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High-resolution experimental and computational profiling of tissue-specific known and novel miRNAs in Arabidopsis
Author(s) -
Natalie W. Breakfield,
David L. Corcoran,
Jalean J. Petricka,
Jeffrey D. Shen,
Juthamas Sae-Seaw,
Ignacio RubioSomoza,
Detlef Weigel,
Uwe Ohler,
Philip N. Benfey
Publication year - 2011
Publication title -
genome research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.556
H-Index - 297
eISSN - 1549-5469
pISSN - 1088-9051
DOI - 10.1101/gr.123547.111
Subject(s) - biology , microrna , computational biology , small rna , arabidopsis , rna , genetics , phenotype , non coding rna , deep sequencing , gene knockdown , bioinformatics , gene , genome , mutant
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.

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