Sequencing-Based Bin Map Construction of a Tomato Mapping Population, Facilitating High-Resolution Quantitative Trait...

Area of Science:

• Plant genetics and genomics
• Agricultural science
• Molecular biology

Background:

• Developing high-resolution genetic maps is crucial for identifying genes controlling important crop traits.
• Previous genetic maps in tomato have limitations in marker density and resolution.
• Recombinant inbred line (RIL) populations are valuable for genetic studies.

Purpose of the Study:

• To construct a highly saturated genetic linkage map for tomato using genotyping-by-sequencing (GBS).
• To develop and validate a computational pipeline (SNPbinner) for converting SNP data into genomic bins for fine mapping.
• To refine the localization of quantitative trait loci (QTL) for fruit quality traits in a tomato RIL population.

Main Methods:

• Genotyping-by-sequencing (GBS) was used to generate single nucleotide polymorphism (SNP) data.
• A custom Python script, SNPbinner, was developed using a hidden Markov model to create genomic bins.
• The new genetic map was utilized to re-evaluate QTL for fruit weight (FW) and lycopene content (LYC).

Main Results:

• A high-resolution genetic map of tomato was successfully constructed, significantly increasing map length compared to previous maps.
• The SNPbinner pipeline accurately converted SNP data into genomic bins for QTL fine mapping.
• Two major QTL for FW were precisely mapped to their causative genes, and a major LYC QTL was refined to its underlying gene, ζ-lycopene cyclase.

Conclusions:

• The developed genetic map and SNPbinner pipeline offer enhanced resolution for genetic analysis in tomato.
• Precise mapping of fruit quality QTL provides valuable information for marker-assisted breeding.
• The publicly available resources will facilitate future research in tomato genetics and crop improvement.