Department of Biology, University of Virginia, Charlottesville VA 22904, USA.
Biology (Basel). 2012 Aug 15;1(2):297-310. doi: 10.3390/biology1020297.
MicroRNAs (miRNAs) are 20- to 24-nucleotide endogenous small RNA molecules emerging as an important class of sequence-specific, trans-acting regulators for modulating gene expression at the post-transcription level. There has been a surge of interest in the past decade in identifying miRNAs and profiling their expression pattern using various experimental approaches. In particular, ultra-deep sampling of specifically prepared low-molecular-weight RNA libraries based on next-generation sequencing technologies has been used successfully in diverse species. The challenge now is to effectively deconvolute the complex sequencing data to provide comprehensive and reliable information on the miRNAs, miRNA precursors, and expression profile of miRNA genes. Here we review the recently developed computational tools and their applications in profiling the miRNA transcriptomes, with an emphasis on the model plant Arabidopsis thaliana. Highlighted is also progress and insight into miRNA biology derived from analyzing available deep sequencing data.
MicroRNAs (miRNAs) 是 20-24 个核苷酸的内源性小 RNA 分子，作为一类重要的序列特异性、反式作用调节剂，在转录后水平调节基因表达。在过去的十年中，人们对 miRNA 的鉴定和表达谱分析产生了浓厚的兴趣，使用了各种实验方法。特别是，基于下一代测序技术的专门制备的低分子量 RNA 文库的超深度采样已在多种物种中成功应用。现在的挑战是如何有效地解卷积复杂的测序数据，以提供有关 miRNA、miRNA 前体和 miRNA 基因表达谱的全面可靠信息。在这里，我们回顾了最近开发的计算工具及其在 miRNA 转录组分析中的应用，重点是模式植物拟南芥。还强调了从分析可用的深度测序数据中获得的 miRNA 生物学的进展和见解。
