Estimation of heritability is crucial for breeding purposes and for understanding the genetic basis of phenotypic traits. For the specific case of expression traits, heritability estimates can be used to prioritize expression quantitative trait loci (eQTL) genes. Estimates of heritability are usually obtained by linking phenotypic records with the estimated relationship matrix. The relationship matrices can be derived from pedigree, marker information or both. We propose an approach to estimate heritability of gene expression that takes full advantage of next generation sequencing platforms. A GBLUP-based animal model was used to fit all genetic markers simultaneously to each gene expression profile individually. A preliminary study using longissimus muscle (LM) transcriptome sequence data (RNaseq) for 24 animals from the Michigan State University pig resource population (MSUPRP) showed that more power was needed to identify significant genetic effects when using gene expression profiles as a trait phenotype. A subsequent study involving LM RNaseq for 144 MSUPRP animals was conducted using a similar GBLUP-based model. Results showed great improvement in the detection of significantly heritable expression traits (HET). A total of 226 statistically significant HET were discovered at FDR = 1%. The range of heritability estimates for these significant expression traits was between 0.27 and 1.00. Furthermore, 3 gene expression profiles showed extremely high heritability (h² > 0.99, with GBV q-values <1 × 10⁻⁸). Pathway Analyses of the significant HET revealed multiple genes involved in organismal development and transcriptional regulation emphasizing cellular growth and proliferation. The top genes involved in these molecular processes include TGFB3, BMPR1A and MCM8, the former 2 associated with weight gain. This research shows that genomic prediction models can be effectively used to elucidate the molecular mechanisms driving variations in heritable expression traits and to identify important regulatory gene networks.