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Abstract Global crop production faces increasing threats from the rise in frequency, duration, and intensity of drought and heat stress events due to climate change. Most staple food crops, including wheat, rice, soybean, and corn that provide over half of the world’s caloric intake, are not well adapted to withstand heat or drought. Efforts to breed or engineer stress-tolerant crops have had limited success due to the complexity of tolerance mechanisms and the variability of agricultural environments. Effective solutions require a shift towards fundamental research that incorporates realistic agricultural settings and focuses on practical outcomes for farmers. This review explores the genetic and environmental factors affecting heat and drought tolerance in major crops, examines the physiological and molecular mechanisms underlying these stress responses, and evaluates the limitations of current breeding programs and models. It also discusses emerging technologies and approaches that could enhance crop resilience, such as synthetic biology, advanced breeding techniques, and high-throughput phenotyping. Finally, this review emphasizes the need for interdisciplinary research and collaboration with stakeholders to translate fundamental research into practical agricultural solutions. 

ABSTRACT For most species, transcriptome data are much more readily available than genome data. Without a reference genome, gene calling is cumbersome and inaccurate because of the high degree of redundancy in de novo transcriptome assemblies. To simplify and increase the accuracy of de novo transcriptome assembly in the absence of a reference genome, we developed UnigeneFinder. Combining several clustering methods, UnigeneFinder substantially reduces the redundancy typical of raw transcriptome assemblies. This pipeline offers an effective solution to the problem of inflated transcript numbers, achieving a closer representation of the actual underlying genome. UnigeneFinder performs comparably or better, compared with existing tools, on plant species with varying genome complexities. UnigeneFinder is the only available transcriptome redundancy solution that fully automates the generation of primary transcript, coding region, and protein sequences, analogous to those available for high‐quality reference genomes. These features, coupled with the pipeline’s cross‐platform implementation, focus on automation, and an accessible, user‐friendly interface, make UnigeneFinder a useful tool for many downstream sequence‐based analyses in nonmodel organisms lacking a reference genome, including differential gene expression analysis, accurate ortholog identification, functional enrichments, and evolutionary analyses. UnigeneFinder also runs efficiently both on high‐performance computing (HPC) systems and personal computers, further reducing barriers to use.