Legume Genomics and Genetics 2024, Vol.15, No.6, 270-279 http://cropscipublisher.com/index.php/lgg 271 This study aims to provide a comprehensive overview of the combined application of Genome-Wide Association Studies (GWAS) and Genomic Selection (GS) in soybean breeding. It will explore the advancements of these technologies, their application in the identification and selection of key agronomic traits, and the potential benefits of their integrated use in breeding programs. Additionally, the study will address the challenges and future directions in this field, offering insights on how to leverage these innovative approaches to meet the global demand for improved soybean varieties. The goal is to highlight the transformative potential of integrating GWAS and GS to enhance soybean breeding efforts. 2 Background on Soybean Breeding 2.1 Traditional breeding methods and their limitations Traditional soybean breeding methods primarily involve phenotypic selection, where plants are selected based on observable traits such as yield, plant height, and disease resistance. These methods have been effective in improving soybean varieties over the years but come with several limitations. One major limitation is the long breeding cycle, which can span several years due to the time required for plants to grow and express the desired traits. Additionally, phenotypic selection is often influenced by environmental factors, making it challenging to accurately select for genetic potential. The complexity of quantitative traits, which are controlled by multiple genes, further complicates the breeding process, as traditional methods may not effectively capture the genetic variation underlying these traits (Ravelombola et al., 2021; Budhlakoti et al., 2022). 2.2 Achievements in soybean breeding over the decades Despite the limitations of traditional breeding methods, significant achievements have been made in soybean breeding over the decades. Advances in breeding techniques have led to the development of high-yielding soybean varieties with improved resistance to diseases and pests. For instance, the identification and incorporation of specific genes responsible for disease resistance have resulted in varieties that are more resilient to common soybean pathogens. Additionally, breeding efforts have focused on improving agronomic traits such as seed composition, including protein and oil content, which are critical for both human consumption and industrial applications (Duhnen et al., 2017; Miller et al., 2023). The integration of molecular markers and genomic tools has further accelerated the breeding process, enabling more precise selection and faster development of superior soybean varieties (He et al., 2014; Sonah et al., 2015). 2.3 Role of molecular markers in improving breeding efficiency The advent of molecular markers has revolutionized soybean breeding by providing tools for more accurate and efficient selection. Molecular markers, such as Single Nucleotide Polymorphisms (SNPs), allow breeders to identify and select for specific genetic variations associated with desirable traits. Marker-assisted selection (MAS) has been particularly effective in improving traits that are difficult to measure phenotypically or are influenced by multiple genes (He et al., 2014). The use of Genotyping-By-Sequencing (GBS) and Genome-Wide Association Studies (GWAS) has enabled the identification of numerous SNPs linked to important agronomic traits, such as yield, plant height, and seed composition (Sonah et al., 2015). These markers can be used in Genomic Selection (GS) models to predict the breeding value of individuals, thereby enhancing the accuracy and efficiency of the breeding process. The integration of GWAS and GS has shown promising results in increasing genetic gain and accelerating the development of improved soybean varieties (Ma et al., 2016; Ravelombola et al., 2021; Budhlakoti et al., 2022). 3 Principles of GWAS in Soybean 3.1 Explanation of GWAS and its application in crop genetics Genome-Wide Association Studies (GWAS) are a powerful tool used to identify genetic variants associated with specific traits by scanning the genomes of many individuals. In crop genetics, GWAS helps in understanding the genetic basis of complex traits such as yield, disease resistance, and quality traits. By leveraging high-density Single Nucleotide Polymorphism (SNP) markers, GWAS can pinpoint loci that contribute to phenotypic variation, facilitating Marker-Assisted Selection (MAS) and Genomic Selection (GS) in breeding programs (Sonah et al., 2015; Ravelombola et al., 2021; Priyanatha et al., 2022).
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