mutations has been developed. For increasing the accuracy as compared to the others approaches, we introduce the usage of mutation-caused alterations in the pattern of regulatory DNA binding to nuclear proteins (the so-called, "gel-shift" data) in addition to the DNA sequences commonly taken into account. The second novelty is that all predicted regulatory signals are control tested for robustness by varying several cluster-analysis methods and similarity scales. This meta-tools was applied in practice to study several single nucleotide mutations damaging #2 intron K-ras gene and #6 intron TDO2 gene, which have the clinical diagnostics, i.e., (ⅰ) mutagen-induced tumor susceptibility in lung, and (ⅱ) drug dependence, Tourette syndrome, attention deficit, and hyperactivity disorder, respectively. For discussing our meta-algorithm usage, the NTFα, pC, GpIbβ, fVII, and Gγ genes with mutations having both known defective signals and clinical diagnostics were treated. This meta-algorithm is addressed to the modern genetic clinical trials.