Integrative genome-wide analysis in non-small cell lung cancer cells

We used complementing high-throughput sequencing technologies, including RNA-seq, DNase I-seq, and ChIP-seq, to examine the distribution of DNase I hypersensitive sites and H3K4me2 histone marks, to infer transcription factor binding sites, to identify key pathways in Gefinitib resistant and sensitive cell lines, PC9R and PC9 respectively, and to verify that some of up-regulated genes in PC9R can be found in Gefinitib resistant patients, which indicated that our study has valid clinical relevance. Total mRNA profiles of PC9 and PC9R cell lines were generated by deep sequencing, in duplicate, using Illumina Hiseq2000.The mapping results of RNA-seq reads by the TopHat algorithm (version 1.1.4) to the hg19 reference genome were used to count the number of reads per gene with the hgseq-count algorithm. Then, DESeq was used to detect the genes differentially expressed between the PC9 and PC9R samples, with a p-value of 0.05 as the threshold. DNase-Seq and ChIP-Seq raw reads were aligned with Bowtie0.12.9 to hg19. MACS2 (https://github.com/taoliu/MACS/downloads) was employed to call PC9-specific regions using PC9 cells as the treatment and PC9R cells as the control, with a q-value threshold (DNase-Seq: 10-2; ChIP-Seq: 10-3) to minimise false positives; then, the process was repeated with the treatment and control cell lines switched. Overall design: All methodes used in 2 cell lines including drug sensitive and resistant cells