Maize Genomics and Genetics 2024, Vol.15, No.3, 111-122 http://cropscipublisher.com/index.php/mgg 112 The purpose of this study is to provide a comprehensive overview of the techniques and outcomes associated with genomics-assisted breeding in maize. By examining the current state of genomics technologies and their applications in maize breeding, this study highlights the potential benefits and challenges of integrating genomics into breeding programs. The expectations of this study include identifying key advancements in genomics-assisted breeding, evaluating the impact of these advancements on maize production, and providing insights into future directions for research and development in this field. Ultimately, this study seeks to contribute to the ongoing efforts to enhance maize breeding and ensure global food security in the face of growing population and climate change challenges. 2 Genomic Technologies in Maize Breeding 2.1 Genotyping-by-sequencing (GBS) Genotyping-by-Sequencing (GBS) is a cost-effective, high-throughput genotyping method that utilizes restriction enzymes to reduce genome complexity, making it suitable for large-scale genetic studies in maize. GBS has been successfully applied to various maize populations, including association populations, backcross generations, double haploids, and recombinant inbred lines. This technique generates a substantial number of SNPs, although it often results in high rates of missing data, which can be mitigated through imputation methods. GBS is particularly beneficial for genetic diversity analysis, linkage mapping, and genomic prediction, making it a versatile tool in maize breeding programs (Elbasyoni et al., 2018; Wang et al., 2020; Munyengwa et al., 2021). 2.2 Single nucleotide polymorphism (SNP) arrays SNP arrays are another powerful tool for maize breeding, providing high-quality genotyping data. Although SNP arrays are more expensive per sample compared to GBS, they offer high accuracy and consistency. SNP arrays have been used to develop high-density genetic maps and perform genome-wide association studies (GWAS) in maize. These arrays facilitate the identification of genetic patterns and population structures, which are crucial for genomic selection and marker-assisted selection、 2.3 Whole-genome sequencing (WGS) Whole-Genome Sequencing (WGS) provides comprehensive genotyping data by sequencing the entire genome. This method is highly accurate and can identify millions of genetic markers, making it ideal for fine mapping and high-resolution GWAS. However, WGS is costly, especially when applied to large populations. Despite its expense, WGS is invaluable for constructing high-density genetic maps and understanding the genetic basis of complex traits in maize (Elbasyoni et al., 2018; Rice and Lipka, 2021; Chen et al., 2021). 2.4 Marker-assisted selection (MAS) Marker-Assisted Selection (MAS) involves using molecular markers linked to desirable traits to select individuals in breeding programs. MAS has been widely used in maize breeding to improve traits such as yield, disease resistance, and abiotic stress tolerance. The integration of MAS with other genomic technologies, such as QTL mapping and RNA-sequencing, has enhanced the efficiency of selecting superior genotypes. MAS is particularly effective for traits controlled by major QTLs, providing a targeted approach to breeding (Torkamaneh et al., 2021). 2.5 Genomic selection (GS) Genomic Selection (GS) is a cutting-edge approach that uses genome-wide marker data to predict the breeding values of individuals. GS has revolutionized maize breeding by increasing genetic gains and reducing the number of breeding cycles required to develop new varieties. This method captures both major and minor genetic effects, making it suitable for complex traits. GS models have been refined to account for non-additive genetic effects, genotype-by-environment interactions, and other factors, further improving prediction accuracy. The integration of high-throughput phenotypic and genotypic data has made GS a powerful tool for accelerating maize breeding programs. By leveraging these genomic technologies, maize breeders can achieve significant improvements in crop performance, ensuring food security and sustainability in agriculture (Guo et al., 2019; Rice and Lipka, 2021; Merrick et al., 2022).
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