A pipeline for high throughput detection and mapping of SNPs from EST databases

Area of Science:

• Genomics
• Bioinformatics
• Plant Genetics

Background:

• Single nucleotide polymorphisms (SNPs) are abundant genetic variations crucial for molecular markers.
• Utilizing SNPs from sequence databases requires robust bioinformatic tools for accurate selection.
• High-quality, locus-specific SNPs are essential for successful genotyping platforms.

Purpose of the Study:

• To develop and validate a bioinformatics pipeline for mining and selecting reliable SNPs from public EST databases.
• To prepare selected SNPs for genotyping on the Illumina GoldenGate platform.
• To demonstrate the pipeline's effectiveness in mapping SNPs in potato populations.

Main Methods:

• Developed a pipeline using QualitySNP software to mine SNPs from EST databases, with or without quality information.
• Selected reliable SNPs suitable for the Illumina GoldenGate genotyping platform.
• Applied the pipeline to potato EST data, genotyped mapping populations, and mapped SNP markers.

Main Results:

• Identified over 7000 reliable SNPs meeting GoldenGate genotyping criteria.
• Approximately 12% of SNPs on the array experienced dropout.
• Successfully mapped 165 and 185 segregating SNP loci in two respective potato mapping populations.

Conclusions:

• The developed pipeline is effective for selecting and validating SNPs from public EST data for genetic mapping.
• The method facilitates the discovery and application of valuable molecular markers in crop species like potato.
• This approach enhances the utility of public sequence databases for genetic research.