Miniaturization Technologies for Efficient Single-Cell Library Preparation for Next-Generation Sequencing. (August 2016)

• Record Type: Journal Article
• Authors: Mora-Castilla, Sergio; To, Cuong; Vaezeslami, Soheila; Morey, Robert; Srinivasan, Srimeenakshi; Dumdie, Jennifer N.; Cook-Andersen, Heidi; Jenkins, Joby; Laurent, Louise C.
• Is Part Of: SLAS technology. Volume 21:Number 4(2016)
• Page Start: 557
• Page End: 567
• Publication Date: 2016-08
• Subjects: miniaturization -- single cell -- library -- scale-down; Medical laboratory technology -- Periodicals; Laboratories -- Equipment and supplies -- Periodicals; Diagnosis, Laboratory -- Periodicals; 616.075
• DOI: 10.1177/2211068216630741
• Languages: English
• ISSNs: 2472-6303

Abstract

As the cost of next-generation sequencing has decreased, library preparation costs have become a more significant proportion of the total cost, especially for high-throughput applications such as single-cell RNA profiling. Here, we have applied novel technologies to scale down reaction volumes for library preparation. Our system consisted of in vitro differentiated human embryonic stem cells representing two stages of pancreatic differentiation, for which we prepared multiple biological and technical replicates. We used the Fluidigm (San Francisco, CA) C1 single-cell Autoprep System for single-cell complementary DNA (cDNA) generation and an enzyme-based tagmentation system (Nextera XT; Illumina, San Diego, CA) with a nanoliter liquid handler (mosquito HTS; TTP Labtech, Royston, UK) for library preparation, reducing the reaction volume down to 2 µL and using as little as 20 pg of input cDNA. The resulting sequencing data were bioinformatically analyzed and correlated among the different library reaction volumes. Our results showed that decreasing the reaction volume did not interfere with the quality or the reproducibility of the sequencing data, and the transcriptional data from the scaled-down libraries allowed us to distinguish between single cells. Thus, we have developed a process to enable efficient and cost-effective high-throughput single-cell transcriptome sequencing.