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  • Title: Seed coat color genetics and genotype × environment effects in yellow beans via machine-learning and genome-wide association.
    Author: Sadohara R, Long Y, Izquierdo P, Urrea CA, Morris D, Cichy K.
    Journal: Plant Genome; 2022 Mar; 15(1):e20173. PubMed ID: 34817119.
    Abstract:
    Common bean (Phaseolus vulgaris L.) is consumed worldwide, with strong regional preferences for seed appearance characteristics. Colors of the seed coat, hilum ring, and corona are all important, along with susceptibility to postharvest darkening, which decreases seed value. This study aimed to characterize a collection of 295 yellow bean genotypes for seed appearance and postharvest darkening, evaluate genotype × environment (G × E) effects and map those traits via genome-wide association analysis. Yellow bean germplasm were grown for 2 yr in Michigan and Nebraska and seed were evaluated for L*a*b* color values, postharvest darkening, and hilum ring and corona colors. A model to exclude the hilum ring and corona of the seeds, black background, and light reflection was developed by using machine learning, allowing for targeted and efficient L*a*b* value extraction from the seed coat. The G × E effects were significant for the color values, and Michigan-grown seeds were darker than Nebraska-grown seeds. Single-nucleotide polymorphisms (SNPs) were associated with L* and hilum ring color on Pv10 near the J gene involved in mature seed coat color and hilum ring color. A SNP on Pv07 associated with L*, a*, postharvest darkening, and hilum ring and corona colors was near the P gene, the ground factor gene for seed coat color expression. The machine-learning-aided model used to extract color values from the seed coat, the wide variability in seed morphology traits, and the associated SNPs provide tools for future breeding and research efforts to meet consumers' expectations for bean seed appearance.
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