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According to a linear model with genotype and block fixed effects, analysis of variance was performed for each site separately.
The ANOVA performed in this step was a mixed model with genotype, age and genotype×age interaction as fixed effects and chip (nested within interaction) as a random effect.
Analysis model and data type: A, GLM model with genotype data; B, MLM model with genotype data; C, GLM model with haplotype data; D, MLM model with haplotype data.
For genetic analysis, heritability of traits was estimated with a mixed-effects model with genotype as random effect.
Protein quantities were modeled using a linear model with genotype, age and their interaction term controlling for blot.
Enzyme activity measurements were analyzed by analysis of variance (ANOVA) by using a split-plot model with genotype as the main plot.
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The adjusted entry means, computed as best linear unbiased estimates by using a mixed model with genotypes treated as fixed effects, are provided in Supporting Information, File S1.
Each single environment was separately analyzed for grain yield using a mixed model with genotypes as fixed and replications and incomplete blocks nested within replications as random.
For each response variable (courtship latency, copulation latency, and copulation duration), we built a model with male genotype, female genotype, male age, female age, and male genotype × female genotype interaction, which we refer to as the base model.
Linear regression modeling with genotype and lead variable cross-product terms was used to evaluate effect modification by genotype on associations between lead biomarkers and uric acid.
Logistic regression models with genotype coded 0, 1, 2 and treated as a continuous covariate (one at a time), were fitted for each SNP that passed quality control.
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