Cotton (Gossypium spp.) is a vital global crop, essential for both fiber and oil production, contributing significantly to the agricultural economy. However, its productivity is increasingly compromised by a range of biotic stresses, particularly viral diseases. Among these, CLRDV poses a substantial threat to cotton cultivation, resulting in significant yield reductions (Edula et al., 2023, Heilsnis et al., 2023). CLRDV is a member of the genus Polerovirus in the family Solemoviridae, and is an emerging pathogen with rapid evolution in cotton-producing regions, particularly in the United States (Edula et al., 2023). It is phloem-limited and transmitted by the cotton aphid (Aphis gossypii), resulting in symptoms such as leaf curling, dwarfing, reddening of foliage, and yield loss in infected plants (Ali et al., 2020, Avelar et al., 2020, Edula et al., 2023). Due to the overlapping symptoms of cotton blue disease (CBD) and Cotton Leafroll Dwarf Disease (CLRDD), attention must be paid to symptomatology, and accurate identification should be confirmed through molecular diagnostics to avoid misleading etiological discrepancies between CLRDD and CBD. Recent research on CLRDV has revealed considerable adverse effects on cotton physiology and productivity. For example, a field study in Georgia found that CLRDV infection significantly reduces photosynthetic rate (63–101 %), stomatal conductance (65–99 %), and thylakoid response efficiency in symptomatic cotton plants (32–92 %) (Parkash et al., 2021). Interestingly, asymptomatic cultivars exhibited more conservative gas exchange responses than apparently healthy symptomatic cultivars, indicating potential tolerance mechanisms that should be investigated further. Moreover, the absence of strong genetic resistance, along with CLRDV's wide host range, its ability to survive on overwintering cotton, and its genetic diversity (Sedhain et al., 2021), including early detection in cotton samples.

Early and accurate detection of CLRDV in cotton tissues is critical for effective disease management. Therefore, there is a need for simple, reliable, and sensitive diagnostic methods that can detect the virus at early stages of infection. Traditional plant virus detection approaches, such as RT-PCR and sequencing, are highly sensitive and sequence-specific; however, theyare largely restricted to well-equipped laboratories and require trained personnel (Mehetre et al., 2021). Antibody-based assays, such as enzyme-linked immunosorbent assay (ELISA), offer a relatively faster and simpler alternative, but they still depend on laboratory infrastructure and cannot be readily used in true field conditions. Moreover, ELISA typically has lower specificity compared to nucleic acid-based methods. For some plant viruses, commercial kits such as lateral flow immunoassay strips (LFAs) are available. They work similarly to the ELISA technique, based on the interaction of antigen and antibody, resulting in the formation of a visible signal, usually in the form of a color band, making them convenient to use. However, they lack specificity and may produce false-positive or false-negative results, which reduces the reliability of the diagnosis.

In recent years, digital PCR (dPCR) has emerged as a powerful tool for plant virus detection, including for pathogens like Cotton leafroll dwarf virus (CLRDV) (Mehraj et al., 2025). Unlike conventional PCR, dPCR partitions the sample into thousands of individual reactions, enabling the precise quantification of viral copies. This sensitivity allows for the early detection of viral infections, even before symptoms are visible, facilitating timely interventions (Sedlak and Jerome, 2013). For viruses like CLRDV, early and accurate detection is critical for effective disease management, supporting field surveillance, evaluating control strategies, and guiding breeding programs aimed at developing resistant cotton varieties. As illustrated in Fig. 1B, the workflow begins with RNA extraction from infected cotton leaves, which is then reverse transcribed into cDNA and subjected to dPCR. Using CLRDV-specific probes and primers, each droplet functions as an independent reaction unit, and fluorescence-positive droplets signify the presence of viral RNA, providing a precise measurement of viral load.

Recently, the CRISPR-based SHERLOCK method has been developed as a rapid, sensitive, and equipment-independent approach to detect viral nucleic acids (Gootenberg et al., 2017). While this method has been widely used for human pathogens, its implementation for plant virus detection is still emerging (Freije and Sabeti, 2021, Wolter and Puchta, 2018). In plants, the presence of complex inhibitors in tissue extracts and the wide diversity of viral strains pose challenges for diagnostic sensitivity and specificity. Targeting conserved genomic regions is a key strategy to ensure broad detection across viral variants (Edula et al., 2023, Tabassum et al., 2021).

These improvements in CRISPR-based diagnostics provide an alternate technique for the rapid and sensitive identification of plant viruses (Chertow, 2018, Wolter and Puchta, 2018). Currently, CRISPR/Cas12 technology has been utilized to detect numerous plant viruses with DNA as genetic material (Aman et al., 2020, Mahas et al., 2022, Marqués et al., 2021, Xu and Yuan, 2025). The newly developed CRISPR/Cas13a approach employs the CRISPR-associated 13a (Cas13a) protein to recognize complementary RNA sequences within the RNA viral genome (Karimi et al., 2025, Schindele et al., 2018). In addition to the sequence-specific digestion, Cas13 binds to its targets, activates them, and facilitates the non-specific collateral cleavage of single-stranded (ss)RNA molecules (Freije and Sabeti, 2021). Thus, CRISPR-based diagnostic systems take advantage of the unique non-specific collateral cleavage (trans-cleavage) activity that is triggered upon recognition of a specific nucleic acid target. In this approach, a CRISPR RNA (crRNA) binds with Cas13a to form a ribonucleoprotein (RNP) complex. Once the complex locates and binds to its complementary target sequence, referred to as cis cleavage, it activates the Cas protein’s trans-cleavage function. This leads to the nonspecific cleavage of nearby reporter molecules, typically fluorescently labelled single-stranded RNA probes (FAM-labelled probes). As the probe is cleaved, the fluorophore is separated from its quencher, producing a detectable fluorescent signal that can be measured quantitatively for detection (Fig. 1C-D) (Gootenberg et al., 2017, Hak et al., 2024, Sahel et al., 2024). With this system, viral RNA sequences can be detected with high sensitivity and specificity without the need for complicated equipment. Furthermore, a few studies have been conducted on Cas13's potential for plant virus diagnosis. For instance, Cas13 can be used for direct, amplification-free detection of plant RNA viruses due to its ability to bind directly to certain RNA molecules (Wolter and Puchta, 2018).

In this study, we evaluated multiple diagnostic methods for detecting CLRDV, including conventional RT-PCR, digital PCR (dPCR), and a CRISPR/Cas13a-based fluorescent assay. The graphical abstract represented in Fig. 1 shows the workflow of the two assays. Samples can be collected from symptomatic plants (Fig. 1A) for absolute quantification digital PCR can be used (Fig. 1B), for rapid detection CRISPR/Cas13a-based fluorescent assay can be applied (Fig. 1C-D). While RT-PCR remains a traditional tool for detection, it is limited by accuracy, time consuming, and reliance on specialized lab infrastructure. Digital PCR demonstrated superior accuracy and sensitivity for viral quantification, particularly in low-titer samples, but requires expensive equipment. Among the methods tested, the CRISPR/Cas13a-based fluorescent assay emerged as the most practical for rapid, sensitive, and field-deployable detection. It enabled direct detection of CLRDV from crude leaf RNA extracts without the need for specific reagents or kits for RNA extraction or thermal cycling. This approach holds great promise for use in resource-limited settings, offering a cost-effective and user-friendly alternative to traditional molecular tools. Our findings highlight the potential of multiplexed CRISPR/Cas13a diagnostics targeting conserved viral genome positions for early detection and timely management of viral infections in cotton.