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Identification of novel genetic regulations associated with airway epithelial homeostasis using next-generation sequencing data and bioinformatics approaches.

ABSTRACT: Airway epithelial cells play important roles in airway remodeling. Understanding gene regulations in airway epithelial homeostasis may provide new insights into pathogenesis and treatment of asthma. This study aimed to combine gene expression (GE) microarray, next generation sequencing (NGS), and bioinformatics to explore genetic regulations associated with airway epithelial homeostasis. We analyzed expression profiles of mRNAs (GE microarray) and microRNAs (NGS) in normal and asthmatic bronchial epithelial cells, and identified 9 genes with potential microRNA-mRNA interactions. Of these 9 dysregulated genes, downregulation of MEF2C and MDGA1 were validated in a representative microarray (GSE43696) from the gene expression omnibus (GEO) database. Our findings suggested that upregulated mir-203a may repress MEF2C, a transcription factor, leading to decreased cellular proliferation. In addition, upregulated mir-3065-3p may repress MDGA1, a cell membrane anchor protein, resulting in suppression of cell-cell adhesion. We also found that KCNJ2, a potassium channel, was downregulated in severe asthma and may promote epithelial cell apoptosis. We proposed that aberrant regulations of mir-203a-MEF2C and mir-3065-3p-MDGA1, as well as downregulation of KCNJ2, play important roles in airway epithelial homeostasis in asthma. These findings provide new perspectives on diagnostic or therapeutic strategies targeting bronchial epithelium for asthma. The approach in this study also provides a new aspect of studying asthma.

SUBMITTER: Sheu CC

PROVIDER: S-EPMC5669919 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Identification of novel genetic regulations associated with airway epithelial homeostasis using next-generation sequencing data and bioinformatics approaches.

Sheu Chau-Chyun CC Tsai Ming-Ju MJ Chen Feng-Wei FW Chang Kuo-Feng KF Chang Wei-An WA Chong Inn-Wen IW Kuo Po-Lin PL Hsu Ya-Ling YL

Oncotarget 20170731 47

Airway epithelial cells play important roles in airway remodeling. Understanding gene regulations in airway epithelial homeostasis may provide new insights into pathogenesis and treatment of asthma. This study aimed to combine gene expression (GE) microarray, next generation sequencing (NGS), and bioinformatics to explore genetic regulations associated with airway epithelial homeostasis. We analyzed expression profiles of mRNAs (GE microarray) and microRNAs (NGS) in normal and asthmatic bronchia ...[more]

PMID: 29137293

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Project description:MicroRNAs (miRNAs) are key post-transcriptional regulators that affect protein translation by targeting mRNAs. Their role in disease etiology and toxicity are well recognized. Given the rapid advancement of next-generation sequencing techniques, miRNA profiling has been increasingly conducted with RNA-seq, namely miRNA-seq. Analysis of miRNA-seq data requires several steps: (1) mapping the reads to miRBase, (2) considering mismatches during the hairpin alignment (windowing), and (3) counting the reads (quantification). The choice made in each step with respect to the parameter settings could affect miRNA quantification, differentially expressed miRNAs (DEMs) detection and novel miRNA identification. Furthermore, these parameters do not act in isolation and their joint effects impact miRNA-seq results and interpretation. In toxicogenomics, the variation associated with parameter setting should not overpower the treatment effect (such as the dose/time-dependent effect). In this study, four commonly used miRNA-seq analysis tools (i.e., miRDeep2, miRExpress, miRNAkey, sRNAbench) were comparatively evaluated with a standard toxicogenomics study design. We tested 30 different parameter settings on miRNA-seq data generated from thioacetamide-treated rat liver samples for three dose levels across four time points, followed by four normalization options. Because both miRExpress and miRNAkey yielded larger variation than that of the treatment effects across multiple parameter settings, our analyses mainly focused on the side-by-side comparison between miRDeep2 and sRNAbench. While the number of miRNAs detected by miRDeep2 was almost the subset of those detected by sRNAbench, the number of DEMs identified by both tools was comparable under the same parameter settings and normalization method. Change in the number of nucleotides out of the mature sequence in the hairpin alignment (window option) yielded the largest variation for miRNA quantification and DEMs detection. However, such a variation is relatively small compared to the treatment effect when the study focused on DEMs that are more critical to interpret the toxicological effect. While the normalization methods introduced a large variation in DEMs, toxic behavior of thioacetamide showed consistency in the trend of time-dose responses. Overall, miRDeep2 was found to be preferable over other choices when the window option allowed up to three nucleotides from both ends.

Dataset Information

Identification of novel genetic regulations associated with airway epithelial homeostasis using next-generation sequencing data and bioinformatics approaches.

Publications

Identification of novel genetic regulations associated with airway epithelial homeostasis using next-generation sequencing data and bioinformatics approaches.

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