One uses DNA information in at least four explanatory settings: as a pure marker where we do not make a direct link to any particular phenotype; when we by statistical means establish an association between one or more chromosomal regions and phenotypic variation; when we can document that a particular DNA variation (natural or imposed) does indeed cause a phenotype; and finally in a causally cohesive setting where we can also explain how the genetic variation causes the observed phenotype in terms of biophysical mechanism at the cell, tissue and organ system levels. Even though there are several challenges associated with the first three types of explanation, they are all dwarfed by those facing us in connection with the fourth type. But these are the ones to be overcome if we are to bridge the gap between the genotype and the phenotype with real understanding, and thus realize the disciplinary goals of both genetics (Bateson, 1906 p.190) and physiology (Gove, 1981). The relation between genotype and phenotype can be conceptualized as a genotype-phenotype map (GP map), assigning a phenotype to each possible genotype. The concept is highly instrumental for physiological research and concords well with the disciplinary goals of physiology as they are laid out in the standard definition of the discipline: “the study of the functions and activities of living matter (as of organs, tissues, or cells) as such and of the physical and chemical phenomena involved” (Webster’s Third New International Dictionary). Fulfilling these goals demands an understanding of the mechanisms underlying the GP map. The GP map concept applies to any time point in the ontogeny of a living system and it is an abstraction of a relation that is the outcome of very complex dynamics that include environmental effects. The concept does not imply that DNA has a privileged place in the chain of causality authorizing the current zoo of anthropomorphic concepts we attribute to it (Omholt, 2012; Noble, 2012). As advocated by Omholt (2012), DNA allows a system to induce perturbations of its own dynamics as a function of its own system state or phenome. Thus there is no direct causal arrow from genotype to phenotype in the sense that DNA is responsible for exerting a direct effect as a sub-system on the system dynamics. The causality flows from the system state through a change in use of DNA (as an inert system component) that results in a change in the production of RNA and protein, which in turn perturbs the system’s dynamics. In those cases where variations in DNA cause changes in the perturbation regime it may lead to different system dynamics and thus physiological variation. This way of perceiving the function of DNA in a GP map context brings physiology back as the major arena for understanding the manifestation and propagation of genetic variation. The talk will elaborate on the above concepts and show how computational physiology is the key to combine genetics and physiology. Starting out from simple illustrations on how to analyse genetic concepts within a systems dynamics framework, the talk will present current work to link genetics with mechanistic multiscale and multiphysics model descriptions of high-dimensional phenotypes by use of so-called causally cohesive genotype to phenotype models (cGP models). It will be shown how this approach is capable of providing a direct link between genetic variation, molecular regulatory biology and phenotypic variation. It can therefore be used to build theory about heredity phrased in terms of regulatory principles, something which standard genetic concepts and approaches are incapable of.