Massively parallel nanowell-based single-cell gene expression profiling

BMC Genomics

Methodology Article

Hermann Hubschle¹  Wenlin Yuan²  Zora Modrusan²  Jeremy Stinson²  Jingli Zhang²  Kanika Bajaj Pahuja²  Somasekar Seshagiri²  Leonard D. Goldstein²  Joseph Guillory²  Bijay Jaiswal²  Ying-Jiun Jasmine Chen²  Alain Mir³  Sherry Wei³  Maithreyan Srinivasan³  Thomas Schaal³  Syed Husain³  Ishminder Mann³  Patricio Espinoza³  Leo Chan³  Harris Shapiro³  Karthikeyan Swaminathan³  Chun-wah Lin³  Jude Dunne³  Sangeetha Anandakrishnan³ 

[1] Axiocor Inc., L2N 5P6, St. Catharines, ON, Canada;Molecular Biology Department, Genentech Inc., 1 DNA Way, 94080, South San Francisco, CA, USA;Wafergen Biosystems Inc., 34700 Campus Drive, 94555, Fremont, CA, USA;

关键词: Single cell profiling;    RNA sequencing;    Single-cell transcriptome;   

DOI  :  10.1186/s12864-017-3893-1

 received in 2017-01-02, accepted in 2017-06-21,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundTechnological advances have enabled transcriptome characterization of cell types at the single-cell level providing new biological insights. New methods that enable simple yet high-throughput single-cell expression profiling are highly desirable.ResultsHere we report a novel nanowell-based single-cell RNA sequencing system, ICELL8, which enables processing of thousands of cells per sample. The system employs a 5,184-nanowell-containing microchip to capture ~1,300 single cells and process them. Each nanowell contains preprinted oligonucleotides encoding poly-d(T), a unique well barcode, and a unique molecular identifier. The ICELL8 system uses imaging software to identify nanowells containing viable single cells and only wells with single cells are processed into sequencing libraries. Here, we report the performance and utility of ICELL8 using samples of increasing complexity from cultured cells to mouse solid tissue samples. Our assessment of the system to discriminate between mixed human and mouse cells showed that ICELL8 has a low cell multiplet rate (< 3%) and low cross-cell contamination. We characterized single-cell transcriptomes of more than a thousand cultured human and mouse cells as well as 468 mouse pancreatic islets cells. We were able to identify distinct cell types in pancreatic islets, including alpha, beta, delta and gamma cells.ConclusionsOverall, ICELL8 provides efficient and cost-effective single-cell expression profiling of thousands of cells, allowing researchers to decipher single-cell transcriptomes within complex biological samples.

【 授权许可】

CC BY   
© The Author(s). 2017