In silico mining of novel microRNAs from coffee (Coffea arabica) using expressed sequence tags

Abstract

MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression either by causing mRNA cleavage or by translational repression in plants and animals, respectively.We are beginning to understand the functional roles played by miRNAs in various life-forms to regulate growth and development. In this regard, there have been no reports on miRNAs in coffee, Coffea arabica, an economically important cash-crop. The experimental identification and characterisation of spatially and temporally expressed miRNAs have proved to be major challenges. Computational approaches that depend on sequence homology and secondary structure verification are important tools. In the present study, 18 novel miRNAs were identified in C. arabica using computational approaches to analyse the 174,275 expressed sequence tag (EST) sequences available in the NCBI-GenBank database. The construction of phylogenetic trees of five large families of miRNAs (those with ≥ 20 miRNAs) clearly indicated that the C. arabica miRNAs are evolutionarily conserved regulators of gene expression. Forty-one potential mRNA targets were also identified by homology searches for all 18 miRNAs against the C. canephora mRNA dataset using psRNATarget (http://plantgrn.noble.org/psRNATarget/; a plant small RNA target analysis site). Functional characterisation of the 18 newly-identified miRNAs revealed that the majority were involved in transcriptional regulation and signal transduction pathways. Our studies will provide new insights into miRNAs and their functions in C. arabica, and have opened-up new avenues for further functional analyses of the control of gene expression.