Computational identification and functional annotation of miRNAs in medicinal plant Helianthus petiolaris

Abstract

MicroRNAs (miRNAs) are short (~22 nucleotide), non-coding RNAs that regulate messenger RNA (mRNA) or protein levels either by promoting mRNA degradation or by attenuating protein translation. Computation identification of miRNAs and their targets in medicinal plant Helianthus petiolaris (H. petiolaris) was carried out. Computational approach for mining of miRNA from EST databases is faster and reliable. Here, the total 27,484 EST sequences of H. petiolaris were assembled and clustered into 4,182 contigs (15 % of EST sequences). These contigs were searched against known miRNA sequences of different plants. An overall 117 unique sequences (precursor miRNAs) were mined from UniGenes. Functional annotation of unique sequences was carried out to eliminate the coding sequences and secondary structure of resulting precursor miRNAs (pre-miRNAs) was determined. The analysis led to identification of 11 miRNAs sequences (10 % of pre-miRNAs). The hpe-mir-395 was found to be the most stable miRNA on the basis of free energy of secondary structure. Targets for novel miRNAs were determined by searching homology between identified miRNA and UniGenes. Eleven miRNA targets were identified of which 67 % are responsible for biological function. The predicted miRNAs were validated by phylogenetic study and belong to four large miRNA families (mir-393, mir-156, mir-1863, mir-169).