In recent years genome-wide association studies (GWAS) have uncovered a plethora of chromosomal loci associated with a variety of cardiac traits. As in most GWAS, a considerable portion of identified signals occur at inter-genic regions of the genome. Trait-associated single nucleotide polymorphisms (SNPs) located in these non-coding regions likely exert their effect through modulation of gene expression. Thus interrogating these variants for association with differential transcript abundance by expression quantitative trait locus (eQTL) analysis is a highly relevant means to unravel the causal genes at loci identified by GWAS. This will in turn further our understanding of the molecular mechanisms underlying cardiac traits. In this study, for the first time, we carried out an eQTL analysis in human heart. A total of 129 human left ventricle samples were collected at four collaborating centers. Samples were acquired from non-diseased hearts that were considered suitable for transplantation, yet not used for logistical reasons. All individuals were of Western European descent. Genome-wide transcript abundance and genotypes were assessed using the Illumina HumanHT-12 and HumanOmniExpress microarrays, respectively. After pre-processing and stringent quality control of transcript and genotypic data, each transcript was tested for association with genotypes genome-wide using linear modelling in R, correcting for age, gender and center effects. We identified 770 independent cis-eQTLs (SNPs within 1 Mb of transcript) mapping to 457 unique transcripts (FDR < 1%). Overlaying these eQTLs with cardiac GWAS loci identified strong candidate genes for functional studies. One of these involves an eQTL effect of rs9912468, a robust modifier of QRS, on PRKCA (p = 1.52E-11). Our findings provide evidence for the role of PRKCA in mediating the effect of the rs9912468-tagged haplotype on QRS duration. Additionally, we identified several trans-eQTL hotspots in the vicinity of transcription factors, regulating targets predominantly involved in immune response, signalling and cardiac muscle structure related processes, all known to impact on the heart function. An on-going effort entails overlaying the eQTLs with known cardiac regulatory regions, such as binding regions of cardiac specific transcription factors (TBX3, TBX5, NKX2-5, GATA4, SRF) and enhancers, identified through ChIP-sequencing in the ENCODE project and other studies. Our study illustrates the power of integrating gene expression, phenotype and genotype data in a systems genetics approach, in identifying novel causal genes for human cardiac phenotypes.