Scientific Journal

Identification, Functional Prediction, and Expression Analysis of Long Non-Coding RNAs in Lentil (Lens culinaris L.) Under Salt Stress

Document Type : Original Article

Authors

Department of Plant Production and Genetic Engineering, Faculty of Agriculture, Lorestan University, Khorramabad, Iran

10.22034/pgr.2025.2081840.1027
Abstract
Throughout evolution, plants have developed complex molecular mechanisms to cope with biotic and abiotic stresses, many of which are driven by the reprogramming of gene expression. Multiple genetic factors regulate the molecular responses of plants to unfavorable environmental conditions, among which long non-coding RNAs (lncRNAs) play a significant role. LncRNAs play a pivotal role in regulating gene expression, epigenetic modifications, and signaling pathways, significantly contributing to responses against both biotic and abiotic stresses. In this study, for the first time, the identification, functional determination, and expression analysis of LncRNAs in lentil (Lens culinaris L.) under salt stress conditions were investigated. LncRNAs were identified using the lentil transcriptome reference, which was generated by assembling RNA sequencing data from the leaf and root tissues of lentil under both stress and control conditions. After filtering protein-coding sequences, several lncRNA sequences were identified using PLncPRO software. The relative expression levels of the identified sequences were measured, and the co-expression network with differentially expressed genes (DEGs) was constructed. To validate the RNA-seq data, the expression of selected lncRNAs was analyzed by qRT-PCR. The processing and refinement of the expression profile of lentil under salt stress resulted in the identification of 7677 lncRNA sequences, with 722 sequences being identified for the first time in lentil. Gene expression analysis revealed that 90 sequences in leaf tissue and 48 in root tissue showed increased expression under salt stress. Functional analysis of the co-expressed genes indicated that these genes were involved in biological processes such as translation, ion transport, and stress response. Metabolic pathway enrichment analysis identified 18 significant pathways, including S-adenosyl-L-methionine cycle, abscisic acid biosynthesis, and cytosolic glycolysis. The qRT-PCR validation confirmed the correlation of RNA-seq and qRT-PCR results with a 95% correlation coefficient. In conclusion, the results of this study revealed that the identified lncRNAs play a significant role in regulating key genes involved in essential metabolic pathways in lentil's molecular response to salt stress. Identifying and analyzing these lncRNAs in lentil can provide a better understanding of the molecular mechanisms underlying these stress responses. Investigating the interactions of these identified RNAs with other regulatory molecules, such as ABA and protein-coding genes, could contribute to the development of breeding strategies aimed at improving lentil’s tolerance to both biotic and abiotic stresses.

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