Plant Breeding with Genomic Selection: Gain per Unit Time and Cost

TLDR

Advances in genotyping lower marker costs and increase genome coverage, enabling marker‑assisted selection, yet MAS struggles with complex traits that require extensive phenotyping, whereas genomic selection uses all marker data to compute genomic estimated breeding values and allows direct selection without further phenotyping. The authors developed an analytical framework to compare genetic gains from MAS and GS and to contextualize GEBV accuracy results in plant breeding. They designed MAS and GS breeding strategies with equal budgets for a high‑investment maize program and a low‑investment winter wheat program. The study found that GS can outperform MAS per year even at low GEBV accuracies, with a 0.53 accuracy yielding three‑fold higher annual gain in maize and two‑fold in wheat, indicating that moderate accuracies can dramatically accelerate genetic gain through a shorter breeding cycle.

Abstract

ABSTRACT Advancements in genotyping are rapidly decreasing marker costs and increasing genome coverage. This is facilitating the use of marker‐assisted selection (MAS) in plant breeding. Commonly employed MAS strategies, however, are not well suited for agronomically important complex traits, requiring extra time for field‐based phenotyping to identify agronomically superior lines. Genomic selection (GS) is an emerging alternative to MAS that uses all marker information to calculate genomic estimated breeding values (GEBVs) for complex traits. Selections are made directly on GEBV without further phenotyping. We developed an analytical framework to (i) compare gains from MAS and GS for complex traits and (ii) provide a plant breeding context for interpreting results from studies on GEBV accuracy. We designed MAS and GS breeding strategies with equal budgets for a high‐investment maize ( Zea mays L.) program and a low‐investment winter wheat ( Triticum aestivum L.) program. Results indicate that GS can outperform MAS on a per‐year basis even at low GEBV accuracies. Using a previously reported GEBV accuracy of 0.53 for net merit in dairy cattle, expected annual gain from GS exceeded that of MAS by about threefold for maize and twofold for winter wheat. We conclude that if moderate selection accuracies can be achieved, GS could dramatically accelerate genetic gain through its shorter breeding cycle.