Abstract
This work addresses a central question in medical genetics – the distinction between disease-causing SNPs and neutral variations. Unlike previous studies that focused mainly on coding SNPs, our efforts were centered around variations in regulatory regions and specifically within transcription factor (TF) binding sites. We have compiled a comprehensive collection of genome wide TF binding sites and developed computational measures to estimate the effects of binding site variations on the expression profiles of the regulated genes. Applying these measures to binding sites of known TFs, we were able to make predictions that were in line with published experimental evidence and with structural data on DNA-protein interactions. We attempted to generalize the properties of expression-altering substitutions by accumulating statistics from many substitutions across multiple binding sites. We found that in the yeast genome substitutions that abolish a G or a C are on average more severe than substitutions that abolish an A or a T. This may be attributed to the low GC content of the yeast genome, in which G and C may be important for conferring specificity. We found additional factors that are correlated with the severity of a substitution. Such factors can be integrated in order to create a set of rules for the prioritization of regulatory SNPs according to their disease-causing potential.
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Lapidot, M., Pilpel, Y. (2007). Characterization of the Effects of TF Binding Site Variations on Gene Expression Towards Predicting the Functional Outcomes of Regulatory SNPs. In: Eskin, E., Ideker, T., Raphael, B., Workman, C. (eds) Systems Biology and Regulatory Genomics. RSB RRG 2005 2005. Lecture Notes in Computer Science(), vol 4023. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-48540-7_5
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DOI: https://doi.org/10.1007/978-3-540-48540-7_5
Publisher Name: Springer, Berlin, Heidelberg
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