Computational identification of microRNAs and their targets from the expressed sequence tags of horsegram (Macrotyloma uniflorum (Lam.) Verdc.).

MicroRNAs (miRNAs) are a class of naturally occurring and small non-coding RNA molecules of about 21-25 nucleotides in length. Their main function is to downregulate gene expression in different manners like translational repression, mRNA cleavage and epigenetic modification. To predict new miRNAs in plants different computational approaches have been developed. In the present study, an EST based approach has been used to identify novel miRNAs in horsegram. Identification of miRNAs was initiated by mining the EST database available at NCBI. Total of 989 ESTs were obtained for the identification of miRNAs. These ESTs were subjected to CAP3 assembly to remove the redundancy. This resulted in an output of 72 contigs and 606 singletons as non redundant datasets. The miRNAs were then predicted by using miRNA-finder. A total of eight potential miRNAs were predicted and named as hor-miR1 to hor-miR8. None of identified miRNAs showed significant homology with the previously reported in plants and therefore should be considered novel. These miRNAs were inputted to miRU2 program to predict their targets. The target mRNAs for these miRNAs mainly belong to zinc finger, chromosome condensation, protein kinase, abscisic acid-responsive, calcineurin-like phosphoesterase, disease resistance and transcriptional factor family proteins. These targets appeared to be involved in plant growth and development and environmental stress responses.