The ability of plants to adapt to rapidly changing environments depends on gene regulatory mechanisms that control stress perception, signaling, and short- and long-term responses. Transcriptomics has become a key tool for elucidating these adaptive processes, enabling researchers to capture the dynamic gene reprogramming of plants under abiotic and biotic stresses. This chapter provides an in-depth overview of transcriptomic technologies and their application in plant stress research. We trace the evolution of transcriptomic techniques, from Northern blotting and RT-qPCR to RNA-sequencing, single-cell RNA-seq, and spatial transcriptomics, and discuss how these tools have advanced our understanding of plant adaptive mechanisms. Particular focus is given to the identification of differentially expressed genes, transcription factors, alternative splicing events, and gene regulatory networks (GRNs) that mediate plant responses to drought, salinity, temperature extremes, flooding, nutrient deficiencies, herbivory, and pathogens. We further highlight how comparative transcriptomics across species and populations reveals both conserved and divergent molecular strategies for adaptation, with special attention to the evolutionary plasticity of GRNs. The chapter also explores the impact of beneficial plant-associated microbiomes, including rhizobacteria and mycorrhizal fungi, on host transcriptomic landscapes, emphasizing the potential of microbial interactions to reprogram plant gene expression and enhance stress tolerance. Finally, we discuss emerging trends in integrating transcriptomic data with multiomics approaches and machine learning, which offer powerful avenues for predictive modeling of gene function and stress-responsive networks.