Physiological genetics attempts to relate the molecular genetic properties of an organism-the genotype-to its integrated or physiological behavior-the phenotype. There has been relatively little progress in this field when compared to the neighboring fields of molecular and population genetics. This is due in part to the large number of highly non-linear interactions that characterize such systems. Biochemical Systems Theory is one approach that shows promise in dealing with the large number of non-linear interactions in a systematically structured manner. A variant of this approach has stressed the use of specific mathematical constraints, called summation and connectivity relationships, among molecular and systemic properties. In particular, the summation relationship has been used to argue that the predominance of recessive mutations is the inevitable consequence of the kinetic structure of enzyme networks and need not be attributed to natural selection. In order to put in broader perspective the implications of such constraints for physiological genetics, we have presented in this paper the outlines of the larger theory and the set of generalized steady state constraints that follow from first principles within this theory. The results show that the summation relationship suffers from a number of fundamental limitations that make it invalid for analyzing realistic biological systems. It also is shown that the more general constraint relationships, while valid, provide nothing new that cannot be obtained directly from the explicit solutions that are available within the larger theory. Thus, one can conclude that approaches based directly on the underlying equations of the system are superior to those based upon constraint relationships as a foundation for the development of physiological genetics.
ASJC Scopus subject areas
- Agricultural and Biological Sciences(all)
- Biochemistry, Genetics and Molecular Biology(all)
- Immunology and Microbiology(all)
- Applied Mathematics
- Modeling and Simulation
- Statistics and Probability