Field Crop 2024, Vol.7, No.1, 9-16 http://cropscipublisher.com/index.php/fc 11 Figure 2 Genome-wide association study methods for improving computational speed and statistical power (Cortes et al., 2021) GWAS technology was born from several key technological advances: The development of high-throughput genotyping techniques made it possible to analyze genome-wide genetic variation in large numbers of samples at a reasonable cost. The creation of public databases and genetic information resources, such as the human genome project (HGP) and the HapMap Project, has provided GWAS with essential reference sequence and background genetic variation information. Advances in bioinformatics and statistical methods have provided tools for processing large-scale genetic data and complex statistical analyses. Early GWAS research focused on human genetic diseases, successfully identifying multiple disease-related genetic markers, such as susceptibility genes for type 2 diabetes, coronary artery disease, and multiple cancers, and these findings not only revealed the genetic basis of disease, but also provided new ideas for disease prediction, prevention, and treatment. Later, the application of GWAS technology was gradually expanded to the agricultural field, and important agronomic traits of crops, such as yield, resistance and quality, were studied (Cortes et al., 2021). In crop research, GWAS has helped scientists identify key genes and genetic markers associated with traits, providing targets for crop molecular breeding and gene editing. In recent years, with the further development of sequencing technology and the reduction of costs, GWAS has begun to evolve towards whole genome sequencing, which can capture genetic variation more comprehensively, improve the ability to find rare variants and resolve the genetic structure of complex traits, and integrate GWAS with other omics data, such as transcriptomic, proteomic and epigenetic data. It has become a new trend in current research. This multi-omics integration analysis is expected to further improve the analytical power of GWAS and reveal more complex genetic regulatory networks. 1.3 Application of GWAS in plant genetics The application of genome-wide association analysis (GWAS) in the field of plant genetics has become an important means to reveal the genetic basis of plant traits. Since the first successful application of GWAS technology in the study of human genetic diseases, its application in plant science has expanded rapidly, and now covers a wide range of research fields from crop yield and quality improvement to stress tolerance. By analyzing correlations between genetic variation and phenotypic traits, this technique enables genome-wide identification of genes or genetic markers associated with important agronomic traits. In terms of crop yield and quality improvement, GWAS has successfully identified many key genes that affect the yield and quality of food crops such as rice, wheat, maize, etc. These genes are involved in many aspects such as photosynthetic efficiency, nutrient absorption and utilization, grain size and component accumulation, and through the discovery and functional research of these key genes, scientists can carry out targeted molecular breeding to improve crop yield and quality (Liu and Yan, 2019). In the study of stress tolerance, GWAS technology also shows its strong potential. With the intensification of global climate change, crops are facing increasing biological and abiotic stress, such as drought, salinity, low temperature, pests and diseases. By identifying genes associated with these stress responses, GWAS technology
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