Long non-coding RNA landscape and ceRNA networks underlying the drought response of Cannabis sativa L.

BACKGROUND: Drought is a major constraint on plant productivity, and long non-coding RNAs (lncRNAs) are increasingly recognized as key regulators of plant stress responses. Yet drought-responsive lncRNAs remain largely uncharacterized in Cannabis sativa L., a species of growing economic and medicinal importance. METHODS: We combined RNA-seq analysis of C. sativa leaves under progressive drought stress with physiological monitoring and independent qRT-PCR validation. A stringent identification pipeline integrating StringTie assembly with CPC2 and Pfam coding-potential filtering was applied, followed by differential expression analysis (DESeq2), cis-target prediction, functional enrichment, ceRNA network construction, and transcription-factor profiling. RESULTS: The pipeline yielded 2,096 high-confidence novel lncRNAs with the canonical structural signatures of plant lncRNAs - shorter length, simpler exonic architecture, and lower steady-state expression than mRNAs. Differential expression analysis identified 51 high-confidence differentially expressed lncRNAs and 575 differentially expressed mRNAs in response to drought. Functional enrichment of predicted lncRNA cis-targets highlighted phenylpropanoid and lignin biosynthesis, abscisic acid signaling, and vacuolar ion transport as dominant themes. Transcription-factor profiling revealed a striking over-representation of FAR1-family regulators among lncRNA targets. A DEL-anchored ceRNA sub-network further uncovered two candidate regulatory modules, both showing directionally concordant qRT-PCR expression profiles. CONCLUSIONS: These results provide the first systematic characterisation of polyA-selected, leaf-expressed drought-responsive lncRNAs in C. sativa, propose a hypothesis of lncRNA-mediated light-drought crosstalk via FAR1/FHY3 regulators, requiring future functional validation, and nominate candidate regulatory nodes for future functional studies and stress-resilience breeding.