Dataset Information

Genomic Selection for Yield and Seed Composition Traits Within an Applied Soybean Breeding Program.

ABSTRACT: Genomic selection (GS) has become viable for selection of quantitative traits for which marker-assisted selection has often proven less effective. The potential of GS for soybean was characterized using 483 elite breeding lines, genotyped with BARCSoySNP6K iSelect BeadChips. Cross validation was performed using RR-BLUP and predictive abilities (r MP) of 0.81, 0.71, and 0.26 for protein, oil, and yield, were achieved at the largest tested training set size. Minimal differences were observed when comparing different marker densities and there appeared to be inflation in r MP due to population structure. For comparison purposes, two additional methods to predict breeding values for lines of four bi-parental populations within the GS dataset were tested. The first method predicted within each bi-parental population (WP method) and utilized a training set of full-sibs of the validation set. The second method utilized a training set of all remaining breeding lines except for full-sibs of the validation set to predict across populations (AP method). The AP method is more practical as the WP method would likely delay the breeding cycle and leverage smaller training sets. Averaging across populations for protein and oil content, r MP for the AP method (0.55, 0.30) approached r MP for the WP method (0.60, 0.52). Though comparable, r MP for yield was low for both AP and WP methods (0.12, 0.13). Based on increases in r MP as training sets increased and the effectiveness of WP vs. AP method, the AP method could potentially improve with larger training sets and increased relatedness between training and validation sets.

SUBMITTER: Stewart-Brown BB

PROVIDER: S-EPMC6643879 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Genomic Selection for Yield and Seed Composition Traits Within an Applied Soybean Breeding Program.

Stewart-Brown Benjamin B BB Song Qijian Q Vaughn Justin N JN Li Zenglu Z

G3 (Bethesda, Md.) 20190709 7

Genomic selection (GS) has become viable for selection of quantitative traits for which marker-assisted selection has often proven less effective. The potential of GS for soybean was characterized using 483 elite breeding lines, genotyped with BARCSoySNP6K iSelect BeadChips. Cross validation was performed using RR-BLUP and predictive abilities (<i>r</i><sub>MP</sub>) of 0.81, 0.71, and 0.26 for protein, oil, and yield, were achieved at the largest tested training set size. Minimal differences we ...[more]

PMID: 31088906

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Project description:BACKGROUND: Several techniques are available to study gene function, but many are less than ideal for soybean. Reverse genetics, a relatively new approach, can be utilized to identify novel mutations in candidate genes; this technique has not produced an allelic variant with a confirmed phenotype in soybean. Soybean raffinose synthase genes and microsomal omega-6 fatty acid desaturase genes were screened for novel alleles in mutagenized soybean populations. RESULTS: Four mutations in independent lines were identified in the raffinose synthase gene RS2; two mutations resulted in amino acid mutations and one resulted in an altered seed oligosaccharide phenotype. The resulting phenotype was an increase in seed sucrose levels as well as a decrease in both raffinose and stachyose seed oligosaccharide levels. Three mutations in independent lines were identified in the omega-6 fatty acid desaturase gene FAD2-1A; all three mutations resulted in missense amino acid mutations and one resulted in an altered seed fatty acid profile that led to an increase in oleic acid and a decrease in linoleic acid in the seed oil. CONCLUSION: The oligosaccharide phenotype controlled by the novel RS2 allele is similar to previously observed seed oligosaccharide phenotypes in RS2 mutant (PI 200508) allele-containing lines. Due to the anti-nutritional characteristics of raffinose and stachyose, this represents a positive change in seed composition. The fatty acid phenotype controlled by the novel FAD2-1A allele controls an increase in oleic acid in the seed oil, a phenotype also observed in a line previously characterized to have a null allele of the FAD2-1A gene. Molecular marker assays were developed to reliably detect the inheritance of the mutant alleles and can be used in efficient breeding for these desired seed phenotypes. Our results serve as the first demonstration of the identification of soybean mutants controlling seed phenotypes discovered through the reverse genetics technique TILLING.

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Dataset Information

Genomic Selection for Yield and Seed Composition Traits Within an Applied Soybean Breeding Program.

Publications

Genomic Selection for Yield and Seed Composition Traits Within an Applied Soybean Breeding Program.

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