Next-generation sequencing facilitates quantitative analysis of CreAlbMYC and CreAlbScarb2F/FMYC mice liver tissue transcriptomes. Next-generation sequencing facilitates quantitative analysis of CreAlbMYC and CreAlbScarb2F/FMYC mice liver tissue transcriptomes

Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to analyse the differential genes and pathways in liver tissue of CreAlbMYC and CreAlbScarb2F/FMYC mice by using RNA-seq. Methods: CreAlbMYC and CreAlbScarb2F/FMYC liver tissue mRNA profiles were generated by deep sequencing, using Illumina Novaseq 6000. The sequence reads that passed quality filters were analyzed at the transcript isoform level with following methods: Alignment by using HISAT2, IGV was used to view the mapping result by the Heatmap, histogram, scatter plot or other style, FPKM was then calculated to estimate the expression level of genes in each sample, DEGseq 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 CreAlbMYC and CreAlbScarb2F/FMYC liver tissue 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. Overall design: CreAlbMYC and CreAlbScarb2F/FMYC liver tissue mRNA profiles were generated by deep sequencing using Illumina Novaseq 6000.

研究目的：下一代测序（Next-generation Sequencing, NGS）已彻底革新了基于系统的细胞通路分析方法。本研究旨在通过RNA测序（RNA-seq）分析CreAlbMYC与CreAlbScarb2F/FMYC小鼠肝组织中的差异基因及通路。
研究方法：本研究通过Illumina NovaSeq 6000平台开展深度测序，获取了CreAlbMYC与CreAlbScarb2F/FMYC小鼠肝组织的mRNA表达谱。对通过质量过滤的测序reads，我们在转录本异构体层面开展分析，具体方法如下：使用HISAT2进行序列比对；利用整合基因组浏览器（Integrative Genomics Viewer, IGV）以热图、直方图、散点图等形式可视化比对结果；计算每百万比对reads的转录本每千碱基片段数（Fragments Per Kilobase of transcript per Million mapped reads, FPKM）以评估各样本中基因的表达水平；针对无生物学重复的两组样本，采用DEGseq进行差异基因表达分析；并开展功能富集分析，涵盖基因本体（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。
研究结论：本研究是首次结合生物学重复，利用RNA-seq技术对CreAlbMYC与CreAlbScarb2F/FMYC小鼠肝组织转录组开展的详细分析。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参考框架。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遗传网络分析，并助力解析复杂的生物学功能。
整体实验设计：通过Illumina NovaSeq 6000平台开展深度测序，获取CreAlbMYC与CreAlbScarb2F/FMYC小鼠肝组织的mRNA表达谱。