RNA-Sequencing Analysis of HepG2 Cells Treated with Atorvastatin Camilla Stormo1*, Marianne K. Kringen2, Robert Lyle3, Ole Kristoffer Olstad1, Daniel Sachse4, Jens P. Berg1,4, Armin P. Piehler5 1 Department of Medical Biochemistry, Oslo University Hospital, Ulleva˚l, Oslo, Norway, 2 Department of Pharmacology, Oslo University Hospital, Ulleva˚l, Oslo, Norway, 3 Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway, 4 Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway, 5 Fu¨rst Medical Laboratory, Oslo, Norway Abstract The cholesterol-lowering drug atorvastatin is among the most prescribed drug in the world. Alternative splicing in a number of genes has been reported to be associated with variable statin response. RNA-seq has proven to be a powerful technique for genome-wide splice variant analysis. In the present study, we sought to investigate atorvastatin responsive splice variants in HepG2 cells using RNA-seq analysis to identify novel candidate genes implicated in cholesterol homeostasis and in the statin response. HepG2 cells were treated with 10 mM atorvastatin for 24 hours. RNA-seq and exon array analyses were performed. The validation of selected genes was performed using Taqman gene expression assays. RNA-seq analysis identified 121 genes and 98 specific splice variants, of which four were minor splice variants to be differentially expressed, 11 were genes with potential changes in their splicing patterns (SYCP3, ZNF195, ZNF674, MYD88, WHSC1, KIF16B, ZNF92, AGER, FCHO1, SLC6A12 and AKAP9), and one was a gene (RAP1GAP) with differential promoter usage. The IL21R transcript was detected to be differentially expressed via RNA-seq and RT-qPCR, but not in the exon array. In conclusion, several novel candidate genes that are affected by atorvastatin treatment were identified in this study. Further studies are needed to determine the biological significance of the atorvastatin responsive splice variants that have been uniquely identified using RNA-seq. Citation: Stormo C, Kringen MK, Lyle R, Olstad OK, Sachse D, et al. (2014) RNA-Sequencing Analysis of HepG2 Cells Treated with Atorvastatin. PLoS ONE 9(8): e105836. doi:10.1371/journal.pone.0105836 Editor: Ken Mills, Queen’s University Belfast, United Kingdom Received May 28, 2013; Accepted July 30, 2014; Published August 25, 2014 Copyright: ß 2014 Stormo et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This work was funded by the Division of Diagnostics and Intervention, Oslo University Hospital, Norway and by grants from The Blix Family Foundation and Sigrid Wolmar Fund for Heart and Lung Diseases. The sequencing service was provided by the Norwegian Sequencing Centre (www.sequencing.uio.no) a national technology platform supported by the Research Council of Norway and the Southeastern Regional Health Authorities. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: Armin Piehler is a consultant in medical biochemstry at Fu¨rst Medical Laboratory. He has received lecturer fees from Siemens. He has no competing interests to declare, and this does not alter the authors’ adherence to all the PLOS ONE policies on sharing data and materials. * Email: [email protected] Introduction events in 1–5% of patients [6]. In addition, beneficial effects of statins on endothelial function, inflammation, and plaque stability Atorvastatin is an efficient competitive inhibitor of 3-hydroxy-3- have been demonstrated, suggesting that statins have effects methylglutaryl-Coenzyme A (HMG-CoA) reductase (HMGCR), beyond lowering cholesterol [7]. The exact molecular mechanisms the rate-limiting enzyme in cholesterol synthesis. Atorvastatin underlying these LDL-cholesterol independent effects of statins are belongs to the statin class of drugs and is widely used to reduce still unclear. cholesterol levels and the risk of cardiovascular disease. The Studies on global gene expression effects of statin treatment cholesterol-lowering effect of statins is well documented. Statins have mostly been performed by microarray analysis [8–13]. block HMGCR and prevent the conversion of HMG-CoA to Microarrays have been used in gene expression studies for nearly mevalonate and thereby decrease the level of sterol and non-sterol two decades, whereas RNA sequencing (RNA-seq) is a relatively products derived from mevalonate, including cholesterol. As a new approach for this purpose [14,15]. Briefly, RNA is converted compensatory effect, sterol-regulated genes, such as HMGCR and into cDNA, which is fragmented and PCR-amplified before being low-density lipoprotein (LDL) receptor (LDLR), are upregulated to subjected to parallel sequencing to generate millions of reads. The increase de novo cholesterol synthesis and the receptor-mediated gene expression and splice variant levels are determined using the uptake of LDL-cholesterol from the blood. RNA-seq data by counting the number of sequence reads aligned Statins are generally well tolerated in most people [1–3]; to each gene in the genome. however, there is a large amount of variability in the responses Human hepatoma HepG2 cells are considered a useful model across individuals, which can be partly explained by genetic factors for studying the effects of statin treatment on hepatocytes [16–18]. [4]. Interestingly, the expression level of a minor splice variant of Because alternative splicing has been reported to be relevant for HMGCR lacking exon 13 has been shown to be associated with cholesterol homeostasis and variation in statin response in a variations in the plasma LDL-cholesterol levels and statin response number of genes [5,19–23], we sought to investigate statin [5]. Statins may also induce a range of adverse, muscle-related responsive splice variant expression changes to identify novel PLOS ONE | www.plosone.org 1 August 2014 | Volume 9 | Issue 8 | e105836 RNA-Sequencing Analysis and Atorvastatin Treatment candidate genes as potential regulators of the statin response. In ping allowing up to two mismatches [25]. An average of this study, we used RNA-seq in combination with microarray 25.860.34 (mean 6 STD) and 24.060.42 million 26100-bp analysis to provide a comprehensive transcriptome profile of reads per control and atorvastatin-treated sample were obtained, HepG2 cells exposed to atorvastatin. respectively. The aligned reads were assembled into transcripts using the Cufflinks software [26]. Cufflinks computes normalized Methods values termed FPKM (fragments per kilobase of exon per million fragments mapped), which reflect the mRNA expression levels Cell culture and treatment [26]. The reads were mapped to a total of 23,138 Refseq genes The human hepatoblastoma cell line HepG2 (American Type and 39,843 Refseq transcript splice variants. Statistical analysis of Culture Collection, Manassas, VA, USA) was maintained in differentially expressed genes and transcript splice variants, collagen I-coated tissue culture flasks (BD Biosciences, San Jose, differential splicing and differential promoter usage was performed CA, USA) and modified Eagle’s minimal essential medium (MEM; using Cuffdiff, which is integrated into Cufflinks. In the differential ATCC), supplemented with 10% heat inactivated fetal bovine splicing analysis, Cuffdiff calculates the changes in the relative serum (FBS) and 1% penicillin-streptomycin-glutamine mixture abundance of splice variants produced from a single primary (Sigma-Aldrich, St Louis, MO, USA). In the treatment experi- 5 transcript sharing a common transcription start site, such as a ments, cells were seeded at 2610 cells/mL in a 12-well collagen change in the splicing pattern. In the differential promoter usage I-coated plate (BD Biosciences). The following day, the medium analysis, Cuffdiff tests for differential promoter use in genes with was changed to 1 mL growth medium containing 3 mg/mL of two or more promoters that generate primary transcripts with human lipoprotein deficient serum (LPDS; Millipore, Billerica, different start sites. The status code ‘‘OK’’ in Cuffdiff indicates MA, USA) instead of FBS. Because we wanted to study the effects that there are a sufficient number of reads in a locus to make a of statin that were due to the inhibition of cholesterol biosynthesis, reliable calculation. The default false discovery rate (FDR) of we used the magnitude of increased HMGCR mRNA expression Cuffdiff is 5%. The results were visualized using the CummeR- as a marker for statin response. The initial experiments showed bund package [27] in the statistics environment R [28]. The that HepG2 cells grown in medium containing 10% FBS had low CummeRbund package is available from the Bioconductor mRNA levels, which remained unchanged when treated HMGCR website [29]. Sequence reads have been deposited in the NCBI with atorvastatin. We therefore took advantage of LPDS to BioSample database (http://www.ncbi.nlm.nih.gov/biosample) activate cholesterol biosynthesis and increase the expression of with the following accessions: SAMN02808181, SAMN02808182, HMGCR in both the control and atorvastatin-treated cells, as SAMN02808183, SAMN02808184, SAMN02808185 and previously demonstrated [24]. In the dose response experiments, SAMN02808186. cells were treated with water