Transcriptome of the liquid fraction of synovial fluid from patients with osteoarthritis at the knee joints

  • Peng Jiang
  • Shui Sun
  • Ju Zhang
  • Cuidan Li
  • Guannan Ma
  • Jian Wang
  • Fei Chen
  • Dezhong Joshua Liao


Since few studies have been focused on the RNA profile of the liquid fraction of synovial fluid (SF) from osteoarthritis (OA) patients, we determined whether it contains enough RNA for profiling. We removed cells from SF and extract RNA for building a cDNA library, followed by the second-generation sequencing and bioinformatic analyses. From one SF sample of an OA patient, we obtained 0.096 µg RNA for building a cDNA library. From this library the second-generation sequencing produced 66,154,562 clean reads, 91.28% of which were matched to the reference with 2,682 genes identified. From another patient’s SF sample, 0.24 µg RNA was obtained and sequencing of the established cDNA library produced 64,463,162 clean reads but, unexpectedly, only 22.40% of the reads were matched to the human genome, although 5,081 genes were identified. Some of the unmatchable reads matched RNAs of bacteria, mainly pseudomonas, likely derived from previous infections since the patients had no obvious systemic infection or knee joint infection at the time of sample collection. The detected human RNAs in both samples fall into different categories of genes, including protein-coding ones, processed and unprocessed pseudogenes, and long noncoding, antisense and miscellaneous RNAs that mediate various biological functions. Interestingly, eight of the ten most abundantly expressed genes belong to the mitochondrial genome. These results suggest that less than 0.1 µg RNA is sufficient for establishing cDNA library and deep sequencing, and the liquid fraction of SF contains a whole RNA repertoire and may reflect a history of previous microorganism infection.

How to Cite
JIANG, Peng et al. Transcriptome of the liquid fraction of synovial fluid from patients with osteoarthritis at the knee joints. Current Science, [S.l.], v. 113, n. Issue 6, oct. 2017. ISSN 0011-3891. Available at: <>. Date accessed: 15 dec. 2017.