Chen Kevin, Maaskola Jonas, Siegal Mark L, Rajewsky Nikolaus
Center for Genomics and Systems Biology, Department of Biology, New York University, New York, New York, United States of America.
PLoS One. 2009 May 25;4(5):e5681. doi: 10.1371/journal.pone.0005681.
Kertesz et al. (Nature Genetics 2008) described PITA, a miRNA target prediction algorithm based on hybridization energy and site accessibility. In this note, we used a population genomics approach to reexamine their data and found that the PITA algorithm had lower specificity than methods based on evolutionary conservation at comparable levels of sensitivity.We also showed that deeply conserved miRNAs tend to have stronger hybridization energies to their targets than do other miRNAs. Although PITA had higher specificity in predicting targets than a naïve seed-match method, this signal was primarily due to the use of a single cutoff score for all miRNAs and to the observed correlation between conservation and hybridization energy. Overall, our results clarify the accuracy of different miRNA target prediction algorithms in Drosophila and the role of site accessibility in miRNA target prediction.
凯泰斯等人(《自然遗传学》,2008年)描述了PITA,一种基于杂交能和位点可及性的微小RNA(miRNA)靶标预测算法。在本论文中,我们采用群体基因组学方法重新审视了他们的数据,发现PITA算法在灵敏度相当的水平下,其特异性低于基于进化保守性的方法。我们还表明,深度保守的miRNA与其靶标的杂交能往往比其他miRNA更强。尽管PITA在预测靶标方面比单纯的种子匹配方法具有更高的特异性,但该信号主要归因于对所有miRNA使用单一的截止分数以及观察到的保守性与杂交能之间的相关性。总体而言,我们的结果阐明了不同miRNA靶标预测算法在果蝇中的准确性以及位点可及性在miRNA靶标预测中的作用。