Integration of Expressed Sequence Tag Data Flanking Predicted RNA Secondary Structures Facilitates Novel Non-Coding RNA Discovery

Many computational methods have been used to predict novel non-coding RNAs (ncRNAs), but none, to our knowledge, have explicitly investigated the impact of integrating existing cDNA-based Expressed Sequence Tag (EST) data that flank structural RNA predictions. To determine whether flanking EST data can assist in microRNA (miRNA) prediction, we identified genomic sites encoding putative miRNAs by combining functional RNA predictions with flanking ESTs data in a model consistent with miRNAs undergoing cleavage during maturation. In both human and mouse genomes, we observed that the inclusion of flanking ESTs adjacent to and not overlapping predicted miRNAs significantly improved the performance of various methods of miRNA prediction, including direct high-throughput sequencing of small RNA libraries. We analyzed the expression of hundreds of miRNAs predicted to be expressed during myogenic differentiation using a customized microarray and identified several known and predicted myogenic miRNA hairpins. Our results indicate that integrating ESTs flanking structural RNA predictions improves the quality of cleaved miRNA predictions and suggest that this strategy can be used to predict other non-coding RNAs undergoing cleavage during maturation.

已有诸多计算方法被用于预测新型非编码RNA（non-coding RNAs, ncRNAs），但据我们所知，尚无研究明确探讨整合现有基于互补DNA（complementary DNA, cDNA）的、侧翼结合结构RNA预测结果的表达序列标签（Expressed Sequence Tag, EST）数据所带来的影响。为探明侧翼EST数据是否可辅助微小RNA（microRNA, miRNA）预测，我们结合功能性RNA预测结果与侧翼EST数据，采用与成熟过程中经历剪切的miRNA相符的模型，鉴定出了编码潜在miRNA的基因组位点。在人类与小鼠基因组中，我们观察到：将相邻且不与预测miRNA重叠的侧翼EST纳入分析，可显著提升各类miRNA预测方法的性能，其中包括针对小RNA文库的直接高通量测序技术。我们借助定制化微阵列，对数百种据预测可在肌源性分化过程中表达的miRNA进行了表达分析，并鉴定出了数个已知的以及预测得到的肌源性miRNA发夹结构。我们的研究结果表明，整合侧翼带有结构RNA预测结果的EST数据，可提升剪切型miRNA预测的质量，同时提示该策略可用于预测其他在成熟过程中经历剪切的非编码RNA。