Computational analysis of small RNA cloning data

被引:52
作者
Berninger, Philipp [1 ,2 ]
Gaidatzis, Dimos [1 ,2 ]
van Nimwegen, Erik [1 ,2 ]
Zavolan, Mihaela [1 ,2 ]
机构
[1] Univ Basel, Biozentrum, CH-4056 Basel, Switzerland
[2] Swiss Inst Bioinformat, CH-4056 Basel, Switzerland
关键词
deep sequencing; annotation; alignment; expression profiling;
D O I
10.1016/j.ymeth.2007.10.002
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Cloning and sequencing is the method of choice for small regulatory RNA identification. Using deep sequencing technologies one can now obtain up to a billion nucleotides - and tens of millions of small RNAs-from a single library. Careful computational analyses of such libraries enabled the discovery of miRNAs, rasiRNAs, piRNAs, and 21 U RNAs. Given the large number of sequences that can be obtained from each individual sample, deep sequencing may soon become an alternative to oligonucleotide microarray technology for mRNA expression profiling. In this report we present the methods that we developed for the annotation and expression profiling of small RNAs obtained through large-scale sequencing. These include a fast algorithm for finding nearly perfect matches of small RNAs in sequence databases, a web-accessible software system for the annotation of small RNA libraries, and a Bayesian method for comparing small RNA expression across samples. (c) 2007 Elsevier Inc. All rights reserved.
引用
收藏
页码:13 / 21
页数:9
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