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Single-RNA counting reveals alternative modes of gene expression in yeast
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Proper execution of transcriptional programs is a key requirement of gene expression regulation, demanding accurate control of timing and amplitude. How precisely the transcription machinery fulfills this task is not known. Using an in situ hybridization approach that detects single mRNA molecules, we measured mRNA abundance and transcriptional activity within single Saccharomyces cerevisiae cells. We found that expression levels for particular genes are higher than initially reported and can vary substantially among cells. However, variability for most constitutively expressed genes is unexpectedly small. Combining single-transcript measurements with computational modeling indicates that low expression variation is achieved by transcribing genes using single transcription-initiation events that are clearly separated in time, rather than by transcriptional bursts. In contrast, PDR5, a gene regulated by the transcription coactivator complex SAGA, is expressed using transcription bursts, resulting in larger variation. These data directly demonstrate the existence of multiple expression modes used to modulate the transcriptome.
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“In recent years, single-molecule fluorescence microscopy has been used to count mRNA (12-16) or protein (8, 17) molecules in individual cells, especially in bacteria. However, these methods have only been applied to limited number of specific genes.”
From Quantifying E. coli Proteome and Transcriptome with Single-Molecule Sensitivity in Single Cells (2010) · cites this paper as [16]
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“SCM estimates of absolute mRNA levels matched FISH measurements well [53] (average difference of 1.2-fold between estimated and measured levels [Fig 5B], with one outlier estimate overshooting the FISH value by 1.7-fold).”
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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
Spellman, P. T., Sherlock, G. J., Zhang, M. Q., Iyer, V. R., Anders, K. R., Eisen, M. B., Brown, P. O., Botstein, D., & Futcher, B. (1998) · Molecular Biology of the Cell · doi:10.1091/mbc.9.12.3273 · Cited by 4,724
Global analysis of protein expression in yeast
Ghaemmaghami, S., Huh, W.-K., Bower, K., Howson, R. W., Belle, A., Dephoure, N., O'Shea, E. K., & Weissman, J. S. (2003) · Nature · doi:10.1038/nature02046 · Cited by 3,750
The Role of Chromatin during Transcription
Li, B., Carey, M., & Workman, J. L. (2007) · Cell · doi:10.1016/j.cell.2007.01.015 · Cited by 3,503
Precise Nanometer Localization Analysis for Individual Fluorescent Probes
Thompson, R. E., Larson, D. R., & Webb, W. W. (2002) · Biophysical Journal · doi:10.1016/s0006-3495(02)75618-x · Cited by 2,320
Self-citationStochasticity in gene expression: from theories to phenotypes
Kærn, M., Elston, T. C., Blake, W. J., & Collins, J. J. (2005) · Nature Reviews Genetics · doi:10.1038/nrg1615 · Cited by 2,318
Transcriptional regulatory code of a eukaryotic genome
Harbison, C. T., Gordon, D. B., Lee, T. I., Rinaldi, N. J., MacIsaac, K. D., Danford, T., Hannett, N. M., Tagne, J., Reynolds, D. B., Yoo, J. Y., et al. (2004) · Nature · doi:10.1038/nature02800 · Cited by 2,135
The economics of ribosome biosynthesis in yeast
Warner, J. R. (1999) · Trends in Biochemical Sciences · doi:10.1016/s0968-0004(99)01460-7 · Cited by 1,933
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
Dissecting the regulatory circuitry of a eukaryotic genome
Holstege, F. C. P., Jennings, E. G., Wyrick, J. J., Lee, T. I., Hengartner, C. J., Green, M. R., Golub, T. R., Lander, E. S., & Young, R. A. (1998) · Cell · doi:10.1016/s0092-8674(00)81641-4 · Cited by 1,670
Flagged first, then by citations
2 of the 63 references couldn’t be matched to a known paper.
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Quantifying E. coli Proteome and Transcriptome with Single-Molecule Sensitivity in Single Cells
Taniguchi, Y., Choi, P. J., Li, G.-W., Chen, H., Babu, M., Hearn, J., Emili, A., & Xie, X. S. (2010) · Science · doi:10.1126/science.1188308 · Cited by 1,982
Functional roles for noise in genetic circuits
Eldar, A., & Elowitz, M. B. (2010) · Nature · doi:10.1038/nature09326 · Cited by 1,482
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
Using Gene Expression Noise to Understand Gene Regulation
Munsky, B., Neuert, G., & van Oudenaarden, A. (2012) · Science · doi:10.1126/science.1216379 · Cited by 745
Real-Time Observation of Transcription Initiation and Elongation on an Endogenous Yeast Gene
Larson, D. R., Zenklusen, D., Wu, B., Chao, J. A., & Singer, R. H. (2011) · Science · doi:10.1126/science.1202142 · Cited by 680
Self-citationIn the right place at the right time: visualizing and understanding mRNA localization
Buxbaum, A. R., Haimovich, G., & Singer, R. H. (2014) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm3918 · Cited by 610
Self-citationMarguerat, S., Schmidt, A., Codlin, S., Chen, W., Aebersold, R., & Bähler, J. (2012) · Cell · doi:10.1016/j.cell.2012.09.019 · Cited by 571
From single-cell to cell-pool transcriptomes: Stochasticity in gene expression and RNA splicing
Marinov, G. K., Williams, B. A., McCue, K., Schroth, G. P., Gertz, J., Myers, R. M., & Wold, B. J. (2014) · Genome Research · doi:10.1101/gr.161034.113 · Cited by 468
Genetic Determinants and Cellular Constraints in Noisy Gene Expression
Sánchez, Á., & Golding, I. (2013) · Science · doi:10.1126/science.1242975 · Cited by 460
Role of a ribosome-associated E3 ubiquitin ligase in protein quality control
Bengtson, M. H., & Joazeiro, C. A. P. (2010) · Nature · doi:10.1038/nature09371 · Cited by 483
Rate-Limiting Steps in Yeast Protein Translation
Shah, P., Ding, Y., Niemczyk, M., Kudla, G., & Plotkin, J. B. (2013) · Cell · doi:10.1016/j.cell.2013.05.049 · Cited by 463
Single-cell systems biology by super-resolution imaging and combinatorial labeling
Lubeck, E., & Cai, L. (2012) · Nature Methods · doi:10.1038/nmeth.2069 · Cited by 462
Hager, G. L., McNally, J. G., & Misteli, T. (2009) · Molecular Cell · doi:10.1016/j.molcel.2009.09.005 · Cited by 469
Padovan-Merhar, O. M., Nair, G. P., Biaesch, A. G., Mayer, A., Scarfone, S., Foley, S. W., Wu, A. R., Churchman, L. S., Singh, A., & Raj, A. (2015) · Molecular Cell · doi:10.1016/j.molcel.2015.03.005 · Cited by 435
Deng, R., Tang, L., Tian, Q., Wang, Y., Lin, L., & Li, J. (2014) · Angewandte Chemie International Edition · doi:10.1002/anie.201309388 · Cited by 450
General properties of transcriptional time series in Escherichia coli
So, L., Ghosh, A., Zong, C. C., Sepúlveda, L. A., Segev, R., & Golding, I. (2011) · Nature Genetics · doi:10.1038/ng.821 · Cited by 393
Control of Transcript Variability in Single Mammalian Cells
Battich, N., Stoeger, T., & Pelkmans, L. (2015) · Cell · doi:10.1016/j.cell.2015.11.018 · Cited by 324
Non-AUG translation: a new start for protein synthesis in eukaryotesPreprint
Kearse, M. G., & Wilusz, J. E. (2017) · Genes & Development · doi:10.1101/gad.305250.117 · Cited by 398
Non-genetic heterogeneity from stochastic partitioning at cell division
Huh, D., & Paulsson, J. (2010) · Nature Genetics · doi:10.1038/ng.729 · Cited by 373
FISH-quant: automatic counting of transcripts in 3D FISH images
Mueller, F., Senecal, A., Tantale, K., Marie-Nelly, H., Ly, N. Y., Collin, O., Basyuk, E. I., Bertrand, É., Darzacq, X., & Zimmer, C. (2013) · Nature Methods · doi:10.1038/nmeth.2406 · Cited by 369
Gene Expression Is Circular: Factors for mRNA Degradation Also Foster mRNA Synthesis
Haimovich, G., Medina, D. A., Causse, S., Garber, M. G., Millán-Zambrano, G., Barkai, O., Chávez, S., Pérez-Ortín, J. E., Darzacq, X., & Choder, M. (2013) · Cell · doi:10.1016/j.cell.2013.05.012 · Cited by 356
Enhancer Regulation of Transcriptional Bursting Parameters Revealed by Forced Chromatin Looping
Bartman, C. R., Hsu, S. C., Hsiung, C. C.-S., Raj, A., & Blobel, G. A. (2016) · Molecular Cell · doi:10.1016/j.molcel.2016.03.007 · Cited by 345
Single-molecule transcript counting of stem-cell markers in the mouse intestine
Itzkovitz, S., Lyubimova, A., Blat, I. C., Maynard, M. A., van Es, J. H., Lees, J. A., Jacks, T., Clevers, H. C., & van Oudenaarden, A. (2011) · Nature Cell Biology · doi:10.1038/ncb2384 · Cited by 352
Izeddin, I., Récamier, V., Bosanac, L., Cissé, I. I., Boudarène, L., Dugast‐Darzacq, C., Proux, F., Bénichou, O., Voituriez, R., Bensaude, O., et al. (2014) · eLife · doi:10.7554/elife.02230 · Cited by 338
HIV-1 uncoats in the nucleus near sites of integration
Burdick, R. C., Li, C., Munshi, M., Rawson, J. M. O., Nagashima, K., Hu, W.-S., & Pathak, V. K. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1920631117 · Cited by 313
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Tutucci, E., Vera, M., Biswas, J., Garcia, J. F., Parker, R., & Singer, R. H. (2017) · Nature Methods · doi:10.1038/nmeth.4502 · Cited by 332
Self-citationTranscription termination and the control of the transcriptome: why, where and how to stop
Porrúa, O., & Libri, D. (2015) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm3943 · Cited by 349
Eukaryotic transcriptional dynamics: from single molecules to cell populations
Coulon, A., Chow, C. C., Singer, R. H., & Larson, D. R. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3484 · Cited by 309
Self-citationVisualization of Dynamics of Single Endogenous mRNA Labeled in Live Mouse
Park, H. Y., Lim, H., Yoon, Y. J., Follenzi, A., Nwokafor, C., Lopez-Jones, M., Meng, X., & Singer, R. H. (2014) · Science · doi:10.1126/science.1239200 · Cited by 308
Self-citationNucleosome positioning: How is it established, and why does it matter?
Radman‐Livaja, M., & Rando, O. J. (2009) · Developmental Biology · doi:10.1016/j.ydbio.2009.06.012 · Cited by 304
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Lee, M. V., Topper, S. E., Hubler, S. L., Hose, J., Wenger, C. D., Coon, J. J., & Gasch, A. P. (2011) · Molecular Systems Biology · doi:10.1038/msb.2011.48 · Cited by 290
Single-molecule analysis of gene expression using two-color RNA labeling in live yeast
Hocine, S., Raymond, P., Zenklusen, D., Chao, J. A., & Singer, R. H. (2013) · Nature Methods · doi:10.1038/nmeth.2305 · Cited by 297
Self-citationSun, M., Schwalb, B., Schulz, D., Pirkl, N., Etzold, S., Larivière, L., Maier, K. C., Seizl, M., Tresch, A., & Cramer, P. (2012) · Genome Research · doi:10.1101/gr.130161.111 · Cited by 305
RNA Polymerase II cluster dynamics predict mRNA output in living cells
Cho, W., Jayanth, N., English, B. P., Inoue, T., Andrews, J. O., Conway, W., Grimm, J. B., Spille, J.-H., Lavis, L. D., Lionnet, T., et al. (2016) · eLife · doi:10.7554/elife.13617 · Cited by 291
Rationally Engineered Nucleic Acid Architectures for Biosensing Applications
Xiao, M., Lai, W., Man, T., Chang, B., Li, L., Chandrasekaran, A. R., & Pei, H. (2019) · Chemical Reviews · doi:10.1021/acs.chemrev.9b00121 · Cited by 291
Classic and contemporary approaches to modeling biochemical reactionsPreprint
Chen, W. W., Niepel, M., & Sorger, P. K. (2010) · Genes & Development · doi:10.1101/gad.1945410 · Cited by 287
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Buxbaum, A. R., Wu, B., & Singer, R. H. (2014) · Science · doi:10.1126/science.1242939 · Cited by 280
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Singer, Z. S., Yong, J., Tischler, J., Hackett, J. A., Altınok, A., Surani, M. A., Cai, L., & Elowitz, M. B. (2014) · Molecular Cell · doi:10.1016/j.molcel.2014.06.029 · Cited by 275
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Senecal, A., Munsky, B. E., Proux, F., Ly, N. Y., Brayé, F., Zimmer, C., Mueller, F., & Darzacq, X. (2014) · Cell Reports · doi:10.1016/j.celrep.2014.05.053 · Cited by 268
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Little, S. C., Tikhonov, M., & Gregor, T. (2013) · Cell · doi:10.1016/j.cell.2013.07.025 · Cited by 271
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Trcek, T., Larson, D. R., Moldón, A., Query, C. C., & Singer, R. H. (2011) · Cell · doi:10.1016/j.cell.2011.11.051 · Cited by 261
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Halpern, K. B., Tanami, S., Landen, S., Chapal, M., Szlak, L., Hutzler, A., Nizhberg, A., & Itzkovitz, S. (2015) · Molecular Cell · doi:10.1016/j.molcel.2015.01.027 · Cited by 251
Skinner, S. O., Sepúlveda, L. A., Xu, H., & Golding, I. (2013) · Nature Protocols · doi:10.1038/nprot.2013.066 · Cited by 236
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Papantonis, A., & Cook, P. R. (2013) · Chemical Reviews · doi:10.1021/cr300513p · Cited by 255
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Oesterreich, F. C., Preibisch, S., & Neugebauer, K. M. (2010) · Molecular Cell · doi:10.1016/j.molcel.2010.11.004 · Cited by 244
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Riba, A., Di Nanni, N., Mittal, N., Arhné, E., Schmidt, A., & Zavolan, M. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1817299116 · Cited by 209
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Coulon, A., Ferguson, M., de Turris, V., Palangat, M., Chow, C. C., & Larson, D. R. (2014) · eLife · doi:10.7554/elife.03939 · Cited by 229
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Itzkovitz, S., & van Oudenaarden, A. (2011) · Nature Methods · doi:10.1038/nmeth.1573 · Cited by 205
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Tuller, T., Veksler‐Lublinsky, I., Gazit, N., Kupiec, M., Ruppin, E., & Ziv-Ukelson, M. (2011) · Genome biology · doi:10.1186/gb-2011-12-11-r110 · Cited by 194
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Self-citationDigital Quantification of Proteins and mRNA in Single Mammalian Cells
Albayrak, C., Jordi, C. A., Zechner, C., Lin, J., Bichsel, C. A., Khammash, M., & Tay, S. (2016) · Molecular Cell · doi:10.1016/j.molcel.2016.02.030 · Cited by 176
Genome-Scale Analysis of Translation Elongation with a Ribosome Flow Model
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Symmons, O., & Raj, A. (2016) · Molecular Cell · doi:10.1016/j.molcel.2016.05.023 · Cited by 186
Gorin, G., Fang, M., Chari, T., & Pachter, L. (2022) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1010492 · Cited by 186
Transcription Dynamics in Living Cells
Lenstra, T. L., Rodriguez, J., Chen, H., & Larson, D. R. (2016) · Annual Review of Biophysics · doi:10.1146/annurev-biophys-062215-010838 · Cited by 186
Self-citationNilsson, D., Gunasekera, K., Mani, J., Østerås, M., Farinelli, L., Bærlocher, L., Roditi, I. J., & Ochsenreiter, T. (2010) · PLoS Pathogens · doi:10.1371/journal.ppat.1001037 · Cited by 183
Pichon, X., Lagha, M., Mueller, F., & Bertrand, É. (2018) · Molecular Cell · doi:10.1016/j.molcel.2018.07.022 · Cited by 190
Csárdi, G., Franks, A., Choi, D. S., Airoldi, E. M., & Drummond, D. A. (2015) · PLOS Genetics · doi:10.1371/journal.pgen.1005206 · Cited by 181
Detection of Individual Endogenous RNA Transcripts In Situ Using Multiple Singly Labeled Probes
Raj, A., & Tyagi, S. (2010) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/s0076-6879(10)72004-8 · Cited by 175
A single molecule view of gene expression
Larson, D. R., Singer, R. H., & Zenklusen, D. (2009) · Trends in Cell Biology · doi:10.1016/j.tcb.2009.08.008 · Cited by 177
Self-citationHe, X., Samee, M. A. H., Blatti, C. A., & Sinha, S. (2010) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000935 · Cited by 171
Nicholson, D. J. (2019) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2019.06.002 · Cited by 189
Gasch, A. P., Yu, F. B., Hose, J., Escalante, L. E., Place, M., Bacher, R. L., Kanbar, J. N., Ciobanu, D., Sandor, L., Grigoriev, I. V., et al. (2017) · PLoS Biology · doi:10.1371/journal.pbio.2004050 · Cited by 162
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Corrigan, A. M., Tunnacliffe, E., Cannon, D., & Chubb, J. R. (2016) · eLife · doi:10.7554/elife.13051 · Cited by 166
A universal code for RNA recognition by PUF proteins
Filipovska, A., Razif, M. F. M., Nygård, K. K. A., & Rackham, O. (2011) · Nature Chemical Biology · doi:10.1038/nchembio.577 · Cited by 164
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Maheshri, N., Zopf, C. J., Quinn, K., & Zeidman, J. (2013) · DSpace@MIT (Massachusetts Institute of Technology) · Cited by 164
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Pelechano, V., Chávez, S., & Pérez-Ortín, J. E. (2010) · PLoS ONE · doi:10.1371/journal.pone.0015442 · Cited by 162
Noise–mean relationship in mutated promotersPreprint
Hornung, G., Bar‐Ziv, R., Rosin, D., Tokuriki, N., Tawfik, D. S., Oren, M., & Barkai, N. (2012) · Genome Research · doi:10.1101/gr.139378.112 · Cited by 156
Thompson, M. A., Casolari, J. M., Badieirostami, M., Brown, P. O., & Moerner, W. E. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1012868107 · Cited by 160
Creamer, T. J., Darby, M. M., Jamonnak, N., Schaughency, P., Hao, H., Wheelan, S. J., & Corden, J. L. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002329 · Cited by 173
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Cao, Z., & Grima, R. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1910888117 · Cited by 152
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Larson, D. R., Fritzsch, C., Sun, L. D., Meng, X., Lawrence, D. S., & Singer, R. H. (2013) · eLife · doi:10.7554/elife.00750 · Cited by 147
Self-citationA Novel Role of Vimentin Filaments: Binding and Stabilization of Collagen mRNAs
Challa, A. A., & Stefanovic, B. (2011) · Molecular and Cellular Biology · doi:10.1128/mcb.05263-11 · Cited by 155
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Chen, K., Johnston, J. J., Shao, W., Meier, S. R., Staber, C. J., & Zeitlinger, J. (2013) · eLife · doi:10.7554/elife.00861 · Cited by 158
Schaefer, M., Kapoor, U., & Jantsch, M. F. (2017) · Open Biology · doi:10.1098/rsob.170077 · Cited by 159
Rullan, M., Benzinger, D., Schmidt, G. W., Gupta, A., Milias‐Argeitis, A., & Khammash, M. (2018) · Molecular Cell · doi:10.1016/j.molcel.2018.04.012 · Cited by 147
Single-cell analysis of transcription kinetics across the cell cycle
Skinner, S. O., Xu, H., Nagarkar-Jaiswal, S., Freire, P. R., Zwaka, T. P., & Golding, I. (2016) · eLife · doi:10.7554/elife.12175 · Cited by 151
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Kar, S., Baumann, W. T., Paul, M. R., & Tyson, J. J. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0810034106 · Cited by 148
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Sánchez, Á., García, H. G., Jones, D., Phillips, R., & Kondev, J. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1001100 · Cited by 144
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Adivarahan, S., Livingston, N. M., Nicholson, B. L., Rahman, S., Wu, B., Rissland, O. S., & Zenklusen, D. (2018) · Molecular Cell · doi:10.1016/j.molcel.2018.10.010 · Cited by 149
Self-citationG-quadruplex structures trigger RNA phase separation
Zhang, Y., Yang, M., Duncan, S. H., Yang, X., Abdelhamid, M. A. S., Huang, L., Zhang, H., Benfey, P. N., Waller, Z. A. E., & Ding, Y. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz978 · Cited by 144
Stimulus-induced modulation of transcriptional bursting in a single mammalian gene
Molina, N., Suter, D. M., Cannavò, R., Zoller, B., Gotić, I., & Naef, F. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1312310110 · Cited by 143
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Metadata
- Authors
- Zenklusen, D., Larson, D. R., & Singer, R. H.
- Affiliations
- Albert Einstein College of Medicine (US)
- Corresponding author
- Singer, Robert H
- Venue
- Nature Structural & Molecular Biology
- Published
- 2008-11-16
- Volume
- 15
- Issue
- 12
- Pages
- 1263-1271
- ISSN
- 1545-9985 (ISSN-L)
- 1545-9993
- PMC
- PMC3154325
- OpenAlex
- W1992927069
- Cited by
- 684
- References
- 63
- Citations by year
- 2026: 16 · 2025: 25 · 2024: 45 · 2023: 35 · 2022: 22 · 2021: 38 · 2020: 37 · 2019: 40 · 2018: 44 · 2017: 36 · 2016: 52 · 2015: 47 · 2014: 38 · 2013: 64 · 2012: 40
- FWCI
- 14.41
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Structural & Molecular Biology (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of General Medical Sciences (R01GM057071)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Keywords
- transcriptional bursting, gene expression variation, Saccharomyces cerevisiae, PDR5, nascent RNA, mRNA levels, housekeeping genes, transcriptional regulation
- MeSH terms
- RNA, Fungal, RNA, Messenger, Saccharomyces cerevisiae, Transcription, Genetic, Trans-Activators, Gene Expression, In Situ Hybridization, Fluorescence, Saccharomyces cerevisiae Proteins
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