Gains through selection for grain yield in a winter wheat breeding program

Authors: LOZADA, DENNIS - Washington State University; Ward, Brian; CARTER, ARRON - Washington State University

Submitted to: PLOS ONE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/26/2020
Publication Date: 4/28/2020
Citation: Lozada, D., Ward, B.P., Carter, A.H. 2020. Gains through selection for grain yield in a winter wheat breeding program. PLoS One. https://doi.org/10.1371/journal.pone.0221603.
DOI: https://doi.org/10.1371/journal.pone.0221603

Interpretive Summary: In breeding programs, genetic gain is defined as the improvement or increase in performance for a particular trait over cycles of artificial selection (i.e. generations). The realization of genetic gain may become difficult for more complex traits, as these are influenced by environment to varying degrees. In this study, we evaluated genetic gain for the trait grain yield in ten populations of Washington State University winter wheat breeding lines by evaluating the response to selection (R) achieved through using several different selection strategies, including phenotypic selection (PS), marker-assisted selection (MS, where specific markers known to be associated with a trait are used for selection), and genomic selection (GS, where many markers spread across the genome are used for selection). PS is a direct selection strategy, where selections are made using measurements of the target trait itself, while MS and GS are both indirect selection strategies, where selections are made using correlated data (in this case marker data) that is cheaper or easier to obtain. Within individual environments, PS performed best, producing the highest mean response to selection. However, the within-environment response to selection could be further improved (by 23% on average) by combining predictions generated using PS and GS in combination. In general, the MS strategy underperformed both the PS and GS strategies in all scenarios. Superior plants selected in one environment did not necessarily perform well in other environments; the selection to response in these scenarios was often zero or occasionally even negative. This highlights the confounding role of environment in determining the expression of a complex trait such as grain yield, and the low reliability of yield estimates based on few environments and data points. Nevertheless, the results indicate that the use of PS in combination with GS can help to optimize selection within environments.

Technical Abstract: Increased genetic gain for complex traits in plant breeding programs can be achieved through different selection strategies. The objective of this study was to compare potential gains for grain yield in a winter wheat breeding program through estimating response to selection R values across several selection approaches including phenotypic (PS), marker-based (MS), genomic (GS), and a combination of PS and GS (PS+GS). Ten populations of Washington State University (WSU) winter wheat breeding lines including a diversity panel and F5 and double haploid lines evaluated from 2015 to 2019 growing seasons for grain yield in Lind and Pullman, WA, USA were used in the study. Selection was conducted by selecting the top 20% of lines based on observed yield (PS strategy), genomic estimated breeding values (GS), presence of yield “enhancing” alleles of the most significant single nucleotide polymorphism (SNP) markers identified from genome-wide association mapping (MS), and high observed yield and estimated breeding values (PS+GS). Overall, PS compared to other individual selection strategies (MS and GS) showed the highest mean response (R = 0.61) within the same environment. When combined with GS, a 23% improvement in R for yield was observed, indicating that gains could be improved by complementing traditional PS with GS within the same environment. Validating selection strategies in different environments resulted in low to negative R values indicating the effects of genotype-by-environment interactions for grain yield. MS was not successful in terms of R relative to the other selection approaches; using this strategy resulted in a significant (P < 0.05) decrease in response to selection compared with the other approaches. An integrated PS+GS approach could result in optimal genetic gain within the same environment, whereas a PS strategy might be a viable option for grain yield validated in different environments. Altogether, we demonstrated that gains through increased response to selection for yield could be achieved in the WSU winter wheat breeding program by implementing different selection strategies either exclusively or in combination.