Dataset Information

Aberrant expression of lncRNAs and mRNAs in patients with intracranial aneurysm.

ABSTRACT: Intracranial aneurysm (IA) is pathological dilatations of the cerebral artery and rupture of IAs can cause subarachnoid hemorrhage, which has a high ratio of fatality and morbidity. However, the pathogenesis of IAs remains unknown. We performed long noncoding RNA (lncRNA) and messenger RNA (mRNA) expression profiles in IA tissues and superficial temporal arteries (STAs). A total of 4129 differentially expressed lncRNAs and 2926 differentially expressed mRNAs were obtained from the microarrays (P < 0.05). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses showed that up-regulated mRNAs were enriched in immune response, inflammatory response, regulation of immune response and lysosome, et al; while the down-regulated mRNAs were enriched in muscle contraction, smooth muscle contraction, cGMP-PKG signaling pathway and vascular smooth muscle contraction, et al. The lncRNA-mRNA co-expression networks were represented in immune response, inflammatory response, muscle contraction and vascular smooth muscle contraction. These findings may gain insight in the pathogenesis of IAs and provide clues to find key roles for IA patients.

SUBMITTER: Wang W

PROVIDER: S-EPMC5356817 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature

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Aberrant expression of lncRNAs and mRNAs in patients with intracranial aneurysm.

Wang Wen W Li Hao H Yu Lanbing L Zhao Zheng Z Wang Haoyuan H Zhang Dong D Zhang Yan Y Lan Qing Q Wang Jiangfei J Zhao Jizong J

Oncotarget 20170101 2

Intracranial aneurysm (IA) is pathological dilatations of the cerebral artery and rupture of IAs can cause subarachnoid hemorrhage, which has a high ratio of fatality and morbidity. However, the pathogenesis of IAs remains unknown. We performed long noncoding RNA (lncRNA) and messenger RNA (mRNA) expression profiles in IA tissues and superficial temporal arteries (STAs). A total of 4129 differentially expressed lncRNAs and 2926 differentially expressed mRNAs were obtained from the microarrays (P ...[more]

PMID: 27965470

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Project description:Messenger RNA (mRNA) and long noncoding RNA (lncRNA) are two main subgroups of RNAs participating in transcription regulation. With the development of next generation sequencing, increasing lncRNAs are identified. Many hidden functions of lncRNAs are also revealed. However, the differences in lncRNAs and mRNAs are still unclear. For example, we need to determine whether lncRNAs have stronger tissue specificity than mRNAs and which tissues have more lncRNAs expressed. To investigate such tissue expression difference between mRNAs and lncRNAs, we encoded 9339 lncRNAs and 14,294 mRNAs with 71 expression features, including 69 maximum expression features for 69 types of cells, one feature for the maximum expression in all cells, and one expression specificity feature that was measured as Chao-Shen-corrected Shannon's entropy. With advanced feature selection methods, such as maximum relevance minimum redundancy, incremental feature selection methods, and random forest algorithm, 13 features presented the dissimilarity of lncRNAs and mRNAs. The 11 cell subtype features indicated which cell types of the lncRNAs and mRNAs had the largest expression difference. Such cell subtypes may be the potential cell models for lncRNA identification and function investigation. The expression specificity feature suggested that the cell types to express mRNAs and lncRNAs were different. The maximum expression feature suggested that the maximum expression levels of mRNAs and lncRNAs were different. In addition, the rule learning algorithm, repeated incremental pruning to produce error reduction algorithm, was also employed to produce effective classification rules for classifying lncRNAs and mRNAs, which gave competitive results compared with random forest and could give a clearer picture of different expression patterns between lncRNAs and mRNAs. Results not only revealed the heterogeneous expression pattern of lncRNA and mRNA, but also gave rise to the development of a new tool to identify the potential biological functions of such RNA subgroups.

Project description:Non-coding RNAs (ncRNAs) have been previously reported to serve an important role in transcription. In addition, several studies have revealed that long ncRNAs (lncRNAs) have a crucial role in human diseases. However, the association between lncRNAs and inflammation‑induced intestinal macrophages in the intestinal mucosal barrier has remained elusive. In the present study, intestinal macrophages from healthy Sprague Dawley rats were divided into two groups: The experimental group, consisting of intestinal macrophages treated with 1 mg/l lipopolysaccharide (LPS) and the control group, composed of untreated cells. Differentially expressed (DE) lncRNAs and mRNAs between the control and experimental groups were identified using microarray profiling. The levels of DE mRNAs and lncRNAs were measured by reverse transcription‑quantitative PCR (RT‑qPCR). Furthermore, Gene Ontology (GO) and pathway enrichment analyses of DE mRNAs and lncRNAs were performed. To identify core regulatory factors among DE lncRNAs and mRNAs, a lncRNA‑mRNA network was constructed. A total of 357 DE lncRNAs and 542 DE mRNAs between the LPS‑treated and untreated groups were identified (fold-change >1.5; P<0.05). In addition, selected microarray data were confirmed by RT‑qPCR. GO analysis of the DE mRNAs indicated that the biological functions of the upregulated mRNAs included inflammatory response, immune response, metabolic process and signal transduction, whereas those of the downregulated mRNAs were metabolic process, cell cycle, apoptosis and inflammatory response. In addition, pathway enrichment analysis of the upregulated mRNAs revealed that the most enriched pathways were the NF‑κB signaling pathway, B‑cell receptor signaling pathway and apoptosis, while the downregulated mRNAs were significantly involved in metabolic pathways, the phosphatidylinositol signaling system, cytokine‑cytokine receptor interaction and the Toll‑like receptor signaling pathway. The lncRNA‑mRNA co‑expression network suggested that lncRNAs NONMMUT024673 and NONMMUT062258 may have an important role in LPS‑induced intestinal macrophages. The present study identified the DE profiles between LPS‑ and non‑LPS‑treated intestinal macrophages. These DE lncRNAs and mRNAs may be used as potential targets for attenuating excessive inflammatory response in intestinal mucosal barrier dysfunction.

Project description:Intracranial aneurysm (IA) is a severe clinical condition of primary concern and currently, there is no effective therapeutic reagent. The present study aimed to investigate the molecular mechanism of IA via bioinformatic analysis. Various gene expression profiles (GSE26969) were downloaded from the Gene Expression Omnibus database, including 3 IA and 3 normal superficial temporal artery samples. Firstly, the limma package in R language was used to identify differentially expressed genes (DEGs; P‑value <0.01 and |log2 FC|≥1). Secondly, the database for annotation, visualization and integrated discovery software was utilized to perform pathway and functional enrichment analyses (false discovery rate ≤0.05). Finally, protein‑protein interaction (PPI) network and sub‑network clustering analyses were performed using the biomolecular interaction network database and ClusterONE software, respectively. Following this, a transcription factor regulatory network was identified from the PPI network. A total of 1,124 DEGs were identified, of which 989 were upregulated and 135 downregulated. Pathway and functional enrichment analyses revealed that the DEGs primarily participated in RNA splicing, functioning of the spliceosome, RNA processing and the mRNA metabolic process. Following PPI network analysis, 1 hepatocyte nuclear factor (HNF) 4A (transcription factor)‑centered regulatory network and 5 DEG‑centered sub‑networks were identified. On analysis of the transcription factor regulatory network, 6 transcription factors (HNF6, HNF4A, E2F4, YY1, H4 and H31T) and a regulatory pathway (HNF6‑HNF4‑E2F4) were identified. The results of the present study suggest that activating transcription factor‑5, Jun proto‑oncogene, activator protein‑1 transcription factor subunit, HNF6, HNF4 and E2F4 may participate in IA progression via vascular smooth muscle cell apoptosis, inflammation, vessel wall remodeling and damage and the tumor necrosis factor‑β signaling pathway. However, further experimental studies are required to validate these predictions.

Dataset Information

Aberrant expression of lncRNAs and mRNAs in patients with intracranial aneurysm.

Publications

Aberrant expression of lncRNAs and mRNAs in patients with intracranial aneurysm.

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