Long non-coding RNA transcriptome of uncharacterized samples can be accurately imputed using protein-coding genes.
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ABSTRACT:
SUBMITTER: Nath A
PROVIDER: S-EPMC7299297 | biostudies-literature | 2020 Mar
REPOSITORIES: biostudies-literature
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Project description:Transposable elements (TEs) are abundant in mammalian genomes and appear to have contributed to the evolution of their hosts by providing novel regulatory or coding sequences. We analyzed different regions of long intergenic non-coding RNA (lincRNA) genes in human and mouse genomes to systematically assess the potential contribution of TEs to the evolution of the structure and regulation of expression of lincRNA genes. Introns of lincRNA genes contain the highest percentage of TE-derived sequences (TES), followed by exons and then promoter regions although the density of TEs is not significantly different between exons and promoters. Higher frequencies of ancient TEs in promoters and exons compared to introns implies that many lincRNA genes emerged before the split of primates and rodents. The content of TES in lincRNA genes is substantially higher than that in protein-coding genes, especially in exons and promoter regions. A significant positive correlation was detected between the content of TEs and evolutionary rate of lincRNAs indicating that inserted TEs are preferentially fixed in fast-evolving lincRNA genes. These results are consistent with the repeat insertion domains of LncRNAs hypothesis under which TEs have substantially contributed to the origin, evolution, and, in particular, fast functional diversification, of lincRNA genes.
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Project description:BackgroundThe prognosis of renal cell carcinoma (RCC) varies greatly among different risk groups, and the traditional indicators have limited effect in the identification of risk grade in patients with RCC. The purpose of our study is to explore a glycolysis-based long non-coding RNAs (lncRNAs) signature and verify its potential clinical significance in prognostic prediction of RCC patients.MethodsIn this study, RNA data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. Univariate and multivariate cox regression displayed six significantly related lncRNAs (AC124854.1, AC078778.1, EMX2OS, DLGAP1-AS2, AC084876.1, and AC026401.3) which were utilized in construction of risk score by a formula. The accuracy of risk score was verified by a series of statistical methods such as receiver operating characteristic (ROC) curves, nomogram and Kaplan-Meier curves. Its potential clinical significance was excavated by gene enrichment analysis.ResultsKaplan-Meier curves and ROC curves showed reliability of the risk score to predict the prognosis of RCC patients. Stratification analysis indicated that the risk score was independent predictor compare to other traditional clinical parameters. The clinical nomogram showed highly rigorous with index of 0.73 and precisely predicted 1-, 3-, and 5-year survival time of RCC patients. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene set enrichment analysis (GSEA) depicted the top ten correlated pathways in both high-risk group and low-risk group. There are 6 lncRNAs and 25 related mRNAs including 36 lncRNA-mRNA links in lncRNA-mRNA co-expression network.ConclusionThis research demonstrated that glycolysis-based lncRNAs possessed an important value in survival prediction of RCC patients, which would be a potential target for future treatment.
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