Genomics and Applied Biology 2024, Vol.15, No.4, 212-222 http://bioscipublisher.com/index.php/gab 213 2 Background on GWAS in Plant Genomics 2.1 Fundamental concepts of GWAS Genome-wide association studies (GWAS) have become a cornerstone in the field of genomics, particularly for identifying the genetic basis of phenotypic variation. The fundamental concept of GWAS involves scanning the genome for genetic variants, typically single nucleotide polymorphisms (SNPs), that are associated with specific traits. This approach leverages the natural genetic diversity within a population to identify loci that contribute to phenotypic differences (Burghardt et al., 2017; Cortes et al., 2021). The mixed model framework has been particularly influential in reducing false positives, thereby increasing the reliability of GWAS findings (Cortes et al., 2021). 2.2 Historical development of GWAS in Plants The application of GWAS in plant genomics has evolved significantly over the past decade. Initially, the focus was on human genetics, but the methodology quickly found applications in plant science due to advances in genotyping and sequencing technologies (Visscher et al., 2017; Liu and Yan, 2018). Early plant GWAS studies were limited by the availability of genomic resources and computational tools. However, the development of high-throughput sequencing and improved statistical methods has enabled more comprehensive and accurate association studies in plants. Over 1000 GWAS have been conducted in various crop species, revealing substantial genotype-phenotype associations and providing insights into the genetic architecture of complex traits (Liu and Yan, 2018). 2.3 Technical approaches and methodologies in GWAS Several technical approaches and methodologies have been developed to enhance the efficiency and accuracy of GWAS. The use of high-density genotyping arrays and next-generation sequencing technologies has been pivotal in capturing a wide range of genetic variants (Yang et al., 2015; Liu and Yan, 2018). Statistical methods such as the mixed model framework, which accounts for population structure and relatedness, have been crucial in reducing false positives (Burghardt et al., 2017; Cortes et al., 2021). Additionally, novel methods like extreme-phenotype GWAS (XP-GWAS) have been introduced to identify trait-associated variants by sequencing pools of individuals with extreme phenotypes, thereby reducing the need for extensive genotyping (Yang et al., 2015). These advancements have facilitated the detection of genomic variants associated with both traditional agronomic traits and molecular phenotypes (Cortes et al., 2021). 2.4 Challenges and limitations in plant GWAS Despite the progress, several challenges and limitations persist in plant GWAS. One major issue is the complexity of plant genomes, which often include large amounts of repetitive DNA and polyploidy, complicating the identification of causal variants (Liu and Yan, 2018). Population structure and relatedness within plant populations can also lead to spurious associations, necessitating the use of sophisticated statistical models to control for these factors (Barsh et al., 2012; Burghardt et al., 2017). Additionally, the phenomenon of synthetic associations, where non-causal variants appear to be associated with traits due to linkage disequilibrium, can lead to false conclusions (Liu and Yan, 2018) Finally, the validation of GWAS findings remains a significant hurdle, as it requires extensive functional studies to confirm the biological relevance of identified variants (Barsh et al., 2012). 3 GWAS in Fabaceae: Progress and Key Findings 3.1 Overview of fabaceae and genetic diversity The Fabaceae family, also known as the legume family, is one of the largest and most diverse plant families. This family is economically and ecologically significant, particularly due to its ability to fix atmospheric nitrogen through symbiotic relationships with rhizobial bacteria. The genetic diversity within Fabaceae is vast, with numerous polyploidization events contributing to its evolutionary history and adaptation to various environments (Zhao et al., 2021). 3.2 Major Crops studied (e.g., soybean, pea, common bean, lentil) Several major crops within the Fabaceae family have been extensively studied using genome-wide association studies (GWAS). These include:
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