Expression profiling of microRNAs by deep sequencing

被引:218
作者
Creighton, Chad J. [1 ]
Reid, Jeffrey G. [1 ]
Gunaratne, Preethi H. [1 ]
机构
[1] Baylor Coll Med, Duncan Canc Ctr Div Biostat, Houston, TX 77030 USA
基金
美国国家卫生研究院;
关键词
deep sequencing; expression profiling; microRNA; COMPUTATIONAL ANALYSIS; IDENTIFICATION; ARGONAUTE2; GENES; RNAS;
D O I
10.1093/bib/bbp019
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
MicroRNAs are short non-coding RNAs that regulate the stability and translation of mRNAs. Profiling experiments, using microarray or deep sequencing technology, have identified microRNAs that are preferentially expressed in certain tissues, specific stages of development, or disease states such as cancer. Deep sequencing utilizes massively parallel sequencing, generating millions of small RNA sequence reads from a given sample. Profiling of microRNAs by deep sequencing measures absolute abundance and allows for the discovery of novel microRNAs that have eluded previous cloning and standard sequencing efforts. Public databases provide in silico predictions of microRNA gene targets by various algorithms. To better determine which of these predictions represent true positives, microRNA expression data can be integrated with gene expression data to identify putative microRNA:mRNA functional pairs. Here we discuss tools and methodologies for the analysis of microRNA expression data from deep sequencing.
引用
收藏
页码:490 / 497
页数:8
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