Computational identification of conserved micro RNAs from Kodo millet (Paspalum scrobiculatum)

Abstract

Small RNA-guided gene silencing at the transcriptional and post-transcriptional levels has emerged as an important mode of gene regulation in plants and animals. Micro RNAs (miRNA) arise from long stem loop precursors which acted upon by DICER-Like enzymes. The miRNA and their precursor sequences are highly conserved among the species and this forms a key feature for their identification through homology alignment. Computational approach guides to identify the mature miRNAs as well as their precursors. The main principle behind the computational miRNA prediction is sequence and structure homologies. The in silico search for the homologues miRNA and their precursors among the Kodo millet ESTs enabled us to identify 4 miRNAs belonging to 3 families. A total of 34 targets were identified among which most were targeting the enzymes involved in fuel metabolism, cellular transporters, and structural proteins.

Key Words: Enzymes, in silico, structural proteins