Cotton Genomics and Genetics 2025, Vol.16, No.5, 222-231 http://cropscipublisher.com/index.php/cgg 222 Research Insight Open Access Multi-Trait GWAS for Fiber Quality and Disease Resistance in Cotton Shanjun Zhu, Mengting Luo Institute of Life Science, Jiyang College of Zhejiang A&F University, Zhuji, 311800, China Corresponding email: mengting.luo@jicat.org Cotton Genomics and Genetics, 2025, Vol.16, No.5 doi: 10.5376/cgg.2025.16.0022 Received: 11 Jul., 2025 Accepted: 22 Aug., 2025 Published: 13 Sep., 2025 Copyright © 2025 Zhu and Luo, This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Zhu S.J., and Luo M.T., 2025, Multi-trait GWAS for fiber quality and disease resistance in cotton, Cotton Genomics and Genetics, 16(5): 222-231 (doi: 10.5376/cgg.2025.16.0022) Abstract Cotton is a globally important dual-purpose crop valued for its fiber yield, but both its yield and quality are severely impacted by a variety of pathogens. This study reviews the genetic architecture of fiber quality traits (such as strength, length, and fineness) and resistance to major diseases such as Verticillium wilt, Fusarium wilt, and bacterial wilt, focusing on potential genetic overlap and independence. We explore the methodological framework for multi-trait genome-wide association studies (MT-GWAS), highlighting statistical models such as multivariate linear mixed models and Bayesian methods, which outperform single-trait analyses by capturing pleiotropic loci and genetic correlations. We present key findings from cotton MT-GWAS, including the identification of co-localized QTLs, novel candidate genes, and genotype-by-environment interactions across multiple environmental datasets. We also highlight the integration of MT-GWAS with transcriptomic, metabolomic, epigenomic, and proteomic data, and the validation of functional genes using CRISPR, RNAi, and overexpression technologies. A case study demonstrates the practical application of MT-GWAS in a breeding program targeting fiber quality and disease resistance, enabling genetic validation and germplasm improvement. While MT-GWAS faces challenges such as population structure, statistical complexity, and translational gaps, advances in high-resolution phenotyping, pan-genomics, and predictive breeding strategies hold promise for broader application. This study highlights the potential of MT-GWAS to accelerate cotton improvement by revealing complex trait architecture and informing integrated breeding processes. Keywords Multi-trait GWAS; Fiber quality; Disease resistance; Cotton breeding; Pleiotropy 1 Introduction Globally, if one were to look for a crop that is extremely important for both the agricultural economy and the textile industry, cotton (Gossypiumspp.) would probably be the most prominent example. It provides over 95% of the natural fiber output and builds the livelihood foundation for countless farmers and enterprises (Su et al., 2018; Thyssen et al., 2018). The continuous pursuit of high-quality fibers determines its commercial value and makes its position in the industrial chain unshakable (Sun et al., 2017). But things are not that simple. During the planting process, common diseases such as Fusarium wilt and Fusarium wilt often recur, not only affecting the yield but also directly lowering the quality of fibers, ultimately impacting profits and supply stability. Although traditional breeding efforts have been considerable, most of them have focused on improving fiber quality or enhancing disease resistance, with few achievements that balance both (Cheng and Zhang, 2025). One of the reasons is that the genetic regulatory networks behind these two traits are rather complex, and sometimes there is a situation of "one rising and the other falling" (Wang et al., 2021). Especially in the context of constantly changing environments and evolving pathogenic bacteria, the improvement of single traits is becoming increasingly inadequate. In recent years, multitrait GWAS analysis and QTL mapping techniques have gradually demonstrated their advantages, beginning to reveal some pleomorphic loci and key candidate genes that not only affect fiber quality but also participate in disease resistance. This has opened up new ideas for molecular breeding and also made the practice of marker-assisted selection more targeted. This study does not intend to focus merely on a single trait. On the contrary, we aim to systematically review the genetic research progress made over the years in the improvement of the dual traits of "fiber quality + disease resistance", especially the key achievements from multi-trait GWAS and QTL. In addition, the economic value and agronomic significance of such research will be briefly discussed to see how upland cotton and island cotton
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