Ulrike Gaul

The role of site accessibility in microRNA target recognition

MicroRNAs are key regulators of gene expression, 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.

Predicting expression patterns from regulatory sequence in Drosophila segmentation

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.

A putative Ras GTPase activating protein acts as a negative regulator of signaling by the Sevenless receptor tyrosine kinase

A Drosophila gene with similarity to the mammalian Ras GTPase activating protein has been isolated in screens for mutations that affect eye development. Inactivation of the locus, Gap1, mimics constitutive activation of the Sevenless receptor tyrosine kinase and eliminates the need for a functional Sevenless protein in the R7 cell. Our results suggest that Gap1 acts as a negative regulator of signaling by Sevenless by down-regulating the activity of the Ras1 protein, which has been shown to be a key element in signaling by Sevenless.

Computational detection of genomic cis- regulatory modules applied to body patterning in the early Drosophila embryo

BackgroundRegulation of gene transcription is crucial for the function and development of all organisms. While gene prediction programs that identify protein coding sequence are used with remarkable success in the annotation of genomes, the development of computational methods to analyze noncoding regions and to delineate transcriptional control elements is still in its infancy.ResultsHere we present novel algorithms to detect cis- regulatory modules through genome wide scans for clusters of transcription factor binding sites using three levels of prior information. When binding sites for the factors are known, our statistical segmentation algorithm, Ahab, yields about 150 putative gap gene regulated modules, with no adjustable parameters other than a window size. If one or more related modules are known, but no binding sites, repeated motifs can be found by a customized Gibbs sampler and input to Ahab, to predict genes with similar regulation. Finally using only the genome, we developed a third algorithm, Argos, that counts and scores clusters of overrepresented motifs in a window of sequence. Argos recovers many of the known modules, upstream of the segmentation genes, with no training data.ConclusionsWe have demonstrated, in the case of body patterning in the Drosophila embryo, that our algorithms allow the genome-wide identification of regulatory modules. We believe that Ahab overcomes many problems of recent approaches and we estimated the false positive rate to be about 50%. Argos is the first successful attempt to predict regulatory modules using only the genome without training data. Complete results and module predictions across the Drosophila genome are available at http://uqbar.rockefeller.edu/~siggia/.

Transcriptional Control in the Segmentation Gene Network of Drosophila

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 Ahabs 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.

The Drosophila afadin homologue Canoe regulates linkage of the actin cytoskeleton to adherens junctions during apical constriction.

Cadherin-based adherens junctions (AJs) mediate cell adhesion and regulate cell shape change. The nectin–afadin complex also localizes to AJs and links to the cytoskeleton. Mammalian afadin has been suggested to be essential for adhesion and polarity establishment, but its mechanism of action is unclear. In contrast, Drosophila melanogaster’s afadin homologue Canoe (Cno) has suggested roles in signal transduction during morphogenesis. We completely removed Cno from embryos, testing these hypotheses. Surprisingly, Cno is not essential for AJ assembly or for AJ maintenance in many tissues. However, morphogenesis is impaired from the start. Apical constriction of mesodermal cells initiates but is not completed. The actomyosin cytoskeleton disconnects from AJs, uncoupling actomyosin constriction and cell shape change. Cno has multiple direct interactions with AJ proteins, but is not a core part of the cadherin–catenin complex. Instead, Cno localizes to AJs by a Rap1- and actin-dependent mechanism. These data suggest that Cno regulates linkage between AJs and the actin cytoskeleton during morphogenesis.

GPCR Signaling Is Required for Blood-Brain Barrier Formation in Drosophila

The blood-brain barrier of Drosophila is established by surface glia, which ensheath the nerve cord and insulate it against the potassium-rich hemolymph by forming intercellular septate junctions. The mechanisms underlying the formation of this barrier remain obscure. Here, we show that the G protein-coupled receptor (GPCR) Moody, the G protein subunits G alpha i and G alpha o, and the regulator of G protein signaling Loco are required in the surface glia to achieve effective insulation. Our data suggest that the four proteins act in a complex common pathway. At the cellular level, the components function by regulating the cortical actin and thereby stabilizing the extended morphology of the surface glia, which in turn is necessary for the formation of septate junctions of sufficient length to achieve proper sealing of the nerve cord. Our study demonstrates the importance of morphogenetic regulation in blood-brain barrier development and places GPCR signaling at its core.

moody encodes two GPCRs that regulate cocaine behaviors and blood-brain barrier permeability in Drosophila

We identified moody in a genetic screen for Drosophila mutants with altered cocaine sensitivity. Hypomorphic mutations in moody cause an increased sensitivity to cocaine and nicotine exposure. In contrast, sensitivity to the acute intoxicating effects of ethanol is reduced. The moody locus encodes two novel GPCRs, Moody-alpha and Moody-beta. While identical in their membrane-spanning domains, the two Moody proteins differ in their long carboxy-terminal domains, which are generated by use of alternative reading frames. Both Moody forms are required for normal cocaine sensitivity, suggesting that they carry out distinct but complementary functions. Moody-alpha and Moody-beta are coexpressed in surface glia that surround the nervous system, where they are actively required to maintain the integrity of the blood-brain barrier in the adult fly. We propose that a Moody-mediated signaling pathway functions in glia to regulate nervous system insulation and drug-related behaviors.

miR-184 Has Multiple Roles in Drosophila Female Germline Development

Posttranscriptional regulation plays a crucial role in germline and early embryonic development, but the underlying mechanisms are only partially understood. Here we report the genetic and molecular analysis of the maternally and zygotically expressed microRNA miR-184 in Drosophila. Loss of miR-184 leads to multiple severe defects during oogenesis and early embryogenesis, culminating in the complete loss of egg production. Using both in vitro and in vivo assays, we characterize the relevant miR-184 targets and target sites for three of the observed phenotypes. miR-184 controls germline stem cell differentiation by tuning the DPP receptor Saxophone, dorsoventral patterning of the egg shell by regulating the gurken transport factor K10, and anteroposterior patterning of the blastoderm by tuning the transcriptional repressor Tramtrack69. Our study highlights the importance of microRNA-mediated regulation in the major developmental transitions of the female germline, and provides insights into several aspects of microRNA function.

Cross-species comparison significantly improves genome-wide prediction of cis-regulatory modules in Drosophila.

BackgroundThe 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.ResultsWe 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.ConclusionEvolutionary 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.