Dataset Information

Systematic Analysis of Differential Expression Profile in Rheumatoid Arthritis Chondrocytes Using Next-Generation Sequencing and Bioinformatics Approaches.

ABSTRACT: Cartilage destruction in rheumatoid arthritis (RA) occurs primarily in the pannus-cartilage interface. The close contact of the synovium-cartilage interface implicates crosstalk between synovial fibroblasts and chondrocytes. The aim of this study is to explore the differentially expressed genes and novel microRNA regulations potentially implicated in the dysregulated cartilage homeostasis in joint destruction of RA. Total RNAs were extracted from human primary cultured normal and RA chondrocytes for RNA and small RNA expression profiling using next-generation sequencing. Using systematic bioinformatics analyses, we identified 463 differentially expressed genes in RA chondrocytes were enriched in biological functions related to altered cell cycle process, inflammatory response and hypoxic stimulation. Moreover, fibroblast growth factor 9 (FGF9), kynureninase (KYNU), and regulator of cell cycle (RGCC) were among the top dysregulated genes identified to be potentially affected in the RA joint microenvironment, having similar expression patterns observed in arrays of clinical RA synovial tissues from the Gene Expression Omnibus database. Additionally, among the 31 differentially expressed microRNAs and 10 candidate genes with potential microRNA-mRNA interactions in RA chondrocytes, the novel miR-140-3p-FGF9 interaction was validated in different microRNA prediction databases, and proposed to participate in the pathogenesis of joint destruction through dysregulated cell growth in RA. The findings provide new perspectives for target genes in the management of cartilage destruction in RA.

SUBMITTER: Chen YJ

PROVIDER: S-EPMC6097257 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Systematic Analysis of Differential Expression Profile in Rheumatoid Arthritis Chondrocytes Using Next-Generation Sequencing and Bioinformatics Approaches.

Chen Yi-Jen YJ Chang Wei-An WA Wu Ling-Yu LY Hsu Ya-Ling YL Chen Chia-Hsin CH Kuo Po-Lin PL

International journal of medical sciences 20180713 11

Cartilage destruction in rheumatoid arthritis (RA) occurs primarily in the pannus-cartilage interface. The close contact of the synovium-cartilage interface implicates crosstalk between synovial fibroblasts and chondrocytes. The aim of this study is to explore the differentially expressed genes and novel microRNA regulations potentially implicated in the dysregulated cartilage homeostasis in joint destruction of RA. Total RNAs were extracted from human primary cultured normal and RA chondrocytes ...[more]

PMID: 30123050

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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

Systematic Analysis of Differential Expression Profile in Rheumatoid Arthritis Chondrocytes Using Next-Generation Sequencing and Bioinformatics Approaches.

Publications

Systematic Analysis of Differential Expression Profile in Rheumatoid Arthritis Chondrocytes Using Next-Generation Sequencing and Bioinformatics Approaches.

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