Bioinformatics profiling and expressional studies of microRNAs in root, stem and leaf of the bioenergy plant switchgrass (Panicum virgatum L.) under drought stress

Abstract

Switchgrass (Panicum virgatum L.) is a perennial fodder grass and well known as a model renewable bioenergy crop. The plant's high production of biomass for biofuel supply is due to its fast-growing and wide adaptation properties. Very little studies and data are available about microRNAs (miRNAs) in this important biofuel crop. This situation demands to focus and identify new miRNAs and also to study their expressional analysis. In current research, a combination of computational and expressional approaches is applied to profile and characterize miRNAs in switchgrass and analyze some of them under drought stress. A total of 158 new miRNAs belonging to 83 families are identified and characterized from switchgrass expressed sequence tags (ESTs) and genomic survey sequences (GSS). In addition, five pre-miRNA clusters as well as four sense and antisense pre-miRNAs are also predicted from these newly identified miRNAs. Furthermore, 39 miRNAs were randomly selected and subjected to quantitative real-time RT-PCR expressional studies in root, leaf and stem of switchgrass under drought stress. A set of 13, 20 and 25 miRNAs are found as drought responding miRNAs in root, stem and leaf respectively. A total of 894 putative targets are also predicted for 158 switchgrass' miRNAs. These targets play roles in metabolism, transcription factor, signaling pathways, growth & development, stress-related, transport protein and other vital processes. Such findings in switchgrass improved the baseline data of miRNAs and their targets. This data can be utilized to fine-tune this important bioenergy crop under biotic and abiotic stresses. Furthermore, it can also be used for the improvement of biofuel properties of the plant.