MPB_2025v16n1

Molecular Plant Breeding 2025, Vol.16, No.1, 1-12 http://genbreedpublisher.com/index.php/mpb 9 Figure 3 Fine mapping of FS5.2 major-effect QTL (Adopted from Pan et al., 2022) Image caption: (A1) Representative fruits from NIL-derived F2 plants showing segregation of fruit size/shape in this population. (A2) Distribution of mature fruit length (MFL) and diameter (MFD) among 82 F2 plants based on field data. Genotype of each plant at the fs5.2 locus was also shown. (B-D) From 864 F2 plants, 33 recombinants were identified with flanking markers 98C06 and 97C12, which were phenotyped and genotyped with eight additional markers (C). Twelve haplotypes (HAP) could be recognized, which allowed mapping of FS5.2 into a 95.5 kb region with 15 predicted genes (D). In (D), S=short fruit, L=long fruit, and n=# recombinants with the specific haplotype. The light-green, light-blue, and orange bars indicate the genotypes of NIL, WI7237, and F1, respectively. L and D are mean fruit length and diameter, respectively, of the haplotype (in cm) (Adopted from Pan et al., 2022) 7 Future Directions in QTL Mapping for Cucumber 7.1 Potential of next-generation sequencing in enhancing QTL resolution Next-generation sequencing (NGS) technologies have revolutionized genetic research by providing high-resolution data that can significantly enhance QTL mapping. The application of NGS allows for the generation of dense genome-wide markers, which improves the accuracy and resolution of QTL identification. For instance, the use of genotyping-by-sequencing (GBS) has enabled the construction of high-density haplotype maps, facilitating the identification of significant SNPs and candidate genes for various traits in cucumber (Lee et al., 2020). Additionally, NGS-based bulked segregant analysis (BSA) has been employed to identify QTLs with greater precision, as demonstrated in the mapping of fruit neck length in cucumber (Xu et al., 2020). The integration of NGS with traditional QTL mapping approaches can thus provide a more detailed understanding of the genetic architecture of agronomic traits in cucumber (Nguyen et al., 2019).

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