A transcriptomic profile of topping responsive non-coding RNAs in tobacco roots (Nicotiana tabacum)

Abstract

BackgroundNon-coding RNAs (ncRNAs), including microRNAs (miRNAs), long ncRNAs (lncRNAs) and circular RNAs (circRNAs), accomplish remarkable variety of biological functions. However, the composition of ncRNAs and their interactions with coding RNAs in modulating and controlling of cellular process in plants is largely unknown. Using a diverse group of high-throughput sequencing strategies, the mRNA, miRNA, lncRNA and circRNA compositions of tobacco (Nicotiana tabacum) roots determined and their alteration and potential biological functions in response to topping treatment analyzed.ResultsA total of 688 miRNAs, 7423 non-redundant lncRNAs and 12,414 circRNAs were identified, among which, some selected differentially expressed RNAs were verified by quantitative real-time PCR. Using the differentially expressed RNAs, a co-expression network was established that included all four types of RNAs. The number of circRNAs identified were higher than that of miRNAs and lncRNAs, but only two circRNAs were present in the co-expression network. LncRNAs appear to be the most active ncRNAs based on their numbers presented in the co-expression network, but none of them seems to be an eTM (endogenous Target Mimicry) of miRNAs. Integrated with analyses of sequence interaction, several mRNA-circRNA-miRNA interaction networks with a potential role in the regulation of nicotine biosynthesis were uncovered, including a QS-circQS-miR6024 interaction network. In this network miR6024 was significantly down-regulated, while the expression levels of its two targets, circQS and its host gene QS, were sharply increased following the topping treatment.ConclusionsThese results illustrated the transcriptomic profiles of tobacco roots, the organ responsible for nicotine biosynthesis. mRNAs always play the most important roles, while ncRNAs are also expressed extensively for topping treatment response, especially circRNAs are the most activated in the ncRNA pool. These studies also provided insights on the coordinated regulation module of coding and non-coding RNAs in a single plant biological sample. The findings reported here indicate that ncRNAs appear to form interaction complex for the regulation of stress response forming regulation networks with transcripts involved in nicotine biosynthesis in tobacco.

Degradome, small RNAs and transcriptome sequencing of a high-nicotine cultivated tobacco uncovers miRNA’s function in nicotine biosynthesis

“…In recent years, the availability of diverse germplasms and high-throughput sequencing platform provided an opportunity to study secondary metabolism. Although many genes involved in nicotine biosynthesis and regulation have been reported, the studies about small RNA’s role are elusive 56 . In our work, three important high-throughput methods, namely, small RNA, degradome and transcriptomics sequencing were applied to investigate mechanisms of nicotine biosynthesis in tobacco.…”

Global Profiling of lncRNAs Expression Responsive to Allopolyploidization in Cucumis

“…In the present study, a total of 1593 lncRNA loci (2206 isoforms) were identified in C. hytivus based on stringent criteria. lncRNAs were also identified in other polyploid plants, example given bread wheat (44,698) [ 77 ], cotton (8514) [ 34 ], tobacco (7423) [ 78 ], and Brassica napus (549) [ 79 ]. The identification efficiency of lncRNAs may be affected by their reference genome, RNA sequencing methods, and different identification strategies.…”

Genome-Wide Identification and Analysis of the Class III Peroxidase Gene Family in Tobacco (Nicotiana tabacum)

“…Raw sequence data of different tissues were obtained from PLncDB ( http://plncdb.tobaccodb.org/ ) ( Jin et al, 2021 ) and our unpublished data. Raw RNA-seq datasets, including cold ( Jin et al, 2017 ), drought ( Yang H et al, 2017 ), cadmium (Cd) ( He et al, 2016 ), topping ( Chen et al, 2019 ), NaCl, abscisic acid (ABA) ( Wu et al, 2021 ), cucumber mosaic virus (CMV) ( Liu et al, 2019 ), and Phytophthora nicotianae ( Yang J. K et al, 2017 ) were obtained from the SRA database ( Leinonen et al, 2010 ). All clean reads were mapped to the tobacco reference genome using Hisat2 (2.2.1) ( Kim et al, 2019 ).…”