Depicting Soybean Diversity via Complementary Application of Three Marker Types

Area of Science:

• Plant genetics and breeding
• Agricultural science

Background:

• Increasing demand for plant-based proteins, particularly in Europe.
• Need for soybean breeding programs to enhance variety productivity and genetic resource utilization.

Purpose of the Study:

• To comprehensively assess genetic diversity in a soybean working collection.
• To provide data for focused breeding targets and improve genetic resource utilization efficiency.

Main Methods:

• Evaluation of 90 soybean accessions using morphological descriptors, agronomic traits, and Simple Sequence Repeat (SSR) markers.
• Application of Homogeneity Analysis by Means of Alternating Least Squares (HOMALS) for morphological data.
• Analysis of Molecular Variance (AMOVA) to assess genetic differentiation.

Main Results:

• Genotype grouping varied by marker type; SSRs best matched pedigree data, and agronomic traits matched maturity.
• Morphological descriptors showed the highest genetic distance (GD = 517), followed by SSRs (GD = 0.317) and agronomic traits (GD = 0.244).
• Weak differentiation among geographic groups (Φ = 0.061) was observed, with Canadian genotypes showing the highest differentiation (Φ = 0.148).

Conclusions:

• Morphological descriptors are highly effective for classifying soybean genotypes and identifying diversity.
• Low correlation between molecular and phenotypic data suggests complementary roles in diversity assessment.
• Introduction of new genetic variation is essential for the long-term improvement of soybean breeding.