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Multidimensional conservation analysis decodes the expression of conserved long noncoding RNAs.

ABSTRACT: Although long noncoding RNAs (lncRNAs) experience weaker evolutionary constraints and exhibit lower sequence conservation than coding genes, they can still conserve their features in various aspects. Here, we used multiple approaches to systemically evaluate the conservation between human and mouse lncRNAs from various dimensions including sequences, promoter, global synteny, and local synteny, which led to the identification of 1,731 conserved lncRNAs with 427 high-confidence ones meeting multiple criteria. Conserved lncRNAs, compared with non-conserved ones, generally have longer gene bodies, more exons and transcripts, stronger connections with human diseases, and are more abundant and widespread across different tissues. Transcription factor (TF) profile analysis revealed a significant enrichment of TF types and numbers in the promoters of conserved lncRNAs. We further identified a set of TFs that preferentially bind to conserved lncRNAs and exert stronger regulation on conserved than non-conserved lncRNAs. Our study has reconciled some discrepant interpretations of lncRNA conservation and revealed a new set of transcriptional factors ruling the expression of conserved lncRNAs.

SUBMITTER: Zhou Q

PROVIDER: S-EPMC10078953 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

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Multidimensional conservation analysis decodes the expression of conserved long noncoding RNAs.

Zhou Qiuzhong Q Jiang Yuxi Y Cai Chaoqun C Li Wen W Leow Melvin Khee-Shing MK Yang Yi Y Liu Jin J Xu Dan D Sun Lei L

Life science alliance 20230405 6

Although long noncoding RNAs (lncRNAs) experience weaker evolutionary constraints and exhibit lower sequence conservation than coding genes, they can still conserve their features in various aspects. Here, we used multiple approaches to systemically evaluate the conservation between human and mouse lncRNAs from various dimensions including sequences, promoter, global synteny, and local synteny, which led to the identification of 1,731 conserved lncRNAs with 427 high-confidence ones meeting multi ...[more]

PMID: 37024123

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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

Multidimensional conservation analysis decodes the expression of conserved long noncoding RNAs.

Publications

Multidimensional conservation analysis decodes the expression of conserved long noncoding RNAs.

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