Using expression profiling data to identify human microRNA targets
Using expression profiling data to identify human microRNA targets
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DOI：
10.1038/nmeth1130
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发表时间：
2007-12-01
期刊：
影响因子：
48
通讯作者：
Morris, Quaid D.
中科院分区：
文献类型：
--
作者：
Huang, Jim C.;Babak, Tomas;Morris, Quaid D.
我们证明了microRNAs （miRNAs）和mrna的配对表达谱可以用于高精度地识别功能性mirna -靶标关系。我们使用贝叶斯数据分析算法GenMiR++，确定了104个人类mirna的1597个高可信度目标预测网络，并得到了88种组织和细胞类型的RNA表达数据、序列互补和比较基因组学数据的支持。我们通过使用定量逆转录酶(RT)-PCR和微阵列分析研究视网膜母细胞瘤中let-7b下调的结果，实验验证了我们的预测：我们验证的一些let-7b靶点包括CDC25A和BCL7A。与基于序列的预测相比，我们的高分GenMiR++预测具有更一致的基因本体注释，并且更准确地预测哪些mRNA水平响应let-7b水平的变化。
We demonstrate that paired expression profiles of microRNAs ( miRNAs) and mRNAs can be used to identify functional miRNA-target relationships with high precision. We used a Bayesian data analysis algorithm, GenMiR++, to identify a network of 1,597 high-confidence target predictions for 104 human miRNAs, which was supported by RNA expression data across 88 tissues and cell types, sequence complementarity and comparative genomics data. We experimentally verified our predictions by investigating the result of let-7b downregulation in retinoblastoma using quantitative reverse transcriptase (RT)-PCR and microarray profiling: some of our verified let-7b targets include CDC25A and BCL7A. Compared to sequence-based predictions, our high-scoring GenMiR++ predictions had much more consistent Gene Ontology annotations and were more accurate predictors of which mRNA levels respond to changes in let-7b levels.