Abstract
The quantification of transcriptional variation in single cells, particularly within the same cell population, is currently limited by the low sensitivity and high technical noise of single-cell RNA-seq assays. We report multiple annealing and dC-tailing-based quantitative single-cell RNA-seq (MATQ-seq), a highly sensitive and quantitative method for single-cell sequencing of total RNA. By systematically determining technical noise, we show that MATQ-seq captures genuine biological variation between whole transcriptomes of single cells.
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Acknowledgements
This work is supported by the McNair Scholarship and McNair Single Cell Initiative. We are grateful to the McNair family and C. Neblett for their kind support. We would like to thank Z. Hu, Y. Zhao and J. Yuan for their help. The MCF10A cell line was generously provided by S. Zhang (Baylor College of Medicine). We also would like to thank S. Rosenberg, C. Herman and H. Dierick for their helpful comments on the manuscript.
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Authors and Affiliations
Contributions
K.S. and C.Z. developed the MATQ-seq assay, performed the data analysis and wrote the manuscript. K.S., W.C., Y.N. and Q.D. performed the single-cell RNA sequencing.
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Baylor College of Medicine has submitted a patent application on MATQ-seq.
Supplementary information
Supplementary Text and Figures
Supplementary Figures 1–24 and Supplementary Tables 1–4. (PDF 4066 kb)
Supplementary Data 1
ERCC mapping data. (XLSX 12 kb)
Supplementary Data 2
Exon-based gene list. (XLSX 20 kb)
Supplementary Data 3
Intron-based gene list. (XLSX 22 kb)
Supplementary Data 4
Exon-based transcriptional factors. (XLSX 15 kb)
Supplementary Data 5
Intron-based transcriptional factors. (XLSX 17 kb)
Supplementary Software
MATLAB Scripts (ZIP 28495 kb)
Supplementary Protocol
MATQ-seq protocol (PDF 168 kb)
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Sheng, K., Cao, W., Niu, Y. et al. Effective detection of variation in single-cell transcriptomes using MATQ-seq. Nat Methods 14, 267–270 (2017). https://doi.org/10.1038/nmeth.4145
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DOI: https://doi.org/10.1038/nmeth.4145
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