Next Generation Sequencing to understand the pathogenic role of synovial fibroblasts in experimental models of arthritis

The goal of this study is to define the pathophysiology of synovial fibroblasts in chroninc joint inflammation using NGS-derived synovial transcriptome profiling (RNA-seq) Methods: Synovial fibroblasts were isolated by FACs sorting [CD45-CD31-Popdoplanin+] from the synovium of healthy mice and mice undergoing experimental Collagen-Induced Arthritis (12 weeks old)(CIA). Methods: Whole Transcriptome Profiling of healthy and CIA synovial fibroblasts were generated by deep sequencing, in triplicate, using Illumina NextSeq™ 500 platform. Libraries were prepared using polyA selection (TruSeq stranded mRNA kit). Methods: The sequence reads that passed quality filters were aligned to mouse reference genome (GRCM38) using Hisat2 version 2.1.0. we mapped about 30 million sequence reads per sample (75 bp, paired-end) Methods: Featurecounts version 1.4.6 was used to quantify reads counts. Data quality control, non-expressed gene filtering, median ratio normalization (MRN) implemented in DESeq2 package and identification of differentially expressed (DE) genes were done using the R bioconductor project DEbrowser. Results: Results: We detected several differentially expressed (DE) genes in CIA synovial fibroblasts compared to naïve cells. These included 298 up-regulated genes and 88 down-regulated (>2 fold, adjp <0.05). DE genes reflected the reflecting the hyperplasia and activation observed during chronic joint disease. Pathways associated to DE genes were cell cycle and cell division and inflammatory response. Conclusions: our study shows pathophysiological changes associated to inflammatory synovial fibroblasts in a model of rheumatoid arthritis. Cells were directly isolated from fresh tissue, providing a valuable tool to study stromal inflammation. Synovial fibroblast mRNA profiles of naïve healthy DBA1J and CIA mice.