ObjectivesThe aim of this study was to identify key pathological genes in osteoarthritis (OA).MethodsWe searched and downloaded mRNA expression data from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs) of joint synovial tissues from OA and normal individuals. Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analyses were used to assess the function of identified DEGs. The protein-protein interaction (PPI) network and transcriptional factors (TFs) regulatory network were used to further explore the function of identified DEGs. The quantitative real-time polymerase chain reaction (qRT-PCR) was applied to validate the result of bioinformatics analysis. Electronic validation was performed to verify the expression of selected DEGs. The diagnosis value of identified DEGs was accessed by receiver operating characteristic (ROC) analysis.ResultsA total of 1085 DEGs were identified. KEGG pathway analysis displayed that Wnt was a significantly enriched signalling pathway. Some hub genes with high interactions such as USP46, CPVL, FKBP5, FOSL2, GADD45B, PTGS1, and ZNF423 were identified in the PPI and TFs network. The results of qRT-PCR showed that GADD45B, ADAMTS1, and TFAM were down-regulated in joint synovial tissues of OA, which was consistent with the bioinformatics analysis. The expression levels of USP46, CPVL, FOSL2, and PTGS1 in electronic validation were compatible with the bio-informatics result. CPVL and TFAM had a potential diagnostic value for OA based on the ROC analysis.ConclusionThe deregulated genes including USP46, CPVL, FKBP5, FOSL2, GADD45B, PTGS1, ZNF423, ADAMTS1, and TFAM might be involved in the pathology of OA.Cite this article: X. Zhang, Y. Bu, B. Zhu, Q. Zhao, Z. Lv, B. Li, J. Liu. Global transcriptome analysis to identify critical genes involved in the pathology of osteoarthritis. Bone Joint Res 2018;7:298–307. DOI: 10.1302/2046-3758.74.BJR-2017-0245.R1.

Rose is one of the most fundamental ornamental crops, but its yield and quality are highly limited by drought. The key transcription factors (TFs) and co-expression networks during rose’s response to drought stress and recovery after drought stress are still limited. In this study, the transcriptomes of leaves of 2-year-old cutting seedlings of Rosa chinensis ‘Old Blush’ from three continuous droughted stages (30, 60, 90 days after full watering) and rewatering were analyzed using RNA sequencing. Weighted gene co-expression network analysis (WGCNA) was used to construct a co-expression network, which was associated with the physiological traits of drought response to discovering the hub TFs involved in drought response. More than 45 million high-quality clean reads were generated from the sample and used for comparison with the rose reference genome. A total of 46433 differentially expressed genes (DEGs) were identified. Gene Ontology (GO) term enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated that drought stress caused significant changes in signal transduction, plant hormones including ABA, auxin, brassinosteroid (BR), cytokinin, ethylene (ET), jasmonic acid (JA) and salicylic acid (SA), primary and secondary metabolism, and a certain degree of recovery after rewatering. Gene co-expression analysis identified 18 modules, in which four modules showed a high degree of correlation with physiological traits. In addition, 42 TFs including members of NACs, WRKYs, MYBs, AP2/ERFs, ARFs, and bHLHs with high connectivity in navajowhite1 and blue modules were screened. This study provides the transcriptome sequencing report of R. chinensis ‘Old Blush’ during drought stress and rewatering process. The study also identifies the response of candidate TFs to drought stress, providing guidelines for improving the drought tolerance of the rose through molecular breeding in the future.

Background: Rose is one of the most important ornamental crops, but drought limits its yield and quality seriously. Although serval abiotic stress related genes have been identified, the molecular mechanism during rose’s responding to drought stress is still limited. In this study, the transcriptomes of leaves of two-year-old cutting seedlings of Rosa chinensis ’Old Blush’ from three continuous droughted stages (30, 60, 90 days after full watering) and rewatering were analyzed using RNA sequencing. Meanwhile, weighted gene co-expression network analysis (WGCNA) was used to construct a co-expression network associated with the physiological traits of drought response to discover the hub transcription factors involved in drought response.Results: More than 45 million high-quality clean reads were generated from samples and used for comparison with the rose reference genome. A total of 46433 differentially expressed genes were identified. Gene ontology (GO) term enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated that drought stress caused significant changes in signal transduction, plant hormones, primary and secondary metabolism, and a certain degree of recovery after rewatering. Gene co-expression analysis identified 18 modules, in which four modules have highly degree of correlation with physiological traits. In addition, twenty-two transcription factors including members of NACs, WRKYs, MYBs, ERFs, ARFs and bHLHs with high connectivity in these four modules were screened. Conclusions: The results of this study provided the first transcriptome sequencing report of the drought stress in R.chinensis, and also provided candidate transcription factors in response to drought stress, providing clues for improving the drought tolerance of the rose through molecular breeding in the future.