Furthermore, the importance of NAergic neurotransmission for social memory has been demonstrated in mouse model of locus coeruleus lesion and in transgenic mice lacking the dopamine beta-hydroxylase.
For example, our model could be used to shed light on shadow enhancers (Perry et al. 2010; Barolo 2012), by using the GEMSTAT-GL model of locus-level modeling for regulatory function prediction instead of the GEMSTAT model of enhancer function.
To analyze the locus in its active state we used primary erythroid cells from fetal liver which were compared to fetal brain cells as a model of inactive loci.
We next simulated genetic heterogeneity (Table 3B) with 0.5/0.5, 0.7/0.3 proportions of subjects affected by a mixture model of epistasis from loci 1x2 and loci 4*5.
Assuming a log-additive model of interaction between loci, the currently known loci define a polygenic risk profile that could be used for risk stratification (Pharoah et al, 2008; Pashayan et al, 2011).
In biological terms, this model has subsets of loci which are entirely linear in effect, some which are entirely nonlinear, and interactions between these subsets.
Thus the basic requirements for adaptation in our model were presence of loci in the host and worm that interact and genetic variation in both the worm and host locus.
Many would acknowledge that simultaneous modeling of all loci potentially yields fairer estimates of genetic effect, more stable phenotypic predictions, and better characterization of between-locus confounding [Hoggart et al., 2008; Lee et al., 2008].
For the logistic regression analysis, we used the methodology proposed by Cordell and Clayton [12] in which nested hypotheses involving logistic regression models of different loci are compared using likelihood ratio tests.
Simultaneous modeling of multiple loci should help.
