Senotoxins target senescence via lipid binding specificity, ion imbalance and lipidome remodelling.

A total of 16 samples were processed for RNA sequencing. Sequencing data passed quality control was referred to as clean data. In this project, a total of 386.81 M Reads (115.24 Gb) Clean Data were obtained with minimum yield of 6.02 Gb clean data per sample. Percentage of Q30 bases in each sample was above 93.64 %. Overall design: Cellular senescence was induced by incubation with 5 microM palbociclib in 75 cm2 flask (DMEM 10% FBS, 1% penicillin-streptomycin and 1% non-essential aminoacids) Senescent SKMel147 cells (570x10e3 cell/well) were treated with StnI 100nM following a time course at 0, 3, 6 and 12 h. We investigated mRNA changes over thr time course of the treatments with the senotoxin StnI 1.3.1 RNA Quality Assessment Purity, concentration and integrity of RNA sample were examined by NanoDrop, Qubit 2.0, Agilent 2100, etc. Only RNA with good quality could move on to following procedures. 1.3.2 RNA Library Construction Qualified RNA were processed for library construction. The procedures are described as follow: (1) mRNA was isolated by Oligo(dT)-attached magnetic beads. (2) mRNA was then randomly fragmented in fragmentation buffer. (3) First-strand cDNA was synthesized with fragmented mRNA as template and random hexamers as primers, followed by second-strand synthesis with addition of PCR buffer, dNTPs, RNase H and DNA polymerase I. Purification of cDNA was processed with AMPure XP beads. (4) Double-strand cDNA was subjected to end repair. Adenosine was added to the end and ligated to adapters. AMPure XP beads were applied here to select fragments within certain size range. (5) cDNA library was obtained by certain rounds of PCR on cDNA fragments generated from step 4. 1.3.3 Library Quality Assessment In order to ensure the quality of library, Qubit 2.0 and Agilent 2100 were used to examine the concentration of cDNA and insert size. Q-PCR was processed to obtain a more accurate library concentration and assure adequate library concentration. 1.3.4 Sequencing Qualified libraries were uploaded on Illumina NovaSeq 6000 platform for sequencing with read length of PE150. 2 Data Quality Control 2.1 Sequencing Data In next generation sequencing, e.g. Illumina NovaSeq 6000, etc., bases are inferred from light intensity signals generated by Illumina sequencing platform, which is known as base calling. Data generated directly from base calling is referred to as Raw data or Raw reads. Raw data was normally provided in FASTQ(fq) format, containing sequences and corresponding quality information. A demo FASTQ file is shown as below. 2.1.1 Sequence Quality Phred quality score described above represents the probability of an error base calling. Correspondence table of Qphred was shown below. TIn NovaSeq 6000 sequencing, one DNA library template is firstly captured on flowcell and generats a cluster. The first cour cycels are used for cluster calling and establishing more suitable parameter setting based on current flowcell. Therefore, Base-calls of first several bases, which are generated relying on a standard parameter setting, are usually of low quality. The Q-score will increased back to normal with calibrated setting. Besides, it is also common to see that error rate climbs in the last few bases due to comsumption of reagents. Despite this, Q-score of most bases are higher than Q30.