M Fu1, G Huang1, Z Zhang1, J Liu3, Z Zhang1, Z Huang1, B Yu1, F Meng1. 1. Department of Joint Surgery, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China. 2. Department of Joint Surgery, First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China. Electronic address: zhiqi_zh@163.com. 3. Institute for Advancing Translational Medicine in Bone & Joint Disease, School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR, China.
Abstract
OBJECTIVES: Long noncoding RNAs (lncRNAs) have emerged as a novel class of regulatory molecules involved in various biological processes, but their role in osteoarthritis (OA) remains unknown. Therefore, we aimed to reveal lncRNAs expression profile in human osteoarthritic cartilage and explore the potential functions of lncRNAs in OA. METHODS: The expression profiles of lncRNAs and mRNAs in OA cartilage were obtained using microarray and verified by quantitative reverse transcription polymerase chain reaction (qRT-PCR). Bioinformatics analyses including lncRNA classification and subgroup analysis, gene ontology (GO) analysis, pathway analysis, network analysis and target prediction were performed. RESULTS: There were 3007 upregulated lncRNAs and 1707 downregulated lncRNAs in OA cartilage compared with normal samples (Fold change ≥ 2.0). In addition, 2136 mRNAs were upregulated and 2,241 mRNAs were downregulated in OA cartilage (Fold change ≥ 2.0). The qRT-PCR results of six dysregulated lncRNAs were consistent with the microarray data. 106 lncRNAs and 291 mRNAs composed the coding-non-coding gene co-expression network (CNC network). In the 600 top differentially expressed lncRNAs, 48 lncRNAs were predicted to have more than five cis-regulated target genes and up to 530 lncRNAs might regulate their trans target genes through collaboration with transcriptional factor (TF) SP1. The positive correlation between lncRNA uc.343 and predicted target homeobox gene C8 (HOXC8) expression in SW1353 cells treating with interleukin-1 beta confirmed the target prediction to some extent. CONCLUSIONS: This study revealed the expression pattern of lncRNAs in OA cartilage and predicted the potential function and targets, which indicated that lncRNAs may be new biomarkers for diagnosis or novel therapeutic targets of OA.
OBJECTIVES: Long noncoding RNAs (lncRNAs) have emerged as a novel class of regulatory molecules involved in various biological processes, but their role in osteoarthritis (OA) remains unknown. Therefore, we aimed to reveal lncRNAs expression profile in humanosteoarthritic cartilage and explore the potential functions of lncRNAs in OA. METHODS: The expression profiles of lncRNAs and mRNAs in OA cartilage were obtained using microarray and verified by quantitative reverse transcription polymerase chain reaction (qRT-PCR). Bioinformatics analyses including lncRNA classification and subgroup analysis, gene ontology (GO) analysis, pathway analysis, network analysis and target prediction were performed. RESULTS: There were 3007 upregulated lncRNAs and 1707 downregulated lncRNAs in OA cartilage compared with normal samples (Fold change ≥ 2.0). In addition, 2136 mRNAs were upregulated and 2,241 mRNAs were downregulated in OA cartilage (Fold change ≥ 2.0). The qRT-PCR results of six dysregulated lncRNAs were consistent with the microarray data. 106 lncRNAs and 291 mRNAs composed the coding-non-coding gene co-expression network (CNC network). In the 600 top differentially expressed lncRNAs, 48 lncRNAs were predicted to have more than five cis-regulated target genes and up to 530 lncRNAs might regulate their trans target genes through collaboration with transcriptional factor (TF) SP1. The positive correlation between lncRNA uc.343 and predicted target homeobox gene C8 (HOXC8) expression in SW1353 cells treating with interleukin-1 beta confirmed the target prediction to some extent. CONCLUSIONS: This study revealed the expression pattern of lncRNAs in OA cartilage and predicted the potential function and targets, which indicated that lncRNAs may be new biomarkers for diagnosis or novel therapeutic targets of OA.
Authors: Eric A Lewallen; Carolina A Bonin; Xin Li; Jay Smith; Marcel Karperien; A Noelle Larson; David G Lewallen; Simon M Cool; Jennifer J Westendorf; Aaron J Krych; Alexey A Leontovich; Hee-Jeong Im; Andre J van Wijnen Journal: Gene Date: 2016-07-01 Impact factor: 3.688