MPB_2025v16n1

Molecular Plant Breeding 2025, Vol.16, No.1, 24-34 http://genbreedpublisher.com/index.php/mpb 27 5.2 Marker-assisted selection (MAS) and its application in breeding programs Marker-assisted selection (MAS) has revolutionized plant breeding by integrating molecular markers with traditional breeding techniques. MAS allows for the selection of plants carrying desirable traits based on their genetic makeup rather than solely on phenotypic expression. This method significantly accelerates the breeding process and increases the precision of selecting for complex traits. MAS has been particularly effective in improving traits that are difficult to score phenotypically, such as disease resistance and abiotic stress tolerance (Zhou and Xu, 2024). For instance, MAS has been used to enhance drought adaptation in maize through marker-assisted backcrossing (MABC), which involves the introgression of favorable alleles at specific target regions (Ribaut and Ragot, 2006). Additionally, the development of high-throughput genotyping technologies, such as genotyping-by-sequencing (GBS), has further enhanced the efficiency of MAS by enabling the simultaneous discovery and genotyping of single nucleotide polymorphisms (SNPs) in large crop genomes (He et al., 2014). The application of MAS in maize breeding has led to significant improvements in yield, stress tolerance, and other agronomically important traits. For example, the use of MAS in wheat breeding has shown promise in improving complex polygenic traits through advanced strategies like marker-assisted recurrent selection and genome-wide selection (Gupta et al., 2010). 5.3 Genomic selection as a modern approach to breeding Genomic selection (GS) represents a modern approach to plant breeding that leverages genome-wide marker data to predict the breeding value of individuals. Unlike MAS, which focuses on specific markers linked to target traits, GS uses a large number of markers distributed across the entire genome to capture the genetic variance associated with complex traits. GS has the potential to further accelerate the breeding process by enabling the selection of superior genotypes at an early stage, even before phenotypic traits are expressed. This approach has been facilitated by advancements in next-generation sequencing technologies and the development of dense SNP marker panels. For instance, the use of kompetitive allele specific PCR (KASP) SNP markers developed from RNA-Seq data has provided a valuable resource for map-based cloning and GS in maize (Chen et al., 2021). The integration of GS into breeding programs has shown promising results in improving traits such as kernel size, yield, and stress tolerance. By combining linkage and association mapping, researchers have identified numerous SNPs and quantitative trait loci (QTLs) associated with key agronomic traits, providing a robust foundation for GS (Figure 1) (Liu et al., 2019). The continuous improvement of genomic prediction models and the increasing availability of high-quality genomic data are expected to further enhance the efficiency and accuracy of GS in maize breeding. Figure 1 Phenotypes of kernel size traits and variations of kernel size between two parental lines of the IBM Syn 10 DH population (Adopted from Liu et al., 2019) Image caption: Phenotypes of KL, KW and KT illustrated with 10 kernels of the two parental lines in IBM Syn 10 DH population. Bar = 1 cm (Adopted from Liu et al., 2019)

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