Next Generation Sequencing Facilitates Quantitative Analysis of WT and GSH or Ctrl and Cas9 mouse breast cancer cells Transcriptomes

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 WT and WT+GSH or Ctrl-Cas9 and Scarb2-Cas9 mouse breast cancer cells by using NGS-derived transcriptome profiling (RNA-seq). Methods: 4T1 cells treated with or without GSH (500 µM) and 4T1 stably expressing Ctrl-Cas9 or Scarb2-Cas9 were collected. 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 WT and WT+GSH or Ctrl-Cas9 and Scarb2-Cas9 mouse breast cancer 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. WT and GSH or Ctrl and Cas9 mouse breast cancer cells' mRNA profiles were generated by deep sequencing, in triplicate, using Illumina HiSeq 4000.

研究目的：下一代测序（Next-generation sequencing, NGS）已系统性革新了细胞通路的系统生物学分析。本研究拟通过NGS衍生的转录组谱分析（RNA-seq），解析野生型（Wild Type, WT）与WT+谷胱甘肽（Glutathione, GSH）组、以及Ctrl-Cas9与Scarb2-Cas9组小鼠乳腺癌细胞中的差异基因及通路。
研究方法：收集经500 μM GSH处理与未处理的4T1细胞，以及稳定表达Ctrl-Cas9或Scarb2-Cas9的4T1细胞。采用Illumina HiSeq 4000平台开展三次生物学重复的深度测序，获取上述细胞的mRNA表达谱。对通过质量过滤的测序reads，在转录本异构体水平进行分析：使用HISAT2 v2.1完成序列比对，借助IGV（Integrative Genomics Viewer）以热图、柱状图、散点图等形式可视化比对结果；随后计算各样本中基因的FPKM（Fragments Per Kilobase of transcript per Million fragments mapped）值，以评估基因表达水平；针对两组均无生物学重复的样本，采用DEGseq v1.18.0进行差异基因表达分析，并开展包含基因本体（Gene Ontology, GO）富集分析与京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Genomes, KEGG）富集分析的功能富集分析。
研究结论：本研究首次针对WT与WT+GSH组、Ctrl-Cas9与Scarb2-Cas9组小鼠乳腺癌细胞的转录组开展了详细解析，所有样本均设置生物学重复，测序数据由RNA-seq技术生成。本研究报道的优化数据分析流程，可为表达谱的比较研究提供标准化框架。研究结果显示，NGS可对细胞或组织内的mRNA含量实现全面且更为精准的定量与定性评估。综上，基于RNA-seq的转录组表征可加速基因网络分析，并为复杂生物学功能的解析提供可能。