Abstract
The development of high-throughput single-cell RNA sequencing (scRNA-seq) has enabled access to information about gene expression in individual cells and insights into new biological areas. Although the interest in scRNA-seq has rapidly grown in recent years, the existing methods are plagued by many challenges when performing scRNA-seq on multiple samples. To simultaneously analyze multiple samples with scRNA-seq, we developed a universal sample barcoding method through transient transfection with short barcode oligonucleotides. By conducting a species-mixing experiment, we have validated the accuracy of our method and confirmed the ability to identify multiplets and negatives. Samples from a 48-plex drug treatment experiment were pooled and analyzed by a single run of Drop-Seq. This revealed unique transcriptome responses for each drug and target-specific gene expression signatures at the single-cell level. Our cost-effective method is widely applicable for the single-cell profiling of multiple experimental conditions, enabling the widespread adoption of scRNA-seq for various applications.
Original language | English |
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Article number | eaav2249 |
Journal | Science Advances |
Volume | 5 |
Issue number | 5 |
DOIs | |
Publication status | Published - 2019 May 15 |
Bibliographical note
Funding Information:We thank W. Namkung (Department of Pharmacy, Yonsei University) for contributing the kinase inhibitor library (catalog no. L1200, Selleck Chemicals). This work was supported by the following sources: (i) the Mid-career Researcher Program (NRF-2018R1A2A1A05079172) through the National Research Foundation of Korea (NRF), funded by the Ministry of Science, ICT and Future Planning; (ii) the Bio & Medical Technology Development Program of the National Research Foundation (NRF) funded by the Korean government (MSIT; NRF-2016M3A9B6948494); (iii) the Bio & Medical Technology Development Program of the National Research Foundation (NRF) funded by the Korean government (MSIT; NRF-2018M3A9H3024850); and (iv) by the Ministry of Science, ICT and Future Planning (grant no. NRF-2018R1A2B2001322).
Publisher Copyright:
Copyright © 2019 The Authors.
All Science Journal Classification (ASJC) codes
- General