Identification of Known and Novel MicroRNAs in Raspberry Organs Through High-Throughput Sequencing

Abstract

MicroRNAs (miRNAs) are a class of small endogenous RNAs that play important regulatory roles in plants by negatively affecting gene expression. Studies on the identification of miRNAs and their functions in various plant species and organs have significantly contributed to plant development research. In the current study, we utilized high-throughput sequencing to detect the miRNAs in the root, stem, and leaf tissues of raspberry (Rubus idaeus). A total of more than 35 million small RNA reads ranging in size from 18 to 35 nucleotides were obtained, with 147 known miRNAs and 542 novel miRNAs identified among the three organs. Sequence verification and the relative expression profiles of the six known miRNAs were investigated by stemloop quantitative real-time PCR. Furthermore, the potential target genes of the known and novel miRNAs were predicted and subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway annotation. Enrichment analysis of the GO-associated biological processes and molecular functions revealed that these target genes were potentially involved in a wide range of metabolic pathways and developmental processes. Moreover, the miRNA target prediction revealed that most of the targets predicted as transcription factor-coding genes are involved in cellular and metabolic processes. This report is the first to identify miRNAs in raspberry. The detected miRNAs were analyzed by cluster analysis according to their expression, which revealed that these conservative miRNAs are necessary for plant functioning. The results add novel miRNAs to the raspberry transcriptome, providing a useful resource for the further elucidation of the functional roles of miRNAs in raspberry growth and development.

A global analysis of the Rubus virome using public transcriptome data

“…This work confirms that virus discovery can be accelerated through the analysis and reinterpretation of public sequencing data (Maree, 2018;Villamor et al, 2019;Buddenhagen et al, 2021 andGhosh et al, 2022). In our case, datasets were derived from studies focused on basic genome and transcriptome characterization of Rubus species (Hyun et al, 2014;Garcia-Seco et al, 2015;Sharma et al, 2019;Chen et al, 2018;Yan et al, 2020;Li et al, 2021;Yang et al, 2021;Wu et al, 2022a,b;Brůna et al, 2023 andMcGavin et al, 2023); analysis of the transcriptional response to upon infection with pathogens (Arias et al, 2019 andGonzález et al, 2020); and the validation of virus detection pipelines (Baizan-Edge et al, 2019;Gauthier et al, 2022 andMcGavin et al, 2023). Our most interesting results involved the identification of a putative new member of the genus Brambyvirus in data from a transcriptomic analysis of flavonoid biosynthesis (Li et al, 2021); and a putative new member of the family Virgaviridae in data used to test a plant virus detection workflow (Baizan-Edge et al, 2019).…”

Identification of Conserved and Novel MicroRNAs with their Targets in Garden Pea (Pisum sativum L.) Leaves by High-Throughput Sequencing

“…[28][29][30] The mature sequences of miRNA were downloaded from miRbase (https://www.mirbase.org/), a local miRNA database was constructed, then a homology search was performed using the ncbi-blast-2.13.0 + program to identify the conserved miRNA with E-value of 0.001 and non-gap alignment. [31][32][33][34][35] Subsequently, the unaligned reads were used for predicting novel miRNAs using the MIREAP program. A total of 29 novel miRNAs were predicted using the software; however, only 11 novel miRNAs have proper precursor secondary structure and MFEI values of > 0.70.…”

Integrated transcriptome and small RNA sequencing in revealing miRNA-mediated regulatory network of floral bud break in Prunus mume

“…Genes were mapped to Gene Ontology (GO) terms of biological progress (BP), molecular function (MF), and cell component (CC) in the GO database (Gene Ontology Consortium, 2004). GO terms with FDR corrected p-values < 0.05 were considered as significantly enriched in hypergeometric tests (Yan et al, 2020). P-values were calculated as follows:…”