Extensive studies have been conducted on the analysis of genome function, especially on expression quantitative trait loci (eQTL). These studies offered promising results for characterization of the functional sequencing variation and understanding of the basic processes of gene regulation. Parent of origin effect (POE) as an important epigenetic phenomenon describing that the expression of certain genes depends on their allelic parent-of-origin and it is known to play important roles in human complex diseases.However,traditional eQTL mapping approaches do not allow for the detection of imprinting, or they focus on modeling the additive genetic effect thereby ignoring the estimation of the dominant genetic effect. In this study,we proposed a statistical framework to test the additive and dominant genetic effects of the candidate eQTLs along with detection of POE with a functional model and an orthogonal model for RNA-seq data. We demonstrated the desirable power and preserved Type I errors of the methods in most scenarios, especially the orthogonal model with un-biased estimation of the genetic effects and over-dispersion of the RNA-seq data. The application to a HapMap project trio dataset validated existing imprinted genes and discovered two novel imprinted genes with potential dominance genetic effect. This study provides new insights into the next generation statistical modeling of eQTL mapping for better understanding the genetic architecture underlying the mechanisms of gene expression regulation.