Dataset Information

Using RNA sequencing to identify putative competing endogenous RNAs (ceRNAs) potentially regulating fat metabolism in bovine liver.

ABSTRACT: RNA sequencing has been extensively used to study specific gene expression patterns to discover potential key genes related to complex traits of interest in animals. Of note, a new regulatory mechanism builds a large-scale regulatory network among transcriptome, where lncRNAs act as competing endogenous RNAs (ceRNAs) to sponge miRNAs to regulate the expression of miRNA target genes post-transcriptionally. In this study, we sequenced the cDNA and sRNA libraries of nine liver samples from three Holstein cows during dry period, early lactation, and peak of lactation with HiSeq platform. As a result, we identified 665 genes, 57 miRNAs and 33 lncRNAs that displayed differential expression patterns across periods. Subsequently, a total of 41ceRNA pairs (lncRNA-mRNA) sharing 11 miRNAs were constructed including 30 differentially expressed genes. Importantly, 12 among them were presented in our large metabolic networks, and predicted to influence the lipid metabolism through insulin, PI3K-Akt, MAPK, AMPK, mTOR, and PPAR signaling pathways, thus, these genes were considered as the most promising candidates for milk fat formation. To our knowledge, this is first investigation to profile the ceRNA regulatory networks of liver transcriptome that could affect milk fat synthesis in bovine, providing a new view of the regulatory mechanism of RNAs.

SUBMITTER: Liang R

PROVIDER: S-EPMC5527063 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

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Using RNA sequencing to identify putative competing endogenous RNAs (ceRNAs) potentially regulating fat metabolism in bovine liver.

Liang Ruobing R Han Bo B Li Qian Q Yuan Yuwei Y Li Jianguo J Sun Dongxiao D

Scientific reports 20170725 1

RNA sequencing has been extensively used to study specific gene expression patterns to discover potential key genes related to complex traits of interest in animals. Of note, a new regulatory mechanism builds a large-scale regulatory network among transcriptome, where lncRNAs act as competing endogenous RNAs (ceRNAs) to sponge miRNAs to regulate the expression of miRNA target genes post-transcriptionally. In this study, we sequenced the cDNA and sRNA libraries of nine liver samples from three Ho ...[more]

PMID: 28743867

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Project description:Liver cancer is the most common cancer and is the epitome of a recalcitrant cancer. Increasing evidence shown that long noncoding RNAs (lncRNA) were associated with cancer-related death and could function as a competing endogenous RNA (ceRNA). To explore regulatory roles and potential prognostic biomarkers of lncRNA for liver cancer, RNA-sequencing expression data were downloaded from the TCGA database and GEO database. A total of 357 patients were randomly divided into a discovery group and a validation group, of which 313 patients can obtain clinical data. In discovery phrase, 58 lncRNAs, 16 miRNAs, and 34 mRNAs were screened to construct the ceRNA network based on 252 patients employed from discovery group. Univariate and multivariate Cox hazard regression analysis model revealed that five lncRNAs (AATK-AS1, C10orf91, LINC00162, LINC00200, and LINC00501) from 58 lncRNAs were formulated to predict the overall survival (OS). We used the value of gene expression and regression coefficients to construct a risk score based on the five lncRNAs. Next, we validated our model in the GSE116174 dataset (n = 64) and the validation group (n = 94) from TCGA database. Subgroup analysis suggest that the five lncRNAs played critical parts in early stage in cancer from both discovery and validation groups. The five lncRNAs were also found to be associated with immune cells infiltration including CD4+ memory activated, NK cells activated and mast cells activated, then the results were also validated according to the validation group. Furthermore, KEGG pathway enrichment analysis showed that these nine coexpressed modules using the method of WGCNA, and many of these pathways are associated with the development and progression of disease. At last, the transcription factor binding sites (TFBS) of the five lncRNAs were predicted, which help us to understand the potential mechanism that the TFBS adjusted the ceRNA network. In summary, the ceRNA regulatory network may contribute to a better understanding of liver cancer mechanism and provide potential prognostic biomarkers and therapeutic targets.

Dataset Information

Using RNA sequencing to identify putative competing endogenous RNAs (ceRNAs) potentially regulating fat metabolism in bovine liver.

Publications

Using RNA sequencing to identify putative competing endogenous RNAs (ceRNAs) potentially regulating fat metabolism in bovine liver.

Similar Datasets

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