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BioMed Central, BMC Genomics, 1(12), 2011

DOI: 10.1186/1471-2164-12-129

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Discovery of barley miRNAs through deep sequencing of short reads

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Preprint: archiving allowed
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Postprint: archiving allowed
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Data provided by SHERPA/RoMEO

Abstract

Background: MicroRNAs are important components of the regulatory network of biological systems and thousands have been discovered in both animals and plants. Systematic investigations performed in species with sequenced genomes such as Arabidopsis, rice, poplar and Brachypodium have provided insights into the evolutionary relationships of this class of small RNAs among plants. However, miRNAs from barley, one of the most important cereal crops, remain unknown. Results: We performed a large scale study of barley miRNAs through deep sequencing of small RNAs extracted from leaves of two barley cultivars. By using the presence of miRNA precursor sequences in related genomes as one of a number of supporting criteria, we identified up to 100 miRNAs in barley. Of these only 56 have orthologs in wheat, rice or Brachypodium that are known to be expressed, while up to 44 appear to be specifically expressed in barley. Conclusions: Our study, the first large scale investigation of small RNAs in barley, has identified up to 100 miRNAs. We demonstrate that reliable identification of miRNAs via deep sequencing in a species whose genome has not been sequenced requires a more careful analysis of sequencing errors than is commonly performed. We devised a read filtering procedure for dealing with errors. In addition, we found that the use of a large dataset of almost 35 million reads permits the use of read abundance distributions along putative precursor sequences as a practical tool for isolating miRNAs in a large background of reads originating from other non-coding and coding RNAs. This study therefore provides a generic approach for discovering novel miRNAs where no genome sequence is available. ; Andreas W Schreiber, Bu-Jun Shi, Chun-Yuan Huang, Peter Langridge, Ute Baumann