Synthetic spike-in standards for RNA-seq experiments
Synthetic spike-in standards for RNA-seq experiments
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DOI：
10.1101/gr.121095.111
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发表时间：
2011-09-01
期刊：
影响因子：
7
通讯作者：
Oliver, Brian
中科院分区：
文献类型：
--
作者：
Jiang, Lichun;Schlesinger, Felix;Oliver, Brian
高通量cDNA测序（RNA-seq）是一种广泛应用的转录组分析和注释技术，但关于不同协议和平台的性能问题仍然存在。我们使用新开发的96种不同长度的合成rna， GC含量覆盖2（20）浓度范围作为峰值控制，以测量RNA-seq实验的灵敏度、准确性和偏差，并推导出用于定量转录本丰度的标准曲线。在整个检测范围内，我们观察到读取密度和RNA输入之间存在线性关系，并且重复之间具有良好的一致性，但在纯泊松采样误差下，我们观察到的不精确性明显大于预期。我们使用对照RNA直接测量由GC含量和转录本长度以及与RNA末端相对位置和引物序列偏差相关的转录本覆盖范围的刻板异质性引起的可重复的协议依赖偏差。这些影响导致短转录本和单个外显子的偏差量化，这是测量同工异构体丰度的严重问题，但可以使用适当的偏差模型部分纠正。通过使用对照rna，我们得出了在RNA-seq实验中发现和检测稀有转录本的限制。通过使用作为模式生物和人类DNA元件百科全书项目（ENCODE和modENCODE）的一部分收集的数据，我们证明了外部RNA对照是评估RNA-seq实验的敏感性和准确性的有用资源，用于转录组发现和定量。这些质量指标促进了跨不同样本、协议和平台的比较分析。
High-throughput sequencing of cDNA (RNA-seq) is a widely deployed transcriptome profiling and annotation technique, but questions about the performance of different protocols and platforms remain. We used a newly developed pool of 96 synthetic RNAs with various lengths, and GC content covering a 2(20) concentration range as spike-in controls to measure sensitivity, accuracy, and biases in RNA-seq experiments as well as to derive standard curves for quantifying the abundance of transcripts. We observed linearity between read density and RNA input over the entire detection range and excellent agreement between replicates, but we observed significantly larger imprecision than expected under pure Poisson sampling errors. We use the control RNAs to directly measure reproducible protocol-dependent biases due to GC content and transcript length as well as stereotypic heterogeneity in coverage across transcripts correlated with position relative to RNA termini and priming sequence bias. These effects lead to biased quantification for short transcripts and individual exons, which is a serious problem for measurements of isoform abundances, but that can partially be corrected using appropriate models of bias. By using the control RNAs, we derive limits for the discovery and detection of rare transcripts in RNA-seq experiments. By using data collected as part of the model organism and human Encyclopedia of DNA Elements projects (ENCODE and modENCODE), we demonstrate that external RNA controls are a useful resource for evaluating sensitivity and accuracy of RNA-seq experiments for transcriptome discovery and quantification. These quality metrics facilitate comparable analysis across different samples, protocols, and platforms.