Computational Identification of miRNAs and Their Target Genes from Expressed Sequence Tags of Tea (<i>Camellia Sinensis</i>)

Abstract

MicroRNAs (miRNAs) are a newly identified class of small non-protein-coding post-transcriptional regulatory RNA in both plants and animals. The use of computational homology based search for expressed sequence tags (ESTs) with the Ambros empirical formula and other structural feature criteria filter is a suitable combination towards the discovery and isolation of conserved miRNAs from tea and other plant species whose genomes are not yet sequenced. In the present study, we blasted the database of tea (Camellia sinensis) ESTs to search for potential miRNAs, using previously known plant miRNAs. For the first time, four candidate miRNAs from four families were identified in tea. Using the newly identified miRNA sequences, a total of 30 potential target genes were identified for 11 miRNA families; 6 of these predicted target genes encode transcription factors (20%), 16 target genes appear to play roles in diverse physiological processes (53%) and 8 target genes have hypothetical or unknown functions (27%). These findings considerably broaden the scope of understanding the functions of miRNA in tea.