SUMMARY The core promoter, the region immediately surrounding the transcription start site, plays a central role in setting metazoan gene expression levels, but how exactly it ‘computes’ expression remains poorly understood. To dissect core promoter function, we carried out a comprehensive structure-function analysis to measure synthetic promoters’ activities, with and without an external stimulus (hormonal activation). By using robotics and a dual-luciferase reporter assay, we tested ∼3000 mutational variants representing 19 different Drosophila melanogaster promoter architectures. We explored the impact of different types of mutations, including knockout of individual sequence motifs and motif combinations, variations of motif strength, positioning, and flanking sequences. We observe strong effects of the mutations on activity, and a linear combination of the individual motif features can largely account for the combinatorial effects on core promoter activity. Our findings shed new light on the quantitative assessment of gene expression, a fundamental process in all metazoans.

ABSTRACT Hunchback (Hb) is considered a context-dependent transcription factor, able to activate or repress different enhancers during Drosophila embryo segmentation. The mechanism driving the contextdependent activity of Hb is however not well understood. Here we measure the activity of a large set of 20 synthetic enhancers that we design to elucidate the effect of Hb binding sites in Drosophila segmentation. We obtain quantitative data on the spatiotemporal dynamics of activity of all synthetic enhancers in-vivo , by using a quantitative and sensitive reporter system we recently developed. Our data reveal the dual role of Hb binding sites in segmentation enhancers: on the one hand, Hb act as a typical short range repressor by binding to its cognate sequences; on the other hand, we report a novel effect of a sequence containing multiple Hb binding sites, which is able to increase enhancer activity independently from Hb binding. This sequence, which contains multiple Poly-dA stretches, increases the activity of enhancers driven by different activators, possibly by disfavoring nucleosome occupancy. AUTHOR SUMMARY The control of gene expression is a fundamental process that allows cells to respond to external stimuli and take on various identities in complex organisms. Enhancers are DNA sequences that play a key role in this process. In the simplest model of an enhancer, small parts of its sequence can be specifically bound by proteins called transcription factors and the occupancy pattern of these proteins on the enhancer determines the expression level of a specific gene. In this research work we have studied enhancers in the context of the development of a fruit fly embryo. We have built synthetic enhancer sequences containing binding sites for a few specific factors and measured their activity in living embryos using fluorescence microscopy. Our results revealed that binding sites for a particular protein, Hunchback, are able to influence the activity of the enhancer even independently from Hunchback binding to them. This discovery might help to explain the complex effects that have been observed when studying Hunchback binding sites in natural enhancers.

The DNA of eukaryotes is wrapped around histone octamers to form nucleosomes. Although it is well established that the DNA sequence significantly influences nucleosome formation, its precise contribution has remained controversial, partially owing to the lack of quantitative affinity data. Here, we present a method to measure DNA-histone binding free energies at medium throughput and with high sensitivity. Competitive nucleosome formation is achieved through automation, and a modified epi-fluorescence microscope is used to rapidly and accurately measure the fractions of bound/unbound DNA based on fluorescence anisotropy. The procedure allows us to obtain full titration curves with high reproducibility. We applied this technique to measure the histone-DNA affinities for 47 DNA sequences and analyzed how the affinities correlate with relevant DNA sequence features. We found that the GC content has a significant impact on nucleosome-forming preferences, but 10 bp dinucleotide periodicities and the presence of poly(dA:dT) stretches do not.

The gene regulatory network governing anterior-posterior axis formation in Drosophila is a well-established paradigm to study transcription in developmental biology. The rapid temporal dynamics of gene expression during early stages of development, however, are difficult to track with standard techniques. We optimized the bright and fast-maturing fluorescent protein mNeonGreen as a real-time, quantitative reporter of enhancer expression. We derive enhancer activity from the reporter fluorescence dynamics with high spatial and temporal resolution, using a robust reconstruction algorithm. By comparing our results with data obtained with the established MS2-MCP system, we demonstrate the higher detection sensitivity of our reporter. We used the reporter to quantify the activity of variants of a simple synthetic enhancer, and observe increased activity upon reduction of enhancer-promoter distance or addition of binding sites for the pioneer transcription factor Zelda. Our reporter system constitutes a powerful tool to study spatio-temporal gene expression dynamics in live embryos.

In the original version of this Article, equation three contained a sign error whereby the term RT was added when it should have been subtracted. This has now been corrected in the PDF and HTML versions of the Article.

Establishment of spatial coordinates during Drosophila embryogenesis relies on differential regulatory activity of axis patterning enhancers. Concentration gradients of activator and repressor transcription factors (TFs) provide positional information to each enhancer, which in turn promotes transcription of a target gene in a specific spatial pattern. However, the interplay between an enhancer regulatory activity and its accessibility as determined by local chromatin organization is not well understood. We profiled chromatin accessibility with ATAC-seq in narrow, genetically tagged domains along the antero-posterior axis in the Drosophila blastoderm. We demonstrate that one-quarter of the accessible genome displays significant regional variation in its ATAC-seq signal immediately after zygotic genome activation. Axis patterning enhancers are enriched among the most variable intervals, and their accessibility changes correlate with their regulatory activity. In an embryonic domain where an enhancer receives a net activating TF input and promotes transcription, it displays elevated accessibility in comparison to a domain where it receives a net repressive input. We propose that differential accessibility is a signature of patterning cis-regulatory elements in the Drosophila blastoderm and discuss potential mechanisms by which accessibility of enhancers may be modulated by activator and repressor TFs.

Accurate quantification of transcription factor (TF)-DNA interactions is essential for understanding the regulation of gene expression. Since existing approaches suffer from significant limitations, we have developed a new method for determining TF-DNA binding affinities with high sensitivity on a large scale. The assay relies on the established fluorescence anisotropy (FA) principle but introduces important technical improvements. First, we measure a full FA competitive titration curve in a single well by incorporating TF and a fluorescently labeled reference DNA in a porous agarose gel matrix. Unlabeled DNA oligomer is loaded on the top as a competitor and, through diffusion, forms a spatio-temporal gradient. The resulting FA gradient is then read out using a customized epifluorescence microscope setup. This improved setup greatly increases the sensitivity of FA signal detection, allowing both weak and strong binding to be reliably quantified, even for molecules of similar molecular weights. In this fashion, we can measure one titration curve per well of a multi-well plate, and through a fitting procedure, we can extract both the absolute dissociation constant (KD) and active protein concentration. By testing all single-point mutation variants of a given consensus binding sequence, we can survey the entire binding specificity landscape of a TF, typically on a single plate. The resulting position weight matrices (PWMs) outperform those derived from other methods in predicting in vivo TF occupancy. Here, we present a detailed guide for implementing HiP-FA on a conventional automated fluorescent microscope and the data analysis pipeline.

The establishment of complex expression patterns at precise times and locations is key to metazoan development, yet a mechanistic understanding of the underlying transcription control networks is still missing. Here we describe a novel thermodynamic model that computes expression patterns as a function of cis-regulatory sequence and of the binding-site preferences and expression of participating transcription factors. We apply this model to the segmentation gene network of Drosophila melanogaster and find that it predicts expression patterns of cis-regulatory modules with remarkable accuracy, demonstrating that positional information is encoded in the regulatory sequence and input factor distribution. Our analysis reveals that both strong and weaker binding sites contribute, leading to high occupancy of the module DNA, and conferring robustness against mutation; short-range homotypic clustering of weaker sites facilitates cooperative binding, which is necessary to sharpen the patterns. Our computational framework is generally applicable to most protein-DNA interaction systems.

MicroRNAs are key regulators of gene expression1,2,3,4, but the precise mechanisms underlying their interaction with their mRNA targets are still poorly understood. Here, we systematically investigate the role of target-site accessibility, as determined by base-pairing interactions within the mRNA, in microRNA target recognition. We experimentally show that mutations diminishing target accessibility substantially reduce microRNA-mediated translational repression, with effects comparable to those of mutations that disrupt sequence complementarity. We devise a parameter-free model for microRNA-target interaction that computes the difference between the free energy gained from the formation of the microRNA-target duplex and the energetic cost of unpairing the target to make it accessible to the microRNA. This model explains the variability in our experiments, predicts validated targets more accurately than existing algorithms, and shows that genomes accommodate site accessibility by preferentially positioning targets in highly accessible regions. Our study thus demonstrates that target accessibility is a critical factor in microRNA function.

MicroRNAs are small noncoding RNAs that control gene function posttranscriptionally through mRNA degradation or translational inhibition. Much has been learned about the processing and mechanism of action of microRNAs, but little is known about their biological function. Here, we demonstrate that injection of 2'O-methyl antisense oligoribonucleotides into early Drosophila embryos leads to specific and efficient depletion of microRNAs and thus permits systematic loss-of-function analysis in vivo. Twenty-five of the forty-six embryonically expressed microRNAs show readily discernible defects; pleiotropy is moderate and family members display similar yet distinct phenotypes. Processes under microRNA regulation include cellularization and patterning in the blastoderm, morphogenesis, and cell survival. The largest microRNA family in Drosophila (miR-2/6/11/13/308) is required for suppressing embryonic apoptosis; this is achieved by differential posttranscriptional repression of the proapoptotic factors hid, grim, reaper, and sickle. Our findings demonstrate that microRNAs act as specific and essential regulators in a wide range of developmental processes.

BACKGROUND:The discovery of cis-regulatory modules in metazoan genomes is crucial for understanding the connection between genes and organism diversity. It is important to quantify how comparative genomics can improve computational detection of such modules.RESULTS:We run the Stubb software on the entire D. melanogaster genome, to obtain predictions of modules involved in segmentation of the embryo. Stubb uses a probabilistic model to score sequences for clustering of transcription factor binding sites, and can exploit multiple species data within the same probabilistic framework. The predictions are evaluated using publicly available gene expression data for thousands of genes, after careful manual annotation. We demonstrate that the use of a second genome (D. pseudoobscura) for cross-species comparison significantly improves the prediction accuracy of Stubb, and is a more sensitive approach than intersecting the results of separate runs over the two genomes. The entire list of predictions is made available online.CONCLUSION:Evolutionary conservation of modules serves as a filter to improve their detection in silico. The future availability of additional fruitfly genomes therefore carries the prospect of highly specific genome-wide predictions using Stubb.

The segmentation gene network of Drosophila consists of maternal and zygotic factors that generate, by transcriptional (cross-) regulation, expression patterns of increasing complexity along the anterior-posterior axis of the embryo. Using known binding site information for maternal and zygotic gap transcription factors, the computer algorithm Ahab recovers known segmentation control elements (modules) with excellent success and predicts many novel modules within the network and genome-wide. We show that novel module predictions are highly enriched in the network and typically clustered proximal to the promoter, not only upstream, but also in intronic space and downstream. When placed upstream of a reporter gene, they consistently drive patterned blastoderm expression, in most cases faithfully producing one or more pattern elements of the endogenous gene. Moreover, we demonstrate for the entire set of known and newly validated modules that Ahab's prediction of binding sites correlates well with the expression patterns produced by the modules, revealing basic rules governing their composition. Specifically, we show that maternal factors consistently act as activators and that gap factors act as repressors, except for the bimodal factor Hunchback. Our data suggest a simple context-dependent rule for its switch from repressive to activating function. Overall, the composition of modules appears well fitted to the spatiotemporal distribution of their positive and negative input factors. Finally, by comparing Ahab predictions with different categories of transcription factor input, we confirm the global regulatory structure of the segmentation gene network, but find odd skipped behaving like a primary pair-rule gene. The study expands our knowledge of the segmentation gene network by increasing the number of experimentally tested modules by 50%. For the first time, the entire set of validated modules is analyzed for binding site composition under a uniform set of criteria, permitting the definition of basic composition rules. The study demonstrates that computational methods are a powerful complement to experimental approaches in the analysis of transcription networks.