BACKGROUND: The predominant model for regulation of gene expression through DNA 
methylation is an inverse association in which increased methylation results in 
decreased gene expression levels. However, recent studies suggest that the 
relationship between genetic variation, DNA methylation and expression is more 
complex.
RESULTS: Systems genetic approaches for examining relationships between gene 
expression and methylation array data were used to find both negative and 
positive associations between these levels. A weighted correlation network 
analysis revealed that i) both transcriptome and methylome are organized in 
modules, ii) co-expression modules are generally not preserved in the 
methylation data and vice-versa, and iii) highly significant correlations exist 
between co-expression and co-methylation modules, suggesting the existence of 
factors that affect expression and methylation of different modules (i.e., trans 
effects at the level of modules). We observed that methylation probes associated 
with expression in cis were more likely to be located outside CpG islands, 
whereas specificity for CpG island shores was present when methylation, 
associated with expression, was under local genetic control. A structural 
equation model based analysis found strong support in particular for a 
traditional causal model in which gene expression is regulated by genetic 
variation via DNA methylation instead of gene expression affecting DNA 
methylation levels.
CONCLUSIONS: Our results provide new insights into the complex mechanisms 
between genetic markers, epigenetic mechanisms and gene expression. We find 
strong support for the classical model of genetic variants regulating 
methylation, which in turn regulates gene expression. Moreover we show that, 
although the methylation and expression modules differ, they are highly 
correlated.