The genetic basis of complex diseases is expected to be highly heterogeneous, with complex interactions among multiple disease loci and environment factors.
Ultimately, individual fitness, controlling the production of offspring to which genetic material is transmitted, is determined by an individual's functional loci and environment.
T2D is also associated with aging, and the underlying mechanisms that increase susceptibility of an individual to develop the disease implicate epigenetics: interactions between susceptible loci and the environment.
Most researchers use logistic regressions to model odds as the additive combination of main effects of a single-locus and the environment, and a residual term.
Given that most common human diseases are outcome of a complex interaction between many genetic loci and the environment, there are obvious advantages to studying the genetics of gene expression in cells that represent the in vivo state.
CNPs are likely to have variable affects on phenotypes, depending on the sensitivity of the gene to dose, interactions with other loci, and the environment.
This is a formidable task since it is likely that many of these loci will be complex in their local operation as well as in their interaction with other loci and the environment.
We define an individual-based computational model in which genotypes are represented by L loci, and the environment is composed of L resources for which the two populations compete.
Keynote speaker Fred van Eeuwijk (Wageningen University) gave a comprehensive overview of genome × environment modeling in plants, from basic models taught in an introductory course for plant breeders, to recent developments incorporating temperature-responsive quantitative trait loci, and characterizing environments through additional variables such as temperature, rainfall, etc.
The number of scale and environment specific loci identified in any environment present as a crossover within 60 kb were counted.
