Inferring gene regulatory logic from high-throughput measurements of thousands of systematically designed promoters
Open accessAbstract
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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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 [32]
The Results section (“Parallel expression measurements of thousands of designed promoters,” page unavailable) describes a library of synthetic promoters used to measure how designed TF-binding-site changes affect reporter expression. But the paper measures promoter expression, not enhancer activity, and its Results section on surrounding sequence shows that the sequence context can itself affect expression; it does not establish an otherwise inert context. (LLM, conf=0.88)
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- Authors
- Sharon, E., Kalma, Y., Sharp, A., Raveh-Sadka, T., Levo, M., Zeevi, D., Keren, L., Yakhini, Z., Weinberger, A., & Segal, E.
- Affiliations
- Weizmann Institute of Science (IL)
- Corresponding author
- Weinberger, Adina
- Segal, Eran
- Venue
- Nature Biotechnology
- Published
- 2012-05-20
- Volume
- 30
- Issue
- 6
- Pages
- 521-530
- ISSN
- 0733-222X (ISSN-L)
- 1087-0156
- 1546-1696
- PMC
- PMC3374032
- OpenAlex
- W2145674897
- Cited by
- 457
- References
- 3
- Citations by year
- 2026: 17 · 2025: 26 · 2024: 17 · 2023: 31 · 2022: 27 · 2021: 42 · 2020: 30 · 2019: 27 · 2018: 33 · 2017: 30 · 2016: 53 · 2015: 36 · 2014: 45 · 2013: 35 · 2012: 8
- FWCI
- 14.92
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Biotechnology (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (5r01ca119176-10)
- National Cancer Institute (R01-CA119176)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fungal and yeast genetics research
- Keywords
- cis-regulatory sequences, transcription factor binding sites, promoter design, yeast promoters, transcriptional regulation, sequence context effects
- MeSH terms
- Binding Sites, Genetic Engineering, Genotype, Models, Genetic, Nucleosomes, Promoter Regions, Genetic, Research Design, Transcription Factors, Yeasts, Gene Expression Regulation, Fungal, Cluster Analysis, Genome, Fungal, Computational Biology, Gene Regulatory Networks, High-Throughput Nucleotide Sequencing
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