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Methods

Computational prediction of miRNAs in Arabidopsis thaliana

¹ Biological and Medical Informatics, University of California San Francisco, San Francisco, California 94143, USA ² Section of Plant Biology, Division of Biological Sciences, University of California Davis, Davis, California 95616, USA ³ Department of Plant and Microbial Biology, University of California Berkeley, Berkeley, California 94720, USA ⁴ Department of Biological Sciences, University of South Carolina, Columbia, South Carolina 29208, USA

MicroRNAs (miRNAs) are post-transcriptional regulators of gene expression in animals and plants. Comparative genomic computational methods have been developed to predict new miRNAs in worms, flies, and humans. Here, we present a novel single genome approach for the detection of miRNAs in Arabidopsis thaliana. This was initiated by producing a candidate miRNA-target data set using an algorithm called findMiRNA, which predicts potential miRNAs within candidate precursor sequences that have corresponding target sites within transcripts. From this data set, we used a characteristic divergence pattern of miRNA precursor families to select 13 potential new miRNAs for experimental verification, and found that corresponding small RNAs could be detected for at least eight of the candidate miRNAs. Expression of some of these miRNAs appears to be under developmental control. Our results are consistent with the idea that targets of miRNAs encompass a wide range of transcripts, including those for F-box factors, ubiquitin conjugases, Leucine-rich repeat proteins, and metabolic enzymes, and that regulation by miRNAs might be widespread in the genome. The entire set of annotated transcripts in the Arabidopsis genome has been run through findMiRNA to yield a data set that will enable identification of potential miRNAs directed against any target gene.

⁵ These authors contributed equally to this work.

⁶ Present address: Waksman Institute of Microbiology, Rutgers University, Piscataway, New Jersey 08854, USA.

⁷ Corresponding author.
E-mail sundar{at}ucdavis.edu; fax (530) 752-5410.

[Supplemental material is available online at www.genome.org. All programs are freely available, and the miRNA candidate data is available through a Web interface at http://sundarlab.ucdavis.edu/mirna/.]

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