Next Generation Sequencing Facilitates Quantitative Analysis of control and Pep2-CM4-treated cells' Transcriptomes in lymphoma

Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to analysis the differiational genes and pathways in control and Pep2-CM4-treated lymphoma cells by using NGS-derived lymphoma transcriptome profiling (RNA-seq). Methods: Control and Pep2-CM4-treated cells' mRNA profiles were generated by deep sequencing, in triplicate, using Illumina HiSeq 4000. The sequence reads that passed quality filters were analyzed at the transcript isoform level with following methods: Alignment by using HISAT2 v2.1, IGV was used to to view the mapping result by the Heatmap, histogram, scatter plot or other stytle, FPKM was then calculated to estimate the expression level of genes in each sample, DEGseq v1.18.0 was used for differential gene expression analysis between two samples with non biological replicates and Function Enrichment Analysis including GO enrichment analysis and KEGG . Conclusions: Our study represents the first detailed analysis of Control and Pep2-CM4-treated cells' transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions. Control and Pep2-CM4-treated cells' mRNA profiles were generated by deep sequencing, in triplicate, using Illumina HiSeq 4000.