Cited by 304Gene Regulatory Network AnalysisGenomics and Chromatin DynamicsFungal and yeast genetics research

Analysis of combinatorial cis-regulation in synthetic and genomic promoters

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Gertz, Jason, Siggia, Eric D., Cohen, Barak A.·2009·Nature

Abstract

Transcription factor binding sites are being discovered at a rapid pace. It is now necessary to turn attention towards understanding how these sites work in combination to influence gene expression. Quantitative models that accurately predict gene expression from promoter sequence will be a crucial part of solving this problem. Here we present such a model, based on the analysis of synthetic promoter libraries in yeast (Saccharomyces cerevisiae). Thermodynamic models based only on the equilibrium binding of transcription factors to DNA and to each other captured a large fraction of the variation in expression in every library. Thermodynamic analysis of these libraries uncovered several phenomena in our system, including cooperativity and the effects of weak binding sites. When applied to the S. cerevisiae genome, a model of repression by Mig1 (which was trained on synthetic promoters) predicts a number of Mig1-regulated genes that lack significant Mig1-binding sites in their promoters. The success of the thermodynamic approach suggests that the information encoded by combinations of cis-regulatory sites is interpreted primarily through simple protein-DNA and protein-protein interactions, with complicated biochemical reactions-such as nucleosome modifications-being downstream events. Quantitative analyses of synthetic promoter libraries will be an important tool in unravelling the rules underlying combinatorial cis-regulation.

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  • Measuring enhancer activity of synthetic, systematically designed DNA sequences with TFBSs placed in an otherwise inert sequence context is an alternative way to study the cis-regulatory code.

    “An alternative way to study the cis-regulatory code is to measure the enhancer activity of synthetic, systematically designed DNA sequences, where TF binding sites (TFBSs) are placed in an otherwise inert sequence context.27,30,31,32,33,34”

    From Design principles of cell-state-specific enhancers in hematopoiesis (2025) · cites this paper as [31]

    The paper describes synthetic libraries of transcription-factor binding sites placed upstream of a basal promoter, with activity measured by YFP expression (Abstract; page unavailable). It studies promoter activity rather than explicitly measuring enhancer activity. Moreover, a spacer designed to lack known regulatory elements appeared to recruit RNA polymerase, so the copy does not establish that the surrounding sequence was inert. (LLM, conf=0.88)

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  1. [1]Harbison CT Transcriptional regulatory code of a eukaryotic genome Nature 431 99 104 2004 15343339 PMC3006441
  2. [2]Hu Z Killion PJ Iyer VR Genetic reconstruction of a functional transcriptional regulatory network Nature genetics 39 683 687 2007 17417638
  3. [3]Beer MA Tavazoie S Predicting gene expression from sequence Cell 117 185 198 2004 15084257
  4. [4]Bussemaker HJ Li H Siggia ED Regulatory element detection using correlation with expression Nature genetics 27 167 171 2001 11175784
  5. [5]Das D Banerjee N Zhang MQ Interacting models of cooperative gene regulation Proceedings of the National Academy of Sciences of the United States of America 101 16234 16239 2004 15534222 PMC528978
  6. [6]Segal E Raveh-Sadka T Schroeder M Unnerstall U Gaul U Predicting expression patterns from regulatory sequence in Drosophila segmentation Nature 451 535 540 2008 18172436
  7. [7]Zinzen RP Senger K Levine M Papatsenko D Computational models for neurogenic gene expression in the Drosophila embryo Curr Biol 16 1358 1365 2006 16750631
  8. [8]Murphy KF Balazsi G Collins JJ Combinatorial promoter design for engineering noisy gene expression Proceedings of the National Academy of Sciences of the United States of America 104 12726 12731 2007 17652177 PMC1931564
  9. [9]Ligr M Siddharthan R Cross FR Siggia ED Gene expression from random libraries of yeast promoters Genetics 172 2113 2122 2006 16415362 PMC1456374
  10. [10]Cox RS 3rd Surette MG Elowitz MB Programming gene expression with combinatorial promoters Molecular systems biology 3 145 2007 18004278 PMC2132448
  11. [11]Shea MA Ackers GK The OR control system of bacteriophage lambda. A physical-chemical model for gene regulation Journal of molecular biology 181 211 230 1985 3157005
  12. [12]Buchler NE Gerland U Hwa T On schemes of combinatorial transcription logic Proceedings of the National Academy of Sciences of the United States of America 100 5136 5141 2003 12702751 PMC404558
  13. [13]Ptashne M Gann A Genes & signals Cold Spring Harbor Laboratory Press Cold Spring Harbor, N.Y. 2002
  14. [14]Tanay A Extensive low-affinity transcriptional interactions in the yeast genome Genome Res 16 962 972 2006 16809671 PMC1524868
  15. [15]Lutfiyya LL Characterization of three related glucose repressors and genes they regulate in Saccharomyces cerevisiae Genetics 150 1377 1391 1998 9832517 PMC1460414
  16. [16]Hertz GZ Stormo GD Identifying DNA and protein patterns with statistically significant alignments of multiple sequences Bioinformatics (Oxford, England) 15 563 577 1999 10487864
  17. [17]Matys V TRANSFAC: transcriptional regulation, from patterns to profiles Nucleic acids research 31 374 378 2003 12520026 PMC165555
  18. [18]Nehlin JO Ronne H Yeast MIG1 repressor is related to the mammalian early growth response and Wilms' tumour finger proteins The EMBO journal 9 2891 2898 1990 2167835 PMC552004
  19. [19]Monteiro PT YEASTRACT-DISCOVERER: new tools to improve the analysis of transcriptional regulatory associations in Saccharomyces cerevisiae Nucleic acids research 36 D132 136 2008 18032429 PMC2238916
  20. [20]Teixeira MC The YEASTRACT database: a tool for the analysis of transcription regulatory associations in Saccharomyces cerevisiae Nucleic acids research 34 D446 451 2006 16381908 PMC1347376
  21. [22]Gietz RD Schiestl RH Large-scale high-efficiency yeast transformation using the LiAc/SS carrier DNA/PEG method Nature protocols 2 38 41 2007 17401336

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Sorted by citations

Authors
Gertz, J., Siggia, E. D., & Cohen, B. A.
Affiliations
  • Washington University in St. Louis (US)
  • Rockefeller University (US)
Corresponding author
Cohen, Barak A.
Venue
Nature
Published
2008-11-23
Volume
457
Issue
7226
Pages
215-218
ISSN
  • 0028-0836 (ISSN-L)
  • 1476-4687
OpenAlex
W2143855992
Cited by
304
References
1
Citations by year
2026: 5 · 2025: 3 · 2024: 8 · 2023: 8 · 2022: 11 · 2021: 11 · 2020: 14 · 2019: 11 · 2018: 15 · 2017: 14 · 2016: 18 · 2015: 27 · 2014: 17 · 2013: 34 · 2012: 28
FWCI
10.00
Type
journal article
Language
en
Open access
Locations
  • Nature (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Funders
National Institute of General Medical Sciences (R01GM078222)
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 › Fungal and yeast genetics research
Keywords
transcription factor binding sites, synthetic promoters, promoter library, cooperativity, Saccharomyces cerevisiae, chromatin, protein-DNA interactions, protein-protein interaction, gene expression prediction
MeSH terms
Allosteric Site, DNA, DNA-Binding Proteins, Genes, Synthetic, Models, Genetic, Promoter Regions, Genetic, Regulatory Sequences, Nucleic Acid, Repressor Proteins, Saccharomyces cerevisiae, Thermodynamics, Transcription Factors, Down-Regulation, Gene Library, Gene Expression Regulation, Fungal, Genome, Fungal, Saccharomyces cerevisiae Proteins

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