Identifying conserved microRNAs in a large dataset of wheat small RNAs

Abstract

MicroRNAs (miRNAs) play a vital role in regulating gene expression. Detecting conserved and novel miRNAs in very large genomic datasets generated using next generation sequencing platforms is a new research area in the field of gene regulation, but finding useful miRNA information from a large wheat genome is a challenging research project. We propose to design a toolchain that will identify conserved miRNAs using various software tools such as Basic Local Alignment Search Tool (BLAST), Bowtie 2, MAFFT and RNAfold. Our toolchain identified 36 wheat conserved miRNA families that matched with 232 experimental sequences. Moreover, we found 87 plant conserved miRNA families that matched between 613 experimental sequences and the miRBase dataset. In addition, we observed significant differential expression for the wheat exposed to the heat stress compared to those exposed to light and UV stresses or no stress (control).