Molecular Plant Breeding 2025, Vol.16, No.2, 133-145 http://genbreedpublisher.com/index.php/mpb 139 starch content (Figure 2; Table 1) (Wang et al., 2019). Additionally, the technology has been applied to improve traits such as yield, quality, disease resistance, and abiotic stress tolerance in other crops, demonstrating its broad potential for sweet potato improvement (Tussipkan and Manabayeva, 2021; Wan et al., 2021; Das et al., 2023). The availability of whole-genome sequencing data and functional information about key genes further enhances the efficacy of CRISPR/Cas9 in sweet potato breeding (Rodriguez-Leal et al., 2017; Chen et al., 2019). Figure 2 Schematic representation of the workflow designed to analyze targeted gene mutations of CRISPR/Cas9 editing. Transgenic lines were identified by PCR detection of Cas9 genes. Mutation detection in transgenic lines by PCR amplification with primers flanking the sgRNA target sites and running gel electrophoresis to roughly estimate the mutation types. PCR products sequencing analysis was performed by examining their sequencing chromatograms for accurate mutation status (Adopted from Wang et al., 2019) Table 1 Chain length distributions proportion in 90>DP>6 of debranched sweet potato starches a,b (Adopted from Wang et al., 2019) Sample 6<DP<12 (%) 13<DP<24 (%) 25<DP<36 (%) 37<DP<90 (%) Xushu22 29.2 d (0.42) 42.7 c (0.752) 14.7 c (0.40) 13.4 c (0.35) IbSBEII-sgRNA12-24 24.6 e (0.63) 44.6 b (0.53) 15.0 c (0.16) 15.8 b (0.78) IbSBEII-sgRNA12-26 16.4 g (0.03) 45.6 ab (0.06) 19.2 a (0.04) 18.8 a (0.05) IbSBEII-sgRNA2-1 19.1 f (0.25) 46.3 a (0.34) 16.3 b (0.04) 18.3 a (0.62) IbGBSSI-sgRNA2-2 33.7 b (0.07) 41.7 cd (0.27) 13.8 d (0.13) 11.2 d (0.23) IbGBSSI-sgRNA2-6 34.7 a (0.21) 41.4 d (0.46) 13.1 e (0.13) 10.8 d (0.31) IbGBSSI-sgRNA2-7 30.4 c (0.08) 42.6 c (0.10) 13.6 d (0.23) 13.4 c (0.23) Note: a Standard deviations are given within parenthesis. b The values in the same column with different two letters (a and b, b and c, a and d, d and e, e and f, f and g) differ significantly (p<0.05) 7.2 Marker-assisted selection (MAS) for desirable traits Marker-assisted selection (MAS) leverages molecular markers to enhance the efficiency of breeding programs by enabling the selection of desirable traits at the genetic level. Techniques such as genotyping-by-sequencing (GBS) have revolutionized MAS by providing high-throughput sequencing capabilities that facilitate the discovery and genotyping of single nucleotide polymorphisms (SNPs) in crop genomes (He et al., 2014). This approach has been successfully implemented in various crops, including maize and wheat, to identify and select for traits related to yield, disease resistance, and nutritional quality. The integration of MAS in sweet potato breeding can accelerate the development of new varieties with improved nutrient composition and yield by enabling the precise selection of beneficial alleles.
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