Comprehensive Method for Soybean Cultivar Identification Using MGIseq, VCF2GENOME, and REST API

Area of Science:

• Agricultural Science
• Genomics
• Bioinformatics

Background:

• Accurate soybean (Glycine max) cultivar identification is crucial for breeding, genetics, and quality control.
• Existing methods may lack the high-throughput and high-accuracy required for modern agricultural applications.

Purpose of the Study:

• To develop and present a comprehensive protocol for high-throughput, high-accuracy soybean cultivar identification.
• To integrate genomic sequencing with bioinformatic analysis for precise varietal determination.

Main Methods:

• DNA extraction from soybean leaf tissue.
• MGIseq library preparation and high-throughput sequencing.
• Bioinformatic analysis including quality control, genome mapping, variant calling (VCF file generation), and database comparison via VCF2GENOME and a REST API.

Main Results:

• Successful implementation of a protocol for accurate soybean cultivar identification.
• Generation of a Variant Call Format (VCF) file for genetic profiling.
• Facilitation of cultivar comparison against a curated database using a REST API.

Conclusions:

• The developed method offers a robust solution for identifying soybean cultivars with high accuracy and throughput.
• This protocol supports advancements in soybean genetics, breeding programs, and seed industry quality assurance.