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analyzing the microrna transcriptome in plants using deep sequencing data分析微rna转录组植物中使用深度测序数据
Biology 2012, 1, 297-310; doi:10.3390/biology1020297
OPEN ACCESS
biology
ISSN 2079-7737
/journal/biology
Review
Analyzing the microRNA Transcriptome in Plants Using Deep
Sequencing Data
Xiaozeng Yang and Lei Li *
Department of Biology, University of Virginia, Charlottesville VA 22904, USA;
E-Mail: xy2y@
* Author to whom correspondence should be addressed; E-Mail: ll4jn@;
Tel.: +1-434-982-5481.
Received: 24 July 2012; in revised form: 3 August 2012 / Accepted: 9 August 2012 /
Published: 15 August 2012
Abstract: 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 tran
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