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RNA-Seq gene expression profiling of HepG2 cells: the influence of experimental factors and comparison with liver tissue.

ABSTRACT: Human hepatoma HepG2 cells are used as an in vitro model of the human liver. High-throughput transcriptomic sequencing is an advanced approach for assessing the functional state of a tissue or cell type. However, the influence of experimental factors, such as the sample preparation method and inter-laboratory variation, on the transcriptomic profile has not been evaluated.The whole-transcriptome sequencing of HepG2 cells was performed using the SOLiD platform and validated using droplet digital PCR. The gene expression profile was compared to the results obtained with the same sequencing method in another laboratory and using another sample preparation method. We also compared the transcriptomic profile HepG2 cells with that of liver tissue. Comparison of the gene expression profiles between the HepG2 cell line and liver tissue revealed the highest variation, followed by HepG2 cells submitted to two different sample preparation protocols. The lowest variation was observed between HepG2 cells prepared by two different laboratories using the same protocol. The enrichment analysis of the genes that were differentially expressed between HepG2 cells and liver tissue mainly revealed the cancer-associated gene signature of HepG2 cells and the activation of the response to chemical stimuli in the liver tissue. The HepG2 transcriptome obtained with the SOLiD platform was highly correlated with the published transcriptome obtained with the Illumina and Helicos platforms, with moderate correspondence to microarrays.In the present study, we assessed the influence of experimental factors on the HepG2 transcriptome and identified differences in gene expression between the HepG2 cell line and liver cells. These findings will facilitate robust experimental design in the fields of pharmacology and toxicology. Our results were supported by a comparative analysis with previous HepG2 gene expression studies.

SUBMITTER: Tyakht AV

PROVIDER: S-EPMC4378340 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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RNA-Seq gene expression profiling of HepG2 cells: the influence of experimental factors and comparison with liver tissue.

Tyakht Alexander V AV Ilina Elena N EN Alexeev Dmitry G DG Ischenko Dmitry S DS Gorbachev Alexey Y AY Semashko Tatiana A TA Larin Andrei K AK Selezneva Oksana V OV Kostryukova Elena S ES Karalkin Pavel A PA Vakhrushev Igor V IV Kurbatov Leonid K LK Archakov Alexander I AI Govorun Vadim M VM

BMC genomics 20141215

<h4>Background</h4>Human hepatoma HepG2 cells are used as an in vitro model of the human liver. High-throughput transcriptomic sequencing is an advanced approach for assessing the functional state of a tissue or cell type. However, the influence of experimental factors, such as the sample preparation method and inter-laboratory variation, on the transcriptomic profile has not been evaluated.<h4>Results</h4>The whole-transcriptome sequencing of HepG2 cells was performed using the SOLiD platform a ...[more]

PMID: 25511409

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Project description:RNA sequencing (RNA-Seq) is often used for transcriptome profiling as well as the identification of novel transcripts and alternative splicing events. Typically, RNA-Seq libraries are prepared from total RNA using poly(A) enrichment of the mRNA (mRNA-Seq) to remove ribosomal RNA (rRNA), however, this method fails to capture non-poly(A) transcripts or partially degraded mRNAs. Hence, a mRNA-Seq protocol will not be compatible for use with RNAs coming from Formalin-Fixed and Paraffin-Embedded (FFPE) samples.To address the desire to perform RNA-Seq on FFPE materials, we evaluated two different library preparation protocols that could be compatible for use with small RNA fragments. We obtained paired Fresh Frozen (FF) and FFPE RNAs from multiple tumors and subjected these to different gene expression profiling methods. We tested 11 human breast tumor samples using: (a) FF RNAs by microarray, mRNA-Seq, Ribo-Zero-Seq and DSN-Seq (Duplex-Specific Nuclease) and (b) FFPE RNAs by Ribo-Zero-Seq and DSN-Seq. We also performed these different RNA-Seq protocols using 10 TCGA tumors as a validation set.The data from paired RNA samples showed high concordance in transcript quantification across all protocols and between FF and FFPE RNAs. In both FF and FFPE, Ribo-Zero-Seq removed rRNA with comparable efficiency as mRNA-Seq, and it provided an equivalent or less biased coverage on gene 3' ends. Compared to mRNA-Seq where 69% of bases were mapped to the transcriptome, DSN-Seq and Ribo-Zero-Seq contained significantly fewer reads mapping to the transcriptome (20-30%); in these RNA-Seq protocols, many if not most reads mapped to intronic regions. Approximately 14 million reads in mRNA-Seq and 45-65 million reads in Ribo-Zero-Seq or DSN-Seq were required to achieve the same gene detection levels as a standard Agilent DNA microarray.Our results demonstrate that compared to mRNA-Seq and microarrays, Ribo-Zero-Seq provides equivalent rRNA removal efficiency, coverage uniformity, genome-based mapped reads, and consistently high quality quantification of transcripts. Moreover, Ribo-Zero-Seq and DSN-Seq have consistent transcript quantification using FFPE RNAs, suggesting that RNA-Seq can be used with FFPE-derived RNAs for gene expression profiling.

Project description:BackgroundWhile RNA-sequencing (RNA-seq) is becoming a powerful technology in transcriptome profiling, one significant shortcoming of the first-generation RNA-seq protocol is that it does not retain the strand specificity of origin for each transcript. Without strand information it is difficult and sometimes impossible to accurately quantify gene expression levels for genes with overlapping genomic loci that are transcribed from opposite strands. It has recently become possible to retain the strand information by modifying the RNA-seq protocol, known as strand-specific or stranded RNA-seq. Here, we evaluated the advantages of stranded RNA-seq in transcriptome profiling of whole blood RNA samples compared with non-stranded RNA-seq, and investigated the influence of gene overlaps on gene expression profiling results based on practical RNA-seq datasets and also from a theoretical perspective.ResultsOur results demonstrated a substantial impact of stranded RNA-seq on transcriptome profiling and gene expression measurements. As many as 1751 genes in Gencode Release 19 were identified to be differentially expressed when comparing stranded and non-stranded RNA-seq whole blood samples. Antisense and pseudogenes were significantly enriched in differential expression analyses. Because stranded RNA-seq retains strand information of a read, we can resolve read ambiguity in overlapping genes transcribed from opposite strands, which provides a more accurate quantification of gene expression levels compared with traditional non-stranded RNA-seq. In the human genome, it is not uncommon to find genomic loci where both strands encode distinct genes. Among the over 57,800 annotated genes in Gencode release 19, there are an estimated 19 % (about 11,000) of overlapping genes transcribed from the opposite strands. Based on our whole blood mRNA-seq datasets, the fraction of overlapping nucleotide bases on the same and opposite strands were estimated at 2.94 % and 3.1 %, respectively. The corresponding theoretical estimations are 3 % and 3.6 %, well in agreement with our own findings.ConclusionsStranded RNA-seq provides a more accurate estimate of transcript expression compared with non-stranded RNA-seq, and is therefore the recommended RNA-seq approach for future mRNA-seq studies.

Dataset Information

RNA-Seq gene expression profiling of HepG2 cells: the influence of experimental factors and comparison with liver tissue.

Publications

RNA-Seq gene expression profiling of HepG2 cells: the influence of experimental factors and comparison with liver tissue.

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