Comparative Analysis of Droplet-Based Ultra-High-Throughput Single-Cell RNA-Seq Systems

doi:10.1016/j.molcel.2018.10.020

Comparative Study

. 2019 Jan 3;73(1):130-142.e5.

doi: 10.1016/j.molcel.2018.10.020. Epub 2018 Nov 21.

Comparative Analysis of Droplet-Based Ultra-High-Throughput Single-Cell RNA-Seq Systems

Xiannian Zhang¹, Tianqi Li², Feng Liu³, Yaqi Chen⁴, Jiacheng Yao², Zeyao Li⁵, Yanyi Huang⁶, Jianbin Wang⁷

Affiliations

¹ Beijing Advanced Innovation Center for Genomics (ICG), Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, College of Engineering, and Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China.
² School of Life Sciences, and Tsinghua-Peking Center for Life Sciences, Tsinghua University, Beijing 100084, China.
³ National Research Center for Translational Medicine (Shanghai), State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
⁴ Peking University Shenzhen Graduate School, Shenzhen 518055, China.
⁵ School of Life Sciences, and Peking-Tsinghua-NIBS Joint Graduate Program, Tsinghua University, Beijing 100084, China.
⁶ Beijing Advanced Innovation Center for Genomics (ICG), Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, College of Engineering, and Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China. Electronic address: yanyi@pku.edu.cn.
⁷ School of Life Sciences, and Tsinghua-Peking Center for Life Sciences, Tsinghua University, Beijing 100084, China. Electronic address: jianbinwang@tsinghua.edu.cn.

PMID: 30472192
DOI: 10.1016/j.molcel.2018.10.020

Free article

Comparative Study

Comparative Analysis of Droplet-Based Ultra-High-Throughput Single-Cell RNA-Seq Systems

Xiannian Zhang et al. Mol Cell. 2019.

Free article

. 2019 Jan 3;73(1):130-142.e5.

doi: 10.1016/j.molcel.2018.10.020. Epub 2018 Nov 21.

Authors

Xiannian Zhang¹, Tianqi Li², Feng Liu³, Yaqi Chen⁴, Jiacheng Yao², Zeyao Li⁵, Yanyi Huang⁶, Jianbin Wang⁷

Affiliations

¹ Beijing Advanced Innovation Center for Genomics (ICG), Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, College of Engineering, and Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China.
² School of Life Sciences, and Tsinghua-Peking Center for Life Sciences, Tsinghua University, Beijing 100084, China.
³ National Research Center for Translational Medicine (Shanghai), State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
⁴ Peking University Shenzhen Graduate School, Shenzhen 518055, China.
⁵ School of Life Sciences, and Peking-Tsinghua-NIBS Joint Graduate Program, Tsinghua University, Beijing 100084, China.
⁶ Beijing Advanced Innovation Center for Genomics (ICG), Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, College of Engineering, and Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China. Electronic address: yanyi@pku.edu.cn.
⁷ School of Life Sciences, and Tsinghua-Peking Center for Life Sciences, Tsinghua University, Beijing 100084, China. Electronic address: jianbinwang@tsinghua.edu.cn.

PMID: 30472192
DOI: 10.1016/j.molcel.2018.10.020

Abstract

Since its establishment in 2009, single-cell RNA sequencing (RNA-seq) has been a major driver behind progress in biomedical research. In developmental biology and stem cell studies, the ability to profile single cells confers particular benefits. Although most studies still focus on individual tissues or organs, the recent development of ultra-high-throughput single-cell RNA-seq has demonstrated potential power in characterizing more complex systems or even the entire body. However, although multiple ultra-high-throughput single-cell RNA-seq systems have attracted attention, no systematic comparison of these systems has been performed. Here, with the same cell line and bioinformatics pipeline, we developed directly comparable datasets for each of three widely used droplet-based ultra-high-throughput single-cell RNA-seq systems, inDrop, Drop-seq, and 10X Genomics Chromium. Although each system is capable of profiling single-cell transcriptomes, their detailed comparison revealed the distinguishing features and suitable applications for each system.

Keywords: 10X genomics; Drop-seq; RNA-Seq analysis pipeline; barcode analysis; droplet-based microfluidics; high throughput; inDrop; method comparison; single-cell RNA-seq.

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Comparative Analysis of Droplet-Based Ultra-High-Throughput Single-Cell RNA-Seq Systems

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Comparative Analysis of Droplet-Based Ultra-High-Throughput Single-Cell RNA-Seq Systems

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