Molecular Plant Breeding 2025, Vol.16, No.1, 1-12 http://genbreedpublisher.com/index.php/mpb 3 3 QTL Mapping: Methodology and Techniques 3.1 Principles of QTL mapping and its applications in cucumbers Quantitative trait loci (QTL) mapping is a statistical method that links phenotypic data (traits) with genotypic data (genetic markers) to identify regions of the genome associated with specific traits. In cucumbers (Cucumis sativus L.), QTL mapping has been instrumental in understanding the genetic basis of various agronomic traits such as disease resistance, fruit size, and flowering time. The process involves creating a mapping population, phenotyping the population for traits of interest, genotyping the population with molecular markers, and then using statistical methods to identify associations between markers and traits (Wei et al., 2014; Pan et al., 2020; Wang et al., 2020b). 3.2 Advances in QTL mapping methodologies Recent advancements in QTL mapping methodologies have significantly enhanced the resolution and accuracy of QTL detection. Traditional bi-parental mapping, which involves crossing two genetically distinct parents to produce a segregating population, has been widely used in cucumber research. This method has led to the identification of numerous QTLs for traits such as fruit length, fruit diameter, and disease resistance (Wei et al., 2014; Zhu et al., 2016; Pan et al., 2020). Genome-wide association studies (GWAS) represent a more recent approach that leverages natural populations to identify QTLs. GWAS can provide higher resolution mapping compared to bi-parental mapping by utilizing the natural genetic diversity present in a population. This method has been successfully applied in various crops, including cucumbers, to identify QTLs associated with complex traits (Xu et al., 2017; Halladakeri et al., 2023). 3.3 Integration of molecular markers in QTL mapping The integration of molecular markers, such as Single Nucleotide Polymorphisms (SNPs) and Specific Length Amplified Fragment (SLAF) markers, has revolutionized QTL mapping in cucumbers. The development of high-density genetic maps using these markers has facilitated the fine mapping of QTLs and the identification of candidate genes (Takagi et al., 2013; Wei et al., 2014; Zhu et al., 2016). For instance, SLAF sequencing has been used to construct high-density genetic maps, enabling the detection of QTLs for fruit-related traits with high precision (Wei et al., 2014; Zhu et al., 2016). Moreover, the use of next-generation sequencing (NGS) technologies has allowed for the rapid identification and genotyping of molecular markers, making QTL mapping more efficient and cost-effective. Techniques such as QTL-seq, which combines bulked segregant analysis with whole-genome resequencing, have further streamlined the process, enabling the rapid identification of QTLs in cucumbers and other crops (Takagi et al., 2013). 4 QTL Mapping Studies for Major Agronomic Traits 4.1 Yield-related traits Several QTL mapping studies have identified key loci associated with yield-related traits in cucumber. For instance, a high-density genetic map constructed using SLAF sequencing identified nine QTLs for fruit length and weight, with one QTL, fl3.2, explaining 44.60% of the phenotypic variance (Wei et al., 2014). Another study using recombinant inbred lines (RILs) detected multiple QTLs for fruit weight, length, and diameter, highlighting the genetic complexity of these traits (Yuan et al., 2008). Additionally, a study focusing on a narrow cross in cucumber identified QTLs for the number of fruit per plant and lateral branches, which are critical yield components (Fazio et al., 2003). The identified QTLs play significant roles in yield improvement by influencing various yield components. For example, the QTL fl3.2 on chromosome 3 has a major effect on fruit length and weight, making it a prime target for marker-assisted selection (MAS) to enhance yield (Wei et al., 2014). Similarly, QTLs linked to fruit weight and length in RIL populations can be utilized to develop high-yielding cucumber varieties through MAS (Yuan et al., 2008). The loci associated with the number of lateral branches and fruit per plant also offer potential for breeding programs aimed at increasing overall yield (Fazio et al., 2003).
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