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Johannes Jaeger - One of the best experts on this subject based on the ideXlab platform.
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life s attractors continued progress in understanding developmental systems through reverse engineering and in silico evolution
2021Co-Authors: Anton Crombach, Johannes JaegerAbstract:We present a progress report on our efforts to establish a new research program for evolutionary systems biology, based on reverse engineering and in silico evolution. The aim is a mechanistic understanding of the genotype-phenotype map and its evolution. Our review focuses on the case study of the Gap Gene network in dipteran insects (flies and midges). This network is the top regulatory tier of the segmentation Gene hierarchy, Generating a pattern of overlapping expression domains that subdivide the embryo during early embryoGenesis. It is one of the best-understood developmental regulatory networks today. We have studied this system in a comparative way, across three species: the vinegar fly, Drosophila melanogaster; the scuttle fly, Megaselia abdita; and the moth midge, Clogmia albipunctata. In this context, we discuss methodological challenges concerning data processing and model fitting, consider different functional decompositions of the Gap Gene network, and highlight novel insights into network evolution by compensatory developmental system drift. Finally, we discuss the prospect of simulating the phyloGenesis of the Gap Gene network using in silico evolution. We conclude by arguing that our case study is a first step toward a more systematic empirical investigation into the principles of network evolution.
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A damped oscillator governs posterior Gap Gene patterning in Drosophila melanogaster.
2018Co-Authors: Berta Verd, Hilde Janssens, Anton Crombach, Karl R Wotton, Erik Clark, Eva Jiménez-guri, Johannes JaegerAbstract:(A) Kinematic Gap domain shifts and temporal order of Gene expression. Temporal dynamics of Gap Gene expression in posterior nuclei between 55% and 73% A–P position, shown as columns. Developmental time proceeds down the y-axis, covering cleavage cycles 13 (C13) and 14A (C14A; subdivided into time classes T1–T8). C12 shows initial conditions: maternally provided Hb concentrations indicated by yellow shading at the top of each column. Kr concentration is shown in shades of green, Kni in red, and Gt in blue. The kinematic anterior shift of the Kni domain (in red) is clearly visible. Color wheels (at the bottom of the columns) represent ordered succession of Gap Gene expression imposed by the damped oscillator mechanism. Black arrows indicate the section (phase range) of the clock period that the oscillator traverses in each nucleus over the duration of the blastoderm stage. The position of each arrow depends on the initial Hb concentration in that nucleus. See S1 Data, previously published in [32]. (B) Three-dimensional projection of the time-variable phase portrait for the nucleus at 59% A–P position. Axes represent Kr, Kni, and Gt protein concentrations; Hb is present at low levels only early on and is not shown. Spiral sinks are represented by cylinders and are color coded to show the associated developmental time point (see key). The simulated trajectory of the system during C13 and C14A is shown in black (see model parameters in S1 Table); colored points on the trajectory mark its progress through time. Asymptotic convergence of the trajectory (after the blastoderm stage has ended) is shown in gray. S1 Movie shows an animated rotation of this phase portrait to clarify the position of the trajectory in three-dimensional space. (C) Simulated trajectories for nuclei between 53% and 71% A–P position. Projection, axes, and time points as in (B). S2 Movie shows an animated rotation of this graph to clarify the position of trajectories in three-dimensional space. (D) Simulated trajectories for the nuclei between 53% and 73% A–P position are represented unfolded onto the Kr-Kni and Gt-Kni planes, to which they are restricted (see Fig 2C and S2 Movie). Time points as in (B). A–P position of each nucleus in (C) and (D) is given by the shade of gray of the trajectory: lighter colored trajectories correspond to more posterior nuclei (see key). Note that trajectories in (C) and (D) emerge from the same point because initial concentrations of Kr, Kni, and Gt are all zero; Hb is not shown in these panels because it is present as a maternal contribution only in the depicted nuclei. The star marks the nucleus at 59% A–P position. See Materials and methods for time classes and main text for further details. A–P, anteroposterior; Gt, Giant; Hb, Hunchback; Kni, Knirps; Kr, Krüppel.
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Dynamic Maternal Gradients Control Timing and Shift-Rates for Drosophila Gap Gene Expression
PLoS Computational Biology, 2017Co-Authors: Berta Verd, Anton Crombach, Johannes JaegerAbstract:Pattern formation during development is a highly dynamic process. In spite of this, few experimental and modelling approaches take into account the explicit time-dependence of the rules governing regulatory systems. We address this problem by studying dynamic morphogen interpretation by the Gap Gene network in Drosophila melanogaster. Gap Genes are involved in segment determination during early embryoGenesis. They are activated by maternal morphogen gradients encoded by bicoid (bcd) and caudal (cad). These gradients decay at the same time-scale as the establishment of the antero-posterior Gap Gene pattern. We use a reverse-engineering approach, based on data-driven regulatory models called Gene circuits, to isolate and characterise the explicitly time-dependent effects of changing morphogen concentrations on Gap Gene regulation. To achieve this, we simulate the system in the presence and absence of dynamic gradient decay. Comparison between these simulations reveals that maternal morphogen decay controls the timing and limits the rate of Gap Gene expression. In the anterior of the embyro, it affects peak expression and leads to the establishment of smooth spatial boundaries between Gap domains. In the posterior of the embryo, it causes a progressive slow-down in the rate of Gap domain shifts, which is necessary to correctly position domain boundaries and to stabilise the spatial Gap Gene expression pattern. We use a newly developed method for the analysis of transient dynamics in non-autonomous (time-variable) systems to understand the regulatory causes of these effects. By providing a rigorous mechanistic explanation for the role of maternal gradient decay in Gap Gene regulation, our study demonstrates that such analyses are feasible and reveal important aspects of dynamic Gene regulation which would have been missed by a traditional steady-state approach. More Generally, it highlights the importance of transient dynamics for understanding complex regulatory processes in development.
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a damped oscillator imposes temporal order on posterior Gap Gene expression in drosophila
bioRxiv, 2017Co-Authors: Hilde Janssens, Anton Crombach, Karl R Wotton, Eva Jimenezguri, Berta Verd, Erik Clark, Johannes JaegerAbstract:Insects determine their body segments in two different ways. Short-germband insects, such as the flour beetle Tribolium castaneum, use a molecular clock to establish segments sequentially. In contrast, long-germband insects, such as the vinegar fly Drosophila melanogaster, determine all segments simultaneously through a hierarchical cascade of Gene regulation. Gap Genes constitute the first layer of the Drosophila segmentation Gene hierarchy, downstream of maternal gradients. We use data driven modelling and phase space analysis to show that shifting Gap domains in the posterior half of the Drosophila embryo are an emergent property of a robust damped oscillator mechanism. The rate at which Gap domains shift is determined by the level of maternal Caudal (Cad), which also regulates the frequency of the Tribolium molecular clock. Our evidence indicates that the regulatory dynamics underlying long- and short-germband segmentation are much more similar than previously thought. This similarity may help explain why long-germband segmentation evolved convergently multiple times during the radiation of the holometabolan insects.
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dynamic maternal gradients control timing and shift rates for Gap Gene expression
bioRxiv, 2016Co-Authors: Berta Verd, Anton Crombach, Johannes JaegerAbstract:Pattern formation during development is a highly dynamic process. In spite of this, few experimental and modelling approaches take into account the explicit time-dependence of the rules governing regulatory systems. We address this problem by studying dynamic morphogen interpretation by the Gap Gene network in Drosophila melanogaster. Gap Genes are involved in segment determination during early embryoGenesis. They are activated by maternal morphogen gradients encoded by bicoid (bcd) and caudal (cad). These gradients decay at the same time-scale as the establishment of the antero-posterior Gap Gene pattern. We use a reverse-engineering approach, based on data-driven regulatory models called Gene circuits, to isolate and characterise the explicitly time-dependent effects of changing morphogen concentrations on Gap Gene regulation. To achieve this, we simulate the system in the presence and absence of dynamic gradient decay. Comparison between these simulations reveals that maternal morphogen decay controls the timing and limits the rate of Gap Gene expression. In the anterior of the embyro, it affects peak expression and leads to the establishment of smooth spatial boundaries between Gap domains. In the posterior of the embryo, it causes a progressive slow-down in the rate of Gap domain shifts, which is necessary to correctly position domain boundaries and to stabilise the spatial Gap Gene expression pattern. We use a newly developed method for the analysis of transient dynamics in non-autonomous (time-variable) systems to understand the regulatory causes of these effects. By providing a rigorous mechanistic explanation for the role of maternal gradient decay in Gap Gene regulation, our study demonstrates that such analyses are feasible and reveal important aspects of dynamic Gene regulation which would have been missed by a traditional steady-state approach. More Generally, it highlights the importance of transient dynamics for understanding complex regulatory processes in development.
Maria Samsonova - One of the best experts on this subject based on the ideXlab platform.
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translating natural Genetic variation to Gene expression in a computational model of the drosophila Gap Gene regulatory network
PLOS ONE, 2017Co-Authors: Vitaly V Gursky, Sergey V Nuzhdin, Konstantin Kozlov, Ivan V Kulakovskiy, Asif Zubair, Paul Marjoram, David S Lawrie, Maria SamsonovaAbstract:Annotating the genotype-phenotype relationship, and developing a proper quantitative description of the relationship, requires understanding the impact of natural genomic variation on Gene expression. We apply a sequence-level model of Gap Gene expression in the early development of Drosophila to analyze single nucleotide polymorphisms (SNPs) in a panel of natural sequenced D. melanogaster lines. Using a thermodynamic modeling framework, we provide both analytical and computational descriptions of how single-nucleotide variants affect Gene expression. The analysis reveals that the sequence variants increase (decrease) Gene expression if located within binding sites of repressors (activators). We show that the sign of SNP influence (activation or repression) may change in time and space and elucidate the origin of this change in specific examples. The thermodynamic modeling approach predicts non-local and non-linear effects arising from SNPs, and combinations of SNPs, in individual fly genotypes. Simulation of individual fly genotypes using our model reveals that this non-linearity reduces to almost additive inputs from multiple SNPs. Further, we see signatures of the action of purifying selection in the Gap Gene regulatory regions. To infer the specific targets of purifying selection, we analyze the patterns of polymorphism in the data at two phenotypic levels: the strengths of binding and expression. We find that combinations of SNPs show evidence of being under selective pressure, while individual SNPs do not. The model predicts that SNPs appear to accumulate in the genotypes of the natural population in a way biased towards small increases in activating action on the expression pattern. Taken together, these results provide a systems-level view of how Genetic variation translates to the level of Gene regulatory networks via combinatorial SNP effects.
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sequence based model of Gap Gene regulatory network
bioRxiv, 2015Co-Authors: Konstantin Kozlov, Vitaly V Gursky, Ivan V Kulakovskiy, Maria SamsonovaAbstract:Background: The detailed analysis of transcriptional regulation is crucially important for understanding biological processes. The Gap Gene network in Drosophila attracts large interest among researches studying mechanisms of transcriptional regulation. It implements the most upstream regulatory layer of the segmentation Gene network. The knowledge of molecular mechanisms involved in Gap Gene regulation is far less complete than that of Genetics of the system. Mathematical modeling goes beyond insights gained by Genetics and molecular approaches. It allows us to reconstruct wild-type Gene expression patterns in silico, infer underlying regulatory mechanism and prove its sufficiency. Results: We developed a new model that provides a dynamical description of Gap Gene regulatory systems, using detailed DNA-based information, as well as spatial transcription factor concentration data at varying time points. We showed that this model correctly reproduces Gap Gene expression patterns in wild type embryos and is able to predict Gap expression patterns in Kr mutants and four reporter constructs. We used four-fold cross validation test and fitting to random dataset to validate the model and proof its sufficiency in data description. The identifiability analysis showed that most model parameters are well identifiable. We reconstructed the Gap Gene network topology and studied the impact of individual transcription factor binding sites on the model output. We measured this impact by calculating the site regulatory weight as a normalized difference between the residual sum of squares error for the set of all annotated sites and the set, from which the site of interest was left out. Conclusions: The reconstructed topology of the Gap Gene network is in agreement with previous modeling results and data from literature. We showed that 1) the regulatory weights of transcription factor binding sites show very weak correlation with their PWM score; 2) sites with low regulatory weight are important for the model output; 3) functional important sites are not exclusively located in cis-regulatory elements, but are rather dispersed through regulatory region. It is of importance that some of the sites with high functional impact in hb, Kr and kni regulatory regions coincide with strong sites annotated and verified in Dnase I footprint assays. Keywords: transcription; thermodynamics; reaction-diffusion; drosophila
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sequence based model of Gap Gene regulatory network
BMC Genomics, 2014Co-Authors: Konstantin Kozlov, Vitaly V Gursky, Ivan V Kulakovskiy, Maria SamsonovaAbstract:The detailed analysis of transcriptional regulation is crucially important for understanding biological processes. The Gap Gene network in Drosophila attracts large interest among researches studying mechanisms of transcriptional regulation. It implements the most upstream regulatory layer of the segmentation Gene network. The knowledge of molecular mechanisms involved in Gap Gene regulation is far less complete than that of Genetics of the system. Mathematical modeling goes beyond insights gained by Genetics and molecular approaches. It allows us to reconstruct wild-type Gene expression patterns in silico, infer underlying regulatory mechanism and prove its sufficiency. We developed a new model that provides a dynamical description of Gap Gene regulatory systems, using detailed DNA-based information, as well as spatial transcription factor concentration data at varying time points. We showed that this model correctly reproduces Gap Gene expression patterns in wild type embryos and is able to predict Gap expression patterns in Kr mutants and four reporter constructs. We used four-fold cross validation test and fitting to random dataset to validate the model and proof its sufficiency in data description. The identifiability analysis showed that most model parameters are well identifiable. We reconstructed the Gap Gene network topology and studied the impact of individual transcription factor binding sites on the model output. We measured this impact by calculating the site regulatory weight as a normalized difference between the residual sum of squares error for the set of all annotated sites and for the set with the site of interest excluded. The reconstructed topology of the Gap Gene network is in agreement with previous modeling results and data from literature. We showed that 1) the regulatory weights of transcription factor binding sites show very weak correlation with their PWM score; 2) sites with low regulatory weight are important for the model output; 3) functional important sites are not exclusively located in cis-regulatory elements, but are rather dispersed through regulatory region. It is of importance that some of the sites with high functional impact in hb, Kr and kni regulatory regions coincide with strong sites annotated and verified in Dnase I footprint assays.
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modeling of Gap Gene expression in drosophila kruppel mutants
PLOS Computational Biology, 2012Co-Authors: Konstantin Kozlov, John Reinitz, Ekaterina Myasnikova, Svetlana Surkova, Maria SamsonovaAbstract:The segmentation Gene network in Drosophila embryo solves the fundamental problem of embryonic patterning: how to establish a periodic pattern of Gene expression, which determines both the positions and the identities of body segments. The Gap Gene network constitutes the first zygotic regulatory tier in this process. Here we have applied the systems-level approach to investigate the regulatory effect of Gap Gene Kruppel (Kr) on segmentation Gene expression. We acquired a large dataset on the expression of Gap Genes in Kr null mutants and demonstrated that the expression levels of these Genes are significantly reduced in the second half of cycle 14A. To explain this novel biological result we applied the Gene circuit method which extracts regulatory information from spatial Gene expression data. Previous attempts to use this formalism to correctly and quantitatively reproduce Gap Gene expression in mutants for a trunk Gap Gene failed, therefore here we constructed a revised model and showed that it correctly reproduces the expression patterns of Gap Genes in Kr null mutants. We found that the remarkable alteration of Gap Gene expression patterns in Kr mutants can be explained by the dynamic decrease of activating effect of Cad on a target Gene and exclusion of Kr Gene from the complex network of Gap Gene interactions, that makes it possible for other interactions, in particular, between hb and gt, to come into effect. The successful modeling of the quantitative aspects of Gap Gene expression in mutant for the trunk Gap Gene Kr is a significant achievement of this work. This result also clearly indicates that the oversimplified representation of transcriptional regulation in the previous models is one of the reasons for unsuccessful attempts of mutant simulations.
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mechanisms of Gap Gene expression canalization in the drosophila blastoderm
BMC Systems Biology, 2011Co-Authors: Vitaly V Gursky, John Reinitz, Lena Panok, Ekaterina Myasnikova, Maria Samsonova, A M SamsonovAbstract:Background Extensive variation in early Gap Gene expression in the Drosophila blastoderm is reduced over time because of Gap Gene cross regulation. This phenomenon is a manifestation of canalization, the ability of an organism to produce a consistent phenotype despite variations in genotype or environment. The canalization of Gap Gene expression can be understood as arising from the actions of attractors in the Gap Gene dynamical system.
John Reinitz - One of the best experts on this subject based on the ideXlab platform.
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modeling of Gap Gene expression in drosophila kruppel mutants
PLOS Computational Biology, 2012Co-Authors: Konstantin Kozlov, John Reinitz, Ekaterina Myasnikova, Svetlana Surkova, Maria SamsonovaAbstract:The segmentation Gene network in Drosophila embryo solves the fundamental problem of embryonic patterning: how to establish a periodic pattern of Gene expression, which determines both the positions and the identities of body segments. The Gap Gene network constitutes the first zygotic regulatory tier in this process. Here we have applied the systems-level approach to investigate the regulatory effect of Gap Gene Kruppel (Kr) on segmentation Gene expression. We acquired a large dataset on the expression of Gap Genes in Kr null mutants and demonstrated that the expression levels of these Genes are significantly reduced in the second half of cycle 14A. To explain this novel biological result we applied the Gene circuit method which extracts regulatory information from spatial Gene expression data. Previous attempts to use this formalism to correctly and quantitatively reproduce Gap Gene expression in mutants for a trunk Gap Gene failed, therefore here we constructed a revised model and showed that it correctly reproduces the expression patterns of Gap Genes in Kr null mutants. We found that the remarkable alteration of Gap Gene expression patterns in Kr mutants can be explained by the dynamic decrease of activating effect of Cad on a target Gene and exclusion of Kr Gene from the complex network of Gap Gene interactions, that makes it possible for other interactions, in particular, between hb and gt, to come into effect. The successful modeling of the quantitative aspects of Gap Gene expression in mutant for the trunk Gap Gene Kr is a significant achievement of this work. This result also clearly indicates that the oversimplified representation of transcriptional regulation in the previous models is one of the reasons for unsuccessful attempts of mutant simulations.
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mechanisms of Gap Gene expression canalization in the drosophila blastoderm
BMC Systems Biology, 2011Co-Authors: Vitaly V Gursky, John Reinitz, Lena Panok, Ekaterina Myasnikova, Maria Samsonova, A M SamsonovAbstract:Background Extensive variation in early Gap Gene expression in the Drosophila blastoderm is reduced over time because of Gap Gene cross regulation. This phenomenon is a manifestation of canalization, the ability of an organism to produce a consistent phenotype despite variations in genotype or environment. The canalization of Gap Gene expression can be understood as arising from the actions of attractors in the Gap Gene dynamical system.
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mechanisms of Gap Gene expression canalization in the drosophila blastoderm
BMC Systems Biology, 2011Co-Authors: Vitaly V Gursky, John Reinitz, Lena Panok, Ekaterina Myasnikova, Maria Samsonova, A M SamsonovAbstract:Extensive variation in early Gap Gene expression in the Drosophila blastoderm is reduced over time because of Gap Gene cross regulation. This phenomenon is a manifestation of canalization, the ability of an organism to produce a consistent phenotype despite variations in genotype or environment. The canalization of Gap Gene expression can be understood as arising from the actions of attractors in the Gap Gene dynamical system. In order to better understand the processes of developmental robustness and canalization in the early Drosophila embryo, we investigated the dynamical effects of varying spatial profiles of Bicoid protein concentration on the formation of the expression border of the Gap Gene hunchback. At several positions on the anterior-posterior axis of the embryo, we analyzed attractors and their basins of attraction in a dynamical model describing expression of four Gap Genes with the Bicoid concentration profile accounted as a given input in the model equations. This model was tested against a family of Bicoid gradients obtained from individual embryos. These gradients were normalized by two independent methods, which are based on distinct biological hypotheses and provide different magnitudes for Bicoid spatial variability. We showed how the border formation is dictated by the biological initial conditions (the concentration gradient of maternal Hunchback protein) being attracted to specific attracting sets in a local vicinity of the border. Different types of these attracting sets (point attractors or one dimensional attracting manifolds) define several possible mechanisms of border formation. The hunchback border formation is associated with intersection of the spatial gradient of the maternal Hunchback protein and a boundary between the attraction basins of two different point attractors. We demonstrated how the positional variability for hunchback is related to the corresponding variability of the basin boundaries. The observed reduction in variability of the hunchback Gene expression can be accounted for by specific geometrical properties of the basin boundaries. We clarified the mechanisms of Gap Gene expression canalization in early Drosophila embryos. These mechanisms were specified in the case of hunchback in well defined terms of the dynamical system theory.
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canalization of Gene expression and domain shifts in the drosophila blastoderm by dynamical attractors
PLOS Computational Biology, 2009Co-Authors: Svetlana Surkova, Vitaly V Gursky, Maria Samsonova, Hilde Janssens, Carlos E Vanarioalonso, David H Sharp, Alexander V Spirov, Ahram Kim, Ovidiu Radulescu, John ReinitzAbstract:The variation in the expression patterns of the Gap Genes in the blastoderm of the fruit fly Drosophila melanogaster reduces over time as a result of cross regulation between these Genes, a fact that we have demonstrated in an accompanying article in PLoS Biology (see Manu et al., doi:10.1371/journal.pbio.1000049). This biologically essential process is an example of the phenomenon known as canalization. It has been suggested that the developmental trajectory of a wild-type organism is inherently stable, and that canalization is a manifestation of this property. Although the role of Gap Genes in the canalization process was established by correctly predicting the response of the system to particular perturbations, the stability of the developmental trajectory remains to be investigated. For many years, it has been speculated that stability against perturbations during development can be described by dynamical systems having attracting sets that drive reductions of volume in phase space. In this paper, we show that both the reduction in variability of Gap Gene expression as well as shifts in the position of posterior Gap Gene domains are the result of the actions of attractors in the Gap Gene dynamical system. Two biologically distinct dynamical regions exist in the early embryo, separated by a bifurcation at 53% egg length. In the anterior region, reduction in variation occurs because of stability induced by point attractors, while in the posterior, the stability of the developmental trajectory arises from a one-dimensional attracting manifold. This manifold also controls a previously characterized anterior shift of posterior region Gap domains. Our analysis shows that the complex phenomena of canalization and pattern formation in the Drosophila blastoderm can be understood in terms of the qualitative features of the dynamical system. The result confirms the idea that attractors are important for developmental stability and shows a richer variety of dynamical attractors in developmental systems than has been previously recognized.
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canalization of Gene expression in the drosophila blastoderm by Gap Gene cross regulation
PLOS Biology, 2009Co-Authors: Svetlana Surkova, Vitaly V Gursky, Maria Samsonova, Hilde Janssens, Carlos E Vanarioalonso, David H Sharp, Alexander V Spirov, Ahram Kim, Ovidiu Radulescu, John ReinitzAbstract:Developing embryos exhibit a robust capability to reduce phenotypic variations that occur naturally or as a result of experimental manipulation. This reduction in variation occurs by an epiGenetic mechanism called canalization, a phenomenon which has resisted understanding because of a lack of necessary molecular data and of appropriate Gene regulation models. In recent years, quantitative Gene expression data have become available for the segment determination process in the Drosophila blastoderm, revealing a specific instance of canalization. These data show that the variation of the zygotic segmentation Gene expression patterns is markedly reduced compared to earlier levels by the time gastrulation begins, and this variation is significantly lower than the variation of the maternal protein gradient Bicoid. We used a predictive dynamical model of Gene regulation to study the effect of Bicoid variation on the downstream Gap Genes. The model correctly predicts the reduced variation of the Gap Gene expression patterns and allows the characterization of the canalizing mechanism. We show that the canalization is the result of specific regulatory interactions among the zygotic Gap Genes. We demonstrate the validity of this explanation by showing that variation is increased in embryos mutant for two Gap Genes, Kruppel and knirps, disproving competing proposals that canalization is due to an undiscovered morphogen, or that it does not take place at all. In an accompanying article in PLoS Computational Biology (doi:10.1371/journal.pcbi.1000303), we show that cross regulation between the Gap Genes causes their expression to approach dynamical attractors, reducing initial variation and providing a robust output. These results demonstrate that the Bicoid gradient is not sufficient to produce Gap Gene borders having the low variance observed, and instead this low variance is Generated by Gap Gene cross regulation. More Generally, we show that the complex multigenic phenomenon of canalization can be understood at a quantitative and predictive level by the application of a precise dynamical model.
Vitaly V Gursky - One of the best experts on this subject based on the ideXlab platform.
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translating natural Genetic variation to Gene expression in a computational model of the drosophila Gap Gene regulatory network
PLOS ONE, 2017Co-Authors: Vitaly V Gursky, Sergey V Nuzhdin, Konstantin Kozlov, Ivan V Kulakovskiy, Asif Zubair, Paul Marjoram, David S Lawrie, Maria SamsonovaAbstract:Annotating the genotype-phenotype relationship, and developing a proper quantitative description of the relationship, requires understanding the impact of natural genomic variation on Gene expression. We apply a sequence-level model of Gap Gene expression in the early development of Drosophila to analyze single nucleotide polymorphisms (SNPs) in a panel of natural sequenced D. melanogaster lines. Using a thermodynamic modeling framework, we provide both analytical and computational descriptions of how single-nucleotide variants affect Gene expression. The analysis reveals that the sequence variants increase (decrease) Gene expression if located within binding sites of repressors (activators). We show that the sign of SNP influence (activation or repression) may change in time and space and elucidate the origin of this change in specific examples. The thermodynamic modeling approach predicts non-local and non-linear effects arising from SNPs, and combinations of SNPs, in individual fly genotypes. Simulation of individual fly genotypes using our model reveals that this non-linearity reduces to almost additive inputs from multiple SNPs. Further, we see signatures of the action of purifying selection in the Gap Gene regulatory regions. To infer the specific targets of purifying selection, we analyze the patterns of polymorphism in the data at two phenotypic levels: the strengths of binding and expression. We find that combinations of SNPs show evidence of being under selective pressure, while individual SNPs do not. The model predicts that SNPs appear to accumulate in the genotypes of the natural population in a way biased towards small increases in activating action on the expression pattern. Taken together, these results provide a systems-level view of how Genetic variation translates to the level of Gene regulatory networks via combinatorial SNP effects.
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In silico evolution of the Drosophila Gap Gene regulatory sequence under elevated mutational pressure.
BMC evolutionary biology, 2017Co-Authors: Aleksandra A Chertkova, Konstantin N Kozlov, Maria G Samsonova, Joshua S Schiffman, Sergey V Nuzhdin, Vitaly V GurskyAbstract:Cis-regulatory sequences are often composed of many low-affinity transcription factor binding sites (TFBSs). Determining the evolutionary and functional importance of regulatory sequence composition is impeded without a detailed knowledge of the genotype-phenotype map. We simulate the evolution of regulatory sequences involved in Drosophila melanogaster embryo segmentation during early development. Natural selection evaluates Gene expression dynamics produced by a computational model of the developmental network. We observe a dramatic decrease in the total number of transcription factor binding sites through the course of evolution. Despite a decrease in average sequence binding energies through time, the regulatory sequences tend towards organisations containing increased high affinity transcription factor binding sites. Additionally, the binding energies of separate sequence segments demonstrate ubiquitous mutual correlations through time. Fewer than 10% of initial TFBSs are maintained throughout the entire simulation, deemed 'core' sites. These sites have increased functional importance as assessed under wild-type conditions and their binding energy distributions are highly conserved. Furthermore, TFBSs within close proximity of core sites exhibit increased longevity, reflecting functional regulatory interactions with core sites. In response to elevated mutational pressure, evolution tends to sample regulatory sequence organisations with fewer, albeit on average, stronger functional transcription factor binding sites. These organisations are also shaped by the regulatory interactions among core binding sites with sites in their local vicinity.
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sequence based model of Gap Gene regulatory network
bioRxiv, 2015Co-Authors: Konstantin Kozlov, Vitaly V Gursky, Ivan V Kulakovskiy, Maria SamsonovaAbstract:Background: The detailed analysis of transcriptional regulation is crucially important for understanding biological processes. The Gap Gene network in Drosophila attracts large interest among researches studying mechanisms of transcriptional regulation. It implements the most upstream regulatory layer of the segmentation Gene network. The knowledge of molecular mechanisms involved in Gap Gene regulation is far less complete than that of Genetics of the system. Mathematical modeling goes beyond insights gained by Genetics and molecular approaches. It allows us to reconstruct wild-type Gene expression patterns in silico, infer underlying regulatory mechanism and prove its sufficiency. Results: We developed a new model that provides a dynamical description of Gap Gene regulatory systems, using detailed DNA-based information, as well as spatial transcription factor concentration data at varying time points. We showed that this model correctly reproduces Gap Gene expression patterns in wild type embryos and is able to predict Gap expression patterns in Kr mutants and four reporter constructs. We used four-fold cross validation test and fitting to random dataset to validate the model and proof its sufficiency in data description. The identifiability analysis showed that most model parameters are well identifiable. We reconstructed the Gap Gene network topology and studied the impact of individual transcription factor binding sites on the model output. We measured this impact by calculating the site regulatory weight as a normalized difference between the residual sum of squares error for the set of all annotated sites and the set, from which the site of interest was left out. Conclusions: The reconstructed topology of the Gap Gene network is in agreement with previous modeling results and data from literature. We showed that 1) the regulatory weights of transcription factor binding sites show very weak correlation with their PWM score; 2) sites with low regulatory weight are important for the model output; 3) functional important sites are not exclusively located in cis-regulatory elements, but are rather dispersed through regulatory region. It is of importance that some of the sites with high functional impact in hb, Kr and kni regulatory regions coincide with strong sites annotated and verified in Dnase I footprint assays. Keywords: transcription; thermodynamics; reaction-diffusion; drosophila
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sequence based model of Gap Gene regulatory network
BMC Genomics, 2014Co-Authors: Konstantin Kozlov, Vitaly V Gursky, Ivan V Kulakovskiy, Maria SamsonovaAbstract:The detailed analysis of transcriptional regulation is crucially important for understanding biological processes. The Gap Gene network in Drosophila attracts large interest among researches studying mechanisms of transcriptional regulation. It implements the most upstream regulatory layer of the segmentation Gene network. The knowledge of molecular mechanisms involved in Gap Gene regulation is far less complete than that of Genetics of the system. Mathematical modeling goes beyond insights gained by Genetics and molecular approaches. It allows us to reconstruct wild-type Gene expression patterns in silico, infer underlying regulatory mechanism and prove its sufficiency. We developed a new model that provides a dynamical description of Gap Gene regulatory systems, using detailed DNA-based information, as well as spatial transcription factor concentration data at varying time points. We showed that this model correctly reproduces Gap Gene expression patterns in wild type embryos and is able to predict Gap expression patterns in Kr mutants and four reporter constructs. We used four-fold cross validation test and fitting to random dataset to validate the model and proof its sufficiency in data description. The identifiability analysis showed that most model parameters are well identifiable. We reconstructed the Gap Gene network topology and studied the impact of individual transcription factor binding sites on the model output. We measured this impact by calculating the site regulatory weight as a normalized difference between the residual sum of squares error for the set of all annotated sites and for the set with the site of interest excluded. The reconstructed topology of the Gap Gene network is in agreement with previous modeling results and data from literature. We showed that 1) the regulatory weights of transcription factor binding sites show very weak correlation with their PWM score; 2) sites with low regulatory weight are important for the model output; 3) functional important sites are not exclusively located in cis-regulatory elements, but are rather dispersed through regulatory region. It is of importance that some of the sites with high functional impact in hb, Kr and kni regulatory regions coincide with strong sites annotated and verified in Dnase I footprint assays.
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mechanisms of Gap Gene expression canalization in the drosophila blastoderm
BMC Systems Biology, 2011Co-Authors: Vitaly V Gursky, John Reinitz, Lena Panok, Ekaterina Myasnikova, Maria Samsonova, A M SamsonovAbstract:Background Extensive variation in early Gap Gene expression in the Drosophila blastoderm is reduced over time because of Gap Gene cross regulation. This phenomenon is a manifestation of canalization, the ability of an organism to produce a consistent phenotype despite variations in genotype or environment. The canalization of Gap Gene expression can be understood as arising from the actions of attractors in the Gap Gene dynamical system.
Hilde Janssens - One of the best experts on this subject based on the ideXlab platform.
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a damped oscillator imposes temporal order on posterior Gap Gene expression in drosophila
PLOS Biology, 2018Co-Authors: Hilde Janssens, Karl R Wotton, Eva Jimenezguri, Berta Verd, Erik ClarkAbstract:Insects determine their body segments in two different ways. Short-germband insects, such as the flour beetle Tribolium castaneum, use a molecular clock to establish segments sequentially. In contrast, long-germband insects, such as the vinegar fly Drosophila melanogaster, determine all segments simultaneously through a hierarchical cascade of Gene regulation. Gap Genes constitute the first layer of the Drosophila segmentation Gene hierarchy, downstream of maternal gradients such as that of Caudal (Cad). We use data-driven mathematical modelling and phase space analysis to show that shifting Gap domains in the posterior half of the Drosophila embryo are an emergent property of a robust damped oscillator mechanism, suggesting that the regulatory dynamics underlying long- and short-germband segmentation are much more similar than previously thought. In Tribolium, Cad has been proposed to modulate the frequency of the segmentation oscillator. Surprisingly, our simulations and experiments show that the shift rate of posterior Gap domains is independent of maternal Cad levels in Drosophila. Our results suggest a novel evolutionary scenario for the short- to long-germband transition and help explain why this transition occurred convergently multiple times during the radiation of the holometabolan insects.
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A damped oscillator governs posterior Gap Gene patterning in Drosophila melanogaster.
2018Co-Authors: Berta Verd, Hilde Janssens, Anton Crombach, Karl R Wotton, Erik Clark, Eva Jiménez-guri, Johannes JaegerAbstract:(A) Kinematic Gap domain shifts and temporal order of Gene expression. Temporal dynamics of Gap Gene expression in posterior nuclei between 55% and 73% A–P position, shown as columns. Developmental time proceeds down the y-axis, covering cleavage cycles 13 (C13) and 14A (C14A; subdivided into time classes T1–T8). C12 shows initial conditions: maternally provided Hb concentrations indicated by yellow shading at the top of each column. Kr concentration is shown in shades of green, Kni in red, and Gt in blue. The kinematic anterior shift of the Kni domain (in red) is clearly visible. Color wheels (at the bottom of the columns) represent ordered succession of Gap Gene expression imposed by the damped oscillator mechanism. Black arrows indicate the section (phase range) of the clock period that the oscillator traverses in each nucleus over the duration of the blastoderm stage. The position of each arrow depends on the initial Hb concentration in that nucleus. See S1 Data, previously published in [32]. (B) Three-dimensional projection of the time-variable phase portrait for the nucleus at 59% A–P position. Axes represent Kr, Kni, and Gt protein concentrations; Hb is present at low levels only early on and is not shown. Spiral sinks are represented by cylinders and are color coded to show the associated developmental time point (see key). The simulated trajectory of the system during C13 and C14A is shown in black (see model parameters in S1 Table); colored points on the trajectory mark its progress through time. Asymptotic convergence of the trajectory (after the blastoderm stage has ended) is shown in gray. S1 Movie shows an animated rotation of this phase portrait to clarify the position of the trajectory in three-dimensional space. (C) Simulated trajectories for nuclei between 53% and 71% A–P position. Projection, axes, and time points as in (B). S2 Movie shows an animated rotation of this graph to clarify the position of trajectories in three-dimensional space. (D) Simulated trajectories for the nuclei between 53% and 73% A–P position are represented unfolded onto the Kr-Kni and Gt-Kni planes, to which they are restricted (see Fig 2C and S2 Movie). Time points as in (B). A–P position of each nucleus in (C) and (D) is given by the shade of gray of the trajectory: lighter colored trajectories correspond to more posterior nuclei (see key). Note that trajectories in (C) and (D) emerge from the same point because initial concentrations of Kr, Kni, and Gt are all zero; Hb is not shown in these panels because it is present as a maternal contribution only in the depicted nuclei. The star marks the nucleus at 59% A–P position. See Materials and methods for time classes and main text for further details. A–P, anteroposterior; Gt, Giant; Hb, Hunchback; Kni, Knirps; Kr, Krüppel.
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a damped oscillator imposes temporal order on posterior Gap Gene expression in drosophila
bioRxiv, 2017Co-Authors: Hilde Janssens, Anton Crombach, Karl R Wotton, Eva Jimenezguri, Berta Verd, Erik Clark, Johannes JaegerAbstract:Insects determine their body segments in two different ways. Short-germband insects, such as the flour beetle Tribolium castaneum, use a molecular clock to establish segments sequentially. In contrast, long-germband insects, such as the vinegar fly Drosophila melanogaster, determine all segments simultaneously through a hierarchical cascade of Gene regulation. Gap Genes constitute the first layer of the Drosophila segmentation Gene hierarchy, downstream of maternal gradients. We use data driven modelling and phase space analysis to show that shifting Gap domains in the posterior half of the Drosophila embryo are an emergent property of a robust damped oscillator mechanism. The rate at which Gap domains shift is determined by the level of maternal Caudal (Cad), which also regulates the frequency of the Tribolium molecular clock. Our evidence indicates that the regulatory dynamics underlying long- and short-germband segmentation are much more similar than previously thought. This similarity may help explain why long-germband segmentation evolved convergently multiple times during the radiation of the holometabolan insects.
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quantitative system drift compensates for altered maternal inputs to the Gap Gene network of the scuttle fly megaselia abdita
eLife, 2015Co-Authors: Karl R Wotton, Hilde Janssens, Anton Crombach, Eva Jimenezguri, Anna Alcainecolet, Steffen Lemke, Urs Schmidtott, Johannes JaegerAbstract:Similar biological phenomena can result from different processes occurring in different organisms. For example, the early stages of how an insect develops from an egg can vary substantially between different species. Nonetheless, all insects have a body plan that develops in segments. The same outcome occurring as a result of different developmental steps is known as ‘system drift’, but the mechanisms underlying this phenomenon are largely unknown. How the body segments of the fruit fly Drosophila develop has been extensively studied. First, a female fruit fly adds messenger RNA (or mRNA) molecules copied from a number of Genes into her egg cells. These mRNA molecules are then used to produce proteins whose concentration varies along the length of each egg. These proteins in turn switch on so-called ‘Gap Genes’ in differing amounts in different locations throughout the fruit fly embryo. The activity of these Genes goes on to define the position and extent of specific segments along the fruit fly's body. Like the fruit fly, the scuttle fly Megaselia abdita has a segmented body. However, mothers of this species deposit somewhat different protein gradients into their eggs. How the regulation of development differs in the scuttle fly to compensate for this change is unknown. Now, Wotton et al. have studied, in detail, how Gap Genes are regulated in this less well-understood fly species to understand the mechanisms responsible for a specific example of system drift. In the fruit fly, Gap Genes normally switch-off (or reduce the expression of) other Gap Genes within the same developing body segment, and Wotton et al. found that the same kind of interactions tended to occur in the scuttle fly. As such, the overall structure of the Gap Gene network was fairly similar between scuttle and fruit flies. There were, however, differences in the strength of these interactions in the two fly species. These quantitative differences result in a different way of making the same segmental pattern in the embryo. In this way, Wotton et al. show how tinkering with the strength of specific Gene interactions can provide an explanation for system drift.
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Reverse-Engineering Post-Transcriptional Regulation of Gap Genes in Drosophila melanogaster
2013Co-Authors: Kolja Becker, Hilde Janssens, Eva Balsa-canto, Damjan Cicin-sain, Astrid Hoermann, Julio R. Banga, Johannes JaegerAbstract:Systems biology proceeds through repeated cycles of experiment and modeling. One way to implement this is reverse engineering, where models are fit to data to infer and analyse regulatory mechanisms. This requires rigorous methods to determine whether model parameters can be properly identified. Applying such methods in a complex biological context remains challenging. We use reverse engineering to study post-transcriptional regulation in pattern formation. As a case study, we analyse expression of the Gap Genes Krüppel, knirps, and giant in Drosophila melanogaster. We use detailed, quantitative datasets of Gap Gene mRNA and protein expression to solve and fit a model of post-transcriptional regulation, and establish its structural and practical identifiability. Our results demonstrate that post-transcriptional regulation is not required for patterning in this system, but is necessary for proper control of protein levels. Our work demonstrates that the uniqueness and specificity of a fitted model can be rigorously determined in the context of spatio-temporal pattern formation. This greatly increases the potential of reverse engineering for the study of development and other, similarly complex, biological processes
