Dataset Information

Long non-coding RNAs expression profile in HepG2 cells reveals the potential role of long non-coding RNAs in the cholesterol metabolism.

ABSTRACT: Green tea has been shown to improve cholesterol metabolism in animal studies, but the molecular mechanisms underlying this function have not been fully understood. Long non-coding RNAs (lncRNAs) have recently emerged as a major class of regulatory molecules involved in a broad range of biological processes and complex diseases. Our aim was to identify important lncRNAs that might play an important role in contributing to the benefits of epigallocatechin-3-gallate (EGCG) on cholesterol metabolism.Microarrays was used to reveal the lncRNA and mRNA profiles in green tea polyphenol(-)-epigallocatechin gallate in cultured human liver (HepG2) hepatocytes treated with EGCG and bioinformatic analyses of the predicted target genes were performed to identify lncRNA-mRNA targeting relationships. RNA interference was used to investigate the role of lncRNAs in cholesterol metabolism.The expression levels of 15 genes related to cholesterol metabolism and 285 lncRNAs were changed by EGCG treatment. Bioinformatic analysis found five matched lncRNA-mRNA pairs for five differentially expressed lncRNAs and four differentially expressed mRNA. In particular, the lncRNA AT102202 and its potential targets mRNA-3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR) were identified. Using a real-time polymerase chain reaction technique, we confirmed that EGCG down-regulated mRNA expression level of the HMGCR and up-regulated expression of AT102202. After AT102202 knockdown in HepG2, we observed that the level of HMGCR expression was significantly increased relative to the scrambled small interfering RNA control (P < 0.05).Our results indicated that EGCG improved cholesterol metabolism and meanwhile changed the lncRNAs expression profile in HepG2 cells. LncRNAs may play an important role in the cholesterol metabolism.

SUBMITTER: Liu G

PROVIDER: S-EPMC4837827 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature

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Long non-coding RNAs expression profile in HepG2 cells reveals the potential role of long non-coding RNAs in the cholesterol metabolism.

Liu Gang G Zheng Xinxin X Xu Yanlu Y Lu Jie J Chen Jingzhou J Huang Xiaohong X

Chinese medical journal 20150101 1

<h4>Background</h4>Green tea has been shown to improve cholesterol metabolism in animal studies, but the molecular mechanisms underlying this function have not been fully understood. Long non-coding RNAs (lncRNAs) have recently emerged as a major class of regulatory molecules involved in a broad range of biological processes and complex diseases. Our aim was to identify important lncRNAs that might play an important role in contributing to the benefits of epigallocatechin-3-gallate (EGCG) on cho ...[more]

PMID: 25563320

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Project description:Feed efficiency is an important economic trait and reduces the production costs per unit of animal product. Up to now, few studies have conducted transcriptome profiling of liver tissue in feed efficiency-divergent chickens (Ross vs native breeds). Also, molecular mechanisms contributing to differences in feed efficiency are not fully understood, especially in terms of long non-coding RNAs (lncRNAs). Hence, transcriptome profiles of liver tissue in commercial and native chicken breeds were analyzed. RNA-Seq data along with bioinformatics approaches were applied and a series of lncRNAs and target genes were identified. Furthermore, protein-protein interaction network construction, co-expression analysis, co-localization analysis of QTLs and functional enrichment analysis were used to functionally annotate the identified lncRNAs. In total, 2,290 lncRNAs were found (including 1,110 annotated, 593 known and 587 novel), of which 53 (including 39 known and 14 novel), were identified as differentially expressed genes between two breeds. The expression profile of lncRNAs was validated by RT-qPCR. The identified novel lncRNAs showed a number of characteristics similar to those of known lncRNAs. Target prediction analysis showed that these lncRNAs have the potential to act in cis or trans mode. Functional enrichment analysis of the predicted target genes revealed that they might affect the differences in feed efficiency of chicken by modulating genes associated with lipid metabolism, carbohydrate metabolism, growth, energy homeostasis and glucose metabolism. Some gene members of significant modules in the constructed co-expression networks were reported as important genes related to feed efficiency. Co-localization analysis of QTLs related to feed efficiency and the identified lncRNAs suggested several candidates to be involved in residual feed intake. The findings of this study provided valuable resources to further clarify the genetic basis of regulation of feed efficiency in chicken from the perspective of lncRNAs.

Dataset Information

Long non-coding RNAs expression profile in HepG2 cells reveals the potential role of long non-coding RNAs in the cholesterol metabolism.

Publications

Long non-coding RNAs expression profile in HepG2 cells reveals the potential role of long non-coding RNAs in the cholesterol metabolism.

Similar Datasets

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