Defining Gene and QTL Networks.

Unraveling complex traits requires an understanding of how genetic variation results in variation among transcript levels, proteins, and metabolites, and how this variation generates phenotypic variation. These distinct levels in the biological system are interdependent. The ability to model interactions among loci at each of these levels, and relationships between levels, is key to providing insight into complex traits. The promise of genomic and proteomic technology is in capturing variation for thousands of loci simultaneously. This affords an unprecedented opportunity to understand the consequences of genetic variation. Many studies have exploited this ability through the use of mutant analysis applied to whole-genome transcript arrays.  New studies using microarrays for RILs and of classical breeding designs provide insights into cis and trans regulation and  providing insight into how coordinated gene expression affects phenotype. Analytic approaches that allow interpretation of the relationships among transcript levels and modeling of the link between transcript level and phenotype are presented.