Molecular Plant Breeding 2024, Vol.15, No.2, 52-62 http://genbreedpublisher.com/index.php/mpb 56 For example, in cotton breeding, one of the challenges faced by conventional breeding is the narrowing of genetic diversity, which limits the potential for crop improvement. Traditional approaches are based on the evaluation and selection of phenotypic variants, relying on visible or measurable traits such as morphological and cytological markers. However, these methods have limited information content and are not sufficient to solve the problem of improving complex traits. In contrast, GWAS uses DNA molecular markers, such as SNPs, to provide more genetic information and reveal genes or regions that control important agronomic traits in crop genomes, thereby accelerating the improvement of crop traits (Figure 1) (Kushanov et al., 2021). Figure 1 Comparison of marker-assisted selection with traditional breeding, P1 and P2-parental genotypes, F1-first generation cross, Fn-hybrid progeny obtained from the first generation by self-pollination and BCn-backcross generation (Adopted from Kushanov et al., 2021) Compared with traditional breeding methods, GWAS provides an efficient and precise way to identify and utilize genetic variation that affects crop traits. By using GWAS strategies, breeders can more effectively utilize crop genetic resources, accelerate the improvement of crop stress resistance traits, and meet the needs of agricultural production. Although GWAS has significant advantages, combining the advantages of traditional breeding methods with the accuracy of GWAS, using a multi-strategy integrated breeding approach will be a key approach to future crop improvement. 3.3 Advantages and limitations of GWAS in crop genetic research When exploring the advantages and limitations of genome-wide association studies (GWAS) in crop genetic research, we found that GWAS provides a powerful tool that can reveal the genetic basis of complex traits. GWAS identify genotypes associated with specific traits by testing the genomes of multiple individuals in a population for genetic variation. Although this method has made important progress in revealing the genetic mechanisms of crop stress resistance traits, there are also some limitations that need to be noted. With traditional QTL (quantitative trait loci) mapping, GWAS provide higher resolution and can detect historical recombination events, thereby revealing genomic regions associated with numerous physiological, agronomic and adaptive traits. This is especially obvious in plants, such as corn, rice, soybean, sesame, etc., where GWAS has been successfully used to study complex traits such as plant height, flowering time, seed number, stress resistance traits, and grain yield (Figure 2) (Berhe et al., 2021).
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