Computational screening of miRNAs and their targets in saffron (Crocus sativus L.) by transcriptome mining

Abstract

A robust workflow for the identification of miRNAs and their targets in saffron was developed. MicroRNA-mediated gene regulation in saffron is potentially involved in several biological processes, including the biosynthesis of highly valuable apocarotenoids. Saffron (Crocus sativus L.) is the most expensive spice in the world and a major source of apocarotenoids. Even though miRNAs (20-24 nt non-coding small RNAs) are important regulators of gene expression at transcriptional and post-transcriptional levels, their role in saffron has not been thoroughly investigated. As a result, a workflow for computational identification of miRNAs and their targets can be useful to uncover the regulatory networks underlying biological processes in this valuable plant. The efficiency of several assembly tools such as Trans-ABySS, Trinity, Bridger, rnaSPAdes, and EvidentialGene was evaluated based on both reference-based and reference-free metrics using transcriptome data. A reliable workflow for computational identification of miRNAs and their targets in saffron was described. The EvidentialGene was found to be the most efficient de novo transcriptome assembler for saffron as a complex triploid model, followed by the Trinity. In total, 66 miRNAs from 19 different families that target 2880 genes, including several transcription factors involved in the flowering transition, were identified. Three of the identified targets were involved in the terpenoids backbone biosynthesis. CsCCD and CsUGT genes involved in the apocarotenoids biosynthetic pathway were targeted by csa-miR156g and csa-miR156b-3p, revealing a unique post-transcriptional regulation dynamic in saffron. The identified miRNAs and their targets add to our understanding of the many biological roles of miRNAs in saffron and shed new light on the control of the apocarotenoid biosynthetic pathway in this valuable plant.

Keywords: Apocarotenoids; Bioinformatics analysis; Flowering transition; Metabolic engineering; Transcriptome assembly.