The Potential for Genotype-by-Environment Interactions to Maintain Genetic Variation in a Model Legume-Rhizobia Mutualism

Abstract

The maintenance of genetic variation in mutualism-related traits is key for understanding mutualism evolution, yet the mechanisms maintaining variation remain unclear. We asked whether genotype-by-environment (G×E) interaction is a potential mechanism maintaining variation in the model legume-rhizobia system, Medicago truncatula-Ensifer meliloti. We planted 50 legume genotypes in a greenhouse under ambient light and shade to reflect reduced carbon availability for plants. We found an expected reduction under shaded conditions for plant performance traits, such as leaf number, aboveground and belowground biomass, and a mutualism-related trait, nodule number. We also found G×E for nodule number, with ∼83% of this interaction due to shifts in genotype fitness rank order across light environments, coupled with strong positive directional selection on nodule number regardless of light environment. Our results suggest that G×E can maintain genetic variation in a mutualism-related trait that is under consistent positive directional selection across light environments.

Keywords: Medicago truncatula; genetic variation; genotype-by-environment interaction; light availability; mutualism evolution; partner quality.

Figure 1

Effects of Light Treatment and Genotype-by-Treatment Interaction on Plant Performance and Mutualism-Related Traits. (A, C, E, G, and I) The main effect of light treatment (shade and ambient), with points representing raw treatment means ± 95% confidence intervals (CIs).(B, D, F, H, and J) The genotype-by-treatment interaction effect, with points representing least-squares line means ± 95% CIs.

Figure 2

Genetic Correlation Matrix between Traits and across Environments. Correlations are of raw line means for each trait within the ambient (gold) and shade (green) treatments. Dark bordered boxes show between treatment correlations for each trait. Numbers present correlation coefficients, which are also represented by the color legend on the right. Insignificant correlations (p > 0.05) are indicated by the absence of an ellipse.

Figure 3

Partial Regression Plots of Selection-by-Environment Analyses for Plant Performance and Mutualism-Related Traits. Aboveground biomass is used as the fitness proxy, and three scaling methods were applied: absolute (A–C), global (among treatments, D–F), and local (within treatments, G–I). The y axes of all plots were transformed back to their original scale by adding mean relative fitness, and the x axes of (A)–(C) were similarly transformed by adding mean trait values to better reflect the ANCOVA results in Table 2. Points represent raw line means in the ambient (gold, triangle) and shade (green, circle) treatments that were scaled based on the three scaling methods. Solid lines and shading represent selection gradients and ±95% CIs, respectively. Corresponding within-treatment β estimates are provided for all traits, with bolded values representing traits that showed a significant (p < 0.05) selection-by-environment interaction.