Next Generation Sequencing (NGS) for quantitative transcriptomic analysis of colorectal tumor cell lines and their ENU mutants

Purpose: To understand differences of gene expression profiles between colorectal cell lines and their ENU mutants. Methods: RNA profiles were generated by deep sequencing using Illumina Next-seq. Using an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the mouse genome (GRCm38 release-95). Conclusions: Our study represents the detailed differential transcriptomic analysis using ENU mutants of colorectal tumors, 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. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions. mRNA profiles of tumors were generated by deep sequencing, in triplicate, using Illumina Next-seq.