Cotton Genomics and Genetics 2025, Vol.16, No.5, 222-231 http://cropscipublisher.com/index.php/cgg 224 are suitable for mixed analysis-provided that there must be a certain genetic correlation among these traits; otherwise, the advantages of MT-GWAS cannot be brought into play. 3.2 Statistical models used in MT-GWAS MT-GWAS not only has to deal with multiple traits but also has to confront a vast amount of genotype data, so the statistical models behind it must be more powerful. At present, the most widely used model is the multilinear mixed model (mvLMM), because it can consider both fixed effects and random effects simultaneously, and also handle population structure problems and the relationships between traits (Lozano et al., 2023). Some researchers prefer Bayesian methods, such as Bayesian LASSO and EM-Bayesian LASSO. These models are more flexible in variable screening and suitable for high-dimensional data, especially in cases where the trait structure is relatively complex (Tamba et al., 2017; Wen et al., 2018). In recent years, some new models have been proposed, such as regularized versions of multi-trait hybrid models and multi-locus models. They have further enhanced computational efficiency and improved detection performance in certain scenarios. Figure 1 Functional Analysis of GhAMT2 in enhancing resistance to Verticillium Wilt in Cotton and Arabidopsis. (a) Relative transcript levels of GhAMT2 in TRV-VIGS cotton leaves for TRV: EV (empty vector) and TRV: GhAMT2 plants, with GhActin serving as the internal reference gene. Expression levels were normalized to “1” for TRV: EV; (b) Silencing of GhAMT2 reduces cotton resistance to Verticillium dahliae, as evidenced by increased disease symptoms onTRV: GhAMT2plants compared toTRV: EV plants 25 days post-infection; (c) Statistical analysis of the disease index in GhAMT2-silenced plants, showing a significant increase compared to controls; (d) Relative biomass of V. dahliae in TRV: GhAMT2 and TRV: EV plants, illustrating higher pathogen colonization in GhAMT2-silenced plants; (e) GhAMT2 promotes the expression of lignin metabolism-related genes in cotton. Expression analysis of lignin biosynthesis genes showed upregulation in the presence of GhAMT2; (f) Identification of transgenic Arabidopsis plants overexpressing GhAMT2. Semi-quantitative RT-PCR analysis demonstrates GhAMT2 mRNA levels in three transgenic lines compared to WT (Col-0); (g) Overexpression of GhAMT2 enhances Arabidopsis tolerance to Verticillium dahliae, as evidenced by reduced disease symptoms in transgenic lines compared to WT; (h) Statistical analysis of the disease index in WT and OE-GhAMT2Arabidopsis plants, showing significantly lower disease indices in transgenic lines. *, 0.01<P<0.05; **, P< 0.01; ***, P< 0.001 (Adopted from Wang et al., 2025) 3.3 Advantages of MT-GWAS in revealing pleiotropic loci and genetic correlations Compared with the traditional single-trait GWAS, the benefits of MT-GWAS are obvious. As long as there is a moderate or higher genetic correlation among the analyzed traits, this method can often detect the related genes
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