High-resolution experimental and computational profiling of tissue-specific known and novel miRNAs in Arabidopsis

  1. Philip N. Benfey1,2,8
  1. 1Department of Biology, Duke University, Durham, North Carolina 27708, USA;
  2. 2Institute for Genome Science & Policy, Center for Systems Biology, Duke University, Durham, North Carolina 27708, USA;
  3. 3Department of Molecular Biology, Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany;
  4. 4Department of Biostatistics & Bioinformatics, Duke University, Durham, North Carolina 27708, USA
    1. 7 These authors contributed equally to this work.

    • Present addresses: 5Department of Biology, University of North Carolina, Chapel Hill, NC 27514, USA;

    • 6 Department of Biology, Stanford University, Stanford, CA 94305, USA.

    Abstract

    Small non-coding RNAs (ncRNAs) are key regulators of plant development through modulation of the processing, stability, and translation of larger RNAs. We present small RNA data sets comprising more than 200 million aligned Illumina sequence reads covering all major cell types of the root as well as four distinct developmental zones. MicroRNAs (miRNAs) constitute a class of small ncRNAs that are particularly important for development. Of the 243 known miRNAs, 133 were found to be expressed in the root, and most showed tissue- or zone-specific expression patterns. We identified 66 new high-confidence miRNAs using a computational pipeline, PIPmiR, specifically developed for the identification of plant miRNAs. PIPmiR uses a probabilistic model that combines RNA structure and expression information to identify miRNAs with high precision. Knockdown of three of the newly identified miRNAs results in altered root growth phenotypes, confirming that novel miRNAs predicted by PIPmiR have functional relevance.

    Footnotes

    • 8 Corresponding authors.

      E-mail uwe.ohler{at}duke.edu.

      E-mail philip.benfey{at}duke.edu.

    • [Supplemental material is available for this article.]

    • Article published online before print. Article, supplemental material, and publication date are at http://www.genome.org/cgi/doi/10.1101/gr.123547.111.

    • Received March 21, 2011.
    • Accepted September 22, 2011.
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