Standardized Workflow for Long Noncoding RNA Prediction and Expression Profiling in Wheat Under Stem Rust Stress

Long noncoding RNAs (lncRNAs), typically over 200 nucleotides in length, with low or no coding capacity, possess significant regulatory roles in plant growth, development, and stress responses by interacting with DNAs, proteins, and other RNAs. This chapter outlines a comprehensive protocol for identifying and functionally characterizing wheat lncRNAs under stem rust infection. The workflow includes plant growth, pathogen inoculation, RNA isolation, and whole-transcriptome sequencing of wheat. In-silico approaches for data preprocessing, transcriptome assembly and subsequent characterization, and differential expression analysis of candidate lncRNAs are described. The chapter systematically explains the functional analyses performed to detect the lncRNAs as microRNA precursors and targets using sequence homology search and target prediction tools, detect transcription factor binding sites and SSR marker motifs within the lncRNAs through motif scanning and microsatellite detection tools, and assess the lncRNA-mRNA interactions using interaction prediction analyses. qRT-PCR validation of selected lncRNAs supporting in-silico findings is also mentioned. In contrast to conventional methods for studying plant-pathogen interactions that largely focus on protein-coding genes, the approach outlined, in this chapter, presents a comprehensive pipeline for identification and functional interpretation of novel regulatory lncRNAs, making it applicable for exploring ncRNA-mediated regulations in rust-infected wheat and related pathosystems.