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Inferring gene regulatory logic from high-throughput measurements of thousands of systematically designed promoters

Nature Biotechnology volume 30, pages 521–530 (2012)Cite this article

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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.

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Figure 1: Obtaining accurate expression measurements for thousands of designed promoter sequences.
Figure 2: Profiling the activity of 75 yeast transcription factors.
Figure 3: The effect of binding-site location on expression.
Figure 4: The effect of nucleosome disfavoring-sequences on expression.
Figure 5: Effect of binding-site number on expression.
Figure 6: Comparing the effects of different types of sequence changes.

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Gene Expression Omnibus

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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.

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Author notes

  1. Eilon Sharon and Yael Kalma: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel

    Eilon Sharon, Yael Kalma, Tali Raveh-Sadka, Michal Levo, Danny Zeevi, Leeat Keren, Adina Weinberger & Eran Segal

  2. Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel

    Eilon Sharon, Yael Kalma, Ayala Sharp, Danny Zeevi, Leeat Keren, Adina Weinberger & Eran Segal

  3. Computer Science department, Technion, Haifa, Israel.,

    Zohar Yakhini

  4. Agilent Laboratories, Santa Clara, California, USA

    Zohar Yakhini

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  1. Eilon Sharon
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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

Correspondence to Adina Weinberger or Eran Segal.

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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)

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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

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