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Characterization of the Effects of TF Binding Site Variations on Gene Expression Towards Predicting the Functional Outcomes of Regulatory SNPs

机译:TF结合位点变异对预测监管SNP的功能结果的基因表达的表征

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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.
机译:这项工作解决了医学遗传学中的核心问题 - 疾病导致的SNP和中性变化之间的区别。与以往的研究不同,主要专注于编码SNP,我们的努力将围绕调节区的变化,特别是在转录因子(TF)结合位点。我们编制了全面的基因组宽TF结合位点集,并开发了计算措施,以估计结合位点变化对受调节基因表达谱的影响。将这些措施应用于已知TFS的结合位点,我们能够使预测与已发表的实验证据以及关于DNA-蛋白质相互作用的结构数据。我们试图通过在多个结合位点的许多替换中累积统计来概括表达改变取代的性质。我们发现,在废除G或C的酵母基因组取代中,通常比取代A或A T的代表更严重。这可能归因于酵母基因组的低GC含量,其中G和C可以对赋予特异性很重要。我们发现了与替换的严重程度相关的其他因素。可以集成这些因素,以便根据其疾病导致潜力来创建一组用于监管SNP的优先级。

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