The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Single-Molecule Approaches to Stochastic Gene Expression
Open accessAbstract
Both the transcription of mRNAs from genes and their subsequent translation into proteins are inherently stochastic biochemical events, and this randomness can lead to substantial cell-to-cell variability in mRNA and protein numbers in otherwise identical cells. Recently, a number of studies have greatly enhanced our understanding of stochastic processes in gene expression by utilizing new methods capable of counting individual mRNAs and proteins in cells. In this review, we examine the insights that these studies have yielded in the field of stochastic gene expression. In particular, we discuss how these studies have played in understanding the properties of bursts in gene expression. We also compare the array of different methods that have arisen for single mRNA and protein detection, highlighting their relative strengths and weaknesses. In conclusion, we point out further areas where single-molecule techniques applied to gene expression may lead to new discoveries.
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Cites
Stochastic Gene Expression in a Single Cell
Elowitz, M. B., Levine, A. J., Siggia, E. D., & Swain, P. S. (2002) · Science · doi:10.1126/science.1070919 · Cited by 5,441
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
Self-citationVogelstein, B., & Kinzler, K. W. (1999) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.96.16.9236 · Cited by 1,770
Stochastic mRNA Synthesis in Mammalian Cells
Raj, A., Peskin, C. S., Tranchina, D., Vargas, D. Y., & Tyagi, S. (2006) · PLoS Biology · doi:10.1371/journal.pbio.0040309 · Cited by 1,737
Self-citationVisualization of Single RNA Transcripts in Situ
Femino, A. M., Fay, F. S., Fogarty, K., & Singer, R. H. (1998) · Science · doi:10.1126/science.280.5363.585 · Cited by 1,504
Single-cell proteomic analysis of S. cerevisiae reveals the architecture of biological noise
Newman, J. R. S., Ghaemmaghami, S., Ihmels, J., Breslow, D. K., Noble, M., DeRisi, J. L., & Weissman, J. S. (2006) · Nature · doi:10.1038/nature04785 · Cited by 1,483
Intrinsic noise in gene regulatory networks
Thattai, M., & van Oudenaarden, A. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.151588598 · Cited by 1,428
Control of Stochasticity in Eukaryotic Gene Expression
Raser, J. M., & O'Shea, E. K. (2004) · Science · doi:10.1126/science.1098641 · Cited by 1,425
Stochastic protein expression in individual cells at the single molecule level
Cai, L., Friedman, N., & Xie, X. S. (2006) · Nature · doi:10.1038/nature04599 · Cited by 1,145
Probing Gene Expression in Live Cells, One Protein Molecule at a Time
Yu, J., Xiao, J., Ren, X., Lao, K., & Xie, X. S. (2006) · Science · doi:10.1126/science.1119623 · Cited by 918
Cited by
Spatially resolved, highly multiplexed RNA profiling in single cells
Chen, K. H., Boettiger, A. N., Moffitt, J. R., Wang, S., & Zhuang, X. (2015) · Science · doi:10.1126/science.aaa6090 · Cited by 2,969
Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells
Shalek, A. K., Satija, R., Adiconis, X., Gertner, R. S., Gaublomme, J. T., Raychowdhury, R., Schwartz, S., Yosef, N., Malboeuf, C., Lu, D., et al. (2013) · Nature · doi:10.1038/nature12172 · Cited by 1,190
Single-cell RNA-seq reveals dynamic paracrine control of cellular variation
Shalek, A. K., Satija, R., Shuga, J., Trombetta, J. J., Gennert, D., Lu, D., Chen, P., Gertner, R. S., Gaublomme, J. T., Yosef, N., et al. (2014) · Nature · doi:10.1038/nature13437 · Cited by 1,000
Mammalian genes are transcribed with widely different bursting kinetics
Suter, D. M., Molina, N., Gatfield, D., Schneider, K., Schibler, U., & Naef, F. (2011) · Science · doi:10.1126/science.1198817 · Cited by 927
Fluorescence Correlation Spectroscopy: Past, Present, Future
Elson, E. L. (2011) · Biophysical Journal · doi:10.1016/j.bpj.2011.11.012 · Cited by 438
Metadata
- Authors
- Raj, A., & van Oudenaarden, A.
- Venue
- Annual Review of Biophysics
- Publisher
- Annual Reviews
- Published
- 2009-06-01
- Volume
- 38
- Issue
- 1
- Pages
- 255-270
- ISSN
- 1936-122X (ISSN-L)
- 1936-1238
- OpenAlex
- W2098622547
- Cited by
- 335
- References
- 14
- FWCI
- 1.37
- Type
- journal article
- Language
- en
- Open access
- green
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