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Differential Expression of Long Non-Coding RNAs and mRNAs in the active tuberculosis patients, multidrug-resistant tuberculosis patients, cured tuberculosis subjects and healthy controls

ABSTRACT: The expression of the long non-coding RNAs (lncRNAs) in the active tuberculosis patients,multidrug-resistant tuberculosis patients,cured tuberculosis subjects and healthy controls were scanned using lncRNA microarray.The Arraystar Human LncRNA Microarray version 4.0 (Agilent Technologies) was used,containing 40173 lncRNA probes and 20730 mRNA probes for the detection of lncRNAs and mRNAs in the sample. Non-coding RNAs and mRNAs profiling by array

ORGANISM(S): Homo sapiens

PROVIDER: GSE163292 | GEO | 2022/12/22

REPOSITORIES: GEO

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Project description:Purpose: Accurate diagnosis of complete inactivation of tuberculosis lesions is still a challenge with respect to sputum-negative tuberculosis. RNA-sequencing was conducted to uncover potential lncRNA indicators of metabolic activity in tuberculosis lesions. Methods: Lung tissues with high metabolic activity (PET-high) and low metabolic activity (PET-low) demonstrated by fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) were collected from five sputum-negative tuberculosis patients for RNA-sequencing. Differentially expressed mRNAs and lncRNAs were identified, and their correlations were evaluated to constructed lncRNA-mRNA co-expression network. Afterwards, cis- or trans-targets of differentially expressed lncRNAs were predicted, followed by establishing lncRNA-target-pathway network, in which lncRNAs and mRNAs with high degrees were measured by quantitative real-time PCR using samples collected from 11 patients. Prediction efficiencies of lncRNA indicators were assessed by receiver operating characteristic curve analysis, Bioinformatics analysis was performed for potential lncRNAs. Results: In total, 386 mRNAs and 44 lncRNAs were identified to be differentially expressed. Differentially expressed mRNAs in lncRNA-mRNA co-expression network were significantly associated with the fibrillar collagen, platelet-derived growth factor binding, and leukocyte migration involved in inflammatory response. One cis-target gene and 440 trans-target genes were predicted for differentially expressed lncRNAs. Seven genes (C1QB, CD68, CCL5, CCL19, MMP7, HLA-DMB, and CYBB) and two lncRNAs (ENST00000429730.1 and MSTRG.93125.4) were validated to be significantly up-regulated. The area under the curve of ENST00000429730.1 and MSTRG.93125.4 was 0.750 and 0.813, respectively. Conclusion: Two lncRNAs ENST00000429730.1 and MSTRG.93125.4 might be considered as potential indicators of metabolic activity in tuberculosis lesions for sputum-negative tuberculosis.

Project description:Background: Long non-coding RNAs (lncRNAs) are increasingly implicated as gene regulators and may ultimately be more numerous than protein-coding genes in the human genome. Despite large numbers of reported lncRNAs, reference annotations are likely incomplete due to their lower and tighter tissue-specific expression compared to mRNAs. An unexplored factor potentially confounding lncRNA identification is inter-individual expression variability. Here, we characterize lncRNA natural expression variability in human primary granulocytes. Results: We annotate granulocyte lncRNAs and mRNAs in RNA-seq data from ten healthy individuals, identifying multiple lncRNAs absent from reference annotations, and use this to investigate three known features (higher tissue-specificity, lower expression, and reduced splicing efficiency) of lncRNAs relative to mRNAs. Expression variability was examined in seven individuals sampled three times at one or more than one month intervals. We show that lncRNAs display significantly more inter-individual expression variability compared to mRNAs. We confirm this finding in 2 independent human datasets by analyzing multiple tissues from the GTEx project and lymphoblastoid cell lines from the GEUVADIS project. Using the latter dataset we also show that including more human donors into the transcriptome annotation pipeline allows identification of an increasing number of lncRNAs, but minimally affects mRNA gene number. Conclusions: A comprehensive annotation of lncRNAs is known to require an approach that is sensitive to low and tight tissue-specific expression. Here we show that increased inter-individual expression variability is an additional general lncRNA feature to consider when creating a comprehensive annotation of human lncRNAs or proposing their use as prognostic or disease markers. We used PolyA+ RNA-seq data from human primary granulocytes of 10 healthy individuals to de novo annotate lncRNAs and mRNAs in this cell type and ribosomal depleted (total) RNA-seq data from seven of these individuals sampled three times to analyze lncRNA amd mRNA expression variability

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Differential Expression of Long Non-Coding RNAs and mRNAs in the active tuberculosis patients, multidrug-resistant tuberculosis patients, cured tuberculosis subjects and healthy controls

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