Revolutionizing Cotton Leaf Curl Disease Detection: CRISPR-Based Diagnostics for Rapid, Field-Deployable Solutions

Cotton leaf curl disease (CLCuD) continues to cause severe yield losses across South Asia and China, driven by a complex of begomoviruses and betasatellites vectored by Bemisia tabaci. Conventional diagnostics such as PCR, qPCR, and ELISA remain useful in laboratory settings but are constrained by cost, infrastructure requirements, and limited applicability to diverse and recombinant viral strains. Isothermal amplification methods (LAMP, RPA) improve portability and speed but face issues of specificity, cross-reactivity, and primer design challenges in the context of CLCuD’s evolving virome. CRISPR-based diagnostics (CRISPR-Dx) offer a new frontier in plant virology, combining single-nucleotide specificity, attomolar sensitivity, and field-friendly readouts including fluorescence, colorimetric signals, and lateral-flow assays. Proof-of-concept CRISPR assays have been validated in plant systems such as apple, grapevine, and maize, and adapted to closely related begomoviruses including tomato yellow leaf curl virus (TYLCV) and tomato leaf curl New Delhi virus (ToLCNDV). These precedents demonstrate the feasibility of developing CLCuD-specific assays, though no peer-reviewed cotton-specific CRISPR diagnostic has yet been established. This review synthesizes the current landscape of geminivirus diagnostics, critically evaluates CRISPR-Dx platforms (DETECTR, SHERLOCK, AIOD-CRISPR), and identifies research priorities for adapting them to CLCuD. We emphasize key gaps including genetic diversity, multiplexing, reagent stability, field validation, and regulatory pathways. By integrating smartphone-based readouts, GIS-linked surveillance, and farmer-accessible test formats, CRISPR diagnostics could accelerate early detection and support sustainable cotton production in endemic regions.