Bioscience Method 2024, Vol.15, No.1, 8-19 http://bioscipublisher.com/index.php/bm 11 population structure. GCTA (Genome-wide complex trait analysis) is another popular tool specifically used to estimate the contribution of genetic variation to trait variance and perform population structure correction. In addition, software such as Admixture, Eigenstrat and Structure can be used to analyze population structure, and FastLMM Tools such as Factored spectrally transformed linear mixed models are used to handle mixed linear model analysis (Ceballos et al., 2015). The choice of statistical methods and computational tools for GWAS depends on the specific needs of the study, including the type of trait, the genetic background of the sample, and the goals of the study. Correct application of these methods and tools can effectively identify genetic variants associated with traits, providing strong support for understanding the genetic basis of traits. 2 The Role of GWAS in the Study of Crop Genetic Diversity 2.1 GWAS reveals genetic basis of crop traits Genome-wide association studies (GWAS) play an extremely important role in the study of crop genetic diversity. It provides an efficient and powerful method to reveal the genetic basis behind crop traits. Through GWAS, scientists can identify genetic variations related to important agronomic traits, such as yield, stress resistance (including drought resistance, salt-alkali resistance), disease resistance, and quality characteristics, across the entire crop genome . This process not only deepens our understanding of crop genetic diversity, but also provides powerful molecular tools for crop improvement, greatly promoting the development of precision breeding technology. The application of GWAS allows scientists to discover new and beneficial genetic variations in a wide range of crop populations, including traditional varieties, landraces and wild relatives. These genetic resources are valuable assets for crop improvement, and they can be used to develop new varieties that are adapted to different environmental conditions and have high yield and quality traits. For example, in rice and wheat, multiple key genes or gene regions related to yield and disease resistance have been successfully identified through GWAS. These findings not only enhance crop genetic diversity but also improve crop productivity and sustainability (Ceballos et al., 2015). In addition, GWAS also provides a new perspective on understanding the genetic mechanisms of crop traits. By analyzing the association between traits and genetic variation, researchers can uncover the gene networks and regulatory pathways that control complex traits, thereby gaining a deeper understanding of the genetic and molecular basis of traits. This is particularly important for the study of crop adversity stress responses because it involves the interaction of multiple genes and environmental factors (Abdelraheem et al., 2021). Through GWAS, researchers can identify key genetic factors that affect crop phenotypes under specific environmental conditions, providing guidance for environmental adaptability and stress-resistant breeding of crops. Although GWAS has shown great potential in studying crop genetic diversity, its application also faces challenges, including the need for a large number of samples to enhance the statistical power of the study, handling the complexity brought by population structure and genetic background diversity, and the need to extract data from massive amounts of samples. Genetic variation identifies factors that actually influence traits. However, with the advancement of high-throughput sequencing technology, improvements in data analysis methods, and the development of bioinformatics tools, the application of GWAS in the study of crop genetic diversity will become more extensive and in-depth. In the future, GWAS is expected to further promote the process of crop molecular breeding and achieve precise improvement of crop traits and sustainable development of agricultural production. 2.2 Application of GWAS in the study of crop genetic diversity GWAS have made significant progress in the study of genetic diversity in many crops, especially in revealing genetic loci associated with important agronomic traits. Several successful case studies are introduced below, demonstrating the application results of GWAS in crop genetic diversity research.
RkJQdWJsaXNoZXIy MjQ4ODYzMg==