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In our simulation of this scenario, trait values were drawn from an distribution for individuals with a copy of a variant predicted to trigger NMD, and for individuals with a copy of a variant predicted to escape NMD and otherwise (one variant was selected to escape NMD).
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It remains to be established under which water-limiting scenario this trait can be beneficial.
In the first scenario (single trait and m = 10,000,000 SNPs; the sample size varies from 1,000 to 40,000), all methods exhibit a quadratic behavior, and CLAK-C hol is the only algorithm that completed all tests within 25 hours).
The second scenario (single trait and sample size of 10,000; the number of markers varies between 1 and 36 millions) shows a linear dependence on the number of genetic markers for all software packages.
In a meeting scenario, some traits are more strongly manifested than others.
A limitation on the amount of concurrent improvement in both D BH and density is needed in order to ensure that predictions, particularly for future scenarios of trait improvement, are realistic.
This adds up to a total of 13 scenarios per trait.
In all four scenarios, the trait was determined by 50 QTL and had a heritability of 0.5.
Results showed that BLUP|GA outperformed GBLUP in 20 of 21 scenarios (three traits by seven population sizes) in the dairy cattle dataset (Table 2) and in 12 of 13 traits in the three public datasets (Table 4).
Given that the number of genotyped animals is the same in both scenarios, for traits with a low heritability, a half-sib design, as used here is more powerful for association studies than a direct design, in which the same animals are both genotyped and phenotyped [ 14].
For each scenario we simulated trait values of individuals from Equation (2) with Z = I n, B = 0 p, and X a single column of ones representing the trait means.
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