Gourd vegetables are a significant vegetable group known for their medicinal properties and useful fibers. They require a variety of traits, including yield and quality components. The focus is on producing varieties with strong resistance to pathogens, physiological disorders, and stress. Contemporary cultivars have undergone introgression processes to integrate these traits, aiming to provide high-yielding, disease-resistant varieties that meet consumer preferences for quality and nutritional value. Research has been conducted to create a genetic map and pinpoint quantitative trait loci (QTL) in gourd vegetables. QTL mapping is a crucial research process that identifies genes associated with quantitative traits using molecular markers. It involves meticulous crossbreeding planning and precise phenotyping. The primary objectives of QTL mapping include exploring the number of genes influencing a trait, determining gene locations, and assessing the impact of gene dosage on trait variation. Genetic mapping, the initial step in map-based cloning, facilitates DNA-based marker-assisted selection (MAS) and investigates the linkage between genes of interest. QTL mapping is useful for pinpointing genetic regions that co-segregate with the target trait within breeding populations. This methodology is applicable to diverse population types, including F2 populations, double-haploid populations, and families of backcross or recombinant inbred lines. Various markers, such as restriction fragment length polymorphism (RFLP), amplified fragment length polymorphism (AFLP), microsatellite or simple sequence repeat (SSR), and single-nucleotide polymorphism (SNP), can be used in QTL mapping. This chapter aims to explore QTL mapping and GWS analysis, focusing on their potential applications in gourd crops. It aims to provide a comprehensive understanding of QTLs and genome-wide association (GWAS), aiding researchers in identifying areas for further investigation and enhancing their knowledge in this field.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Advances in GWAS and QTL Mapping in Gourd Vegetables

  • Shreyas Aradhya C. S.,
  • K. K. Gangopadhyay,
  • Shyam Sundar Dey

摘要

Gourd vegetables are a significant vegetable group known for their medicinal properties and useful fibers. They require a variety of traits, including yield and quality components. The focus is on producing varieties with strong resistance to pathogens, physiological disorders, and stress. Contemporary cultivars have undergone introgression processes to integrate these traits, aiming to provide high-yielding, disease-resistant varieties that meet consumer preferences for quality and nutritional value. Research has been conducted to create a genetic map and pinpoint quantitative trait loci (QTL) in gourd vegetables. QTL mapping is a crucial research process that identifies genes associated with quantitative traits using molecular markers. It involves meticulous crossbreeding planning and precise phenotyping. The primary objectives of QTL mapping include exploring the number of genes influencing a trait, determining gene locations, and assessing the impact of gene dosage on trait variation. Genetic mapping, the initial step in map-based cloning, facilitates DNA-based marker-assisted selection (MAS) and investigates the linkage between genes of interest. QTL mapping is useful for pinpointing genetic regions that co-segregate with the target trait within breeding populations. This methodology is applicable to diverse population types, including F2 populations, double-haploid populations, and families of backcross or recombinant inbred lines. Various markers, such as restriction fragment length polymorphism (RFLP), amplified fragment length polymorphism (AFLP), microsatellite or simple sequence repeat (SSR), and single-nucleotide polymorphism (SNP), can be used in QTL mapping. This chapter aims to explore QTL mapping and GWS analysis, focusing on their potential applications in gourd crops. It aims to provide a comprehensive understanding of QTLs and genome-wide association (GWAS), aiding researchers in identifying areas for further investigation and enhancing their knowledge in this field.