Cotton Genomics and Genetics 2025, Vol.16, No.6, 278-289 http://cropscipublisher.com/index.php/cgg 286 In addition, the analysis of phosphorylation and acetylation proteomes also revealed more microscopic-level regulations, such as the activation, localization and degradation patterns of proteins during pathogen infection (Wu et al., 2021). Coupled with systems biology tools such as weighted co-expression network analysis (WGCNA) or PPI networks, researchers can now identify the "central nodes" that regulate defense systems more quickly (Zhang et al., 2025). These interwoven data networks are gradually providing actionable resistance biomarkers for cotton molecular breeding. 7.2 Functional validation and genetic engineering Identifying defense proteins is just the beginning. What exactly they "do in the body" still needs to be verified through experiments. To establish a true causal relationship, functional research is still needed. Researchers typically validate the functions of candidate proteins in cotton or model plants (such as Arabidopsis thaliana and tobacco Bursa) using virus-induced gene silencing (VIGS), gene overexpression, or RNA interference (RNAi) (Liu et al., 2022). Many genes have been verified to be closely related to resistance, such as those encoding PR protein, antioxidant enzymes and components of the phenylpropanin metabolic pathway. After artificial regulation, the disease resistance of cotton has been significantly enhanced. Furthermore, the precise editing of CRISPR/Cas9 makes it possible to regulate defense factors (such as WRKY, MYB, NAC and other transcription factors), thereby making the regulation of immune responses more controllable. In addition, the ideas of synthetic biology are also entering this field. By constructing regulatory circuits that can respond to pathogen signals, dynamic expression of defense genes can be achieved. This approach, combined with proteomics results, is bridging the gap between "laboratory mechanisms" and "field performance", making the application of cotton biotechnology more practical. 7.3 High-throughput applications in breeding Over the past few years, high-throughput technology has completely transformed the way proteomics works. Label-free quantification and the DIA/SWATH-MS platform enable researchers to detect thousands of proteins in a single experiment and compare the differences between disease-resistant and susceptible varieties. More importantly, these proteomic features can be directly associated with disease-resistant phenotypes, thus making the data "breeding". When these results are combined with quantitative trait loci (QTL) mapping or genome-wide association studies (GWAS), the recognition speed of resistance-related proteins and molecular markers is greatly enhanced, and the efficiency of marker-assisted selection (MAS) and genomic selection (GS) also improves accordingly. Nowadays, the construction of cotton proteome databases and the introduction of AI algorithms have opened up new channels for research. Machine learning can help identify patterns, predict resistance traits, and integrate complex omics data (Luqman et al., 2025). This data-driven approach is leading us from "seeing changes" to "predicting changes", providing a practical path for designing cotton varieties with broad-spectrum and long-lasting resistance in the future. 8 Concluding Remarks Over the past decade, the research on cotton resistance to the Variegata has almost been completely reshaped by "omics". The introduction of proteomics has enabled us for the first time to observe the true dynamics of the defense system at the molecular level, those protein networks that are activated, rearranged and rebalance during the infection process. Researchers have found that the upregulation of disease-related proteins (PR), antioxidant enzymes, and secondary metabolism-related enzymes is the most prominent indicator of the entire resistance response. They work together to strengthen the cell wall, eliminate reactive oxygen species (ROS), and reduce oxidative damage, forming the core barrier for cotton to resist pathogens. The significance of the phenylpropanin metabolism and lignin synthesis pathways has also been repeatedly confirmed. These two pathways maintain the integrity of the vascular bundles and limit the range of pathogen spread.
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