Next Generation Sequencing Facilitates Quantitative Analysis of lymphoma cells‘ Transcriptomes from the lymph node tissues of Myc-E and Myc-ECreCD19Trib3F/+ mice

ABSTRACT: 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 Myc-E and Myc-ECreCD19Trib3F/+ mice‘ lymphoma cells by using NGS-derived lymphoma transcriptome profiling (RNA-seq). Methods: The Myc-E and Myc-ECreCD19Trib3F/+ mice' lymphoma cells were isolated, then these 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 Myc-E and Myc-ECreCD19Trib3F/+ mice lymphoma 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.

ORGANISM(S): Mus musculus

PROVIDER: GSE126738 | GEO | 2020/10/02

REPOSITORIES: GEO