Transcriptome profiling of MRC5 cells induced in senescence by different stresses

Aging is characterized by a gradual decline of physiological functions causing age-related diseases and increasing vulnerability against cancer. At a cellular level, aging is associated with a progressive accumulation of senescent cells. Senescent cells are involved in tissue homeostasis on one hand but, on another hand, their accumulation can lead to pathological aging processes. The events regulating the elimination of senescent cells by the immune system are still poorly known. Here we want to understand the transcriptome variations between the different kinds on senescences of one same cell line to link them to their immunological properties. Overall design: Primary human fibroblasts MRC5 were induced to senesce by exposure to Bleomycin during 24h at 50 µg/mL. Replicative senescence was induced by continuous passaging of primary human fibroblasts MRC5 at 5% O2 until they reached a plateau in their growth curve. Oncogene-Induced senescence was induced in MRC5 fibroblasts transduced with a vector expressing H-RASG12V and treated with 4-Hydroxytamoxifen at 50nm every 48h for 5 or 8 days. For all experiments, young cells have been used at pdl 30 and senescent cells have been defined as at least 90% SA-b-Galactosidase assay + and no more than 10% of EdU+ cells. RNA from young and senescent cells was extracted using the TRI reagent (Sigma-Aldrich, ref#B8416-15UN) protocol, the quality and concentration was assessed using a nanodropTM and a bioanalyzer (Agilent). Library construction, sequencing and initial data filtering including adaptor removal were performed by BGI Genomics. RNA was sequenced by the DNBSEQ platform in paired-end mode with 150 bp sequencing length. Low quality reads, adaptor contamination and excessively high levels of unknown base N reads were removed from the analysis with SOAPnuke. The reads were aligned to the GCF_000001405.39_GRCh38.p13 reference genome using HISAT2. After that, Ericscript (0.5.5-5) and rMATS (v4.1.1) were used to detect fusion genes and differential splicing genes. Bowtie2 was applied to align the clean reads to the gene set. Quantification was performed by RSEM (v1.2.28).