Assessment of a highly multiplexed RNA sequencing platform and comparison to existing high-throughput gene expression profiling techniques [microarray]

In this study, we report the performance of one such technique denoted as sparse full length sequencing (SFL), a ribosomal RNA depletion-based RNA sequencing approach that allows for the simultaneous sequencing of 96 samples and higher. We offer comparisons to well established single-sample techniques, including: full coverage Poly-A capture RNA-seq and microarray, as well as another low-cost highly multiplexed technique known as 3’ digital gene expression (3’ DGE). Data was generated for a set of exposure experiments on immortalized human lung epithelial (AALE) cells in a two-by-two study design, in which samples received both genetic and chemical perturbations of known oncogenes/tumor suppressors and lung carcinogens. SFL demonstrated improved performance over 3’ DGE in terms of coverage, power to detect differential gene expression, and biological recapitulation of patterns of differential gene expression from in vivo lung cancer mutation signatures. Microarray RNA expression for immortalized human bronchial epithelial cells (AALE) exposed to chemical and genotypic perturbations

本研究报道了一种名为稀疏全长测序（sparse full length sequencing, SFL）的技术性能，该技术属于基于核糖体RNA去除的RNA测序方法，可实现96个及以上样本的同步测序。
本研究将其与多款成熟单样本技术开展对比，包括全覆盖Poly-A捕获RNA测序、微阵列技术，以及另一种名为3'数字基因表达谱（3’ digital gene expression, 3’ DGE）的低成本高多重化技术。
本研究采用二乘二实验设计，对永生化人肺上皮细胞（immortalized human lung epithelial, AALE）完成了一系列暴露实验并生成对应数据，实验中样本同时接受了已知致癌基因/抑癌基因与肺癌致癌物的遗传及化学扰动。
相较于3'数字基因表达谱，稀疏全长测序在测序覆盖度、差异基因表达检测效能以及基于体内肺癌突变特征重现差异基因表达模式的生物学合理性层面均表现更优。
永生化人支气管上皮细胞（immortalized human bronchial epithelial, AALE）经化学与基因型扰动后的微阵列RNA表达数据