Cotton Genomics and Genetics 2025, Vol.16, No.6, 278-289 http://cropscipublisher.com/index.php/cgg 287 Meanwhile, the integration of transcriptome and ChIP-seq studies further revealed that transcription factors such as WRKY, MYB, and NAC, especially GhWRKY41 and GHWRKY1-like proteins, play a key role in regulating lignification and phenylpropanin metabolism. Comparative proteomics results show that resistant varieties respond more rapidly and harmonically in terms of defense protein activation, metabolic reprogramming, and hormone signaling (jasmonic acid, salicylic acid, ethylene). It can be seen from this that resistance is not the product of a single gene, but rather the result of a high degree of coordination of the proteome in the spatiotemporal dimension. However, there are still many shortcomings in the research. The proteome of cotton is extremely complex. Polyploid structure, tissue specificity, and various post-translational modifications (PTMs) all make comprehensive coverage difficult. At present, many experiments still rely on two-dimensional electrophoresis (2-DE), whose resolution and dynamic range are significantly inferior to new techniques such as LC-MS/MS or DIA. Furthermore, the lack of a unified proteome database and standardized procedures for cotton makes it difficult to compare data from different laboratories. The functional annotations of a large number of identified proteins are still incomplete. In addition, most studies only focus on a certain stage or tissue of infection, and the temporal and spatial resolution of pathogen-host interaction is limited. Although single-cell proteomics, spatial omics and other methods have emerged, they are still rare in the cotton system. More importantly, although PTMs such as phosphorylation, ubiquitination and glycosylation are crucial for the regulation of the activity of defense proteins, they have still been studied far from sufficient. Among the candidate resistance proteins that have been discovered, only a few have been verified by CRISPR, VIGS or overexpression. Looking ahead, the direction of cotton proteomics is quietly shifting, from single determination to multi-omics integration, and from phenomenon description to functional verification and application transformation. Combining the proteome with the genome, transcriptome, metabolome and phosphorylation group is expected to reconstruct the disease resistance network of cotton at the systemic level. New technologies such as DIA/SWATH-MS and single-cell proteomics will further enhance the detection sensitivity and spatiotemporal accuracy. Meanwhile, if these findings can be combined with CRISPR/Cas9 gene editing, RNAi interference and synthetic regulatory circuits, it will not only verify the functions of defense-related proteins such as Gh4CL3, GhLac1 and GhWRKY41, but also accelerate the process of disease-resistant breeding. From the perspective of breeding, resistance markers obtained through proteomic-genome integration are gradually becoming the core tools for marker-assisted selection (MAS) and genome selection (GS). With the integration of machine learning and artificial intelligence into the analysis process, the prediction and screening of resistance phenotypes will become more precise. Perhaps in the near future, we will be able to rely on data-driven breeding models to cultivate cotton varieties that are both high-yielding and have long-lasting resistance without the need for chemical agents, achieving true sustainable improvement. Acknowledgments We are grateful to Mrs. Xu for critically reading the manuscript and providing valuable feedback that improved the clarity of the text. Conflict of Interest Disclosure The authors affirm that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest. References Bawa G., Liu Z., Zhou Y., Fan S., Ma Q., Tissue D., and Sun X., 2022, Cotton proteomics: dissecting the stress response mechanisms in cotton, Frontiers in Plant Science, 13: 1035801. https://doi.org/10.3389/fpls.2022.1035801 Cheng J.H., and Zhang J., 2025, High-yield cotton cultivation practices in arid regions, Molecular Soil Biology, 16(1): 27-36. https://doi.org/10.5376/msb.2025.16.0003 Feng Z., Wei F., Feng H., Zhang Y., Zhao L., Zhou J., Xie J., Jiang D., and Zhu H., 2023, Transcriptome analysis reveals the defense mechanism of cotton against Verticillium dahliae induced by hypovirulent fungus Gibellulopsis nigrescens CEF08111, International Journal of Molecular Sciences, 24(2): 1480. https://doi.org/10.3390/ijms24021480
RkJQdWJsaXNoZXIy MjQ4ODYzNA==