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Lack of correlation between in silico projection of function and quantitative real-time PCR-determined gene expression levels in colon tissue

机译:计算机上的功能预测与结肠组织中实时定量PCR测定的基因表达水平之间缺乏相关性

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摘要

There are a number of in silico programs that use algorithms and external web sources to predict the effect of single nucleotide polymorphisms (SNPs). While many of these programs have been shown to predict accurately the effect of SNPs in functional areas of the gene, such as 5′ upstream or coding regions, empiric research may be warranted to confirm the functional consequences of SNPs that are predicted to have little to no effect. We compared predictions from FASTSNP (Function Analysis and Selection Tool for Single Nucleotide Polymorphism) and F-SNP (Functional Single Nucleotide Polymorphism) with experimentally derived genotype-phenotype correlations to determine the accuracy of these programs in predicting SNP functionality. We used normal colon tissue to evaluate 24 TagSNPs within six genes. Two of 16 SNPs that were predicted to have no functional effect in FASTSNP were significantly associated with gene expression. Only one of the eight SNPs that were predicted to have a low to high effect was significantly associated with gene expression. While the two in silico programs that were used were similar in their results for the SNPs predicted by FASTSNP to have no effect, of SNPs with scores from low to high, there were three that received an F-SNP score below what is considered functionally significant. In silico programs can fail to identify functional SNPs, supporting a continuing role for empiric analysis of SNP function. Laboratory analysis is necessary to identify causal SNPs accurately, establish biological plausibility of the effect, and ultimately inform cancer prevention strategies.
机译:许多计算机程序使用算法和外部网络资源来预测单核苷酸多态性(SNP)的影响。尽管许多此类程序已显示可准确预测SNP在基因功能区域(例如5'上游或编码区)的作用,但仍需进行经验研究,以证实预测的SNP几乎没有作用。没有效果。我们将FASTSNP(单核苷酸多态性功能分析和选择工具)和F-SNP(功能性单核苷酸多态性)的预测与实验得出的基因型-表型相关性进行比较,以确定这些程序在预测SNP功能性方面的准确性。我们使用正常结肠组织评估了六个基因中的24个TagSNP。预计在FASTSNP中没有功能作用的16个SNP中有两个与基因表达显着相关。预测有低到高影响的八个SNP中只有一个与基因表达显着相关。虽然使用的两种计算机程序在结果上相似,但FASTSNP预测没有影响,但得分从低到高的SNP却有三个,其F-SNP得分低于功能上显着的分数。计算机程序可能无法识别功能性SNP,从而支持对SNP功能进行经验分析的持续作用。实验室分析对于准确识别病因SNP,确定该效应的生物学合理性并最终为癌症预防策略提供必要的条件。

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