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Data for: Increasing plant group productivity through latent genetic variation for cooperation

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NIAID Data Ecosystem2026-03-13 收录
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https://zenodo.org/record/2659734
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Technologies for crop breeding have become increasingly sophisticated, yet it remains unclear whether these advances are sufficient to meet future demands. A major challenge with current crop selection regimes is that they are often based on individual performance. This tends to select for plants with “selfish” traits, which leads to a yield loss when they compete in high-density stands. In traditional breeding, this well-known “tragedy of the commons” has been addressed by anticipating ideotypes with presumably preferential characteristics. However, this approach is limited to obvious architectural and physiological traits, and it depends on a mechanistic understanding of how these modulate growth and competition. Here, we developed a general and simple method for the discovery of alleles promoting cooperation of plants in stands; it is based on the game-theoretical premise that alleles increasing cooperation incur a cost to the individual but benefit the monoculture group. Testing the approach using the model plant Arabidopsis thaliana, we found a single major effect locus where the rarer allele was associated with increased levels of cooperation and superior monoculture productivity. We show that the allele likely affects a pleiotropic regulator of growth and defense, since it is also associated with reduced root competition but higher race-specific resistance against a specialized parasite. Even though cooperation is considered evolutionarily unstable, conflicting selective forces acting on a pleiotropic gene might thus maintain latent genetic variation for it in nature. Such variation, once identified in a crop, could be rapidly leveraged in modern breeding programs and provide efficient routes to increase yields.
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2022-08-11
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