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Tuning gene expression to changing environments: from rapid responses to evolutionary adaptation

An Erratum to this article was published on 01 January 2009

Key Points

  • Cells show a remarkable resilience that allows them to thrive under different external conditions and to survive harsh situations. Gene regulation has a central role in cellular adaptation to both short- and long-term environmental changes.

  • Recent studies provide exciting advances in our understanding of cellular strategies to stay in tune with environmental fluctuations, most notably at the transcriptional level of control. Many of these concepts have been developed in microorganisms such as yeast, which finely balance energy-efficient growth with the ability to rapidly respond to sudden external challenges.

  • Global expression of stress- and growth-related genes is finely balanced in yeast, reflecting antagonistic programmes that are controlled by different signalling pathways and transcriptional mechanisms. The balance of cellular growth versus stress is highly regulated at the level of general transcription factors.

  • Yeast have a bipolar transcriptome, in terms of distinct types of core promoters that are used to control growth- or stress-related genes. Stress-related genes generally contain a TATA box — a promoter element that not only promotes variability (that is, noise) in short-term transcriptional responses but also promotes regulatory divergence during evolution.

  • Core promoter-complex switching, which allows the selective activation of one transcriptional programme while silencing others during mammalian differentiation, is reminiscent of the mechanism used by yeast to control growth- versus stress-related genes.

  • Maintaining cellular functionality under variable conditions enhances gene expression variability and is both a constraint and a driving force for evolution. Phenotypic heterogeneity caused by gene expression variability increases survival in fluctuating environments.

  • In addition to hard-wired regulatory responses, gene expression networks show a remarkable plasticity to adapt to a wide range of unpredictable conditions, including those not encountered during evolutionary history.

Abstract

Organisms are constantly exposed to a wide range of environmental changes, including both short-term changes during their lifetime and longer-term changes across generations. Stress-related gene expression programmes, characterized by distinct transcriptional mechanisms and high levels of noise in their expression patterns, need to be balanced with growth-related gene expression programmes. A range of recent studies give fascinating insight into cellular strategies for keeping gene expression in tune with physiological needs dictated by the environment, promoting adaptation to both short- and long-term environmental changes. Not only do organisms show great resilience to external challenges, but emerging data suggest that they also exploit these challenges to fuel phenotypic variation and evolutionary innovation.

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Figure 1: Balancing the expression of growth- and stress-related genes.
Figure 2: Stress- and growth-related genes show distinct regulatory features.
Figure 3: Synthetic regulatory circuits to study responses to unknown challenges.

References

  1. Bahn, Y. S. et al. Sensing the environment: lessons from fungi. Nature Rev. Microbiol. 5, 57–69 (2007).

    CAS  Article  Google Scholar 

  2. De Virgilio, C. & Loewith, R. Cell growth control: little eukaryotes make big contributions. Oncogene 25, 6392–6415 (2006).

    CAS  PubMed  Article  Google Scholar 

  3. Roux, P. P. & Blenis, J. ERK and p38 MAPK-activated protein kinases: a family of protein kinases with diverse biological functions. Microbiol. Mol. Biol. Rev. 68, 320–344 (2004).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  4. Wullschleger, S., Loewith, R. & Hall, M. N. TOR signaling in growth and metabolism. Cell 124, 471–484 (2006).

    CAS  PubMed  Article  Google Scholar 

  5. Causton, H. C. et al. Remodeling of yeast genome expression in response to environmental changes. Mol. Biol. Cell 12, 323–337 (2001).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  6. Chen, D. et al. Global transcriptional responses of fission yeast to environmental stress. Mol. Biol. Cell 14, 214–229 (2003).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  7. Gasch, A. P. et al. Genomic expression programs in the response of yeast cells to environmental changes. Mol. Biol. Cell 11, 4241–4257 (2000). This pioneering paper presents a thorough global analysis of gene expression programmes in multiple stress conditions, and defines a core stress response in S. cerevisiae.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  8. Enjalbert, B. et al. Role of the Hog1 stress-activated protein kinase in the global transcriptional response to stress in the fungal pathogen Candida albicans. Mol. Biol. Cell 17, 1018–1032 (2006).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  9. Ma, S. & Bohnert, H. J. Integration of Arabidopsis thaliana stress-related transcript profiles, promoter structures, and cell-specific expression. Genome Biol. 8, R49 (2007).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  10. Girardot, F., Monnier, V. & Tricoire, H. Genome wide analysis of common and specific stress responses in adult Drosophila melanogaster. BMC Genomics 5, 74 (2004).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  11. Sorensen, J. G., Nielsen, M. M. & Loeschcke, V. Gene expression profile analysis of Drosophila melanogaster selected for resistance to environmental stressors. J. Evol. Biol. 20, 1624–1636 (2007).

    CAS  PubMed  Article  Google Scholar 

  12. Murray, J. I. et al. Diverse and specific gene expression responses to stresses in cultured human cells. Mol. Biol. Cell 15, 2361–2374 (2004).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  13. Chen, D. et al. Multiple pathways differentially regulate global oxidative stress responses in fission yeast. Mol. Biol. Cell 19, 308–317 (2008).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  14. Hughes, T. R. et al. Functional discovery via a compendium of expression profiles. Cell 102, 109–126 (2000).

    CAS  PubMed  Article  Google Scholar 

  15. Kultz, D. Molecular and evolutionary basis of the cellular stress response. Annu. Rev. Physiol. 67, 225–257 (2005).

    PubMed  Article  CAS  Google Scholar 

  16. Aragon, A. D., Quinones, G. A., Thomas, E. V., Roy, S. & Werner-Washburne, M. Release of extraction-resistant mRNA in stationary phase Saccharomyces cerevisiae produces a massive increase in transcript abundance in response to stress. Genome Biol. 7, R9 (2006).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  17. Dinneny, J. R. et al. Cell identity mediates the response of Arabidopsis roots to abiotic stress. Science 320, 942–945 (2008).

    CAS  PubMed  Article  Google Scholar 

  18. Jorgensen, P., Tyers, M. & Warner, J. R. in Cell growth (eds Hall, M. N., Raff, M. & Thomas, G.) 329–370 (Cold Spring Harbor Laboratory Press, New York, 2004).

    Google Scholar 

  19. Warner, J. R. The economics of ribosome biosynthesis in yeast. Trends Biochem. Sci. 24, 437–440 (1999).

    CAS  PubMed  Article  Google Scholar 

  20. Gray, J. V. et al. 'Sleeping beauty': quiescence in Saccharomyces cerevisiae. Microbiol. Mol. Biol. Rev. 68, 187–206 (2004).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  21. Truckses, D. M., Garrenton, L. S. & Thorner, J. Jekyll and Hyde in the microbial world. Science 306, 1509–1511 (2004).

    CAS  Article  PubMed  Google Scholar 

  22. Chu, S. et al. The transcriptional program of sporulation in budding yeast. Science 282, 699–705 (1998).

    CAS  Article  PubMed  Google Scholar 

  23. Elliott, B. & Futcher, B. Stress resistance of yeast cells is largely independent of cell cycle phase. Yeast 9, 33–42 (1993).

    CAS  Article  PubMed  Google Scholar 

  24. Bishop, N. A. & Guarente, L. Genetic links between diet and lifespan: shared mechanisms from yeast to humans. Nature Rev. Genet. 8, 835–844 (2007).

    CAS  Article  PubMed  Google Scholar 

  25. Aguirre-Ghiso, J. A. Models, mechanisms and clinical evidence for cancer dormancy. Nature Rev. Cancer 7, 834–846 (2007).

    CAS  Article  Google Scholar 

  26. Castrillo, J. I. et al. Growth control of the eukaryote cell: a systems biology study in yeast. J. Biol. 6, 4 (2007). This paper, together with references 27 and 28, analyzes the relationships between growth rate and global gene expression in S. cerevisiae.

    PubMed  PubMed Central  Article  Google Scholar 

  27. Brauer, M. J. et al. Coordination of growth rate, cell cycle, stress response, and metabolic activity in yeast. Mol. Biol. Cell 19, 352–367 (2008).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  28. Regenberg, B. et al. Growth-rate regulated genes have profound impact on interpretation of transcriptome profiling in Saccharomyces cerevisiae. Genome Biol. 7, R107 (2006).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  29. Levy, S. et al. Strategy of transcription regulation in the budding yeast. PLoS ONE 2, e250 (2007). This paper asks how transcriptional responses to changing environments are coordinated with the actual physiological needs of the cell. Experimental conditions that decouple actual from environmentally expected growth rates reveal that the transcriptional response is determined by environmental rather than by intrinsic conditions.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  30. Kaeberlein, M. et al. Regulation of yeast replicative life span by TOR and Sch9 in response to nutrients. Science 310, 1193–1196 (2005).

    CAS  PubMed  Article  Google Scholar 

  31. Basehoar, A. D., Zanton, S. J. & Pugh, B. F. Identification and distinct regulation of yeast TATA box-containing genes. Cell 116, 699–709 (2004). This paper identifies the TATA box consensus sequence and provides a list of the TATA-containing genes in S. cerevisiae . The authors show that TATA-containing and TATA-less promoters are differentially regulated and associated with stress-response or housekeeping functions, respectively.

    CAS  PubMed  Article  Google Scholar 

  32. Walther, D., Brunnemann, R. & Selbig, J. The regulatory code for transcriptional response diversity and its relation to genome structural properties in A. thaliana. PLoS Genet. 3, e11 (2007).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  33. Yang, C., Bolotin, E., Jiang, T., Sladek, F. M. & Martinez, E. Prevalence of the initiator over the TATA box in human and yeast genes and identification of DNA motifs enriched in human TATA-less core promoters. Gene 389, 52–65 (2007).

    CAS  PubMed  Article  Google Scholar 

  34. Huisinga, K. L. & Pugh, B. F. A genome-wide housekeeping role for TFIID and a highly regulated stress-related role for SAGA in Saccharomyces cerevisiae. Mol. Cell 13, 573–585 (2004).

    CAS  PubMed  Article  Google Scholar 

  35. Zanton, S. J. & Pugh, B. F. Changes in genomewide occupancy of core transcriptional regulators during heat stress. Proc. Natl Acad. Sci. USA 101, 16843–16848 (2004). This paper shows that heat stress causes disassembly of the TFIID pathway at genes that are inhibited by stress, and assembly of the SAGA pathway genes that are induced by stress, and it studies the regulation of these two pathways in response to heat stress.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  36. Zanton, S. J. & Pugh, B. F. Full and partial genome-wide assembly and disassembly of the yeast transcription machinery in response to heat shock. Genes Dev. 20, 2250–2265 (2006).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  37. Deato, M. D. & Tjian, R. Switching of the core transcription machinery during myogenesis. Genes Dev. 21, 2137–2149 (2007). This paper reports that differentiation of myoblasts to myotubes involves the disruption of the canonical TFIID complex and its replacement by a novel TRF3–TAF3 complex. It proposes core promoter-complex switching as an effective process to selectively turn on one transcriptional programme while silencing others.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  38. Bartfai, R. et al. TBP2, a vertebrate-specific member of the TBP family, is required in embryonic development of zebrafish. Curr. Biol. 14, 593–598 (2004).

    CAS  PubMed  Article  Google Scholar 

  39. Jallow, Z., Jacobi, U. G., Weeks, D. L., Dawid, I. B. & Veenstra, G. J. Specialized and redundant roles of TBP and a vertebrate-specific TBP paralog in embryonic gene regulation in Xenopus. Proc. Natl Acad. Sci. USA 101, 13525–13530 (2004).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  40. Hart, D. O., Raha, T., Lawson, N. D. & Green, M. R. Initiation of zebrafish haematopoiesis by the TATA-box-binding protein-related factor Trf3. Nature 450, 1082–1085 (2007).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  41. Saunders, A., Core, L. J. & Lis, J. T. Breaking barriers to transcription elongation. Nature Rev. Mol. Cell Biol. 7, 557–567 (2006).

    CAS  Article  Google Scholar 

  42. Guenther, M. G., Levine, S. S., Boyer, L. A., Jaenisch, R. & Young, R. A. A chromatin landmark and transcription initiation at most promoters in human cells. Cell 130, 77–88 (2007).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  43. Muse, G. W. et al. RNA polymerase is poised for activation across the genome. Nature Genet. 39, 1507–1511 (2007).

    CAS  PubMed  Article  Google Scholar 

  44. Radonjic, M. et al. Genome-wide analyses reveal RNA polymerase II located upstream of genes poised for rapid response upon S. cerevisiae stationary phase exit. Mol. Cell 18, 171–183 (2005).

    CAS  PubMed  Article  Google Scholar 

  45. Zeitlinger, J. et al. RNA polymerase stalling at developmental control genes in the Drosophila melanogaster embryo. Nature Genet. 39, 1512–1516 (2007).

    CAS  PubMed  Article  Google Scholar 

  46. Townsend, J. P., Cavalieri, D. & Hartl, D. L. Population genetic variation in genome-wide gene expression. Mol. Biol. Evol. 20, 955–963 (2003).

    CAS  PubMed  Article  Google Scholar 

  47. Fay, J. C., McCullough, H. L., Sniegowski, P. D. & Eisen, M. B. Population genetic variation in gene expression is associated with phenotypic variation in Saccharomyces cerevisiae. Genome Biol. 5, R26 (2004).

    PubMed  PubMed Central  Article  Google Scholar 

  48. Gerhart, J. & Kirschner, M. The theory of facilitated variation. Proc. Natl Acad. Sci. USA 104 (Suppl 1), 8582–8589 (2007).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  49. Wray, G. A. The evolutionary significance of cis-regulatory mutations. Nature Rev. Genet. 8, 206–216 (2007).

    CAS  PubMed  Article  Google Scholar 

  50. Rockman, M. V. & Kruglyak, L. Genetics of global gene expression. Nature Rev. Genet. 7, 862–872 (2006).

    CAS  PubMed  Article  Google Scholar 

  51. Stranger, B. E. et al. Population genomics of human gene expression. Nature Genet. 39, 1217–1224 (2007).

    CAS  PubMed  Article  Google Scholar 

  52. Borneman, A. R. et al. Divergence of transcription factor binding sites across related yeast species. Science 317, 815–819 (2007).

    CAS  PubMed  Article  Google Scholar 

  53. Odom, D. T. et al. Tissue-specific transcriptional regulation has diverged significantly between human and mouse. Nature Genet. 39, 730–732 (2007).

    CAS  Article  PubMed  Google Scholar 

  54. Tanay, A., Regev, A. & Shamir, R. Conservation and evolvability in regulatory networks: the evolution of ribosomal regulation in yeast. Proc. Natl Acad. Sci. USA 102, 7203–7208 (2005).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  55. Tirosh, I., Weinberger, A., Bezalel, D., Kaganovich, M. & Barkai, N. On the relation between promoter divergence and gene expression evolution. Mol. Syst. Biol. 4, 159 (2008).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  56. Carroll, S. B., Grenier, J. K. & Weatherbee, S. D. From DNA to Diversity (Blackwell Science, Malden, Massachusetts, 2001).

    Google Scholar 

  57. Wagner, A. Robustness and Evolvability in Living Systems (Princeton Univ. Press, Princeton, 2005).

    Google Scholar 

  58. Elena, S. F. & Lenski, R. E. Evolution experiments with microorganisms: the dynamics and genetic bases of adaptation. Nature Rev. Genet. 4, 457–469 (2003).

    CAS  PubMed  Article  Google Scholar 

  59. Cooper, T. F., Rozen, D. E. & Lenski, R. E. Parallel changes in gene expression after 20,000 generations of evolution in Escherichia coli. Proc. Natl Acad. Sci. USA 100, 1072–1077 (2003).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  60. Riehle, M. M., Bennett, A. F., Lenski, R. E. & Long, A. D. Evolutionary changes in heat-inducible gene expression in lines of Escherichia coli adapted to high temperature. Physiol. Genomics 14, 47–58 (2003).

    CAS  PubMed  Article  Google Scholar 

  61. Dekel, E. & Alon, U. Optimality and evolutionary tuning of the expression level of a protein. Nature 436, 588–592 (2005).

    CAS  Article  PubMed  Google Scholar 

  62. Ferea, T. L., Botstein, D., Brown, P. O. & Rosenzweig, R. F. Systematic changes in gene expression patterns following adaptive evolution in yeast. Proc. Natl Acad. Sci. USA 96, 9721–9726 (1999).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  63. Barkai, N. & Shilo, B. Z. Variability and robustness in biomolecular systems. Mol. Cell 28, 755–760 (2007).

    CAS  PubMed  Article  Google Scholar 

  64. Lenski, R. E., Barrick, J. E. & Ofria, C. Balancing robustness and evolvability. PLoS Biol. 4, e428 (2006).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  65. Newman, J. R. et al. Single-cell proteomic analysis of S. cerevisiae reveals the architecture of biological noise. Nature 441, 840–846 (2006).

    CAS  Article  PubMed  Google Scholar 

  66. Blake, W. J. et al. Phenotypic consequences of promoter-mediated transcriptional noise. Mol. Cell 24, 853–865 (2006). This paper models and experimentally verifies the effects of TATA sequences on transcriptional 'bursts' and accompanying noise, which provide a benefit for the response to acute environmental stress.

    CAS  PubMed  Article  Google Scholar 

  67. Raser, J. M. & O'Shea, E. K. Control of stochasticity in eukaryotic gene expression. Science 304, 1811–1814 (2004).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  68. Wapinski, I., Pfeffer, A., Friedman, N. & Regev, A. Natural history and evolutionary principles of gene duplication in fungi. Nature 449, 54–61 (2007).

    CAS  PubMed  Article  Google Scholar 

  69. Ha, M., Li, W. H. & Chen, Z. J. External factors accelerate expression divergence between duplicate genes. Trends Genet. 23, 162–166 (2007).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  70. Balaban, N. Q., Merrin, J., Chait, R., Kowalik, L. & Leibler, S. Bacterial persistence as a phenotypic switch. Science 305, 1622–1625 (2004).

    CAS  PubMed  Article  Google Scholar 

  71. Acar, M., Mettetal, J. T. & van Oudenaarden, A. Stochastic switching as a survival strategy in fluctuating environments. Nature Genet. 40, 471–475 (2008). This study uses an engineered S. cerevisiae strain that stochastically switches between two phenotypes, revealing that survival is increased if the inter-phenotype switching rate is in tune with the frequency of environmental changes.

    CAS  PubMed  Article  Google Scholar 

  72. Tirosh, I., Weinberger, A., Carmi, M. & Barkai, N. A genetic signature of interspecies variations in gene expression. Nature Genet. 38, 830–834 (2006). This comparative genomic study reveals that TATA-containing genes show higher interspecies variability and evolutionary divergence in gene expression across a wide spectrum of eukaryotes.

    CAS  Article  PubMed  Google Scholar 

  73. Landry, C. R., Lemos, B., Rifkin, S. A., Dickinson, W. J. & Hartl, D. L. Genetic properties influencing the evolvability of gene expression. Science 317, 118–121 (2007).

    CAS  PubMed  Article  Google Scholar 

  74. Koonin, E. V. Chance and necessity in cellular response to challenge. Mol. Syst. Biol. 3, 107 (2007).

    PubMed  PubMed Central  Article  Google Scholar 

  75. Giaever, G. et al. Functional profiling of the Saccharomyces cerevisiae genome. Nature 418, 387–391 (2002).

    CAS  Article  PubMed  Google Scholar 

  76. Thorpe, G. W., Fong, C. S., Alic, N., Higgins, V. J. & Dawes, I. W. Cells have distinct mechanisms to maintain protection against different reactive oxygen species: oxidative-stress-response genes. Proc. Natl Acad. Sci. USA 101, 6564–6569 (2004).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  77. Warringer, J., Ericson, E., Fernandez, L., Nerman, O. & Blomberg, A. High-resolution yeast phenomics resolves different physiological features in the saline response. Proc. Natl Acad. Sci. USA 100, 15724–15729 (2003).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  78. Swindell, W. R., Huebner, M. & Weber, A. P. Plastic and adaptive gene expression patterns associated with temperature stress in Arabidopsis thaliana. Heredity 99, 143–150 (2007).

    CAS  PubMed  Article  Google Scholar 

  79. Tanay, A., Steinfeld, I., Kupiec, M. & Shamir, R. Integrative analysis of genome-wide experiments in the context of a large high-throughput data compendium. Mol. Syst. Biol. 1, 2005.0002 (2005).

  80. Stern, S., Dror, T., Stolovicki, E., Brenner, N. & Braun, E. Genome-wide transcriptional plasticity underlies cellular adaptation to novel challenge. Mol. Syst. Biol. 3, 106 (2007). This paper analyzes the global transcriptional reprogramming underlying the adaptation to a novel challenge in S. cerevisiae . The findings suggest that a nonspecific transcriptional response reflecting the natural plasticity of the regulatory network can support cellular adaptation.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  81. Stolovicki, E., Dror, T., Brenner, N. & Braun, E. Synthetic gene recruitment reveals adaptive reprogramming of gene regulation in yeast. Genetics 173, 75–85 (2006).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  82. Fong, S. S., Joyce, A. R. & Palsson, B. O. Parallel adaptive evolution cultures of Escherichia coli lead to convergent growth phenotypes with different gene expression states. Genome Res. 15, 1365–1372 (2005).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  83. Pelosi, L. et al. Parallel changes in global protein profiles during long-term experimental evolution in Escherichia coli. Genetics 173, 1851–1869 (2006).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  84. Kashiwagi, A., Urabe, I., Kaneko, K. & Yomo, T. Adaptive response of a gene network to environmental changes by fitness-induced attractor selection. PLoS ONE 1, e49 (2006). This theoretical study predicts a general mechanism for selecting an adaptive state to different environments in the absence of any specific signalling pathways. The adaptive state shows a higher growth rate and less stochastic gene expression, which makes it inherently more stable than non-adaptive states.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  85. Furusawa, C. & Kaneko, K. A generic mechanism for adaptive growth rate regulation. PLoS Comput. Biol. 4, e3 (2008).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  86. Mata, J., Marguerat, S. & Bähler, J. Post-transcriptional control of gene expression: a genome-wide perspective. Trends Biochem. Sci. 30, 506–514 (2005).

    CAS  PubMed  Article  Google Scholar 

  87. Lackner, D. H. et al. A network of multiple regulatory layers shapes gene expression in fission yeast. Mol. Cell 26, 145–155 (2007).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  88. Ishii, N. et al. Multiple high-throughput analyses monitor the response of E. coli to perturbations. Science 316, 593–597 (2007).

    CAS  PubMed  Article  Google Scholar 

  89. Luscombe, N. M. et al. Genomic analysis of regulatory network dynamics reveals large topological changes. Nature 431, 308–312 (2004).

    CAS  Article  PubMed  Google Scholar 

  90. Bonneau, R. et al. A predictive model for transcriptional control of physiology in a free living cell. Cell 131, 1354–1365 (2007).

    CAS  PubMed  Article  Google Scholar 

  91. Eulalio, A., Behm-Ansmant, I. & Izaurralde, E. P bodies: at the crossroads of post-transcriptional pathways. Nature Rev. Mol. Cell Biol. 8, 9–22 (2007).

    CAS  Article  Google Scholar 

  92. Parker, R. & Sheth, U. P bodies and the control of mRNA translation and degradation. Mol. Cell 25, 635–646 (2007).

    CAS  PubMed  Article  Google Scholar 

  93. Bhattacharyya, S. N., Habermacher, R., Martine, U., Closs, E. I. & Filipowicz, W. Relief of microRNA-mediated translational repression in human cells subjected to stress. Cell 125, 1111–1124 (2006).

    CAS  PubMed  Article  Google Scholar 

  94. Brengues, M., Teixeira, D. & Parker, R. Movement of eukaryotic mRNAs between polysomes and cytoplasmic processing bodies. Science 310, 486–489 (2005).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  95. Anderson, P. & Kedersha, N. RNA granules. J. Cell Biol. 172, 803–808 (2006).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  96. Preiss, T., Baron-Benhamou, J., Ansorge, W. & Hentze, M. W. Homodirectional changes in transcriptome composition and mRNA translation induced by rapamycin and heat shock. Nature Struct. Biol. 10, 1039–1047 (2003).

    CAS  PubMed  Article  Google Scholar 

  97. Holcik, M. & Sonenberg, N. Translational control in stress and apoptosis. Nature Rev. Mol. Cell Biol. 6, 318–327 (2005).

    CAS  Article  Google Scholar 

  98. Mathews, M. B., Sonenberg, N. & Hershey, J. W. B. (eds) Origins and Principles of Translational Control (Cold Spring Harbor Laboratory Press, New York, 2007).

    Google Scholar 

  99. Swain, P. S., Elowitz, M. B. & Siggia, E. D. Intrinsic and extrinsic contributions to stochasticity in gene expression. Proc. Natl Acad. Sci. USA 99, 12795–12800 (2002).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  100. Maheshri, N. & O'Shea, E. K. Living with noisy genes: how cells function reliably with inherent variability in gene expression. Annu. Rev. Biophys. Biomol. Struct. 36, 413–434 (2007).

    CAS  PubMed  Article  Google Scholar 

  101. Dieci, G. & Sentenac, A. Detours and shortcuts to transcription reinitiation. Trends Biochem. Sci. 28, 202–209 (2003).

    CAS  Article  PubMed  Google Scholar 

  102. Choi, J. K. & Kim, Y. J. Epigenetic regulation and the variability of gene expression. Nature Genet. 40, 141–147 (2008).

    CAS  Article  PubMed  Google Scholar 

  103. Tirosh, I. & Barkai, N. Two strategies for gene regulation by promoter nucleosomes. Genome Res. 30 Apr 2008 (doi:10.1101/gr.076059.108).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  104. Goddard, M. R., Godfray, H. C. & Burt, A. Sex increases the efficacy of natural selection in experimental yeast populations. Nature 434, 636–640 (2005).

    CAS  Article  PubMed  Google Scholar 

  105. Wessler, S. R. Turned on by stress. Plant retrotransposons. Curr. Biol. 6, 959–961 (1996).

    CAS  Article  PubMed  Google Scholar 

  106. McClintock, B. The significance of responses of the genome to challenge. Science 226, 792–801 (1984).

    CAS  PubMed  Article  Google Scholar 

  107. Cam, H. P., Noma, K., Ebina, H., Levin, H. L. & Grewal, S. I. Host genome surveillance for retrotransposons by transposon-derived proteins. Nature 451, 431–436 (2008).

    CAS  Article  PubMed  Google Scholar 

  108. Molinier, J., Ries, G., Zipfel, C. & Hohn, B. Transgeneration memory of stress in plants. Nature 442, 1046–1049 (2006).

    CAS  Article  PubMed  Google Scholar 

  109. Rosenberg, S. M. & Hastings, P. J. Microbiology and evolution. Modulating mutation rates in the wild. Science 300, 1382–1383 (2003).

    CAS  Article  PubMed  Google Scholar 

  110. Kishony, R. & Leibler, S. Environmental stresses can alleviate the average deleterious effect of mutations. J. Biol. 2, 14 (2003).

    PubMed  PubMed Central  Article  Google Scholar 

  111. Kaneko, K. Evolution of robustness to noise and mutation in gene expression dynamics. PLoS ONE 2, e434 (2007).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  112. Sangster, T. A., Lindquist, S. & Queitsch, C. Under cover: causes, effects and implications of Hsp90-mediated genetic capacitance. Bioessays 26, 348–362 (2004).

    CAS  PubMed  Article  Google Scholar 

  113. Bell-Pedersen, D. et al. Circadian rhythms from multiple oscillators: lessons from diverse organisms. Nature Rev. Genet. 6, 544–556 (2005).

    CAS  PubMed  Article  Google Scholar 

  114. Wijnen, H. & Young, M. W. Interplay of circadian clocks and metabolic rhythms. Annu. Rev. Genet. 40, 409–448 (2006).

    CAS  PubMed  Article  Google Scholar 

  115. Gallego, M. & Virshup, D. M. Post-translational modifications regulate the ticking of the circadian clock. Nature Rev. Mol. Cell Biol. 8, 139–148 (2007).

    CAS  Article  Google Scholar 

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Acknowledgements

We apologize to colleagues in the field for not citing all relevant papers owing to space constraints. We thank C. Wilkinson, J. Mata, D. Lackner, V. Pancaldi and F. Schubert for comments on the manuscript. Research in our laboratory is supported by Cancer Research UK. L.L.-M. and S.M. are supported by postdoctoral fellowships from FEBS and the Swiss National Science Foundation, respectively.

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Correspondence to Jürg Bähler.

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Glossary

Core stress response

Involves genes with expression levels that are regulated in a stereotypical manner in all (or most) of the environmental stress conditions tested in yeasts. This response is also known as the environmental stress response (ESR), common environmental response (CER) or core environmental stress response (CESR).

Chemostat

A fermenter that is operated in continuous-culture mode and is used in microbiology for growing and harvesting microorganisms at defined growth rates and under tightly controlled conditions.

TFIID

A complex that is composed of TBP and TAFs. Binding of TFIID to DNA is necessary but not sufficient for transcription initiation from most promoters.

SAGA

A large multi-protein complex involved in the regulation of transcription that possesses histone acetyltransferase and TBP-binding activities. The budding-yeast complex includes Gcn5, several proteins of the Spt and Ada families, and several TAFs; analogous complexes in other species have analogous compositions, and usually contain homologues of the yeast proteins.

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López-Maury, L., Marguerat, S. & Bähler, J. Tuning gene expression to changing environments: from rapid responses to evolutionary adaptation. Nat Rev Genet 9, 583–593 (2008). https://doi.org/10.1038/nrg2398

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