Field Crop 2024, Vol.7, No.6, 325-333 http://cropscipublisher.com/index.php/fc 328 4.2 Use of genomic selection (GS) in breeding pipelines Genomic selection (GS) is an emerging approach that leverages genome-wide marker data to predict the breeding value of individuals, thus enhancing the efficiency of selection in breeding programs. GS has shown promise in capturing the genetic variation for complex traits such as yield and fiber quality in cotton. By integrating GWAS hits into prediction models, GS can improve the accuracy of trait predictions, although careful consideration of significance thresholds is necessary (Billings et al., 2022). The development of high-density SNP arrays, such as the CottonSNP63K, provides a robust resource for implementing GS in cotton breeding, enabling the dissection of complex traits and enhancing the genetic gain (Hulse-Kemp et al., 2015). 4.3 Challenges and opportunities in translating marker data to breeding success While the integration of genetic markers into breeding programs offers significant advantages, several challenges remain. One major challenge is the environment-specific nature of many alleles, which can limit their utility across different breeding contexts (Billings et al., 2022). Additionally, the narrow genetic diversity in cotton breeding programs can hinder the effective use of marker data (Aydın et al., 2023). However, opportunities exist in expanding the genetic base by incorporating wild alleles and utilizing advanced genome editing technologies like CRISPR/Cas9 to enhance yield-related traits (Figure 2) (Mubarik et al., 2020). Furthermore, the development of comprehensive genetic maps and the use of diverse molecular markers can facilitate the effective translation of marker data into breeding success (Qin et al., 2015; Sabev et al., 2020). In summary, the integration of genetic markers through MAS and GS offers substantial potential for improving cotton yield and quality. However, addressing challenges such as allele specificity and genetic diversity is crucial for maximizing the benefits of these technologies in breeding programs. Figure 2 Proposed revamped cotton breeding program (Adopted from Mubarik et al., 2020) Image caption: Fine-tune the already present traits and add new traits to cultivated cotton varieties through plant breeding, genetic engineering, and genome editing tools. Pyramiding of useful traits by crossing between genetically altered and elite cultivars to develop climate resilient cotton cultivars (Adopted from Mubarik et al., 2020) 5 Case Study: Marker-Assisted Selection for Cotton Yield Improvement 5.1 Description of a breeding program implementing MAS Marker-assisted selection (MAS) has been effectively implemented in various cotton breeding programs to enhance fiber quality and yield. One notable program targeted the improvement of fiber quality traits such as fiber length, strength, micronaire, and uniformity by utilizing SSR markers associated with specific QTLs. In this program, donor genotypes possessing desirable fiber quality traits were crossed with local elite cultivars, and the resulting populations were backcrossed over multiple generations. The transfer of targeted QTLs was monitored
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