Abstract
Despite extensive research, our understanding of the rules according to which cis-regulatory sequences are converted into gene expression is limited. We devised a method for obtaining parallel, highly accurate gene expression measurements from thousands of designed promoters and applied it to measure the effect of systematic changes in the location, number, orientation, affinity and organization of transcription-factor binding sites and nucleosome-disfavoring sequences. Our analyses reveal a clear relationship between expression and binding-site multiplicity, as well as dependencies of expression on the distance between transcription-factor binding sites and gene starts which are transcription-factor specific, including a striking ∼10-bp periodic relationship between gene expression and binding-site location. We show how this approach can measure transcription-factor sequence specificities and the sensitivity of transcription-factor sites to the surrounding sequence context, and compare the activity of 75 yeast transcription factors. Our method can be used to study both cis and trans effects of genotype on transcriptional, post-transcriptional and translational control.
This is a preview of subscription content, access via your institution
Access options
Subscribe to this journal
Receive 12 print issues and online access
$209.00 per year
only $17.42 per issue
Rent or buy this article
Prices vary by article type
from$1.95
to$39.95
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
Accession codes
References
Chiang, D.Y., Nix, D.A., Shultzaberger, R.K., Gasch, A.P. & Eisen, M.B. Flexible promoter architecture requirements for coactivator recruitment. BMC Mol. Biol. 7, 16 (2006).
Ligr, M., Siddharthan, R., Cross, F.R. & Siggia, E.D. Gene expression from random libraries of yeast promoters. Genetics 172, 2113–2122 (2006).
Kinkhabwala, A. & Guet, C.C. Uncovering cis regulatory codes using synthetic promoter shuffling. PLoS ONE 3, e2030 (2008).
Gertz, J., Siggia, E.D. & Cohen, B.A. Analysis of combinatorial cis-regulation in synthetic and genomic promoters. Nature 457, 215–218 (2009).
Cox, R.S. III., Surette, M.G. & Elowitz, M.B. Programming gene expression with combinatorial promoters. Mol. Syst. Biol. 3, 145 (2007).
Kinney, J.B., Murugan, A., Callan, C.G. Jr. & Cox, E.C. Using deep sequencing to characterize the biophysical mechanism of a transcriptional regulatory sequence. Proc. Natl. Acad. Sci. USA 107, 9158–9163 (2010).
Giniger, E. & Ptashne, M. Cooperative DNA binding of the yeast transcriptional activator GAL4. Proc. Natl. Acad. Sci. USA 85, 382–386 (1988).
Iyer, V. & Struhl, K. Poly(dA:dT), a ubiquitous promoter element that stimulates transcription via its intrinsic DNA structure. EMBO J. 14, 2570–2579 (1995).
Lam, F.H., Steger, D.J. & O'Shea, E.K. Chromatin decouples promoter threshold from dynamic range. Nature 453, 246–250 (2008).
Murphy, K.F., Balazsi, G. & Collins, J.J. Combinatorial promoter design for engineering noisy gene expression. Proc. Natl. Acad. Sci. USA 104, 12726–12731 (2007).
Patwardhan, R.P. et al. High-resolution analysis of DNA regulatory elements by synthetic saturation mutagenesis. Nat. Biotechnol. 27, 1173–1175 (2009).
Patwardhan, R.P. et al. Massively parallel functional dissection of mammalian enhancers in vivo. Nat. Biotechnol. 30, 265–270 (2012).
Melnikov, A. et al. Systematic dissection and optimization of inducible enhancers in human cells using a massively parallel reporter assay. Nat. Biotechnol. 30, 271–277 (2012).
LeProust, E.M. et al. Synthesis of high-quality libraries of long (150mer) oligonucleotides by a novel depurination controlled process. Nucleic Acids Res. 38, 2522–2540 (2010).
Kaplan, N. et al. The DNA-encoded nucleosome organization of a eukaryotic genome. Nature 458, 362–366 (2009).
Baliga, N.S. Promoter analysis by saturation mutagenesis. Biol. Proced. Online 3, 64–69 (2001).
Anderson, J.D. & Widom, J. Poly(dA-dT) promoter elements increase the equilibrium accessibility of nucleosomal DNA target sites. Mol. Cell. Biol. 21, 3830–3839 (2001).
Segal, E. & Widom, J. Poly(dA:dT) tracts: major determinants of nucleosome organization. Curr. Opin. Struct. Biol. 19, 65–71 (2009).
Zeevi, D. et al. Compensation for differences in gene copy number among yeast ribosomal proteins is encoded within their promoters. Genome Res. 21, 2114–2128 (2011).
Badis, G. et al. Diversity and complexity in DNA recognition by transcription factors. Science 324, 1720–1723 (2009).
Ghaemmaghami, S. et al. Global analysis of protein expression in yeast. Nature 425, 737–741 (2003).
Huh, W.K. et al. Global analysis of protein localization in budding yeast. Nature 425, 686–691 (2003).
Zhao, Y. et al. Fine-structure analysis of ribosomal protein gene transcription. Mol. Cell. Biol. 26, 4853–4862 (2006).
Blaiseau, P.L., Lesuisse, E. & Camadro, J.M. Aft2p, a novel iron-regulated transcription activator that modulates, with Aft1p, intracellular iron use and resistance to oxidative stress in yeast. J. Biol. Chem. 276, 34221–34226 (2001).
Lamb, T.M. & Mitchell, A.P. The transcription factor Rim101p governs ion tolerance and cell differentiation by direct repression of the regulatory genes NRG1 and SMP1 in Saccharomyces cerevisiae. Mol. Cell. Biol. 23, 677–686 (2003).
Hanlon, S.E., Rizzo, J.M., Tatomer, D.C., Lieb, J.D. & Buck, M.J. The stress response factors Yap6, Cin5, Phd1, and Skn7 direct targeting of the conserved co-repressor Tup1-Ssn6 in S. cerevisiae. PLoS ONE 6, e19060 (2011).
Canizares, J.V., Pallotti, C., Sainz-Pardo, I., Iranzo, M. & Mormeneo, S. The SRD2 gene is involved in Saccharomyces cerevisiae morphogenesis. Arch. Microbiol. 177, 352–357 (2002).
Akache, B., Wu, K. & Turcotte, B. Phenotypic analysis of genes encoding yeast zinc cluster proteins. Nucleic Acids Res. 29, 2181–2190 (2001).
Woudt, L.P., Smit, A.B., Mager, W.H. & Planta, R.J. Conserved sequence elements upstream of the gene encoding yeast ribosomal protein L25 are involved in transcription activation. EMBO J. 5, 1037–1040 (1986).
Lieb, J.D., Liu, X., Botstein, D. & Brown, P.O. Promoter-specific binding of Rap1 revealed by genome-wide maps of protein-DNA association. Nat. Genet. 28, 327–334 (2001).
Nutiu, R. et al. Direct measurement of DNA affinity landscapes on a high-throughput sequencing instrument. Nat. Biotechnol. 29, 659–664 (2011).
Maerkl, S.J. & Quake, S.R. A systems approach to measuring the binding energy landscapes of transcription factors. Science 315, 233–237 (2007).
Bulyk, M.L., Gentalen, E., Lockhart, D.J. & Church, G.M. Quantifying DNA-protein interactions by double-stranded DNA arrays. Nat. Biotechnol. 17, 573–577 (1999).
Raveh-Sadka, T. et al. Manipulating nucleosome disfavoring sequences allows fine-tune regulation of gene expression in yeast. Nat. Genet. (in the press).
Kim, J.H., Polish, J. & Johnston, M. Specificity and regulation of DNA binding by the yeast glucose transporter gene repressor Rgt1. Mol. Cell. Biol. 23, 5208–5216 (2003).
Karolchik, D. et al. The UCSC Genome Browser Database. Nucleic Acids Res. 31, 51–54 (2003).
Zhu, C. et al. High-resolution DNA binding specificity analysis of yeast transcription factors. Genome Res. 19, 556–566 (2009).
Cleary, M.A. et al. Production of complex nucleic acid libraries using highly parallel in situ oligonucleotide synthesis. Nat. Methods 1, 241–248 (2004).
Fazekas, A., Steeves, R. & Newmaster, S. Improving sequencing quality from PCR products containing long mononucleotide repeats. Biotechniques 48, 277–285 (2010).
Sheff, M.A. & Thorn, K.S. Optimized cassettes for fluorescent protein tagging in Saccharomyces cerevisiae. Yeast 21, 661–670 (2004).
Breslow, D.K. et al. A comprehensive strategy enabling high-resolution functional analysis of the yeast genome. Nat. Methods 5, 711–718 (2008).
Otsuka, C. et al. Use of yeast transformation by oligonucleotides to study DNA lesion bypass in vivo. Mutat. Res. 502, 53–60 (2002).
Hoaglin, D.C., Mosteller, F. & Tukey, J.W. Understanding Robust and Exploratory Data Anlysis (Wiley, 1983).
Acknowledgements
We thank J. Widom for assistance and inspiration throughout this project. This work was supported by grants from the European Research Council and the US National Institutes of Health to E. Segal. E. Segal is the incumbent of the Soretta and Henry Shapiro career development chair. We thank S. Lubliner for help with computational analyses. We thank C. Boone (University of Toronto) for kindly giving us the Y8205 strain.
Author information
Authors and Affiliations
Contributions
E. Sharon and E. Segal conceived the project. E. Sharon., Y.K., A.W. and E. Segal planned the experiments. E. Sharon and Y.K. performed the experiments. E. Sharon and E. Segal analyzed the results. T.R.-S., M.L. and Z.Y. contributed to the design of the promoters. A.S., D.Z. and L.K. contributed to experimental work. Z.Y. also provided technical guidance.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing financial interests.
Supplementary information
Supplementary Text and Figures
Supplementary Notes 1, 2, Supplementary Figures 1–21 and Supplementary Tables 1, 2 (PDF 2070 kb)
Supplementary Table 3
Library description and measured expression values (XLSX 630 kb)
Rights and permissions
About this article
Cite this article
Sharon, E., Kalma, Y., Sharp, A. et al. Inferring gene regulatory logic from high-throughput measurements of thousands of systematically designed promoters. Nat Biotechnol 30, 521–530 (2012). https://doi.org/10.1038/nbt.2205
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/nbt.2205
This article is cited by
-
A universal system for boosting gene expression in eukaryotic cell-lines
Nature Communications (2024)
-
Genome-wide promoter responses to CRISPR perturbations of regulators reveal regulatory networks in Escherichia coli
Nature Communications (2023)
-
Chance promoter activities illuminate the origins of eukaryotic intergenic transcriptions
Nature Communications (2023)
-
Using Synthetic DNA Libraries to Investigate Chromatin and Gene Regulation
Chromosoma (2023)
-
oFlowSeq: a quantitative approach to identify protein coding mutations affecting cell type enrichment using mosaic CRISPR-Cas9 edited cerebral organoids
Human Genetics (2023)