The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
High-throughput microfluidic single-cell RT-qPCR
Open accessAbstract
A long-sought milestone in microfluidics research has been the development of integrated technology for scalable analysis of transcription in single cells. Here we present a fully integrated microfluidic device capable of performing high-precision RT-qPCR measurements of gene expression from hundreds of single cells per run. Our device executes all steps of single-cell processing, including cell capture, cell lysis, reverse transcription, and quantitative PCR. In addition to higher throughput and reduced cost, we show that nanoliter volume processing reduced measurement noise, increased sensitivity, and provided single nucleotide specificity. We apply this technology to 3,300 single-cell measurements of ( i ) miRNA expression in K562 cells, ( ii ) coregulation of a miRNA and one of its target transcripts during differentiation in embryonic stem cells, and ( iii ) single nucleotide variant detection in primary lobular breast cancer cells. The core functionality established here provides the foundation from which a variety of on-chip single-cell transcription analyses will be developed.
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Bartel (2004) · doi:10.1016/s0092-8674(04)00045-5 · Cited by 34,714
A Mammalian microRNA Expression Atlas Based on Small RNA Library Sequencing
Landgraf, P., Rusu, M., Sheridan, R., Sewer, A., Iovino, N., Aravin, A., Pfeffer, S., Rice, A., Kamphorst, A. O., Landthaler, M., et al. (2007) · Cell · doi:10.1016/j.cell.2007.04.040 · Cited by 3,626
Association of reactive oxygen species levels and radioresistance in cancer stem cells
Diehn, M., Cho, R. W., Lobo, N. A., Kalisky, T., Dorie, M. J., Kulp, A. N., Qian, D., Lam, J. S., Ailles, L. E., Wong, M., et al. (2009) · Nature · doi:10.1038/nature07733 · Cited by 2,555
Imaging individual mRNA molecules using multiple singly labeled probes
Raj, A., van den Bogaard, P., Rifkin, S. A., van Oudenaarden, A., & Tyagi, S. (2008) · Nature Methods · doi:10.1038/nmeth.1253 · Cited by 2,028
Cited by
Single-cell genome sequencing: current state of the science
Gawad, C., Koh, W., & Quake, S. R. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2015.16 · Cited by 1,334
Single-cell sequencing-based technologies will revolutionize whole-organism science
Shapiro, E., Biezuner, T., & Linnarsson, S. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3542 · Cited by 1,177
Functional roles of enhancer RNAs for oestrogen-dependent transcriptional activation
Li, W., Notani, D., Ma, Q., Tanasa, B., Nunez, E., Chen, A. Y., Merkurjev, D., Zhang, J., Ohgi, K., Song, X., et al. (2013) · Nature · doi:10.1038/nature12210 · Cited by 1,049
Single-cell RNA-seq: advances and future challenges
Saliba, A.-E., Westermann, A. J., Gorski, S. A., & Vogel, J. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku555 · Cited by 847
“Until recently the method of choice to study gene expression of single cells was multiplexed qRT-PCR; however, its throughput has remained limited to several hundreds of genes even when using highly parallel microfluidic systems (85–87).”
Zhu, Y., Piehowski, P. D., Zhao, R., Chen, J., Shen, Y., Moore, R. J., Shukla, A. K., Petyuk, V. A., Campbell-Thompson, M., Mathews, C. E., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-03367-w · Cited by 587
Metadata
- Authors
- White, A. K., VanInsberghe, M., Petriv, O. I., Hamidi, M., Sikorski, D., Marra, M. A., Piret, J., Aparicio, S., & Hansen, C. L.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2011-08
- Volume
- 108
- Issue
- 34
- Pages
- 13999-14004
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W1986163307
- Cited by
- 440
- References
- 4
- FWCI
- 24.43
- Type
- journal article
- Language
- en
- Open access
- green
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- White, A. K., VanInsberghe, M., Petriv, O. I., Hamidi, M., Sikorski, D., Marra, M. A., Piret, J., Aparicio, S., & Hansen, C. L. (2011). High-throughput microfluidic single-cell RT-qPCR. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1019446108
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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