The cis-regulatory logic of Hedgehog gradient responses: key roles for gli binding affinity, competition, and cooperativity - PubMed
- ️Sat Jan 01 2011
The cis-regulatory logic of Hedgehog gradient responses: key roles for gli binding affinity, competition, and cooperativity
David S Parker et al. Sci Signal. 2011.
Abstract
Gradients of diffusible signaling proteins control precise spatial patterns of gene expression in the developing embryo. Here, we use quantitative expression measurements and thermodynamic modeling to uncover the cis-regulatory logic underlying spatially restricted gene expression in a Hedgehog (Hh) gradient in Drosophila. When Hh signaling is low, the Hh effector Gli, known as Cubitus interruptus (Ci) in Drosophila, acts as a transcriptional repressor; when Hh signaling is high, Gli acts as a transcriptional activator. Counterintuitively and in contrast to previous models of Gli-regulated gene expression, we found that low-affinity binding sites for Ci were required for proper spatial expression of the Hh target gene decapentaplegic (dpp) in regions of low Hh signal. Three low-affinity Ci sites enabled expression of dpp in response to low signal; increasing the affinity of these sites restricted dpp expression to regions of maximal signaling. A model incorporating cooperative repression by Ci correctly predicted the in vivo expression of a reporter gene controlled by a single Ci site. Our work clarifies how transcriptional activators and repressors, competing for common binding sites, can transmit positional information to the genome. It also provides an explanation for the widespread presence of conserved, nonconsensus Gli binding sites in Hh target genes.
Conflict of interest statement
Competing interests: The authors declare that they have no competing interests.
Figures

The Hh target genes ptc and dpp differ in sequence and affinity of Ci/Gli binding sites in their enhancers. (A) Diagram of the third-instar wing disc, showing individual gene and protein expression patterns across a transect of the disc. The dashed line indicates the anterior/posterior boundary. Engrailed (En) directly represses dpp in cells closest to the boundary, as shown by the white bar. (B) Sequence and in vitro relative affinity of the three Ci binding sites within enhancers of ptc (red) and dpp (blue). Matches to the optimal consensus sequence are shown as dashes. (C) Matrix similarity scores (predicted affinity) of Ci sites in ptc (red) and dpp (blue), across 12 Drosophila species genomes. Drosophila melanogaster scores are shown as black dots.

Optimizing the affinity of Ci sites in the dpp enhancer restricts expression to the most strongly Hh-responding cells. (A) Diagrams of versions of the dpp disc enhancer (dppD) with low-affinity Ci binding sites [blue, wild type (WT)], high-affinity Ci sites (red, Ciptc), or mutated sites that do not bind Ci (black, CiKO). (B) Expression of altered dpp enhancers across the Hh gradient of the wing imaginal disc. Confocal images of segments of wing discs from double-transgenic reporter larvae are shown. Green, dppD-GFP reporters; magenta, dppD-Ciptc-RFP used as an internal control for fluorescence and stripe position. (C) Normalized GFP fluorescence data collected from wing discs. Arrows show medians of fluorescence along the anterior-posterior axis for each construct. Yellow circles indicate the positions at which Ci switches from net activation to net repression. (D) Net effect of wild-typeor high-affinity Ci sites on dppD expression (normalized expression minus normalized dppD-CiKO expression). Increased Ci affinity provides stronger activation in region 1, as well as stronger repression in region 3, but switches from activation to repression in region 2. Yellow circles indicate the positions at which Ci switches from net activation to net repression. A, anterior; P, posterior.

Thermodynamic model of the dpp response to Hh. (A) Schematic of the protein-protein and protein-DNA interactions captured by the model. Each arrow represents a free energy (ΔG) that determines the probability of specific interactions occurring on the dpp enhancer. (B) The repressor cooperativity model accurately reproduces the low-affinity (Cidpp) and high-affinity (Ciptc) enhancer–GFP data. Modeled relative expression (enhancer expression minus basal expression, y axis) accurately captures the position of the measured switch from activation to repression (circles) along the Hh gradient (x axis). RMS = root mean square of residuals; vertical line indicates A/P boundary. (C) A noncooperative differential affinity model, in which CiACT exhibits higher affinity for Cidpp sites than CiREP, and CiREP exhibits higher affinity for Ciptc sites than CiACT, also accurately models the switch from activation to repression.

The repressor cooperativity model successfully predicts expression from a single high-affinity Ci site. (A) Relative measured GFP expression from a 1xCiptc enhancer compared with 1xCiptc predictions of the repressor cooperativity (RC) and differential affinity (DA) models. 3xCidpp and 3xCiptc are the original data sets on which the models were trained. The vertical line indicates the A/P boundary. (B) A model incorporating cooperative repression and repressor-activator competition explains why intermediate amounts of Hh produce activation from low-affinity sites and repression from high-affinity sites. The Hh gradient produces opposing gradients of CiACT and CiREP competing for common binding sites. At intermediate amounts of CiACT and CiREP, the high-affinity enhancer, which has higher overall occupancy than the low-affinity enhancer, favors cooperative repression by CiREP. In each example, only one of many possible binding states is shown.
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