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Coupling and coordination in gene expression processes: a systems biology view

Key Points

  • Traditionally, the different stages of gene expression were considered to be separate processes that operated independently. Biochemical and genetic studies have instead revealed high levels of coupling between the different stages. In recent years, genome-wide and systems-level analyses have greatly extended our understanding of coupling in gene expression, by both revealing the effect that certain forms of coupling have on a more global scale, and unveiling novel forms of coupling that had not been identified using more traditional techniques.

  • Genomic analyses of the binding of transcription factors and chromatin remodellers with DNA have revealed extensive coordination and coupling between these factors, forming regulatory networks that control how many genes are expressed.

  • Genome-wide analysis of associations between the nuclear pore and nuclear lamina revealed extensive coupling between the transcription level of a given gene and its nuclear localization. In particular, different subcomplexes within the nuclear pore associate with specific types of genetic loci.

  • Genomic analyses of mRNA processing have shown that splicing commitment occurs co-transcriptionally, but that in yeast the splicing completes post-transcriptionally, and that the spliceosome can regulate expression of specific types of mRNAs by increasing or decreasing their splicing efficiencies.

  • Microarray analyses have also shown that the co-transcriptional recruitment of mRNA export factors results in functional specificities, in which different factors transport specific types of mRNAs; the combination of whole-genome screens and array analyses also demonstrated an important role for the exosome in mRNA export.

  • Chromatin immunoprecipitation coupled with microarray (ChIP–chip) analyses in higher eukaryotes provide support for a dynamic messenger ribonucleoprotein (mRNP) model, in which the composition of the mRNP associated with the nascent transcript changes along the length of the transcript.

  • Whole-genome analysis of the associations between proteasomal components and chromatin revealed a widespread role for the proteasome in transcriptional activation and enrichment of binding of the proteasome at ribosomal protein genes. This coupling between the protein synthesis and degradation machineries could allow feedback that globally reduces expression levels when the proteasome is compromised.

  • Network analysis of the genomic associations of many factors involved in gene expression revealed novel connections between the different levels of gene expression. In particular, factors involved in nuclear transport, general transcription factors, RNA-processing factors and nucleosome remodellers were found to exhibit highly similar binding profiles and to have a large number of neighbours, allowing them to exert global influences on many genes at once.

Abstract

Genome-scale analyses have allowed us to progress beyond studying gene expression at the level of individual components of a given process by providing global information about functional connections between genes, mRNAs and their regulatory proteins. Such analyses have greatly increased our understanding of the interplay between different events in gene regulation and have highlighted previously unappreciated functional connections, including coupling between nuclear and cytoplasmic processes. Genome-wide approaches have also revealed extensive coordination within regulatory levels, such as the organization of transcription factors into regulatory motifs. Overall, these studies enhance our understanding of how the many components of the eukaryotic cell function as a system to allow both coordination and versatility in gene expression.

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Figure 1: Feedforward and multi-input network motifs.
Figure 2: Coordination between chromatin remodellers and transcription factors.
Figure 3: Coupling between steps in mRNA processing.
Figure 4: Overview of interconnectivities between eukaryotic gene regulatory processes.

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References

  1. Maniatis, T. & Reed, R. An extensive network of coupling among gene expression machines. Nature 416, 499–506 (2002).

    Article  CAS  PubMed  Google Scholar 

  2. Soller, M. Pre-messenger RNA processing and its regulation: a genomic perspective. Cell. Mol. Life Sci. 63, 796–819 (2006).

    Article  CAS  PubMed  Google Scholar 

  3. Li, B., Carey, M. & Workman, J. The role of chromatin during transcription. Cell 128, 707–719 (2007).

    Article  CAS  PubMed  Google Scholar 

  4. Squazzo, S. et al. Suz12 binds to silenced regions of the genome in a cell-type-specific manner. Genome Res. 16, 890–900 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Mikkelsen, T. et al. Genome-wide maps of chromatin state in pluripotent and lineage-committed cells. Nature 448, 553–560 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Funayama, R. & Ishikawa, F. Cellular senescence and chromatin structure. Chromosoma 116, 431–440 (2007).

    Article  PubMed  Google Scholar 

  7. Polo, S. & Almouzni, G. Histone metabolic pathways and chromatin assembly factors as proliferation markers. Cancer Lett. 220, 1–9 (2005).

    Article  CAS  PubMed  Google Scholar 

  8. Lee, T. & Young, R. Transcription of eukaryotic protein-coding genes. Annu. Rev. Genet. 34, 77–137 (2000).

    Article  CAS  PubMed  Google Scholar 

  9. Narlikar, G., Fan, H. & Kingston, R. Cooperation between complexes that regulate chromatin structure and transcription. Cell 108, 475–487 (2002).

    Article  CAS  PubMed  Google Scholar 

  10. Lee, T. et al. Transcriptional regulatory networks in Saccharomyces cerevisiae. Science 298, 799–804 (2002). Reference 10 uses ChIP–chip analysis of all transcription factors in yeast to provide a view of regulatory mechanisms among, and feedback between, all transcription factors.

    CAS  PubMed  Google Scholar 

  11. Sandmann, T. et al. A core transcriptional network for early mesoderm development in Drosophila melanogaster. Genes Dev. 21, 436–449 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Cao, Y. et al. Global and gene-specific analyses show distinct roles for MYOD and MYOG at a common set of promoters. EMBO J. 25, 502–511 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Carroll, J. et al. Chromosome-wide mapping of estrogen receptor binding reveals long-range regulation requiring the forkhead protein FoxA1. Cell 122, 33–43 (2005).

    Article  CAS  PubMed  Google Scholar 

  14. Scacheri, P. et al. Genome-wide analysis of menin binding provides insights into MEN1 tumorigenesis. PLoS Genet. 2, e51 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Lanctot, C., Cheutin, T., Cremer, M., Cavalli, G. & Cremer, T. Dynamic genome architecture in the nuclear space: regulation of gene expression in three dimensions. Nature Rev. Genet. 8, 104–115 (2007).

    Article  CAS  PubMed  Google Scholar 

  16. Akhtar, A. & Gasser, S. M. The nuclear envelope and transcriptional control. Nature Rev. Genet. 8, 507–517 (2007).

    Article  CAS  PubMed  Google Scholar 

  17. Cabal, G. et al. SAGA interacting factors confine sub-diffusion of transcribed genes to the nuclear envelope. Nature 441, 770–773 (2006).

    Article  CAS  PubMed  Google Scholar 

  18. Taddei, A. et al. Nuclear pore association confers optimal expression levels for an inducible yeast gene. Nature 441, 774–778 (2006).

    Article  CAS  PubMed  Google Scholar 

  19. Dieppois, G., Iglesias, N. & Stutz, F. Cotranscriptional recruitment to the mRNA export receptor Mex67p contributes to nuclear pore anchoring of activated genes. Mol. Cell Biol. 26, 7858–7870 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Brickner, J. & Walter, P. Gene recruitment of the activated INO1 locus to the nuclear membrane. PLoS Biol. 2, e342 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Casolari, J. et al. Genome-wide localization of the nuclear transport machinery couples transcriptional status and nuclear organization. Cell 117, 427–439 (2004). Reference 21 provides the first global view of gene associations with the nuclear pore. Using ChIP–chip analysis it shows that specific subcomplexes within the nuclear pore associate with different types of genes.

    Article  CAS  PubMed  Google Scholar 

  22. Casolari, J., Brown, C., Drubin, D., Rando, O. & Silver, P. Developmentally induced changes in transcriptional program alter spatial organization across chromosomes. Genes Dev. 19, 1188–1198 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Pickersgill, H. et al. Characterization of the Drosophila melanogaster genome at the nuclear lamina. Nature Genet. 38, 1005–1014 (2006).

    Article  CAS  PubMed  Google Scholar 

  24. Mendjan, S. et al. Nuclear pore components are involved in the transcriptional regulation of dosage compensation in Drosophila. Mol. Cell 21, 811–823 (2006).

    Article  CAS  PubMed  Google Scholar 

  25. Alekseyenko, A. A., Larschan, E., Lai, W. R., Park, P. J. & Kuroda, M. I. High-resolution ChIP–chip analysis reveals that the Drosophila MSL complex selectively identifies active genes on the male X chromosome. Genes Dev. 20, 848–857 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Gilfillan, G. D. et al. Chromosome-wide gene-specific targeting of the Drosophila dosage compensation complex. Genes Dev. 20, 858–870 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Legube, G., McWeeney, S. K., Lercher, M. J. & Akhtar, A. X-chromosome-wide profiling of MSL-1 distribution and dosage compensation in Drosophila. Genes Dev. 20, 871–883 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Cohen, B., Mitra, R., Hughes, J. & Church, G. A computational analysis of whole-genome expression data reveals chromosomal domains of gene expression. Nature Genet. 26, 183–186 (2000).

    Article  CAS  PubMed  Google Scholar 

  29. Keene, J. RNA regulons: coordination of post-transcriptional events. Nature Rev. Genet. 8, 533–543 (2007).

    Article  CAS  PubMed  Google Scholar 

  30. Beyer, A. L. & Osheim, Y. N. Splice site selection, rate of splicing, and alternative splicing on nascent transcripts. Genes Dev. 2, 754–765 (1988).

    Article  CAS  PubMed  Google Scholar 

  31. Lacadie, S. & Rosbash, M. Cotranscriptional spliceosome assembly dynamics and the role of U1 snRNA:5′ss base pairing in yeast. Mol. Cell 19, 65–75 (2005).

    Article  CAS  PubMed  Google Scholar 

  32. Gornemann, J., Kotovic, K. M., Hujer, K. & Neugebauer, K. M. Cotranscriptional spliceosome assembly occurs in a stepwise fashion and requires the cap binding complex. Mol. Cell 19, 53–63 (2005).

    Article  CAS  PubMed  Google Scholar 

  33. Moore, M., Schwartzfarb, E., Silver, P. & Yu, M. Differential recruitment of the splicing machinery during transcription predicts genome-wide patterns of mRNA splicing. Mol. Cell 24, 903–915 (2006).

    Article  CAS  PubMed  Google Scholar 

  34. Tardiff, D., Lacadie, S. & Rosbash, M. A genome-wide analysis indicates that yeast pre-mRNA splicing is predominantly posttranscriptional. Mol. Cell 24, 917–929 (2006). References 33 and 34 use ChIP–chip analysis to demonstrate that the majority of splicing in yeast occurs post-transcriptionally, although the initiation factors are recruited during transcription.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Listerman, I., Sapra, A. & Neugebauer, K. Cotranscriptional coupling of splicing factor recruitment and precursor messenger RNA splicing in mammalian cells. Nature Struct. Mol. Biol. 13, 815–822 (2006).

    Article  CAS  Google Scholar 

  36. Tennyson, C., Klamut, H. & Worton, R. The human dystrophin gene requires 16 hours to be transcribed and is cotranscriptionally spliced. Nature Genet. 9, 184–190 (1995).

    Article  CAS  PubMed  Google Scholar 

  37. Pleiss, J. A., Whitworth, G. B., Bergkessel, M. & Guthrie, C. Transcript specificity in yeast pre-mRNA splicing revealed by mutations in core spliceosomal components. PLoS Biol. 5, e90 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Pleiss, J. A., Whitworth, G. B., Bergkessel, M. & Guthrie, C. Rapid, transcript-specific changes in splicing in response to environmental stress. Mol. Cell 27, 928–937 (2007). References 37 and 38 use custom–designed microarrays to analyse the splicing efficiencies of individual mRNAs in response to mutations in core components of the spliceosome and to certain stress conditions. This analysis demonstrates regulation of specific types of genes by the splicing machinery in response to cellular stresses.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Gama-Carvalho, M., Barbosa-Morais, N., Brodsky, A., Silver, P. & Carmo-Fonseca, M. Genome-wide identification of functionally distinct subsets of cellular mRNAs associated with two nucleocytoplasmic-shuttling mammalian splicing factors. Genome Biol. 7, R113 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Ule, J. et al. CLIP identifies Nova-regulated RNA networks in the brain. Science 302, 1212–1215 (2003).

    Article  CAS  PubMed  Google Scholar 

  41. Ule, J. et al. Nova regulates brain-specific splicing to shape the synapse. Nature Genet. 37, 844–852 (2005).

    Article  CAS  PubMed  Google Scholar 

  42. Jensen, K. B. et al. Nova-1 regulates neuron-specific alternative splicing and is essential for neuronal viability. Neuron 25, 359–371 (2000).

    Article  CAS  PubMed  Google Scholar 

  43. Lei, E., Krebber, H. & Silver, P. Messenger RNAs are recruited for nuclear export during transcription. Genes Dev. 15, 1771–1782 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Lei, E. & Silver, P. Intron status and 3′-end formation control cotranscriptional export of mRNA. Genes Dev. 16, 2761–2766 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Kim Guisbert, K., Duncan, K., Li, H. & Guthrie, C. Functional specificity of shuttling hnRNPs revealed by genome-wide analysis of their RNA binding profiles. RNA 11, 383–393 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Hieronymus, H. & Silver, P. Genome-wide analysis of RNA–protein interactions illustrates specificity of the mRNA export machinery. Nature Genet. 33, 155–161 (2003).

    Article  CAS  PubMed  Google Scholar 

  47. Herold, A., Teixeira, L. & Izaurralde, E. Genome-wide analysis of nuclear mRNA export pathways in Drosophila. EMBO J. 22, 2472–2483 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Swinburne, I., Meyer, C., Liu, X., Silver, P. & Brodsky, A. Genomic localization of RNA binding proteins reveals links between pre-mRNA processing and transcription. Genome Res. 16, 912–921 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Buttner, K., Wenig, K. & Hopfner, K. P. The exosome: a macromolecular cage for controlled RNA degradation. Mol. Microbiol. 61, 1372–1379 (2006).

    Article  CAS  PubMed  Google Scholar 

  50. Andrulis, E. et al. The RNA processing exosome is linked to elongating RNA polymerase II in Drosophila. Nature 420, 837–841 (2002).

    Article  CAS  PubMed  Google Scholar 

  51. West, S., Gromak, N., Norbury, C. & Proudfoot, N. Adenylation and exosome-mediated degradation of cotranscriptionally cleaved pre-messenger RNA in human cells. Mol. Cell 21, 437–443 (2006).

    Article  CAS  PubMed  Google Scholar 

  52. Brodsky, A. et al. Genomic mapping of RNA polymerase II reveals sites of co-transcriptional regulation in human cells. Genome Biol. 6, R64 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Howe, K., Kane, C. & Ares, M. Perturbation of transcription elongation influences the fidelity of internal exon inclusion in Saccharomyces cerevisiae. RNA 9, 993–1006 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Gromak, N., West, S. & Proudfoot, N. Pause sites promote transcriptional termination of mammalian RNA polymerase II. Mol. Cell Biol. 26, 3986–3996 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Hieronymus, H., Yu, M. & Silver, P. Genome-wide mRNA surveillance is coupled to mRNA export. Genes Dev. 18, 2652–2662 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Hilleren, P., McCarthy, T., Rosbash, M., Parker, R. & Jensen, T. Quality control of mRNA 3′-end processing is linked to the nuclear exosome. Nature 413, 538–542 (2001).

    Article  CAS  PubMed  Google Scholar 

  57. Galy, V. et al. Nuclear retention of unspliced mRNAs in yeast is mediated by perinuclear Mlp1. Cell 116, 63–73 (2004).

    Article  CAS  PubMed  Google Scholar 

  58. Yu, M. et al. Arginine methyltransferase affects interactions and recruitment of mRNA processing and export factors. Genes Dev. 18, 2024–2035 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Wolffe, A. & Meric, F. Coupling transcription to translation: a novel site for the regulation of eukaryotic gene expression. Int. J. Biochem. Cell Biol. 28, 247–257 (1996).

    Article  CAS  PubMed  Google Scholar 

  60. Belostotsky, D. & Rose, A. Plant gene expression in the age of systems biology: integrating transcriptional and post-transcriptional events. Trends Plant Sci. 10, 347–353 (2005).

    Article  CAS  PubMed  Google Scholar 

  61. Nott, A., Le Hir, H. & Moore, M. Splicing enhances translation in mammalian cells: an additional function of the exon junction complex. Genes Dev. 18, 210–222 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Wiegand, H., Lu, S. & Cullen, B. Exon junction complexes mediate the enhancing effect of splicing on mRNA expression. Proc. Natl Acad. Sci. USA 100, 11327–11332 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Windgassen, M. et al. Yeast shuttling SR proteins Npl3p, Gbp2p, and Hrb1p are part of the translating mRNPs, and Npl3p can function as a translational repressor. Mol. Cell Biol. 24, 10479–10491 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Sanford, J. R., Gray, N. K., Beckmann, K. & Caceres, J. F. A novel role for shuttling SR proteins in mRNA translation. Genes Dev. 18, 755–768 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Lemaire, R. et al. Stability of a PKCI-1-related mRNA is controlled by the splicing factor ASF–SF2: a novel function for SR proteins. Genes Dev. 16, 594–607 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Hachet, O. & Ephrussi, A. Splicing of Oskar RNA in the nucleus is coupled to its cytoplasmic localization. Nature 428, 959–963 (2004).

    Article  CAS  PubMed  Google Scholar 

  67. Oleynikov, Y. & Singer, R. Real-time visualization of ZBP1 association with β-actin mRNA during transcription and localization. Curr. Biol. 13, 199–207 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Colón-Ramos, D. et al. Asymmetric distribution of nuclear pore complexes and the cytoplasmic localization of β2-tubulin mRNA in Chlamydomonas reinhardtii. Dev. Cell 4, 941–952 (2003).

    Article  PubMed  Google Scholar 

  69. Brown, V. et al. Microarray identification of FMRP-associated brain mRNAs and altered mRNA translational profiles in fragile X syndrome. Cell 107, 477–487 (2001).

    Article  CAS  PubMed  Google Scholar 

  70. Takizawa, P., DeRisi, J., Wilhelm, J. & Vale, R. Plasma membrane compartmentalization in yeast by messenger RNA transport and a septin diffusion barrier. Science 290, 341–344 (2000).

    Article  CAS  PubMed  Google Scholar 

  71. Tenenbaum, S., Carson, C., Lager, P. & Keene, J. Identifying mRNA subsets in messenger ribonucleoprotein complexes by using cDNA arrays. Proc. Natl Acad. Sci. USA 97, 14085–10490 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Baumeister, W., Walz, J., Zühl, F. & Seemüller, E. The proteasome: paradigm of a self-compartmentalizing protease. Cell 92, 367–380 (1998).

    Article  CAS  PubMed  Google Scholar 

  73. Glickman, M., Rubin, D., Fried, V. & Finley, D. The regulatory particle of the Saccharomyces cerevisiae proteasome. Mol. Cell Biol. 18, 3149–3162 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Schmidt, M., Hanna, J., Elsasser, S. & Finley, D. Proteasome-associated proteins: regulation of a proteolytic machine. Biol. Chem. 386, 725–737 (2005).

    Article  CAS  PubMed  Google Scholar 

  75. Muratani, M. & Tansey, W. How the ubiquitin-proteasome system controls transcription. Nature Rev. Mol. Cell Biol. 4, 192–201 (2003).

    Article  CAS  Google Scholar 

  76. Sun, L., Johnston, S. & Kodadek, T. Physical association of the APIS complex and general transcription factors. Biochem. Biophys. Res. Commun. 296, 991–999 (2002).

    Article  CAS  PubMed  Google Scholar 

  77. Ferdous, A., Gonzalez, F., Sun, L., Kodadek, T. & Johnston, S. The 19S regulatory particle of the proteasome is required for efficient transcription elongation by RNA polymerase II. Mol. Cell 7, 981–991 (2001).

    Article  CAS  PubMed  Google Scholar 

  78. Gonzalez, F., Delahodde, A., Kodadek, T. & Johnston, S. Recruitment of a 19S proteasome subcomplex to an activated promoter. Science 296, 548–550 (2002).

    Article  CAS  PubMed  Google Scholar 

  79. Sulahian, R., Sikder, D., Johnston, S. & Kodadek, T. The proteasomal ATPase complex is required for stress-induced transcription in yeast. Nucleic Acids Res. 34, 1351–1357 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Gillette, T., Gonzalez, F., Delahodde, A., Johnston, S. & Kodadek, T. Physical and functional association of RNA polymerase II and the proteasome. Proc. Natl Acad. Sci. USA 101, 5904–5909 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Ferdous, A., Kodadek, T. & Johnston, S. A nonproteolytic function of the 19S regulatory subunit of the 26S proteasome is required for efficient activated transcription by human RNA polymerase II. Biochemistry 41, 12798–12805 (2002).

    Article  CAS  PubMed  Google Scholar 

  82. Lipford, J. & Deshaies, R. Diverse roles for ubiquitin-dependent proteolysis in transcriptional activation. Nature Cell Biol. 5, 845–850 (2003).

    Article  CAS  PubMed  Google Scholar 

  83. Morris, M. et al. Cks1-dependent proteasome recruitment and activation of CDC20 transcription in budding yeast. Nature 423, 1009–1013 (2003).

    Article  CAS  PubMed  Google Scholar 

  84. Nalley, K., Johnston, S. & Kodadek, T. Proteolytic turnover of the Gal4 transcription factor is not required for function in vivo. Nature 442, 1054–1057 (2006).

    Article  CAS  PubMed  Google Scholar 

  85. Lipford, J., Smith, G., Chi, Y. & Deshaies, R. A putative stimulatory role for activator turnover in gene expression. Nature 438, 113–116 (2005).

    Article  CAS  PubMed  Google Scholar 

  86. Nawaz, Z. & O'Malley, B. Urban renewal in the nucleus: is protein turnover by proteasomes absolutely required for nuclear receptor-regulated transcription? Mol. Endocrinol. 18, 493–499 (2004).

    Article  CAS  PubMed  Google Scholar 

  87. Reid, G. et al. Cyclic, proteasome-mediated turnover of unliganded and liganded ERα on responsive promoters is an integral feature of estrogen signaling. Mol. Cell 11, 695–707 (2003).

    Article  CAS  PubMed  Google Scholar 

  88. Ferdous, A. et al. The role of the proteasomal ATPases and activator monoubiquitylation in regulating Gal4 binding to promoters. Genes Dev. 21, 112–123 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Auld, K., Brown, C., Casolari, J., Komili, S. & Silver, P. Genomic association of the proteasome demonstrates overlapping gene regulatory activity with transcription factor substrates. Mol. Cell 21, 861–871 (2006).

    Article  CAS  PubMed  Google Scholar 

  90. Sikder, D., Johnston, S. & Kodadek, T. Widespread, but non-identical, association of proteasomal 19 and 20 S. proteins with yeast chromatin. J. Biol. Chem. 281, 27346–27355 (2006). References 89 and 90 use ChIP–chip analysis of different proteasomal subunits to demonstrate a widespread role for the proteasome in gene activation, as well as regulation of ribosomal protein genes by the binding of proteasomal subunits.

    Article  CAS  PubMed  Google Scholar 

  91. Dembla-Rajpal, N., Seipelt, R., Wang, Q. & Rymond, B. Proteasome inhibition alters the transcription of multiple yeast genes. Biochim. Biophys. Acta 1680, 34–45 (2004).

    Article  CAS  PubMed  Google Scholar 

  92. Fatica, A., Oeffinger, M., Tollervey, D. & Bozzoni, I. Cic1p–Nsa3p is required for synthesis and nuclear export of 60S ribosomal subunits. RNA 9, 1431–1436 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Fleming, J. et al. Complementary whole-genome technologies reveal the cellular response to proteasome inhibition by PS-341. Proc. Natl Acad. Sci. USA 99, 1461–1466 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Tsankov, A. et al. Communication between levels of transcriptional control improves robustness and adaptivity. Mol. Syst. Biol. 2, 65 (2006). Reference 94 describes a network analysis of many different ChIP–chip datasets in yeast and identifies novel forms of coupling between different levels of gene regulation.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Drubin, D., Garakani, A. & Silver, P. Motion as a phenotype: the use of live-cell imaging and machine visual screening to characterize transcription-dependent chromosome dynamics. BMC Cell Biol. 7, 19 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Luthra, R. et al. Actively transcribed GAL genes can be physically linked to the nuclear pore by the SAGA chromatin modifying complex. J. Biol. Chem. 282, 3042–3049 (2007).

    Article  CAS  PubMed  Google Scholar 

  97. Lee, D. et al. The proteasome regulatory particle alters the SAGA coactivator to enhance its interactions with transcriptional activators. Cell 123, 423–436 (2005).

    Article  CAS  PubMed  Google Scholar 

  98. Zanetti, M., Chang, I., Gong, F., Galbraith, D. & Bailey-Serres, J. Immunopurification of polyribosomal complexes of Arabidopsis for global analysis of gene expression. Plant Physiol. 138, 624–635 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  99. Arava, Y. et al. Genome-wide analysis of mRNA translation profiles in Saccharomyces cerevisiae. Proc. Natl Acad. Sci. USA 100, 3889–3894 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. MacKay, V. L. et al. Gene expression analyzed by high-resolution state array analysis and quantitative proteomics: response of yeast to mating pheromone. Mol. Cell Proteomics 3, 478–489 (2004).

    Article  CAS  PubMed  Google Scholar 

  101. Dekker, J., Rippe, K., Dekker, M. & Kleckner, N. Capturing chromosome conformation. Science 295, 1306–1311 (2002).

    Article  CAS  PubMed  Google Scholar 

  102. Gheldof, N., Tabuchi, T. M. & Dekker, J. The active FMR1 promoter is associated with a large domain of altered chromatin conformation with embedded local histone modifications. Proc. Natl Acad. Sci. USA 103, 12463–12468 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Service, R. Gene sequencing. The race for the $1000 genome. Science 311, 1544–1546 (2006).

    Article  CAS  PubMed  Google Scholar 

  104. Cawley, S. et al. Unbiased mapping of transcription factor binding sites along human chromosomes 21 and 22 points to widespread regulation of noncoding RNAs. Cell 116, 499–509 (2004).

    Article  CAS  PubMed  Google Scholar 

  105. Tsang, J., Zhu, J. & van Oudenaarden, A. MicroRNA-mediated feedback and feedforward loops are recurrent network motifs in mammals. Mol. Cell 26, 753–767 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  106. Mangus, D., Evans, M. & Jacobson, A. Poly(A)-binding proteins: multifunctional scaffolds for the post-transcriptional control of gene expression. Genome Biol. 4, 223 (2003).

    Article  PubMed  PubMed Central  Google Scholar 

  107. Kaern, M., Elston, T., Blake, W. & Collins, J. Stochasticity in gene expression: from theories to phenotypes. Nature Rev. Genet. 6, 451–464 (2005).

    Article  CAS  PubMed  Google Scholar 

  108. Ule, J., Jensen, K., Mele, A. & Darnell, R. B. CLIP: a method for identifying protein–RNA interaction sites in living cells. Methods 37, 376–386 (2005).

    Article  CAS  PubMed  Google Scholar 

  109. Golding, I., Paulsson, J., Zawilski, S. M. & Cox, E. C. Real-time kinetics of gene activity in individual bacteria. Cell 123, 1025–1036 (2005).

    Article  CAS  PubMed  Google Scholar 

  110. Cai, L., Friedman, N. & Xie, X. S. Stochastic protein expression in individual cells at the single molecule level. Nature 440, 358–362 (2006).

    Article  CAS  PubMed  Google Scholar 

  111. Raj, A., Peskin, C. S., Tranchina, D., Vargas, D. Y. & Tyagi, S. Stochastic mRNA synthesis in mammalian cells. PLoS Biol. 4, e309 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  112. Bar-Even, A. et al. Noise in protein expression scales with natural protein abundance. Nature Genet. 38, 636–643 (2006).

    Article  CAS  PubMed  Google Scholar 

  113. Newman, J. et al. Single-cell proteomic analysis of S. cerevisiae reveals the architecture of biological noise. Nature 441, 840–846 (2006). Reference 113 uses fluorescence-activated cell sorting (FACS) analysis of GFP–tagged proteins to examine cell-to-cell variability in the expression levels of different genes and to determine the extent to which certain mRNA characteristics contribute to noise in gene expression.

    Article  CAS  PubMed  Google Scholar 

  114. Blake, W. J., Mads, K. A., Cantor, C. R. & Collins, J. J. Noise in eukaryotic gene expression. Nature 422, 633–637 (2003).

    Article  CAS  PubMed  Google Scholar 

  115. Becskei, A., Kaufmann, B. B. & van Oudenaarden, A. Contributions of low molecule number and chromosomal positioning to stochastic gene expression. Nature Genet. 37, 937–944 (2005).

    Article  CAS  PubMed  Google Scholar 

  116. Raser, J. M. & O'Shea, E. K. Noise in gene expression: origins, consequences, and control. Science 309, 2010–2013 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Bertone, P. et al. Global identification of human transcribed sequences with genome tiling arrays. Science 306, 2242–2246 (2004).

    Article  CAS  PubMed  Google Scholar 

  118. Cheng, J. et al. Transcriptional maps of 10 human chromosomes at 5-nucleotide resolution. Science 308, 1149–1154 (2005).

    Article  CAS  PubMed  Google Scholar 

  119. Kampa, D. et al. Novel RNAs identified from an in-depth analysis of the transcriptome of human chromosomes 21 and 22. Genome Res. 14, 331–342 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  120. Willingham, A. T. & Gingeras, T. R. TUF love for 'junk' DNA. Cell 125, 1215–1220 (2006).

    Article  CAS  PubMed  Google Scholar 

  121. Carninci, P. et al. The transcriptional landscape of the mammalian genome. Science 309, 1559–1563 (2005).

    Article  CAS  PubMed  Google Scholar 

  122. Steinmetz, E. J. et al. Genome-wide distribution of yeast RNA polymerase II and its control by Sen1 helicase. Mol. Cell 24, 735–746 (2006).

    Article  CAS  PubMed  Google Scholar 

  123. Struhl, K. Transcriptional noise and the fidelity of initiation by RNA polymerase II. Nature Struct. Mol. Biol. 14, 103–105 (2007).

    Article  CAS  Google Scholar 

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Acknowledgements

The authors would like to thank D. Muzzey, M. Moore, I. Swinburne and C. Brown for helpful discussions and critical evaluation of the manuscript, and the support of grants from the US National Institutes of Health.

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Glossary

Histone variants

Histone variants share amino-acid sequence homology and core structural similarity with the canonical histone proteins but are functionally distinct. Some variants are restricted to certain regions of the chromosome, such as the centromere-specific H3-like variant CenpA. Others are used only during specialized processes, such as the histone H2A variant H2A.X, which binds to DNA with double-strand breaks and marks the region undergoing DNA repair.

Nuclear pore

The nuclear pore is a large protein complex that traverses the nuclear envelope, allowing transport between the nucleus and cytoplasm. The proteins that form the nuclear pore are known as nucleoporins.

Dosage compensation complex

The dosage compensation complex is an RNA–protein complex in Drosophila melanogaster that mediates the twofold hypertranscription of genes from the X chromosome in males, resulting in equalized levels of X-chromosome products in both sexes.

Synthetic genetic interaction

A synthetic genetic interaction occurs when the severity of the phenotype caused by the absence of two genes is more or less than the sum of the phenotypes of the individual gene knockouts. Two genes that are non-essential when deleted individually but for which the deletion of both is fatal are termed synthetic lethal.

Mutual information

Mutual information is a measure of dependence between two variables. If one variable is highly predictive of the other, then the mutual information between the two will be high. Importantly, this does not imply that the two variables exhibit the same behaviour, for anti-correlated variables are still co-dependent and thus have high mutual information.

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Komili, S., Silver, P. Coupling and coordination in gene expression processes: a systems biology view. Nat Rev Genet 9, 38–48 (2008). https://doi.org/10.1038/nrg2223

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