IN SILICO EST DATA ANALYSIS OF CURCUMA LONGA: A CROSS KINGDOM APPROACH

Abstract

MicroRNAs are a newly discovered class of non-coding small RNAs with 22–24 nucleotides. They play multiple roles in biological processes including development, cell proliferation, apoptosis, stress responses and many other cell functions. In this research, several approaches were combined to make a computational prediction of potential miRNAs and their targets in Curcuma longa. The already available information of the plant miRNAs present in miRbase v21 was used against expressed sequence tags (ESTs). A total of 89 uniq miRNA were detected following a range of strict filtering criteria. The target prediction was carried out for this miRNA having various targets. These targets were functionally annotated and GO terms were assigned. To study the conserved nature of the miRNAs, predicted phylogeny analysis was carried out. These findings will significantly provide the broader picture for understanding the functions of Curcuma longa in Anti-cancer and Anti-Immunosuppressor activity.