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Target gene expression levels and competition between transfected and endogenous microRNAs are strong confounding factors in microRNA high-throughput experiments

机译:靶基因表达水平以及转染和内源性microRNA之间的竞争是microRNA高通量实验中的强大混杂因素

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Background MicroRNA (miRNA) target genes tend to have relatively long and conserved 3' untranslated regions (UTRs), but to what degree these characteristics contribute to miRNA targeting is poorly understood. Different high-throughput experiments have, for example, shown that miRNAs preferentially regulate genes with both short and long 3' UTRs and that target site conservation is both important and irrelevant for miRNA targeting. Results We have analyzed several gene context-dependent features, including 3' UTR length, 3' UTR conservation, and messenger RNA (mRNA) expression levels, reported to have conflicting influence on miRNA regulation. By taking into account confounding factors such as technology-dependent experimental bias and competition between transfected and endogenous miRNAs, we show that two factors - target gene expression and competition - could explain most of the previously reported experimental differences. Moreover, we find that these and other target site-independent features explain about the same amount of variation in target gene expression as the target site-dependent features included in the TargetScan model. Conclusions Our results show that it is important to consider confounding factors when interpreting miRNA high throughput experiments and urge special caution when using microarray data to compare average regulatory effects between groups of genes that have different average gene expression levels.
机译:背景MicroRNA(miRNA)靶基因趋向于具有相对较长且保守的3'非翻译区(UTR),但这些特性在多大程度上有助于miRNA靶向,尚不清楚。例如,不同的高通量实验表明,miRNA优先调节具有短和长3'UTR的基因,并且靶位点保守对于miRNA靶向而言既重要又无关紧要。结果我们分析了几种基因背景相关的特征,包括3'UTR长度,3'UTR保守性和信使RNA(mRNA)表达水平,据报道它们对miRNA调控有冲突的影响。通过考虑混杂因素,例如技术依赖的实验偏差以及转染的和内源性miRNA之间的竞争,我们证明了两个因素-靶基因表达和竞争-可以解释大多数先前报道的实验差异。此外,我们发现这些和其他与靶位点无关的特征可以解释与TargetScan模型中包含的与靶位点依赖性有关的特征在靶基因表达中的变化量。结论我们的结果表明,在解释miRNA高通量实验时,必须考虑混杂因素,并在使用微阵列数据比较具有不同平均基因表达水平的基因组之间的平均调节作用时,要特别小心。

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