Identification of novel drought-responsive lncRNAs in stone apple (Aegle marmelos L.) through whole-transcriptome analysis

Stone apple (Aegle marmelos L.) is a subtropical fruit tree of the Rutaceae family, highly valued in traditional medicine across the Indian subcontinent. We conceived this study with the objective of developing a comprehensive transcriptome dataset, identifying SSRs for marker-assisted breeding, and delineating regulators of gene expression, with a specific emphasis on non-coding RNA (ncRNA), particularly related to drought stress. To achieve this, RNA-seq was conducted using RNA pooled from various tissues, including roots, leaves, inflorescence, and developing seeds from stone apple, and the clean reads were assembled into 40,886 unigenes. Subsequently, the unigenes were categorized into gene ontology categories encompassing biological processes, molecular functions, and cellular components. Within the unigenes, we identified a total of 9,174 perfect simple sequence repeats (SSRs), 2,167 transcription factors (TFs) distributed among 69 families, and 415 transcription regulators (TRs) across 27 families. Additionally, 19 microRNAs (miRNAs) from 12 families, 16,811 potential long noncoding RNAs (lncRNAs), and six functional endogenous target mimics (eTMs) were detected. Analysis of lncRNA-miRNA-mRNA interactions unveiled multiple regulatory nodes, elucidating lncRNA/miRNA-driven gene expression control in stone apple. The increased co-expression of selected drought-related lncRNAs and their cognate target mRNAs supported the aforementioned findings under drought conditions. Overall, this study significantly advances our understanding of stone apple genomics and lays a foundation for future omics-based studies, thereby facilitating the deployment of climate-resilient strategies in the species.