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Modeling of genetic gain for single traits from marker-assisted seedling selection in clonally propagated crops.

Ru S, Hardner C, Carter PA, Evans K, Main D, Peace C - Hortic Res (2016)

Bottom Line: Seedling selection identifies superior seedlings as candidate cultivars based on predicted genetic potential for traits of interest.Both derived and simulated results indicated that marker-based strategies tended to achieve higher genetic gain than phenotypic seedling selection for a trait where the proportion of genotypic variance explained by marker information was greater than the broad-sense heritability.Results from this study provides guidance in optimizing genetic gain from seedling selection for single traits where DNA tests providing marker information are available.

View Article: PubMed Central - PubMed

Affiliation: Department of Horticulture, Washington State University , PO Box 646414, Pullman, WA 99164-6414, USA.

ABSTRACT
Seedling selection identifies superior seedlings as candidate cultivars based on predicted genetic potential for traits of interest. Traditionally, genetic potential is determined by phenotypic evaluation. With the availability of DNA tests for some agronomically important traits, breeders have the opportunity to include DNA information in their seedling selection operations-known as marker-assisted seedling selection. A major challenge in deploying marker-assisted seedling selection in clonally propagated crops is a lack of knowledge in genetic gain achievable from alternative strategies. Existing models based on additive effects considering seed-propagated crops are not directly relevant for seedling selection of clonally propagated crops, as clonal propagation captures all genetic effects, not just additive. This study modeled genetic gain from traditional and various marker-based seedling selection strategies on a single trait basis through analytical derivation and stochastic simulation, based on a generalized seedling selection scheme of clonally propagated crops. Various trait-test scenarios with a range of broad-sense heritability and proportion of genotypic variance explained by DNA markers were simulated for two populations with different segregation patterns. Both derived and simulated results indicated that marker-based strategies tended to achieve higher genetic gain than phenotypic seedling selection for a trait where the proportion of genotypic variance explained by marker information was greater than the broad-sense heritability. Results from this study provides guidance in optimizing genetic gain from seedling selection for single traits where DNA tests providing marker information are available.

No MeSH data available.


Simulated genetic gain from two-stage seedling selection for the population with three segregating genotypes and partial dominance (d3=a3/2). Each plot represents a selection scenario with a given broad-sense heritability (H) of the trait and predictiveness (P) of the DNA test. In each plot, the X-axis indicates the proportion of seedlings selected in the first stage, and the Y-axis indicates simulated genetic gain from two-stage seedling selection based on SPM.
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fig5: Simulated genetic gain from two-stage seedling selection for the population with three segregating genotypes and partial dominance (d3=a3/2). Each plot represents a selection scenario with a given broad-sense heritability (H) of the trait and predictiveness (P) of the DNA test. In each plot, the X-axis indicates the proportion of seedlings selected in the first stage, and the Y-axis indicates simulated genetic gain from two-stage seedling selection based on SPM.

Mentions: In all scenarios, genetic gain from two-stage seedling selection at any SPM tended to decrease as TSP increased (Figure 5 and Supplementary Figure S7). Where P was greater than or equal to H, the highest genetic gain was achieved where as many as seedlings as possible were selected based on marker information (Figure 5 and Supplementary Figure S7). Where P was less than H, relying on phenotype-only or discarding only seedlings with the most undesirable genotype in the first stage of two-stage was associated with higher genetic gain. Where both P and H equaled 1, changes in the proportion of seedlings selected in the first stage did not influence genetic gain and two-stage generated the same genetic gain as marker-only and phenotype-only.


Modeling of genetic gain for single traits from marker-assisted seedling selection in clonally propagated crops.

Ru S, Hardner C, Carter PA, Evans K, Main D, Peace C - Hortic Res (2016)

Simulated genetic gain from two-stage seedling selection for the population with three segregating genotypes and partial dominance (d3=a3/2). Each plot represents a selection scenario with a given broad-sense heritability (H) of the trait and predictiveness (P) of the DNA test. In each plot, the X-axis indicates the proportion of seedlings selected in the first stage, and the Y-axis indicates simulated genetic gain from two-stage seedling selection based on SPM.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4837533&req=5

fig5: Simulated genetic gain from two-stage seedling selection for the population with three segregating genotypes and partial dominance (d3=a3/2). Each plot represents a selection scenario with a given broad-sense heritability (H) of the trait and predictiveness (P) of the DNA test. In each plot, the X-axis indicates the proportion of seedlings selected in the first stage, and the Y-axis indicates simulated genetic gain from two-stage seedling selection based on SPM.
Mentions: In all scenarios, genetic gain from two-stage seedling selection at any SPM tended to decrease as TSP increased (Figure 5 and Supplementary Figure S7). Where P was greater than or equal to H, the highest genetic gain was achieved where as many as seedlings as possible were selected based on marker information (Figure 5 and Supplementary Figure S7). Where P was less than H, relying on phenotype-only or discarding only seedlings with the most undesirable genotype in the first stage of two-stage was associated with higher genetic gain. Where both P and H equaled 1, changes in the proportion of seedlings selected in the first stage did not influence genetic gain and two-stage generated the same genetic gain as marker-only and phenotype-only.

Bottom Line: Seedling selection identifies superior seedlings as candidate cultivars based on predicted genetic potential for traits of interest.Both derived and simulated results indicated that marker-based strategies tended to achieve higher genetic gain than phenotypic seedling selection for a trait where the proportion of genotypic variance explained by marker information was greater than the broad-sense heritability.Results from this study provides guidance in optimizing genetic gain from seedling selection for single traits where DNA tests providing marker information are available.

View Article: PubMed Central - PubMed

Affiliation: Department of Horticulture, Washington State University , PO Box 646414, Pullman, WA 99164-6414, USA.

ABSTRACT
Seedling selection identifies superior seedlings as candidate cultivars based on predicted genetic potential for traits of interest. Traditionally, genetic potential is determined by phenotypic evaluation. With the availability of DNA tests for some agronomically important traits, breeders have the opportunity to include DNA information in their seedling selection operations-known as marker-assisted seedling selection. A major challenge in deploying marker-assisted seedling selection in clonally propagated crops is a lack of knowledge in genetic gain achievable from alternative strategies. Existing models based on additive effects considering seed-propagated crops are not directly relevant for seedling selection of clonally propagated crops, as clonal propagation captures all genetic effects, not just additive. This study modeled genetic gain from traditional and various marker-based seedling selection strategies on a single trait basis through analytical derivation and stochastic simulation, based on a generalized seedling selection scheme of clonally propagated crops. Various trait-test scenarios with a range of broad-sense heritability and proportion of genotypic variance explained by DNA markers were simulated for two populations with different segregation patterns. Both derived and simulated results indicated that marker-based strategies tended to achieve higher genetic gain than phenotypic seedling selection for a trait where the proportion of genotypic variance explained by marker information was greater than the broad-sense heritability. Results from this study provides guidance in optimizing genetic gain from seedling selection for single traits where DNA tests providing marker information are available.

No MeSH data available.