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

By Eilon Sharon, Y. Kalma, A. Sharp, Tali Raveh-Sadka, M. Levo, Danny Zeevi, Leeat Keren, Zohar Yakhini, A. Weinberger, Eran Segal. Nature Biotechnology, 2012

494 citations recorded by the source corpus.

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.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/e2c40ca9aeee01bdcbd9bd9c976b7bbc51cbf853

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In Molecular Biology

Citations in the corpus

Transcriptional enhancers: from properties to genome-wide predictions (2014, background): “Sharon et al.(129) Thousands Yeast Plasmid Fluorescence intensity”
Learning the sequence determinants of alternative splicing from millions of random sequences. (2015, background): “…with extensive variation have been applied to study transcription (Melnikov et al., 2012; Patwardhan et al., 2012; Patwardhan et al., 2009; Sharon et al., 2012; Smith et al., 2013; White et al., 2013), translation (Noderer et al., 2014), mRNA stability (Oikonomou et al., 2014), and even…”
High-throughput functional testing of ENCODE segmentation predictions (2014, unknown): “…of TF-binding preferences, not histone modifications alone, are most predictive of actively expressing genomic sequences, a result supported by other attempts to define the sequence features of enhancers (Heinz et al. 2010; Lee et al. 2011; Arvey et al. 2012; Gorkin et al. 2012; Smith et al. 2013).”
Large-scale de novo DNA synthesis: technologies and applications (2014, background): “Recent efforts focused on understanding the structural and functional characteristics of thousands of cis-regulatory sequences governing transcriptional, translational and other regulatory processes in mammalian, yeast and bacterial systems [78] [79] [80] [81] [82] [83] [84] [85] [86] [87] .”
Deep learning of the regulatory grammar of yeast 5′ untranslated regions from 500,000 random sequences (2017, unknown): “…protein expression resultingfromvariantsin a large library employed fluorescence-activated cell sorting (FACS) for measurement (Kinney et al. 2010; Sharon et al. 2012; Dvir et al. 2013; Kosuri et al. 2013; Noderer et al. 2014; Oikonomou et al. 2014; Lubliner et al. 2015; Shalem et al. 2015),…”