Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and CTCF cKO Transcriptomes

Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived liver transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis Methods: Liver mRNA profiles of 8-week-old wild-type (WT) and liver specific conditional CTCF KO (CTCF cKO) mice were generated by deep sequencing, in quadruplet, using Illumina GAIIx. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. qRT–PCR validation was performed using TaqMan and SYBR Green assays Results: Using an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the mouse genome (build mm9) and identified 16,014 transcripts in the retinas of WT and Nrl−/− mice with BWA workflow and 34,115 transcripts with TopHat workflow. RNA-seq data confirmed stable expression of 25 known housekeeping genes, and 12 of these were validated with qRT–PCR. RNA-seq data had a linear relationship with qRT–PCR for more than four orders of magnitude and a goodness of fit (R2) of 0.8798. Approximately 10% of the transcripts showed differential expression between the WT and Nrl−/− retina, with a fold change ≥1.5 and p value <0.05. Altered expression of 25 genes was confirmed with qRT–PCR, demonstrating the high degree of sensitivity of the RNA-seq method. Hierarchical clustering of differentially expressed genes uncovered several as yet uncharacterized genes that may contribute to retinal function. Data analysis with BWA and TopHat workflows revealed a significant overlap yet provided complementary insights in transcriptome profiling. Conclusions: Our study represents the first detailed analysis of retinal 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. Liver mRNA profiles of 8 weeks old wild type (WT) and CTCF cKO mice研究目的：下一代测序（Next-generation sequencing，NGS）彻底革新了细胞通路的系统级分析。本研究旨在对比基于NGS的肝脏转录组图谱分析（RNA-seq）与基因芯片、定量反转录聚合酶链式反应（qRT–PCR）两种技术，并优化用于最优高通量数据分析的实验流程。 研究方法：本研究通过Illumina GAIIx平台对8周龄野生型（wild-type，WT）及肝脏特异性条件性CTCF敲除（CTCF cKO）小鼠的肝脏mRNA进行深度测序，设置四重复样。对通过质量过滤的序列读段，采用两种方法在转录本异构体水平进行分析：一是Burrows-Wheeler比对工具（Burrows–Wheeler Aligner，BWA）结合方差分析（ANOVA），二是TopHat结合Cufflinks。采用TaqMan探针法与SYBR Green染料法进行qRT–PCR验证。 研究结果：通过优化的数据分析流程，我们将每个样本约3000万条序列读段比对至小鼠基因组（版本mm9）。采用BWA流程在野生型与Nrl−/−小鼠视网膜中鉴定出16014个转录本，采用TopHat流程则鉴定出34115个转录本。RNA-seq数据证实了25个已知持家基因的稳定表达，其中12个通过qRT–PCR得到验证。RNA-seq数据与qRT–PCR数据的线性相关范围超过4个数量级，拟合优度（R²）为0.8798。约10%的转录本在野生型与Nrl−/−小鼠视网膜中存在差异表达，差异倍数≥1.5且p值<0.05。25个基因的表达变化通过qRT–PCR得到证实，证明了RNA-seq技术的高灵敏度。对差异表达基因进行层次聚类后，发现了多个尚未被表征的基因，这些基因可能与视网膜功能相关。采用BWA与TopHat流程进行的数据分析显示，二者存在显著的结果重叠，但同时也提供了互补的转录组分析视角。 研究结论：本研究首次通过RNA-seq技术对小鼠视网膜转录组进行了详细分析，并设置了生物学重复。本文报道的优化数据分析流程可为表达图谱的比较研究提供框架。研究结果表明，NGS可对细胞或组织内的mRNA含量进行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，并助力复杂生物学功能的解析。 8周龄野生型（WT）与CTCF条件性敲除（cKO）小鼠的肝脏mRNA表达谱