We present primary results from the Sequencing Quality Control (SEQC) project, coordinated by the United States Food and Drug Administration. Examining Illumina HiSeq, Life Technologies SOLiD and Roche 454 platforms at multiple laboratory sites using reference RNA samples with built-in controls, we assess RNA sequencing (RNA-seq) performance for junction discovery and differential expression profiling and compare it to microarray and quantitative PCR (qPCR) data using complementary metrics. At all sequencing depths, we discover unannotated exon-exon junctions, with >80% validated by qPCR. We find that measurements of relative expression are accurate and reproducible across sites and platforms if specific filters are used. In contrast, RNA-seq and microarrays do not provide accurate absolute measurements, and gene-specific biases are observed, for these and qPCR. Measurement performance depends on the platform and data analysis pipeline, and variation is large for transcript-level profiling. The complete SEQC data sets, comprising >100 billion reads (10Tb), provide unique resources for evaluating RNA-seq analyses for clinical and regulatory settings.

ABSTRACT:In addition to primary human hepatocytes, hepatoma cell lines, and transfected nonhepatoma, hepatic cell lines have been used for pharmacological and toxicological studies. However, a systematic evaluation and a general report of the gene expression spectra of drug-metabolizing enzymes and transporters (DMETs) in these in vitro systems are not currently available. To fill this information gap and to provide references for future studies, we systematically characterized the basal gene expression profiles of 251 drugmetabolizing enzymes in untreated primary human hepatocytes from six donors, four commonly used hepatoma cell lines (HepG2, Huh7, SK-Hep-1, and Hep3B), and one transfected human liver epithelial cell line. A large variation in DMET expression spectra was observed between hepatic cell lines and primary hepatocytes, with the complete absence or much lower abundance of certain DMETs in hepatic cell lines. Furthermore, the basal DMET expression spectra of five hepatic cell lines are summarized, providing references for researchers to choose carefully appropriate in vitro models for their studies of drug metabolism and toxicity, especially for studies with drugs in which toxicities are mediated through the formation of reactive metabolites.

The patterns of expression of glutathione S-transferases A1 and A2 in human liver (hGSTA1 and hGSTA2, respectively) are highly variable, notably in the ratio of hGSTA1/hGSTA2. We investigated if this variation had a genetic basis by sequencing the proximal promoters (-721 to -1 nucleotides) of hGSTA1 and hGSTA2, using 55 samples of human liver that exemplified the variability of hGSTA1 and hGSTA2 expression. Variants were found in the hGSTA1 gene: -631T or G, -567T, -69C, -52G, designated as hGSTA1*A; and -631G, -567G, -69T, -52A, designated as hGSTA1*B. Genotyping for the substitution -69C > T by polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP), showed that the polymorphism was widespread in Caucasians, African-Americans and Hispanics, and that it appeared to conform to allelic variation. Constructs consisting of the proximal promoters of hGSTA1*A, hGSTA1*B or hGSTA2, with luciferase as a reporter gene, showed differential expression when transfected into HepG2 cells: hGSTA1*A approximately hGSTA2 > hGSTA1*B. Similarly, mean levels of hGSTA1 protein expression in liver cytosols decreased significantly according to genotype: hGSTA1*A > hGSTA1-heterozygous > hGSTA1*B. Conversely, mean hGSTA2 expression increased according to the same order of hGSTA1 genotype. Consequently, the ratio of GSTA1/GSTA2 was highly hGSTA1 allele-specific. Because the polymorphism in hGSTA1 correlates with hGSTA1 and hGSTA2 expression in liver, and hGSTA1-1 and hGSTA2-2 exhibit differential catalysis of the detoxification of carcinogen metabolites and chemotherapeutics, the polymorphism is expected to be of significance for individual risk of cancer or individual response to chemotherapeutic agents.

Published studies have identified genetic variants, somatic mutations, and changes in gene expression profiles that are associated with hepatocellular carcinoma (HCC), particularly involving genes that encode drug metabolizing enzymes (DMEs). CYP2C9, one of the most abundant and important DMEs, is involved in the metabolism of many carcinogens and drugs and is down-regulated in HCC. To investigate the molecular mechanisms that control CYP2C9 expression, we applied integrative approaches including in silico, in vitro, and in vivo analyses to elucidate the role of microRNA hsa-miR-128-3p in the regulation of CYP2C9 expression and translation. RNA electrophoresis mobility shift assays demonstrated a direct interaction between hsa-miR-128-3p and its cognate target, the CYP2C9 transcript. Furthermore, the expression of a luciferase reporter gene containing the 3′-UTR of CYP2C9 and the endogenous expression of CYP2C9 were suppressed by transfection of hsa-miR-128-3p. Importantly, chemically-induced up- or down-regulation of hsa-miR-128-3p correlated inversely with the expression of CYP2C9. Finally, an association analysis revealed that the expression of hsa-miR-128-3p is inversely correlated with the expression of CYP2C9 in HCC tumor tissues. Altogether, the study helped to elucidate the mechanism of CYP2C9 regulation by hsa-miR-128-3p, and the inverse association in HCC.