Abstract
Key message A breeding strategy combining genomic with one-stage phenotypic selection maximizes annual selection gain for net merit. Choice of the selection index strongly affects the selection gain expected in individual traits.Selection indices using genomic information have been proposed in crop-specific scenarios. Routine use of genomic selection (GS) for simultaneous improvement of multiple traits requires information about the impact of the available economic and logistic resources and genetic properties (variances, trait correlations, and prediction accuracies) of the breeding population on the expected selection gain. We extended the R package “selectiongain” from single trait to index selection to optimize and compare breeding strategies for simultaneous improvement of two traits. We focused on the expected annual selection gain (ΔGa) for traits differing in their genetic correlation, economic weights, variance components, and prediction accuracies of GS. For all scenarios considered, breeding strategy GSrapid (one-stage GS followed by one-stage phenotypic selection) achieved higher ΔGa than classical two-stage phenotypic selection, regardless of the index chosen to combine the two traits and the prediction accuracy of GS. The Smith–Hazel or base index delivered higher ΔGa for net merit and individual traits compared to selection by independent culling levels, whereas the restricted index led to lower ΔGa in net merit and divergent results for selection gain of individual traits. The differences among the indices depended strongly on the correlation of traits, their variance components, and economic weights, underpinning the importance of choosing the selection indices according to the goal of the breeding program. We demonstrate our theoretical derivations and extensions of the R package “selectiongain” with an example from hybrid wheat by designing indices to simultaneously improve grain yield and grain protein content or sedimentation volume.
Highlights
Plant breeding aims at the improvement of the economic merit of cultivars, which depends on the performance of the traits composing the product profile or variety concept (Bernardo 2010)
We compared the effects of three different indices on ΔGa for net merit and selection gain expected for individual traits assuming two breeding strategies: (i) classical twostage phenotypic selection and (ii) a combination of genomic selection with one-stage phenotypic selection
We investigated the impact of variance components, correlation of traits and their economic weights on ΔGa, and the Across all investigated scenarios, the breeding strategy GSrapid achieved consistently higher ΔGa than PSstandard (Figs. 1, 2, 3, 4, Table 2)
Summary
Plant breeding aims at the improvement of the economic merit of cultivars, which depends on the performance of the traits composing the product profile or variety concept (Bernardo 2010). The Smith–Hazel index (SH) behaves as an “optimum index” when variances and covariances are obtained without error As this is rarely the case, the base index uses only the economic importance of each trait as the weight and disregard phenotypic and genotypic covariances. The restricted index of Kempthorne and Nordskog uses variance and covariance components and economic importance to improve one trait while keeping the second constant. Despite these three indices requiring knowledge on each trait's economic importance, determining these economic weights is a cumbersome process in plant breeding (Mistele et al 1994). Well-known examples for negatively correlated traits are grain yield and protein content in bread wheat (Longin et al 2013a; Laidig et al 2016) and durum wheat (Longin et al 2013b; Rapp et al 2018), and dry matter yield and dry matter content in maize (Grieder et al 2012)
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
