Simplified theoretical machinery of quantitative genetics under network model. In this simple scenario, the tridimensional architecture of genes denotes the network model and the projection image of genes on the surface of the batholith denotes the mixed model. It is easy to understand that the mixed model is just a dimension reduction mapping of the network model. As hypothesized in , the phenotypic measurement equalizes the accumulated output of gene network, and thus here the batholith supportive of the gene network can be abstractively expressed as the phenotype. Considering a tridimensional relationship in the network model, the batholith only receives the direct input information of adjacent genes, but indirectly the non-adjacent genes act, which means the effects of non-adjacent genes on the batholith are through the adjacent ones. However, the mixed model takes a bidimensional viewpoint to simplify the gene relationship, in which each gene makes a direct projection on the surface of the batholith. Given this, in mixed model, it can be inferred that the non-adjacent genes are unavoidable to produce repeated effects on the phenotype (batholith), which, in our opinion, could be used to alternatively explain why too many candidates or QTLs for the same trait had been reported but most of which are hitherto unidentifiable. A. In mixed model, the projected area could be denotative of the effect size of gene. The overlapped projection on the surface of the batholith reflects the interlocus interaction, where the two-time and three-time projection overlapping denotes the one-order and two-order interactions, respectively. For the intralocus interaction (not reflected here), considering the diploid organism in which a gene has two alleles, the interaction can be also expressed by the varied projection area of two alleles along with different combination of alleles. B. In network model, some regulatory links between genes are development-dependent, which dynamically exist at specific developmental stages. The network model is dynamic rather than static.