Conserved Senescence Associated Genes and Pathways in Primary Human Fibroblasts Detected by RNA-Seq

PLoS One. 2016 May 3;11(5):e0154531. doi: 10.1371/journal.pone.0154531. eCollection 2016.


Cellular senescence correlates with changes in the transcriptome. To obtain a complete view on senescence-associated transcription networks and pathways, we assessed by deep RNA sequencing the transcriptomes of five of the most commonly used laboratory strains of human fibroblasts during their transition into senescence. In a number of cases, we verified the RNA-seq data by real-time PCR. By determining cellular protein levels we observed that the age-related expression of most but not all genes is regulated at the transcriptional level. We found that 78% of the age-affected differentially expressed genes were commonly regulated in the same direction (either up- or down-regulated) in all five fibroblast strains, indicating a strong conservation of age-associated changes in the transcriptome. KEGG pathway analyses confirmed up-regulation of the senescence-associated secretory phenotype and down-regulation of DNA synthesis/repair and most cell cycle pathways common in all five cell strains. Newly identified senescence-induced pathways include up-regulation of endocytotic/phagocytic pathways and down-regulation of the mRNA metabolism and the mRNA splicing pathways. Our results provide an unprecedented comprehensive and deep view into the individual and common transcriptome and pathway changes during the transition into of senescence of five human fibroblast cell strains.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Cell Proliferation
  • Cellular Senescence / genetics*
  • Conserved Sequence*
  • Female
  • Fibroblasts / cytology*
  • Fibroblasts / metabolism*
  • Gene Expression Profiling
  • Humans
  • Male
  • Pregnancy
  • RNA, Messenger / genetics
  • RNA, Messenger / metabolism
  • Sequence Analysis, RNA*


  • RNA, Messenger

Grants and funding

Funding was provided by grant No: 0315581, The work described here is part of the research program of the Jena Centre for Systems Biology of Ageing—JenAge. The authors acknowledge JenAge funding by the German Ministry for Education and Research (Bundesministerium für Bildung und Forschung – BMBF). The publication of this article was funded by the Open Access fund of the Leibniz Association.