Workshop 7: Drosophila Develoipment

(June 8,2009 - June 12,2009 )

Organizers


Michael Levine
Department of Molecular & Cell Biology, University of California, Berkeley
Hans Othmer
School of Mathematics, University of Minnesota

The workshop will cover four broad topics that are particularly well-suited for quantitative analysis: genome analysis, pattern formation of the early embryo and wing imaginal disk, computational modeling of signal transduction pathways, and the elucidation and analysis of gene regulation networks.

As of this writing, the genomes of 12 different Drosophilids have been completely sequenced and assembled. These assemblies provide a rich foundation for the identification of conserved noncoding sequences including microRNA genes and regulatory DNAs.

Whole-genome methods provide the comprehensive identification of just about every gene and associated regulatory DNA responsible for complex developmental processes, including segmentation, gastrulation, neurogenesis, and wing morphogenesis. Current progress in each of these areas of research will be discussed with an eye towards future modeling efforts. Several critical processes such as EGF and TGFß signaling have already been successfully modeled, and the insights gleaned from these efforts will be discussed.

The last sessions will be devoted to gene regulatory networks. A combination of gene disruption assays, DNA binding assays, and cis-regulatory analysis permits the construction of networks, or circuit diagrams, that display the functional inter-connections among all of the regulatory genes and cell signaling components responsible for complex developmental processes. These networks can be used to create predictive changes in patterning processes, and to determine the mechanistic basis for the genesis of embryonic diversity and novelty during insect evolution. We will discuss the logic and topology of these networks, and also consider future goals such as the development of better visualization methods.

Accepted Speakers

Reka Albert
Department of Physics, Pennsylvania State University
David Arnosti
Dept. of Biochemistry and Molecular Biology, Michigan State University
Seth Blair
Department of Zoology, University of Wisconsin
Hamid Bolouri
Division of Biology, California Institute of Technology
Haini Cai
Department of Cellular Biology, University of Georgia
Stephen Crews
Department of Biochemistry and Biophysics, University of North Carolina, Chapel Hill
Claude Desplan
Dept. of Biology, New York University
Albert Erives
Dept. of Biological Sciences, Dartmouth College
Edwin Ferguson
Dept. of Molecular Genetics and Cell Biology, University of Chicago
Manfred Frasch
Dept. Developmental Biology, University Erlangen-Nuremberg
Eileen Furlong
Developmental Biology & Gene Expression Programmes, European Molecular Biology Laboratory - EMBL
Jackie Gavin-Smith
Dept. of Molecular Genetics and Cell Biology, University of Chicago
Manolis Kellis
MIT Computer Science and Artificial Intelligence Laboratory, Harvard University
Tom Kornberg
Department of Biochemistry, University of California
Arthur Lander
Center for Complex Biological Systems, University of California, Irvine
Maria Leptin
Institute for Genetics, Cologne University
Michael Levine
Department of Molecular & Cell Biology, University of California, Berkeley
Hans Othmer
School of Mathematics, University of Minnesota
Lior Pachter
Department of Mathematics, University of California, Berkeley
Norbert Perrimon
Department of Genetics, Harvard Medical School
John Reinitz
Applied Mathematics & Statistics, Stony Brook University
Sharmila Roy
Department of Cellular Biology, University of Georgia
Christine Rushlow
Department of Biology, New York University
Maria Samsonova
Department of Computational Biology, St. Petersburg State Polytechnic University
Ben-Zion (Benny) Shilo
Department of Molecular Genetics, Weizmann Institute of Science
Stanislav Shvartsman
Lewis-Sigler Inst. for Integrative Genomics, Princeton University
Stephen Small
Department of BIology, New York University
Alexander Stark
Research Institute of Molecular Pathology (IMP)
Angela Stathopoulos
Division of Biology, California Institute of Technology
David Umulis
Agricultural & Biological Engineering, Purdue University
Julia Zeitlinger
Zeitlinger Lab, Stowers Institute for Medical Research
Monday, June 8, 2009
Time Session
09:00 AM
09:45 AM
Julia Zeitlinger - Evolution of the DV transcriptional regulatory network in closely related Drosophila species

Changes in cis-regulatory elements for transcription are thought be an important driving force for the evolution of species. To investigate how changes in cis-regulatory sequence affect a transcriptional regulatory network during development, we study the dorso-ventral (DV) patterning network in four closely related Drosophila species, D. melanogaster, D. simulans, D. erecta, and D. yakuba. Chromatin immunoprecipitation combined with high throughput-sequencing (ChIP-seq) is used to compare the genome-wide distribution of the transcriptional activator Twist and repressor Snail.


This is work by Qiye He and Brianne Patton, in collaboration with Alex Stark and Manolis Kellis.

09:45 AM
10:30 AM
Lior Pachter - Drosophila genome dynamics at the nucleotide level

I will talk about how we are performing genome alignments of Drosophila at the nucleotide level, and how the alignments can be leveraged to study the functional drivers of genome evolution. The focus of the talk will be on the mathematical questions and issues, with a view towards large scale alignment of thousands of Drosophila genomes, and their study in conjunction with data from high-throughput sequencing based assays in the near future.

10:45 AM
11:30 AM
Norbert Perrimon - Large scale analyses of signaling networks

N/A

11:30 AM
12:15 PM
Eileen Furlong - Transcription factor binding reveals spatial and temporal aspects of developmental networks

One of the central challenges in biology is to understand how the genome is utilized to orchestrate the development of complex tissues and organisms. While genetic studies have identified a number of essential transcription factors required for cell fate specification, little is known about the molecular mechanisms by which these regulators function. Few of their direct target genes or effector molecules are known. Moreover, the architecture of the underlying transcriptional network in which they operate remains elusive.


Our work attempts to bridge this gap, by integrating genetic, genomic and computational approaches to understand the transcriptional network that drives the selection of cell fates within the mesoderm. By combining ChIP-on-chip through a time-course of Drosophila development we are systematically identifying cis-regulatory module occupancy during developmental progression. These data are enriched by expression profiling of mutant embryos for each transcription factor. The topology of the network was unexpected, showing extensive combinatorial regulation and temporal enhancer occupancy. Current work is focused on understanding how these diverse combinatorial binding 'codes' give rise to specific patterns of enhancer expression.

02:00 PM
02:45 PM
Tom Kornberg - Mechanisms of morphogen dispersion and action

N/A

02:45 PM
03:30 PM
Manolis Kellis - Regulatory genomics of Drosophila tissue- and stage-specific gene expression patterns

A systems-level understanding of gene regulation in animal genomes requires the comprehensive characterization of functional regulatory regions, the sequence motifs within them, and the regulatory logic guiding their spatial and temporal activity. Our group at MIT is developing computational methods to address these challenges in Drosophila melanogaster, in collaboration with large-scale experimental efforts. We have used comparative genomics of 12 Drosophila genomes to recognize characteristic patterns of change, or evolutionary signatures, associated with genes and regulatory elements. We have also developed methods for the de novo discovery of recurring combinations of chromatin marks, or chromatin signatures, revealing a small number of distinct chromatin states associated with distinct functional roles, such as enhancer, promoter, insulator, and other regions. Using evolutionary signatures and chromatin signatures together, we have defined a global map of regions of regulatory importance in the Drosophila genome, and a complete map of high-confidence instances of conserved regulatory motifs and motif combinations within them. In parallel, we have studied spatial and temporal patterns of gene expression from in situ images at varying stages of embryonic development, in order to define recurrent patterns of gene expression, or expression primitives, likely to correspond to regulatory signals established by combinations of transcriptional regulators. In this talk, I will describe our progress in each of these areas, and the computational challenge of defining a coherent map between genome sequence and gene expression patterns in development.


This is work by: Chris Bristow, Pouya Kheradpour, Jason Ernst, Rachel Sealfon. Experimental collaborators: Kevin White, Bing Ren, Gary Karpen, Sue Celniker.

03:45 PM
04:30 PM
Alexander Stark - Comparative genomics of gene regulation in Drosophila

Many developmental phenomena involve processes that lead to determinate outputs. Lineage information and signaling cues at specific time points, though varied at certain levels, are integrated to yield robust cell fate executions. For sensory systems, fine regulation of gene expression is critical so that information is assessed, relayed, and processed in a specific logical manner. Typically, one molecular receptor type is expressed in a single sensory neuron to prevent sensory confusion.


The fly eye is an example of a sensory system that integrates developmental inputs to yield specific robust cell fate determination. The fly eye is composed of 800 ommatidia (unit eyes) which contain six outer photoreceptors (PRs), R1-6, arranged in a trapezoidal shape surrounding two inner PRs, R7 and R8. The outer PRs express the Rhodopsin1 (Rh1) protein and are used for motion detection. The inner PRs, used for color vision, are organized into two coordinated subtypes. In the pale subtype, R7 expresses Rh3 and Rh8 expresses Rh5 whereas in the yellow subtype, R7 expresses Rh4 and R8 expresses Rh5. Though the distribution of these ommatidial subtypes is spatially randomized throughout the eye, subtype fate determination is robust such that each R7 and R8 expresses a particular rhodopsin in a stable manner and conserved ratio.


How does the fly eye ensure robustness? Here, we describe two distinct roles for the K50 homeodomain transcription factor, Defective proventriculus (Dve). In yellow R7s, Dve specifically represses expression of Rh3. In /dve /mutants, Rh3 is de-repressed in all yellow R7s yielding R7s that express both Rh3 and Rh4. In outer PRs, Dve plays a very different role, repressing noisy expression of Rh3, Rh5, and Rh6. In /dve /null mutants, these rhodopsins are de-repressed in random outer PRs. Dve expression itself is robustly controlled by a complex transcriptional regulatory network. Our analysis suggests that the fly eye utilizes transcriptional repression to mask inherently noisy gene expression and ensure robustness.

Tuesday, June 9, 2009
Time Session
09:45 AM
10:30 AM
Haini Cai - The Drosophila SF1 chromatin boundary may regulate enhancer-promoter interactions by organizing dynamic chromatin loop domains

Chromatin boundaries, or insulators, can block enhancer-promoter interactions and/or limit the spread of silent chromatin. Recent studies indicate that boundary elements are widely present in animal genomes, especially between closely apposed gene promoters, further supporting their roles in maintaining regulatory independence between neighboring genes. We have previously identified SF1, a chromatin boundary in the Drosophila Antennapedia Hox cluster. It is located between the divergently transcribed Hox gene Scr and a non-Hox gene ftz. SF1 exhibits strong enhancer-blocking activity in embryos and protects the miniwhite reporter from the influences of surrounding chromatin. Our recent studies further show that SF1 interacts with neighboring genomic elements to form DNA/chromatin loop domains. We propose that SF1 facilitates the formation of independent gene regulatory domains to modulate stage- and tissue- specific enhancer-promoter interactions.

11:00 AM
11:45 AM
Claude Desplan - Stochastic choices in the Drosophila eye

Many developmental phenomena involve processes that lead to determinate outputs. Lineage information and signaling cues at specific time points, though varied at certain levels, are integrated to yield robust cell fate executions. For sensory systems, fine regulation of gene expression is critical so that information is assessed, relayed, and processed in a specific logical manner. Typically, one molecular receptor type is expressed in a single sensory neuron to prevent sensory confusion.


The fly eye is an example of a sensory system that integrates developmental inputs to yield specific robust cell fate determination. The fly eye is composed of 800 ommatidia (unit eyes) which contain six outer photoreceptors (PRs), R1-6, arranged in a trapezoidal shape surrounding two inner PRs, R7 and R8. The outer PRs express the Rhodopsin1 (Rh1) protein and are used for motion detection. The inner PRs, used for color vision, are organized into two coordinated subtypes. In the pale subtype, R7 expresses Rh3 and Rh8 expresses Rh5 whereas in the yellow subtype, R7 expresses Rh4 and R8 expresses Rh5. Though the distribution of these ommatidial subtypes is spatially randomized throughout the eye, subtype fate determination is robust such that each R7 and R8 expresses a particular rhodopsin in a stable manner and conserved ratio.


How does the fly eye ensure robustness? Here, we describe two distinct roles for the K50 homeodomain transcription factor, Defective proventriculus (Dve). In yellow R7s, Dve specifically represses expression of Rh3. In /dve /mutants, Rh3 is de-repressed in all yellow R7s yielding R7s that express both Rh3 and Rh4. In outer PRs, Dve plays a very different role, repressing noisy expression of Rh3, Rh5, and Rh6. In /dve /null mutants, these rhodopsins are de-repressed in random outer PRs. Dve expression itself is robustly controlled by a complex transcriptional regulatory network. Our analysis suggests that the fly eye utilizes transcriptional repression to mask inherently noisy gene expression and ensure robustness.

01:45 PM
02:30 PM
Seth Blair - Crossveins and the extracellular regulation of BMP signaling

N/A

02:30 PM
03:15 PM
David Arnosti - Mechanisms and regulatory grammar of short- and long-range repressors

N/A

03:30 PM
04:15 PM
Arthur Lander - Constraints, tradeoffs and complexity in morphogen-mediated patterning

In recent years, much research on morphogen gradients has shifted from purely mechanistic questions -how gradients form and how morphogens signa l-to strategic ones- how gradients perform well in the face of various kinds of constraints and perturbations. For example, quite a few cellular and molecular processes have been described as contributing to robustness and precision. Do these processes constitute true strategies of control? Why are there so many of them? Why are some used in certain gradients but not others? Drawing on examples from Drosophiladevelopment, I will argue that the constraints imposed by the need to meet multiple performance objectives drives the diversification of strategic approaches, and provides a context within which to understand the perplexing complexity of patterning systems.

04:15 PM
05:00 PM
David Umulis - Organism-scale modeling of early Drosophila patterning via Bone Morphogenetic Proteins

Mathematical models of embryonic development are formulated to illuminate how the spatio-temporal expression of genes that presages the adult body plan of an organism is controlled, but many have limited utility because they oversimplify crucial aspects such as the geometry, the molecular mechanisms, and other components in the system being modeled. To circumvent these limitations we developed a data-driven, 3D, organism-scale model of bone morphogenetic protein (BMP)-mediated embryonic patterning in Drosophila. We tested 7 different receptor/feedback mechanisms and 8 different geometry/gene expression scenarios for their ability to reproduce the mean distributions of pMad signaling in both wild-type and more than twenty different mutant embryos. We found that positive feedback of a secreted BMP binding protein, coupled with the measured embryo geometry, provides the best agreement between model and experiment. The inclusion of all important factors in a 3D model represents a significant step forward in the systems biology of development.


Work done with Hans G. Othmer and Michael B. O'Connor.

Wednesday, June 10, 2009
Time Session
09:45 AM
10:30 AM
Ben-Zion (Benny) Shilo - Robustness and scaling of morphogen patterning in Drosophila and Xenopus embryos

BMPs play a prominent role in early dorso-ventral patterning in vertebrate and invertebrate embryos. At early stages of embryogenesis, BMPs are produced in a broad domain, abutting a region expressing the extracellular inhibitor Chordin/Sog. How is a morphogen gradient generated within the broad domain of uniform BMP expression? We have used the observation that in Drosophila embryos this gradient is robust to fluctuations in the dose of pathway components, as a basis for a quantitative description of the system, with a focus on the numerical solutions which provide robustness. These solutions present the mechanistic basis for the model, which relies on shuttling of BMP ligands towards the region containing the lowest level of inhibitor, to generate a sharp and robust morphogen gradient. Extrapolation of the findings from flies to Xenopus took into account the presence of an additional ligand inXenopus (termed ADMP), which behaves in the opposite manner to BMPs: It is expressed on the opposite side of the embryo, at the dorsal side, and its expression is repressed by BMP signaling. Furthermore, in Xenopus the dorso-ventral system is able to scale pattern with size, as demonstrated in the classical Spemann experiments and the manipulations of J. Cooke, providing a further restriction to the numerical solutions. Based on computational and experimental analyses, we have postulated a shuttling mechanism similar to the one identified in Drosophila, which is also able to scale pattern with size by turning off the expression of ADMP according to the size of the embryo.


Work done in collaboration with Danny Ben-Zvi, Avigdor Eldar, Abraham Fainsod, and Naama Barkai.


Eldar A., Dorfman, R., Weiss, D., Ashe, H., Shilo B-Z. and Barkai N. Robustness of the BMP morphogen gradient inDrosophila embryonic patterning. Nature 419, 304-308 (2002).
Ben-Zvi, D., Shilo, B-Z., Fainsod, A. and Barkai, N. Scaling of the BMP activation gradient in Xenopus embryos. Nature 453, 1205-1211 (2008).

11:00 AM
11:45 AM
Maria Samsonova - Variation and canalization of gene expression in the Drosophila blastoderm

We investigate the mechanisms of canalization and embryonic regulation in the morphogenetic field which controls the segment determination in Drosophila. The data used for this characterization are quantitative with cellular resolution in space and about 6 minutes in time. At cycle 13 and the early time classes of cycle 14A the patterns of zygotic segmentation genes show considerable variation in amplitude, the way, time and sequence of domain formation, as well as significant positional variability. Nevertheless, this variation is dynamically reduced, or canalized by the onset of gastrulation. We characterize the epigenetic mechanism of canalization by means of dynamical systems theory supported by quantitative gene expression data.

01:45 PM
02:30 PM
Reka Albert - Lessons from modeling Drosophila segment polarity: robustness of gene regulatory

While most of the genes that influence the segmentation of the fruit fly embryo act only transiently, the segment polarity genes have a stable expression pattern that defines and maintains the borders between different parasegments. The segment polarity genes refine and maintain their expression through a network of intra- and intercellular regulatory interactions between gene products. This talk will present a family of qualitative (logical) models of these interactions and of how they lead to stable gene expression patterns. We investigated three modeling frameworks: synchronous Boolean, asynchronous Boolean and piece-wise linear ODE-based models, collectively spanning the range between discrete and continuous modeling. All models are able to reproduce the wild type expression pattern of the segment polarity genes, as well as the ectopic expressions obtained for gene mutation experiments. We find that a separation between the timescales of posttranslational and transcription/translation processes is necessary for establishing the regular gene expression pattern in the segment polarity network. All our algorithms concur in suggesting that the divergence from wild type can be attributed to an imbalance between the two opposing Cubitus Interruptus transcription factors (CIA, CIR) in the posterior half of the parasegment. We find that the system is vulnerable to large delays in expression of any gene - except for ci - and, in such delayed conditions, the mutant state characteristic to that gene knockout is generated. Interestingly, cell division increases the robustness of the segment polarity network with respect to perturbations in biological processes. Taken together, the results of the synchronous, asynchronous Boolean and hybrid models convincingly demonstrate the Boolean models' capability for effectively describing the basic structure and functioning of gene control networks when detailed kinetic information is unavailable.


References:



  1. R. Albert and H. G. Othmer. The topology of the regulatory interactions predicts the expression pattern of the Drosophila segment polarity genes. Journal of Theoretical Biology 223, 1-18 (2003).

  2. M. Chaves, R. Albert and E. D. Sontag. Robustness and fragility of Boolean models for genetic regulatory networks. Journal of Theoretical Biology, Volume 235 , pp 431-449 (2005).

  3. M. Chaves, E. D. Sontag and R. Albert. Methods of robustness analysis for Boolean models of gene control networks. IEE Proceedings in Systems Biology 153, 154-167 (2006).

  4. M. Chaves and R. Albert. Studying the effect of cell division on expression patterns of the segment polarity genes. Journal of the Royal Society Interface 6, 5 (2008).

02:45 PM
03:30 PM
Hamid Bolouri - Reconstructing condition-specific gene regulatory interactions in the absence of perturbation data

All development is ultimately encoded in gene regulatory interactions. Transcription factor (TF) perturbations (e.g. knock downs and knock outs) have been used widely to predict candidate TF targets. But practical constraints limit their applicability in many species, and particularly in studies of later embryonic development. To date identification of causal regulatory interactions between transcription factors and target genes without TF-specific perturbation data has been difficult, costly, time-consuming, and error-prone. I will describe computational approaches that we are developing to address these challenges as we attempt to identify the network of gene regulatory interactions that underlie the development of T-cells in mice.

Thursday, June 11, 2009
Time Session
11:00 AM
11:45 AM
Stephen Crews - The Regulation of Drosophila CNS Midline Neuronal and Glial Development and Transcription

The cells that lie along the midline of the Drosophila CNS are few in number (22/ganglion) but are represented by a variety of neuronal and glial cell types. These include motorneurons, local interneurons, projection neurons, and glia. The midline cells represent an excellent system to study the regulatory circuitry that controls the generation of distinct neuronal and glial cell types, their migration, axon guidance, and glial-axonal interactions. To this end, we have employed in situ hybridization to describe the spatial and temporal expression of 278 midline-expressed genes -the data is accessible via a searchable, web-base database. Methods were developed for imaging midline cells by confocal microscopy of sim-Gal4 UAS- auGFP embryos, and expression of 70 genes that include many transcription factor and neural function genes were examined at multiple stages of development. Thus, each midline precursor and mature cell type can be uniquely identified at each stage of CNS development in both wild-type and mutant embryos.


The single-minded (sim), Notch, and lethal of scute (l(1)sc) genes all play major roles in midline cell development. The sim gene is a master regulator of midline development and plays later roles in midline glial and neuronal development. Notch signaling plays multiple roles in midline development including the neuron-glia switch, neuronal precursor formation, and H-cell sib and iVUM neuronal cell fates. One major goal of our research is to understand how sim and Notch signaling work together to control midline cell development. The l(1)sc gene acts to control neural precursor formation as well as H-cell and mVUM gene expression. Current work is involved with identifying and studying the regulatory proteins that are downstream of Notch and l(1)sc that control the differentiated properties of each neuronal cell type.


The midline glia form a scaffold that ensheaths the commissural axons that cross the midline. We used our imaging methods to visualize midline glial migration, ensheathment, and subdivision of axon commissures, and showed that these events are mediated by the Wrapper (midline glial-expressed) and Neurexin IV (neuronal and axonal-expressed) heterophilic adhesion proteins. We have identified 52 genes expressed in midline glia, including 11 transcription factors, and these are being genetically analyzed to understand how they control the complex morphogenetic and functional properties of midline glia. The overall goal is a comprehensive understanding of the regulatory circuitry involved in CNS developmental decision-making and how specific CNS cell types acquire their differentiated properties.


Work done in collabortaion with Scott R. Wheeler, Stephanie B. Stagg, and Joseph C. Pearson


References:



  1. Wheeler, S.R., Banerjee, S., Blauth, K., Rogers, S.L., Bhat, M.A., and Crews, S.T. (2009). Neurexin IV and Wrapper interactions mediate Drosophila midline glial migration and axonal ensheathment. Development 136, 1147-1157.

  2. Wheeler, S.R., Stagg, S.B., and Crews, S.T. (2008). Generation of Drosophila CNS midline glial and neuronal cell types by sequential Notch signaling events. Development 135, 3071-3079.

  3. Wheeler, S. R., Kearney, J. B., Guardiola, A. R. and Crews, S. T. (2006). Single-cell mapping of neural and glial gene expression in the developing Drosophila CNS midline cells. Dev. Biol. 294, 509-524.

  4. Kearney, J. B., Wheeler, S. R., Estes, P., Parente, B. and Crews, S. T. (2004). Gene expression profiling of the developing Drosophila CNS midline cells. Dev. Biol. 275, 473-492.

11:45 AM
12:30 PM
Maria Leptin - From dorso-ventral patterning to cell shape changes

Regulation of gene expression along the dorso-ventral axis of the Drosophila embryo is one of the best understood systems of pattern formation. It is especially interesting because of the immediate translation of the fate determination events into morphogenetic processes. In particular the first steps in the establishment of the mesoderm, the formation of the ventral furrow, present a system in which to trace the steps from a fate-determining transcription factor, the transcriptional activator Twist, to the target genes responsible for morphogenetic activity. Six zygotically active Twist target genes are necessary to direct furrow formation. Five directly affect cell shape changes, the sixth is the transcription factor Snail. For the complete understanding of how the dorso-ventral patterning cascade controls morphogenesis via Twist, it will now be necessary to establish the transcriptional events downstream of Snail.

02:30 PM
03:15 PM
Hans Othmer - Robustness of Pattern Formation in Development

In many developing systems the outcome is buffered to numerous perturbations, ranging from major ones such as separation of the cells at the 2-cell stage in Xenopus (which can lead to one smaller, but normal adult, and an amorphous mass of tissue), to less severe ones such as changes in the ambient temperature or the loss of one copy of a gene. The general question is how systems are buffered against variations in such factors. We address this question in the specific context of scale-invariance: how different size embryos lead to normally-proportioned adults, both in Drosophila and in Xenopus.

03:30 PM
04:15 PM
Stanislav Shvartsman - MAPK substrate competition in the Drosophila embryo

Developmental patterning relies on combinatorial action of inductive cues and employs a number of strategies for signal integration. These include regulation of a single gene by multiple transcription factors and biochemical modification of a single transcription factor by multiple signaling pathways. Using the early Drosophila embryo as a model, we show that signal integration can also be mediated by a simple enzymatic network. The anterior structures of Drosophila embryo are specified by two inductive signals. One of them, a homeodomain protein Bicoid, establishes the anteroposterior morphogen gradient. The second (terminal) signal is provided by the localized activation of the MAPK pathway at both anterior and posterior poles. Activated MAPK phosphorylates the uniformly distributed transcriptional repressors Capicua and Groucho, relieving their repression of the terminal gap genes. At the anterior pole, MAPK phosphorylates Bicoid, potentiating its transcriptional effects. Using a combination of biochemical, imaging, and genetic approaches, we demonstrate that modification of Bicoid by MAPK has a reverse effect on MAPK phosphorylation and signaling. In the resulting model, MAPK substrates compete for access to this kinase, establishing an enzyme-substrate competition network that integrates the anterior and terminal signals.


Work done in collaboration with Yoosik Kim, Mathieu Coppey, Leiore Ajuria, Gerardo Jiménez, and Ze'ev Paroush

Friday, June 12, 2009
Time Session
09:00 AM
09:45 AM
Christine Rushlow - Zelda, a key activator of the early zygotic genome in Drosophila

Embryonic development is first controlled by maternal gene products deposited in the egg. Some time after fertilization, this control is transferred to the zygotic genome in a process called the maternal-zygotic transition (MZT). During this time, maternal components are degraded and zygotic genes are activated. In Drosophila, zygotic gene activation starts about one hour after fertilization with a small set of genes activated during cycle 8 to cycle 13. These genes are referred to as the precellular blastoderm genes (pre-CB genes or primary zygotic genes; ten Bosch et al., 2006), while a major burst of zygotic gene activity occurs during and after cellularization. We have identified the zinc-finger protein, Zelda (Zinc-finger early Drosophila activator) that binds specifically to cis-regulatory heptamer motifs called the TAGteam sites, which have been shown to be overrepresented in the upstream regions of many pre-CB genes (ten Bosch et al., 2006; de Renzis et al., 2007). Mutant embryos lacking Zelda are defective in cellular blastoderm formation, and fail to activate many TAGteam containing genes essential for cellularization, sex determination, and pattern formation. Global expression profiling confirmed that Zelda plays a key role in the activation of the early zygotic genome, and suggests that Zelda may also regulate maternal RNA degradation during the MZT (Liang et al., 2008). The discovery of Zelda has provided opportunities to reveal the underline mechanisms of the MZT. We propose that the biological role of Zelda in the preblastoderm embryo is to set the stage for key processes such as cellular blastoderm formation and gastrulation, counting of X chromosomes for dosage compensation and sex determination, and pattern formation, by ensuring the coordinated accumulation of batteries of gene products during the MZT. This early preparedness should allow sufficient time for the formation of molecular machines involved in these processes, and so are ready to spring into action during the prolonged interphase of cycle 14.

09:45 AM
10:30 AM
Manfred Frasch - Transcriptional and signaling networks during mesodermal tissue development in Drosophila

A dynamic regulatory network among transcription factors and inductive signals leads to the progressive delineation of cell fates of the developing heart and other muscular tissues. Most of the known regulatory factors exert different functions during consecutive steps of in this regulatory cascade. Of note, the NK homeodomain factor Tinman acts in the early mesoderm in combination with Dpp signals to promote the development of all dorsal mesodermal tissue derivatives, whereas the T-box factors Dorsocross are required specifically for the formation of myocardial cells. Upon heart formation, these cardiogenic factors are then required within the dorsal vessel, where they regulate proper diversification of myocardial cell identities and, in the case of Tinman, cardiac remodeling. A current model of the regulatory interactions in the Drosophila embryonic mesoderm with a focus on cardiogenesis and our present approaches to identify additional components will be presented.

11:00 AM
11:45 AM
Michael Levine - Transcriptional precision in the Drosophila embryo

N/A

11:45 AM
12:30 PM
Albert Erives - Gene regulatory evolution in an equivalence class of developmental enhancers

Biological cells behave in complex ways by producing different RNA molecules in response to diverse conditions. These RNA molecules fold into specific functional RNA structures, or are translated into peptide sequences, which fold into proteins. RNA transcripts are encoded in and transcribed from DNA segments called genes, in a process called "gene expression".


Gene expression is accomplished by the presence of regulatory DNA sequences present at each gene locus, where they instruct the cell as to the conditions under which that gene should be expressed. Thus a gene encodes a potential RNA transcript as well as several instructions for when to produce the transcript. Regulatory DNAs therefore are critical for specifying the number of different gene expression states available to a cell, and the situations in which a cell transitions between these states. Regulatory DNAs are vastly more numerous and complex than the easily identifiable protein-coding DNAs that they regulate. Regulatory DNAs represent the latest frontier in biology.


In my talk, I will focus on the structure of an equivalence class of regulatory DNAs and how they have been evolving across different Drosophila lineages. I will also discuss how such an example corpus can help guide a unified computational approach to the study of the native computational infrastructure of living cells.

Name Affiliation
, jsv@stat.osu.edu Department of Statistics, The Ohio State University
Aguda, Baltazar bdaguda@gmail.com Mathematical Biosciences Institute, Critical Care Center, The Ohio State University
Al-Saleem, Jacob al-saleem.1@osu.edu Molecular Genetics, The Ohio State University
Albert, Reka reka.albert@gmail.com Department of Physics, Pennsylvania State University
Arnosti, David arnosti@msu.edu Dept. of Biochemistry and Molecular Biology, Michigan State University
Asano, Maki maki.asano@osumc.edu Molecular Cellular Biochemistry, The Ohio State University
Austin, Christina austin.180@osu.edu Molecular Genetics, The Ohio State University
Ay, Ahmet ayahmet@msu.edu Mathematics, Michigan State University
Best, Janet jbest@mbi.osu.edu Mathematics, The Ohio State University
Blair, Seth ssblair@wisc.edu Department of Zoology, University of Wisconsin
Boettiger, Alistair alistair@berkeley.edu Biophysics, University of California, Berkeley
Bolouri , Hamid HBolouri@caltech.edu Division of Biology, California Institute of Technology
Boushaba, Khalid boushaba@iastate.edu MBI - Long Term Visitor, The Ohio State University
Bremer, Kirsten bremer.9@osu.edu Center for Molecular Neurobiology, The Ohio State University
Bristow, Chris cbristow@princeton.edu Chemical Engineering, Princeton University
Cai, Haini hcai@uga.edu Department of Cellular Biology, University of Georgia
Coskun, Huseyin hcusckun@mbi.osu.edu MBI - Postdoc, The Ohio State University
Crews, Stephen steve_crews@unc.edu Department of Biochemistry and Biophysics, University of North Carolina, Chapel Hill
Crocker, Justin justin.m.crocker@dartmouth.edu Dept. of Biological Sciences, Dartmouth College
Day, Judy jday@mbi.osu.edu MBI - Postdoc, The Ohio State University
Desplan, Claude cd38@nyu.edu Dept. of Biology, New York University
El-Hodiri, Heithem el-hodiri.1@osu.edu Pediatrics, The Ohio State University
Erives, Albert Albert.J.Erives@Dartmouth.EDU Dept. of Biological Sciences, Dartmouth College
Fall, Chris fall@uic.edu MBI - Long Term Visitor, The Ohio State University
Faraimunashe, Chirove chirove_faraimunashe@yahoo.com MBI - Long Term Visitor, The Ohio State University
Federico, Paula pfederico@mbi.osu.edu MBI - Postdoc, The Ohio State University
Feng, Peng pfeng@fgcu.edu Mathematics, Florida Gulf Coast University
Ferguson, Edwin elfergus@uchicago.edu Dept. of Molecular Genetics and Cell Biology, University of Chicago
Frasch, Manfred Manfred.Frasch@mssm.edu Dept. Developmental Biology, University Erlangen-Nuremberg
Friedman, Avner afriedman@mbi.osu.edu MBI - Long Term Visitor, The Ohio State University
Furlong, Eileen eileen.furlong@embl.de Developmental Biology & Gene Expression Programmes, European Molecular Biology Laboratory - EMBL
Gaertner, Bjoern bga@stowers.org Zeitlinger Lab, Stowers Institute for Medical Research
Gavin-Smith, Jackie jgs@uchicago.edu Dept. of Molecular Genetics and Cell Biology, University of Chicago
Green, Edward egreen@mbi.osu.edu MBI - Postdoc, The Ohio State University
Hamilton, Ian hamilton.598@osu.edu MBI - Long Term Visitor, The Ohio State University
Hengenius, James jhengeni@purdue.edu Computational Biology/Biomedical Engineering, Purdue University
Hovmoller, Rasmus rhovmoller@mbi.osu.edu MBI - Postdoc, The Ohio State University
Ishihara, Keisuke ishihara@princeton.edu Lewis-Sigler Inst. for Integrative Genomics, Princeton University
Jacobsen, Tom jacobsen.14@osu.edu Molecular Genetics, The Ohio State University
Kanodia, Jitendra jkanodia@princeton.edu Lewis-Sigler Inst. for Integrative Genomics, Princeton University
Kao, Chiu-Yen kao.71@osu.edu Department of Mathematics, The Ohio State University
Kellis, Manolis manoli@mit.edu MIT Computer Science and Artificial Intelligence Laboratory, Harvard University
Kim, Yangjin ykim@mbi.osu.edu MBI - Postdoc, The Ohio State University
Kim, Yoosik yoosikk@princeton.edu Lewis-Sigler Inst. for Integrative Genomics, Princeton University
Kirov, Nikolai nk2@nyu.edu Department of Biology, New York University
Kornberg, Tom tkornberg@ucsf.edu Department of Biochemistry, University of California
Lander, Arthur adlander@uci.edu Center for Complex Biological Systems, University of California, Irvine
Lee, Jonathan lee.3440@osu.edu Molecular Genetics, The Ohio State University
Lee, Sang-Hun lee323@purdue.edu Agricultural & Biological Engineering, Purdue University
Leptin , Maria mleptin@uni-koeln.de Institute for Genetics, Cologne University
Levine, Michael mlevine@berkeley.edu Department of Molecular & Cell Biology, University of California, Berkeley
Lou, Yuan lou@math.ohio-state.edu Department of Mathematics, The Ohio State University
Lungu, Edward lunguem@mopipi.ub.bw MBI - Long Term Visitor, The Ohio State University
Machiraju, Raghu machiraju@math.ohio-state.edu Computer Science & Engineering, The Ohio State University
Morishita, Yoshihiro ymorishi@bio-math10.biology.kyushu-u.ac.jp Biology Department, Kyushu University
Oster, Andrew aoester@mbi.osu.edu MBI - Postdoc, The Ohio State University
Othmer, Hans othmer@math.umn.edu School of Mathematics, University of Minnesota
Pachter, Lior lpachter@math.berkeley.edu Department of Mathematics, University of California, Berkeley
Park, Jaehong jaehong.park@osumc.edu Comprehensive Cancer Center, The Ohio State University
Park, So Young soyoung.park@osumc.edu Comprehensive Cancer Center, The Ohio State University
Perrimon, Norbert lmancini@genetics.med.harvard.edu Department of Genetics, Harvard Medical School
Reinitz, John reinitz@odd.bio.sunysb.edu Applied Mathematics & Statistics, Stony Brook University
Rembold, Martina mrembold@uni-koeln.de Institute for genetics, Cologne University
Rempe, Michael mrempe@mbi.osu.edu MBI - Postdoc, The Ohio State University
Reynolds, Julie reynolds.473@osu.edu Entomology, The Ohio State University
Roy, Sharmila sarmilaray@gmail.com Department of Cellular Biology, University of Georgia
Rushlow, Christine car2@nyu.edu Department of Biology, New York University
Sample, Christine csample@princeton.edu Lewis-Sigler Inst. for Integrative Genomics, Princeton University
Samsonova, Maria samson@spbcas.ru Department of Computational Biology, St. Petersburg State Polytechnic University
Schmidt, Deena dschmidt@mbi.osu.edu
Seeger, Mark seeger.9@osu.edu Molecular Genetics, The Ohio State University
Shilo, Ben-Zion (Benny) Benny.Shilo@weizmann.ac.il Department of Molecular Genetics, Weizmann Institute of Science
Shvartsman, Stanislav stas@princeton.edu Lewis-Sigler Inst. for Integrative Genomics, Princeton University
Siegal-Gaskins, Dan dsiegal-gaskins@mbi.osu.edu
Simcox, Amanda simcox.1@osu.edu Molecular Genetics, The Ohio State University
Small, Stephen sjs1@nyu.edu Department of BIology, New York University
Stark, Alexander stark@imp.ac.at Research Institute of Molecular Pathology (IMP)
Stathopoulos, Angela angelike@caltech.edu Division of Biology, California Institute of Technology
Sun, Shuying ssun@mbi.osu.edu MBI - Postdoc, The Ohio State University
Umulis, David dumulis@purdue.edu Agricultural & Biological Engineering, Purdue University
Wilczynski, Bartek bartosz.wilczynski@embl.de The Furlong Laboratory, EMBL Heidelberg
Wilson, Tom wilson.1457@osu.edu Entomology, The Ohio State University
Xue, Chuan cxue@mbi.osu.edu MBI - Postdoc, The Ohio State University
Yan, Dong yanzu8@cchmc.org Developmental Biology, Cincinnati Children's Hospital Medical Center
Yarahmadian, Shantia SYarahmadian@math.msstate.edu Indiana Molecular Biology Institute, Indiana University
Zeitlinger, Julia jbz@stowers-institute.org Zeitlinger Lab, Stowers Institute for Medical Research
Zhang, Yifei zhang.410@osu.edu Center for Molecular Neurobiology, The Ohio State University
Zheng, Likun zhen0107@math.umn.edu School of Mathematics, University of Minnesota
Ziyadi, Najat najat_ziyadi@yahoo.fr MBI - Long Term Visitor, The Ohio State University
Lessons from modeling Drosophila segment polarity: robustness of gene regulatory

While most of the genes that influence the segmentation of the fruit fly embryo act only transiently, the segment polarity genes have a stable expression pattern that defines and maintains the borders between different parasegments. The segment polarity genes refine and maintain their expression through a network of intra- and intercellular regulatory interactions between gene products. This talk will present a family of qualitative (logical) models of these interactions and of how they lead to stable gene expression patterns. We investigated three modeling frameworks: synchronous Boolean, asynchronous Boolean and piece-wise linear ODE-based models, collectively spanning the range between discrete and continuous modeling. All models are able to reproduce the wild type expression pattern of the segment polarity genes, as well as the ectopic expressions obtained for gene mutation experiments. We find that a separation between the timescales of posttranslational and transcription/translation processes is necessary for establishing the regular gene expression pattern in the segment polarity network. All our algorithms concur in suggesting that the divergence from wild type can be attributed to an imbalance between the two opposing Cubitus Interruptus transcription factors (CIA, CIR) in the posterior half of the parasegment. We find that the system is vulnerable to large delays in expression of any gene - except for ci - and, in such delayed conditions, the mutant state characteristic to that gene knockout is generated. Interestingly, cell division increases the robustness of the segment polarity network with respect to perturbations in biological processes. Taken together, the results of the synchronous, asynchronous Boolean and hybrid models convincingly demonstrate the Boolean models' capability for effectively describing the basic structure and functioning of gene control networks when detailed kinetic information is unavailable.


References:



  1. R. Albert and H. G. Othmer. The topology of the regulatory interactions predicts the expression pattern of the Drosophila segment polarity genes. Journal of Theoretical Biology 223, 1-18 (2003).

  2. M. Chaves, R. Albert and E. D. Sontag. Robustness and fragility of Boolean models for genetic regulatory networks. Journal of Theoretical Biology, Volume 235 , pp 431-449 (2005).

  3. M. Chaves, E. D. Sontag and R. Albert. Methods of robustness analysis for Boolean models of gene control networks. IEE Proceedings in Systems Biology 153, 154-167 (2006).

  4. M. Chaves and R. Albert. Studying the effect of cell division on expression patterns of the segment polarity genes. Journal of the Royal Society Interface 6, 5 (2008).

Mechanisms and regulatory grammar of short- and long-range repressors

N/A

Crossveins and the extracellular regulation of BMP signaling

N/A

Reconstructing condition-specific gene regulatory interactions in the absence of perturbation data

All development is ultimately encoded in gene regulatory interactions. Transcription factor (TF) perturbations (e.g. knock downs and knock outs) have been used widely to predict candidate TF targets. But practical constraints limit their applicability in many species, and particularly in studies of later embryonic development. To date identification of causal regulatory interactions between transcription factors and target genes without TF-specific perturbation data has been difficult, costly, time-consuming, and error-prone. I will describe computational approaches that we are developing to address these challenges as we attempt to identify the network of gene regulatory interactions that underlie the development of T-cells in mice.

The Drosophila SF1 chromatin boundary may regulate enhancer-promoter interactions by organizing dynamic chromatin loop domains

Chromatin boundaries, or insulators, can block enhancer-promoter interactions and/or limit the spread of silent chromatin. Recent studies indicate that boundary elements are widely present in animal genomes, especially between closely apposed gene promoters, further supporting their roles in maintaining regulatory independence between neighboring genes. We have previously identified SF1, a chromatin boundary in the Drosophila Antennapedia Hox cluster. It is located between the divergently transcribed Hox gene Scr and a non-Hox gene ftz. SF1 exhibits strong enhancer-blocking activity in embryos and protects the miniwhite reporter from the influences of surrounding chromatin. Our recent studies further show that SF1 interacts with neighboring genomic elements to form DNA/chromatin loop domains. We propose that SF1 facilitates the formation of independent gene regulatory domains to modulate stage- and tissue- specific enhancer-promoter interactions.

The Regulation of Drosophila CNS Midline Neuronal and Glial Development and Transcription

The cells that lie along the midline of the Drosophila CNS are few in number (22/ganglion) but are represented by a variety of neuronal and glial cell types. These include motorneurons, local interneurons, projection neurons, and glia. The midline cells represent an excellent system to study the regulatory circuitry that controls the generation of distinct neuronal and glial cell types, their migration, axon guidance, and glial-axonal interactions. To this end, we have employed in situ hybridization to describe the spatial and temporal expression of 278 midline-expressed genes -the data is accessible via a searchable, web-base database. Methods were developed for imaging midline cells by confocal microscopy of sim-Gal4 UAS- auGFP embryos, and expression of 70 genes that include many transcription factor and neural function genes were examined at multiple stages of development. Thus, each midline precursor and mature cell type can be uniquely identified at each stage of CNS development in both wild-type and mutant embryos.


The single-minded (sim), Notch, and lethal of scute (l(1)sc) genes all play major roles in midline cell development. The sim gene is a master regulator of midline development and plays later roles in midline glial and neuronal development. Notch signaling plays multiple roles in midline development including the neuron-glia switch, neuronal precursor formation, and H-cell sib and iVUM neuronal cell fates. One major goal of our research is to understand how sim and Notch signaling work together to control midline cell development. The l(1)sc gene acts to control neural precursor formation as well as H-cell and mVUM gene expression. Current work is involved with identifying and studying the regulatory proteins that are downstream of Notch and l(1)sc that control the differentiated properties of each neuronal cell type.


The midline glia form a scaffold that ensheaths the commissural axons that cross the midline. We used our imaging methods to visualize midline glial migration, ensheathment, and subdivision of axon commissures, and showed that these events are mediated by the Wrapper (midline glial-expressed) and Neurexin IV (neuronal and axonal-expressed) heterophilic adhesion proteins. We have identified 52 genes expressed in midline glia, including 11 transcription factors, and these are being genetically analyzed to understand how they control the complex morphogenetic and functional properties of midline glia. The overall goal is a comprehensive understanding of the regulatory circuitry involved in CNS developmental decision-making and how specific CNS cell types acquire their differentiated properties.


Work done in collabortaion with Scott R. Wheeler, Stephanie B. Stagg, and Joseph C. Pearson


References:



  1. Wheeler, S.R., Banerjee, S., Blauth, K., Rogers, S.L., Bhat, M.A., and Crews, S.T. (2009). Neurexin IV and Wrapper interactions mediate Drosophila midline glial migration and axonal ensheathment. Development 136, 1147-1157.

  2. Wheeler, S.R., Stagg, S.B., and Crews, S.T. (2008). Generation of Drosophila CNS midline glial and neuronal cell types by sequential Notch signaling events. Development 135, 3071-3079.

  3. Wheeler, S. R., Kearney, J. B., Guardiola, A. R. and Crews, S. T. (2006). Single-cell mapping of neural and glial gene expression in the developing Drosophila CNS midline cells. Dev. Biol. 294, 509-524.

  4. Kearney, J. B., Wheeler, S. R., Estes, P., Parente, B. and Crews, S. T. (2004). Gene expression profiling of the developing Drosophila CNS midline cells. Dev. Biol. 275, 473-492.

Stochastic choices in the Drosophila eye

Many developmental phenomena involve processes that lead to determinate outputs. Lineage information and signaling cues at specific time points, though varied at certain levels, are integrated to yield robust cell fate executions. For sensory systems, fine regulation of gene expression is critical so that information is assessed, relayed, and processed in a specific logical manner. Typically, one molecular receptor type is expressed in a single sensory neuron to prevent sensory confusion.


The fly eye is an example of a sensory system that integrates developmental inputs to yield specific robust cell fate determination. The fly eye is composed of 800 ommatidia (unit eyes) which contain six outer photoreceptors (PRs), R1-6, arranged in a trapezoidal shape surrounding two inner PRs, R7 and R8. The outer PRs express the Rhodopsin1 (Rh1) protein and are used for motion detection. The inner PRs, used for color vision, are organized into two coordinated subtypes. In the pale subtype, R7 expresses Rh3 and Rh8 expresses Rh5 whereas in the yellow subtype, R7 expresses Rh4 and R8 expresses Rh5. Though the distribution of these ommatidial subtypes is spatially randomized throughout the eye, subtype fate determination is robust such that each R7 and R8 expresses a particular rhodopsin in a stable manner and conserved ratio.


How does the fly eye ensure robustness? Here, we describe two distinct roles for the K50 homeodomain transcription factor, Defective proventriculus (Dve). In yellow R7s, Dve specifically represses expression of Rh3. In /dve /mutants, Rh3 is de-repressed in all yellow R7s yielding R7s that express both Rh3 and Rh4. In outer PRs, Dve plays a very different role, repressing noisy expression of Rh3, Rh5, and Rh6. In /dve /null mutants, these rhodopsins are de-repressed in random outer PRs. Dve expression itself is robustly controlled by a complex transcriptional regulatory network. Our analysis suggests that the fly eye utilizes transcriptional repression to mask inherently noisy gene expression and ensure robustness.

Gene regulatory evolution in an equivalence class of developmental enhancers

Biological cells behave in complex ways by producing different RNA molecules in response to diverse conditions. These RNA molecules fold into specific functional RNA structures, or are translated into peptide sequences, which fold into proteins. RNA transcripts are encoded in and transcribed from DNA segments called genes, in a process called "gene expression".


Gene expression is accomplished by the presence of regulatory DNA sequences present at each gene locus, where they instruct the cell as to the conditions under which that gene should be expressed. Thus a gene encodes a potential RNA transcript as well as several instructions for when to produce the transcript. Regulatory DNAs therefore are critical for specifying the number of different gene expression states available to a cell, and the situations in which a cell transitions between these states. Regulatory DNAs are vastly more numerous and complex than the easily identifiable protein-coding DNAs that they regulate. Regulatory DNAs represent the latest frontier in biology.


In my talk, I will focus on the structure of an equivalence class of regulatory DNAs and how they have been evolving across different Drosophila lineages. I will also discuss how such an example corpus can help guide a unified computational approach to the study of the native computational infrastructure of living cells.

Transcriptional and signaling networks during mesodermal tissue development in Drosophila

A dynamic regulatory network among transcription factors and inductive signals leads to the progressive delineation of cell fates of the developing heart and other muscular tissues. Most of the known regulatory factors exert different functions during consecutive steps of in this regulatory cascade. Of note, the NK homeodomain factor Tinman acts in the early mesoderm in combination with Dpp signals to promote the development of all dorsal mesodermal tissue derivatives, whereas the T-box factors Dorsocross are required specifically for the formation of myocardial cells. Upon heart formation, these cardiogenic factors are then required within the dorsal vessel, where they regulate proper diversification of myocardial cell identities and, in the case of Tinman, cardiac remodeling. A current model of the regulatory interactions in the Drosophila embryonic mesoderm with a focus on cardiogenesis and our present approaches to identify additional components will be presented.

Transcription factor binding reveals spatial and temporal aspects of developmental networks

One of the central challenges in biology is to understand how the genome is utilized to orchestrate the development of complex tissues and organisms. While genetic studies have identified a number of essential transcription factors required for cell fate specification, little is known about the molecular mechanisms by which these regulators function. Few of their direct target genes or effector molecules are known. Moreover, the architecture of the underlying transcriptional network in which they operate remains elusive.


Our work attempts to bridge this gap, by integrating genetic, genomic and computational approaches to understand the transcriptional network that drives the selection of cell fates within the mesoderm. By combining ChIP-on-chip through a time-course of Drosophila development we are systematically identifying cis-regulatory module occupancy during developmental progression. These data are enriched by expression profiling of mutant embryos for each transcription factor. The topology of the network was unexpected, showing extensive combinatorial regulation and temporal enhancer occupancy. Current work is focused on understanding how these diverse combinatorial binding 'codes' give rise to specific patterns of enhancer expression.

Regulatory genomics of Drosophila tissue- and stage-specific gene expression patterns

A systems-level understanding of gene regulation in animal genomes requires the comprehensive characterization of functional regulatory regions, the sequence motifs within them, and the regulatory logic guiding their spatial and temporal activity. Our group at MIT is developing computational methods to address these challenges in Drosophila melanogaster, in collaboration with large-scale experimental efforts. We have used comparative genomics of 12 Drosophila genomes to recognize characteristic patterns of change, or evolutionary signatures, associated with genes and regulatory elements. We have also developed methods for the de novo discovery of recurring combinations of chromatin marks, or chromatin signatures, revealing a small number of distinct chromatin states associated with distinct functional roles, such as enhancer, promoter, insulator, and other regions. Using evolutionary signatures and chromatin signatures together, we have defined a global map of regions of regulatory importance in the Drosophila genome, and a complete map of high-confidence instances of conserved regulatory motifs and motif combinations within them. In parallel, we have studied spatial and temporal patterns of gene expression from in situ images at varying stages of embryonic development, in order to define recurrent patterns of gene expression, or expression primitives, likely to correspond to regulatory signals established by combinations of transcriptional regulators. In this talk, I will describe our progress in each of these areas, and the computational challenge of defining a coherent map between genome sequence and gene expression patterns in development.


This is work by: Chris Bristow, Pouya Kheradpour, Jason Ernst, Rachel Sealfon. Experimental collaborators: Kevin White, Bing Ren, Gary Karpen, Sue Celniker.

Mechanisms of morphogen dispersion and action

N/A

Constraints, tradeoffs and complexity in morphogen-mediated patterning

In recent years, much research on morphogen gradients has shifted from purely mechanistic questions -how gradients form and how morphogens signa l-to strategic ones- how gradients perform well in the face of various kinds of constraints and perturbations. For example, quite a few cellular and molecular processes have been described as contributing to robustness and precision. Do these processes constitute true strategies of control? Why are there so many of them? Why are some used in certain gradients but not others? Drawing on examples from Drosophiladevelopment, I will argue that the constraints imposed by the need to meet multiple performance objectives drives the diversification of strategic approaches, and provides a context within which to understand the perplexing complexity of patterning systems.

From dorso-ventral patterning to cell shape changes

Regulation of gene expression along the dorso-ventral axis of the Drosophila embryo is one of the best understood systems of pattern formation. It is especially interesting because of the immediate translation of the fate determination events into morphogenetic processes. In particular the first steps in the establishment of the mesoderm, the formation of the ventral furrow, present a system in which to trace the steps from a fate-determining transcription factor, the transcriptional activator Twist, to the target genes responsible for morphogenetic activity. Six zygotically active Twist target genes are necessary to direct furrow formation. Five directly affect cell shape changes, the sixth is the transcription factor Snail. For the complete understanding of how the dorso-ventral patterning cascade controls morphogenesis via Twist, it will now be necessary to establish the transcriptional events downstream of Snail.

Transcriptional precision in the Drosophila embryo

N/A

Robustness of Pattern Formation in Development

In many developing systems the outcome is buffered to numerous perturbations, ranging from major ones such as separation of the cells at the 2-cell stage in Xenopus (which can lead to one smaller, but normal adult, and an amorphous mass of tissue), to less severe ones such as changes in the ambient temperature or the loss of one copy of a gene. The general question is how systems are buffered against variations in such factors. We address this question in the specific context of scale-invariance: how different size embryos lead to normally-proportioned adults, both in Drosophila and in Xenopus.

Drosophila genome dynamics at the nucleotide level

I will talk about how we are performing genome alignments of Drosophila at the nucleotide level, and how the alignments can be leveraged to study the functional drivers of genome evolution. The focus of the talk will be on the mathematical questions and issues, with a view towards large scale alignment of thousands of Drosophila genomes, and their study in conjunction with data from high-throughput sequencing based assays in the near future.

Large scale analyses of signaling networks

N/A

Zelda, a key activator of the early zygotic genome in Drosophila

Embryonic development is first controlled by maternal gene products deposited in the egg. Some time after fertilization, this control is transferred to the zygotic genome in a process called the maternal-zygotic transition (MZT). During this time, maternal components are degraded and zygotic genes are activated. In Drosophila, zygotic gene activation starts about one hour after fertilization with a small set of genes activated during cycle 8 to cycle 13. These genes are referred to as the precellular blastoderm genes (pre-CB genes or primary zygotic genes; ten Bosch et al., 2006), while a major burst of zygotic gene activity occurs during and after cellularization. We have identified the zinc-finger protein, Zelda (Zinc-finger early Drosophila activator) that binds specifically to cis-regulatory heptamer motifs called the TAGteam sites, which have been shown to be overrepresented in the upstream regions of many pre-CB genes (ten Bosch et al., 2006; de Renzis et al., 2007). Mutant embryos lacking Zelda are defective in cellular blastoderm formation, and fail to activate many TAGteam containing genes essential for cellularization, sex determination, and pattern formation. Global expression profiling confirmed that Zelda plays a key role in the activation of the early zygotic genome, and suggests that Zelda may also regulate maternal RNA degradation during the MZT (Liang et al., 2008). The discovery of Zelda has provided opportunities to reveal the underline mechanisms of the MZT. We propose that the biological role of Zelda in the preblastoderm embryo is to set the stage for key processes such as cellular blastoderm formation and gastrulation, counting of X chromosomes for dosage compensation and sex determination, and pattern formation, by ensuring the coordinated accumulation of batteries of gene products during the MZT. This early preparedness should allow sufficient time for the formation of molecular machines involved in these processes, and so are ready to spring into action during the prolonged interphase of cycle 14.

Variation and canalization of gene expression in the Drosophila blastoderm

We investigate the mechanisms of canalization and embryonic regulation in the morphogenetic field which controls the segment determination in Drosophila. The data used for this characterization are quantitative with cellular resolution in space and about 6 minutes in time. At cycle 13 and the early time classes of cycle 14A the patterns of zygotic segmentation genes show considerable variation in amplitude, the way, time and sequence of domain formation, as well as significant positional variability. Nevertheless, this variation is dynamically reduced, or canalized by the onset of gastrulation. We characterize the epigenetic mechanism of canalization by means of dynamical systems theory supported by quantitative gene expression data.

Robustness and scaling of morphogen patterning in Drosophila and Xenopus embryos

BMPs play a prominent role in early dorso-ventral patterning in vertebrate and invertebrate embryos. At early stages of embryogenesis, BMPs are produced in a broad domain, abutting a region expressing the extracellular inhibitor Chordin/Sog. How is a morphogen gradient generated within the broad domain of uniform BMP expression? We have used the observation that in Drosophila embryos this gradient is robust to fluctuations in the dose of pathway components, as a basis for a quantitative description of the system, with a focus on the numerical solutions which provide robustness. These solutions present the mechanistic basis for the model, which relies on shuttling of BMP ligands towards the region containing the lowest level of inhibitor, to generate a sharp and robust morphogen gradient. Extrapolation of the findings from flies to Xenopus took into account the presence of an additional ligand inXenopus (termed ADMP), which behaves in the opposite manner to BMPs: It is expressed on the opposite side of the embryo, at the dorsal side, and its expression is repressed by BMP signaling. Furthermore, in Xenopus the dorso-ventral system is able to scale pattern with size, as demonstrated in the classical Spemann experiments and the manipulations of J. Cooke, providing a further restriction to the numerical solutions. Based on computational and experimental analyses, we have postulated a shuttling mechanism similar to the one identified in Drosophila, which is also able to scale pattern with size by turning off the expression of ADMP according to the size of the embryo.


Work done in collaboration with Danny Ben-Zvi, Avigdor Eldar, Abraham Fainsod, and Naama Barkai.


Eldar A., Dorfman, R., Weiss, D., Ashe, H., Shilo B-Z. and Barkai N. Robustness of the BMP morphogen gradient inDrosophila embryonic patterning. Nature 419, 304-308 (2002).
Ben-Zvi, D., Shilo, B-Z., Fainsod, A. and Barkai, N. Scaling of the BMP activation gradient in Xenopus embryos. Nature 453, 1205-1211 (2008).

MAPK substrate competition in the Drosophila embryo

Developmental patterning relies on combinatorial action of inductive cues and employs a number of strategies for signal integration. These include regulation of a single gene by multiple transcription factors and biochemical modification of a single transcription factor by multiple signaling pathways. Using the early Drosophila embryo as a model, we show that signal integration can also be mediated by a simple enzymatic network. The anterior structures of Drosophila embryo are specified by two inductive signals. One of them, a homeodomain protein Bicoid, establishes the anteroposterior morphogen gradient. The second (terminal) signal is provided by the localized activation of the MAPK pathway at both anterior and posterior poles. Activated MAPK phosphorylates the uniformly distributed transcriptional repressors Capicua and Groucho, relieving their repression of the terminal gap genes. At the anterior pole, MAPK phosphorylates Bicoid, potentiating its transcriptional effects. Using a combination of biochemical, imaging, and genetic approaches, we demonstrate that modification of Bicoid by MAPK has a reverse effect on MAPK phosphorylation and signaling. In the resulting model, MAPK substrates compete for access to this kinase, establishing an enzyme-substrate competition network that integrates the anterior and terminal signals.


Work done in collaboration with Yoosik Kim, Mathieu Coppey, Leiore Ajuria, Gerardo Jiménez, and Ze'ev Paroush

Bicoid-dependent embryonic patterning in Drosophila

Bicoid is a homeodomain-containing transcription factor that is expressed in a long-range anterior gradient in the early embryo. Loss of Bicoid function leads to a mutant embryo that lacks all head and thoracic structures. Previous studies have identified approximately 20 target genes that are directly activated by Bicoid. Activation of each target gene involves direct binding of Bicoid to one or more enhancers that appear as rather tightly linked clusters of Bicoid-binding sites. These enhancers direct expression patterns at different positions along the anterior posterior axis (Figure 3), and a major goal is to understand the cis-regulatory logic that controls the differential positioning of different target genes. We are using an integrated approach in pursuit of this goal. First, we use bio-informatics methods and published ChIP-Chip data to identify all clusters of Bicoid-binding sites that are similar to those in the known target genes. Candidate clusters are cloned into reporter genes, transformed into the genome, and tested for in vivo activity by in situ hybridization experiments. While collecting an ever-growing number of Bcd-dependent elements, we are using data mining techniques to identify sequence motifs or binding site arrangements that correlate with target gene positioning. This will lead to specific hypotheses that can be tested by in vitro mutagenesis of binding sites in the context of the reporter genes.

Comparative genomics of gene regulation in Drosophila

Many developmental phenomena involve processes that lead to determinate outputs. Lineage information and signaling cues at specific time points, though varied at certain levels, are integrated to yield robust cell fate executions. For sensory systems, fine regulation of gene expression is critical so that information is assessed, relayed, and processed in a specific logical manner. Typically, one molecular receptor type is expressed in a single sensory neuron to prevent sensory confusion.


The fly eye is an example of a sensory system that integrates developmental inputs to yield specific robust cell fate determination. The fly eye is composed of 800 ommatidia (unit eyes) which contain six outer photoreceptors (PRs), R1-6, arranged in a trapezoidal shape surrounding two inner PRs, R7 and R8. The outer PRs express the Rhodopsin1 (Rh1) protein and are used for motion detection. The inner PRs, used for color vision, are organized into two coordinated subtypes. In the pale subtype, R7 expresses Rh3 and Rh8 expresses Rh5 whereas in the yellow subtype, R7 expresses Rh4 and R8 expresses Rh5. Though the distribution of these ommatidial subtypes is spatially randomized throughout the eye, subtype fate determination is robust such that each R7 and R8 expresses a particular rhodopsin in a stable manner and conserved ratio.


How does the fly eye ensure robustness? Here, we describe two distinct roles for the K50 homeodomain transcription factor, Defective proventriculus (Dve). In yellow R7s, Dve specifically represses expression of Rh3. In /dve /mutants, Rh3 is de-repressed in all yellow R7s yielding R7s that express both Rh3 and Rh4. In outer PRs, Dve plays a very different role, repressing noisy expression of Rh3, Rh5, and Rh6. In /dve /null mutants, these rhodopsins are de-repressed in random outer PRs. Dve expression itself is robustly controlled by a complex transcriptional regulatory network. Our analysis suggests that the fly eye utilizes transcriptional repression to mask inherently noisy gene expression and ensure robustness.

Patterning a field of cells: a comparison of dorso-ventral patterning of the embryo and anterior-posterior patterning of the wing disc

N/A

Organism-scale modeling of early Drosophila patterning via Bone Morphogenetic Proteins

Mathematical models of embryonic development are formulated to illuminate how the spatio-temporal expression of genes that presages the adult body plan of an organism is controlled, but many have limited utility because they oversimplify crucial aspects such as the geometry, the molecular mechanisms, and other components in the system being modeled. To circumvent these limitations we developed a data-driven, 3D, organism-scale model of bone morphogenetic protein (BMP)-mediated embryonic patterning in Drosophila. We tested 7 different receptor/feedback mechanisms and 8 different geometry/gene expression scenarios for their ability to reproduce the mean distributions of pMad signaling in both wild-type and more than twenty different mutant embryos. We found that positive feedback of a secreted BMP binding protein, coupled with the measured embryo geometry, provides the best agreement between model and experiment. The inclusion of all important factors in a 3D model represents a significant step forward in the systems biology of development.


Work done with Hans G. Othmer and Michael B. O'Connor.

Evolution of the DV transcriptional regulatory network in closely related Drosophila species

Changes in cis-regulatory elements for transcription are thought be an important driving force for the evolution of species. To investigate how changes in cis-regulatory sequence affect a transcriptional regulatory network during development, we study the dorso-ventral (DV) patterning network in four closely related Drosophila species, D. melanogaster, D. simulans, D. erecta, and D. yakuba. Chromatin immunoprecipitation combined with high throughput-sequencing (ChIP-seq) is used to compare the genome-wide distribution of the transcriptional activator Twist and repressor Snail.


This is work by Qiye He and Brianne Patton, in collaboration with Alex Stark and Manolis Kellis.