The genetic architecture revealed by association mapping can be used to inform the GS models—for example, if highly significant SNPs are revealed by a GWAS, these SNPs could be fit as fixed effects in a GS model [ 14 , 17 ], and experimenting with different types of genomic selection statistical methods (i.e., linear versus non-linear, additive versus non-additive) can corroborate inferences about the genetic architecture of a trait.
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Genome-wide association mapping for yield and other agronomic traits in an elite breeding population of tropical rice (Oryza sativa).
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