Santacruz Diana, Enane Francis O, Fundel-Clemens Katrin, Giner Martin, Wolf Gernot, Onstein Svenja, Klimek Christoph, Smith Zachary, Wijayawardena Bhagya, Viollet Coralie
Boehringer Ingelheim Pharma GmbH & Co. KG.
Beckman Coulter Life Sciences.
SLAS Discov. 2022 Mar;27(2):140-147. doi: 10.1016/j.slasd.2022.01.002. Epub 2022 Jan 16.
Over the last decade, whole transcriptome profiling, also known as RNA-sequencing (RNA-seq), has quickly gained traction as a reliable method for unbiased assessment of gene expression. Integration of RNA-seq expression data into other omics datasets (e.g., proteomics, metabolomics, or epigenetics) solidifies our understanding of cell-specific regulatory patterns, yielding pathways to investigate the key rules of gene regulation. A limitation to efficient, at-scale utilization of RNA-seq is the time-demanding library preparation workflows, which is a 2-day or longer endeavor per cohort/sample size. To tackle this bottleneck, we designed an automated workflow that increases throughput capacity, while minimizing human error to enhance reproducibility. To this end, we converted the manual protocol of the NEBNext Directional Ultra II RNA Library Prep Kit for Illumina on the Beckman Coulter liquid handler, Biomek i7 Hybrid workstation. A total of 84 RNA samples were isolated from two human cell lines and subjected to comparative manual and automated library preparation methods. Qualitative and quantitative results indicated a high degree of similarity between libraries generated manually or through automation. Yet, there was a significant reduction in both hands-on and assay time from a 2-day manual to a 9-hour automated workflow. Using linear regression analysis, we found the Pearson correlation coefficient between libraries generated manually or by automation to be almost identical to a sample being sequenced twice (R²= 0.985 vs 0.983). This demonstrates that high-throughput automated workflows can be of great benefit to genomic laboratories by enhancing efficiency of library preparation, reducing hands-on time and increasing throughput potential.
在过去十年中，全转录组分析，也称为RNA测序（RNA-seq），作为一种可靠的基因表达无偏评估方法迅速获得了广泛应用。将RNA-seq表达数据整合到其他组学数据集（如蛋白质组学、代谢组学或表观遗传学）中，巩固了我们对细胞特异性调控模式的理解，为研究基因调控的关键规则提供了途径。RNA-seq高效、大规模应用的一个限制是耗时的文库制备工作流程，每个队列/样本量需要2天或更长时间。为了解决这一瓶颈，我们设计了一种自动化工作流程，提高了通量，同时将人为误差降至最低以提高可重复性。为此，我们在贝克曼库尔特液体处理仪Biomek i7 Hybrid工作站上，将用于Illumina的NEBNext Directional Ultra II RNA文库制备试剂盒的手动操作方案进行了转换。从两个人类细胞系中分离出总共84个RNA样本，并采用手动和自动化文库制备方法进行比较。定性和定量结果表明，手动或通过自动化生成的文库之间具有高度相似性。然而，从2天的手动工作流程到9小时的自动化工作流程，实际操作时间和检测时间都显著减少。通过线性回归分析，我们发现手动或通过自动化生成的文库之间的皮尔逊相关系数与对一个样本进行两次测序的结果几乎相同（R² = 0.985对0.983）。这表明高通量自动化工作流程通过提高文库制备效率、减少实际操作时间和增加通量潜力，可为基因组实验室带来巨大益处。
