Deciphering the RNA landscape by RNAome sequencing [Affymetrix]. Mus musculus

Current RNA expression profiling methods rely on enrichment steps for specific RNA classes, thereby not detecting all RNA species in an unperturbed manner. We report strand-specific RNAome sequencing that determines expression of small and large RNAs from ribosomal RNA-depleted total RNA in a single sequence run. Since current analysis pipelines cannot reliably analyze small and large RNAs simultaneously, we developed TRAP, Total Rna Analysis Pipeline, a robust interface that is also compatible with existing RNA sequencing protocols. RNAome sequencing quantitatively preserved all RNA classes, allowing cross-class comparisons that facilitates the identification of relationships between different RNA classes. We demonstrate the strength of RNAome sequencing in mouse embryonic stem cells treated with cisplatin. MicroRNA and mRNA expression in RNAome sequencing significantly correlated between replicates and was in concordance with both existing RNA sequencing methods and gene expression arrays generated from the same samples. Moreover, RNAome sequencing also detected additional RNA classes such as enhancer RNAs, anti-sense RNAs, novel RNA species and numerous differentially expressed RNAs undetectable by other methods. At the level of complete RNA classes, RNAome sequencing also identified a specific global repression of the microRNA and microRNA isoform classes after cisplatin treatment whereas all other classes such as mRNAs were unchanged. These characteristics of RNAome sequencing will significantly improve expression analysis as well as studies on RNA biology not covered by existing methods. Overall design: 8 mouse embryonic stem cell samples, control and cisplatin treated, 4 replicates per group

当前的RNA表达谱分析方法依赖针对特定RNA类别的富集步骤，因此无法以未受扰动的方式检测到全部RNA物种。本研究报道了一种链特异性RNA组测序（strand-specific RNAome sequencing）方法，该方法可在单次测序运行中，从经核糖体RNA去除处理的总RNA中同时测定小型与大型RNA的表达水平。由于现有分析流程无法可靠地同时分析小型与大型RNA，我们开发了TRAP（总RNA分析流程，Total Rna Analysis Pipeline）——一款稳健的分析界面，同时兼容现有RNA测序实验方案。该链特异性RNA组测序可定量保留所有类别的RNA，支持跨类别比较，从而助力鉴定不同RNA类别间的关联关系。我们以顺铂处理的小鼠胚胎干细胞为模型，验证了该测序方法的优势性能。RNA组测序得到的微小RNA（MicroRNA）与信使RNA（mRNA）的表达量在生物学重复间呈现显著相关性，且与同一样本采用现有RNA测序方法及基因表达芯片得到的结果高度一致。此外，RNA组测序还可检测到其他方法无法检出的额外RNA类别，例如增强子RNA、反义RNA、新型RNA物种以及大量差异表达RNA。在完整RNA类别的层面上，RNA组测序还发现顺铂处理后，微小RNA及其异构体类别出现了特异性的全局抑制，而信使RNA等其他类别则无明显变化。RNA组测序的这些特性将显著提升表达分析及现有方法尚未覆盖的RNA生物学研究水平。实验设计概况：共8份小鼠胚胎干细胞样本，分为对照组与顺铂处理组，每组设置4次生物学重复