Temporal and spatial dynamics of scaling-specific features of a gene regulatory network in Drosophila

Approximated gene expression trajectories for gene regulatory network inference on cell tracks

The study of pattern formation has benefited from our ability to reverse-engineer gene regulatory network (GRN) structure from spatiotemporal quantitative gene expression data. Traditional approaches have focused on systems where the timescales of pattern formation and morphogenesis can be separated. Unfortunately, this is not the case in most animal patterning systems, where pattern formation and morphogenesis are co-occurring and tightly linked. To elucidate patterning mechanisms in such systems we need to adapt our GRN inference methodologies to include cell movements. In this work, we fill this gap by integrating quantitative data from live and fixed embryos to approximate gene expression trajectories (AGETs) in single cells and use these to reverse-engineer GRNs. This framework generates candidate GRNs that recapitulate pattern at the tissue level, gene expression dynamics at the single cell level, recover known genetic interactions and recapitulate experimental perturbations while incorporating cell movements explicitly for the first time.

Body plan evolvability: The role of variability in gene regulatory networks

Recent computational modeling of early fruit fly (Drosophila) development has characterized the degree to which gene regulation networks can be robust to natural variability. In the first few hours of development, broad spatial gradients of maternally derived transcription factors activate embryonic gap genes. These gap patterns determine the subsequent segmented insect body plan through pair-rule gene expression. Gap genes are expressed with greater spatial precision than the maternal patterns. Computational modeling of the gap-gap regulatory interactions provides a mechanistic understanding for this robustness to maternal variability in wild-type (WT) patterning. A long-standing question in evolutionary biology has been how a system which is robust, such as the developmental program creating any particular species' body plan, is also evolvable, i.e. how can a system evolve or speciate, if the WT form is strongly buffered and protected? In the present work, we use the WT model to explore the breakdown of such Waddington-type 'canalization'. What levels of variability will push the system out of the WT form; are there particular pathways in the gene regulatory mechanism which are more susceptible to losing the WT form; and when robustness is lost, what types of forms are most likely to occur (i.e. what forms lie near the WT)? Manipulating maternal effects in several different pathways, we find a common gap 'peak-to-step' pattern transition in the loss of WT. We discuss these results in terms of the evolvability of insect segmentation, and in terms of experimental perturbations and mutations which could test the model predictions. We conclude by discussing the prospects for using continuum models of pattern dynamics to investigate a wider range of evo-devo problems.

Size regulation of the lateral organ initiation zone and its role in determining cotyledon number in conifers

Introduction

Unlike monocots and dicots, many conifers, particularly Pinaceae, form three or more cotyledons. These are arranged in a whorl, or ring, at a particular distance from the embryo tip, with cotyledons evenly spaced within the ring. The number of cotyledons, n_c, varies substantially within species, both in clonal cultures and in seed embryos. n_c variability reflects embryo size variability, with larger diameter embryos having higher n_c. Correcting for growth during embryo development, we extract values for the whorl radius at each n_c. This radius, corresponding to the spatial pattern of cotyledon differentiation factors, varies over three-fold for the naturally observed range of n_c. The current work focuses on factors in the patterning mechanism that could produce such a broad variability in whorl radius. Molecularly, work in Arabidopsis has shown that the initiation zone for leaf primordia occurs at a minimum between inhibitor zones of HD-ZIP III at the shoot apical meristem (SAM) tip and KANADI (KAN) encircling this farther from the tip. PIN1-auxin dynamics within this uninhibited ring form auxin maxima, specifying primordia initiation sites. A similar mechanism is indicated in conifer embryos by effects on cotyledon formation with overexpression of HD-ZIP III inhibitors and by interference with PIN1-auxin patterning.

Methods

We develop a mathematical model for HD-ZIP III/KAN spatial localization and use this to characterize the molecular regulation that could generate (a) the three-fold whorl radius variation (and associated n_c variability) observed in conifer cotyledon development, and (b) the HD-ZIP III and KAN shifts induced experimentally in conifer embryos and in Arabidopsis.

Results

This quantitative framework indicates the sensitivity of mechanism components for positioning lateral organs closer to or farther from the tip. Positional shifting is most readily driven by changes to the extent of upstream (meristematic) patterning and changes in HD-ZIP III/KAN mutual inhibition, and less efficiently driven by changes in upstream dosage or the activation of HD-ZIP III. Sharper expression boundaries can also be more resistant to shifting than shallower expression boundaries.

Discussion

The strong variability seen in conifer n_c (commonly from 2 to 10) may reflect a freer variation in regulatory interactions, whereas monocot (n_c = 1) and dicot (n_c = 2) development may require tighter control of such variation. These results provide direction for future quantitative experiments on the positional control of lateral organ initiation, and consequently on plant phyllotaxy and architecture.

Targeting the mitochondrial Ca2+ uniporter complex in cardiovascular disease

Cardiovascular diseases (CVDs), the leading cause of death worldwide, share in common mitochondrial dysfunction, in specific a dysregulation of Ca²⁺ uptake dynamics through the mitochondrial Ca²⁺ uniporter (MCU) complex. In particular, Ca²⁺ uptake regulates the mitochondrial ATP production, mitochondrial dynamics, oxidative stress, and cell death. Therefore, modulating the activity of the MCU complex to regulate Ca²⁺ uptake, has been suggested as a potential therapeutic approach for the treatment of CVDs. Here, the role and implications of the MCU complex in CVDs are presented, followed by a review of the evidence for MCU complex modulation, genetically and pharmacologically. While most approaches have aimed within the MCU complex for the modulation of the Ca²⁺ pore channel, the MCU subunit, its intra- and extra- mitochondrial implications, including Ca²⁺ dynamics, oxidative stress, post-translational modifications, and its repercussions in the cardiac function, highlight that targeting the MCU complex has the translational potential for novel CVDs therapeutics.

Shaping the scaling characteristics of gap gene expression patterns in Drosophila

How patterns are formed to scale with tissue size remains an unresolved problem. Here we investigate embryonic patterns of gap gene expression along the anterior-posterior (AP) axis in Drosophila. We use embryos that greatly differ in length and, importantly, possess distinct length-scaling characteristics of the Bicoid (Bcd) gradient. We systematically analyze the dynamic movements of gap gene expression boundaries in relation to both embryo length and Bcd input as a function of time. We document the process through which such dynamic movements drive both an emergence of a global scaling landscape and evolution of boundary-specific scaling characteristics. We show that, despite initial differences in pattern scaling characteristics that mimic those of Bcd in the anterior, such characteristics of final patterns converge. Our study thus partitions the contributions of Bcd input and regulatory dynamics inherent to the AP patterning network in shaping embryonic pattern's scaling characteristics.

Scaling dictates the decoder structure

Despite fluctuations in embryo size within a species, the spatial gene expression pattern and hence the embryonic structure can nonetheless maintain the correct proportion to the embryo size. This is known as the scaling phenomenon. For morphogen-induced patterning of gene expression, the positional information encoded in the local morphogen concentrations is decoded by the downstream genetic network (the decoder). In this paper, we show that the requirement of scaling sets severe constraints on the geometric structure of such a local decoder, which in turn enables deduction of mutants' behavior and extraction of regulation information without going into any molecular details. We demonstrate that the Drosophila gap gene system achieves scaling in the way consistent with our theory-the decoder geometry required by scaling correctly accounts for the observed gap gene expression pattern in nearly all maternal morphogen mutants. Furthermore, the regulation logic and the coding/decoding strategy of the gap gene system can also be revealed from the decoder geometry. Our work provides a general theoretical framework for a large class of problems where scaling output is achieved by non-scaling inputs and a local decoder, as well as a unified understanding of scaling, mutants' behavior, and gene regulation for the Drosophila gap gene system.

A systematic review on the effects of acrylamide and bisphenol A on the development of Drosophila melanogaster

The current global scenario has instigated a steady upsurge of synthetic chemicals usage thereby creating a toxic environment unsuitable for animals and humans. Acrylamide and bisphenol A are some of the most common toxins found in the atmosphere due to their extensive involvement in numerous industrial processes. Acrylamide, an occupational hazard toxin has been known to cause severe nerve damage and peripheral neuronal damage in both animals and humans. General sources of acrylamide exposure are effluents from textile and paper industries, cosmetics, and thermally processed foods rich in starch. Bisphenol A (BPA) is generally found in food packaging materials, dental sealants, and plastic bottles. It is highly temperature-sensitive that can easily leach into the food products or humans on contact. The genotoxic and neurotoxic effects of acrylamide and bisphenol A have been widely researched; however, more attention should be dedicated to understanding the developmental toxicity of these chemicals. The developmental impacts of toxin exposure can be easily understood using Drosophila melanogaster as a model given considering its short life span and genetic homology to humans. In this review, we have discussed the toxic effects of acrylamide and BPA on the developmental process of Drosophila melanogaster.

Data-driven modeling predicts gene regulatory network dynamics during the differentiation of multipotential hematopoietic progenitors

Cellular differentiation during hematopoiesis is guided by gene regulatory networks (GRNs) comprising transcription factors (TFs) and the effectors of cytokine signaling. Based largely on analyses conducted at steady state, these GRNs are thought to be organized as a hierarchy of bistable switches, with antagonism between Gata1 and PU.1 driving red- and white-blood cell differentiation. Here, we utilize transient gene expression patterns to infer the genetic architecture—the type and strength of regulatory interconnections—and dynamics of a twelve-gene GRN including key TFs and cytokine receptors. We trained gene circuits, dynamical models that learn genetic architecture, on high temporal-resolution gene-expression data from the differentiation of an inducible cell line into erythrocytes and neutrophils. The model is able to predict the consequences of gene knockout, knockdown, and overexpression experiments and the inferred interconnections are largely consistent with prior empirical evidence. The inferred genetic architecture is densely interconnected rather than hierarchical, featuring extensive cross-antagonism between genes from alternative lineages and positive feedback from cytokine receptors. The analysis of the dynamics of gene regulation in the model reveals that PU.1 is one of the last genes to be upregulated in neutrophil conditions and that the upregulation of PU.1 and other neutrophil genes is driven by Cebpa and Gfi1 instead. This model inference is confirmed in an independent single-cell RNA-Seq dataset from mouse bone marrow in which Cebpa and Gfi1 expression precedes the neutrophil-specific upregulation of PU.1 during differentiation. These results demonstrate that full PU.1 upregulation during neutrophil development involves regulatory influences extrinsic to the Gata1-PU.1 bistable switch. Furthermore, although there is extensive cross-antagonism between erythroid and neutrophil genes, it does not have a hierarchical structure. More generally, we show that the combination of high-resolution time series data and data-driven dynamical modeling can uncover the dynamics and causality of developmental events that might otherwise be obscured.

The supply of blood cells is replenished by the maturation of hematopoietic progenitor cells into different cell types. Which cell type a progenitor cell develops into is determined by a complex network of genes whose protein products directly or indirectly regulate each others’ expression and that of downstream genes characteristic of the cell type. We inferred the nature and causality of the regulatory connections in a 12-gene network known to affect the decision between erythrocyte and neutrophil cell fates using a predictive machine-learning approach. Our analysis showed that the overall architecture of the network is densely interconnected and not hierarchical. Furthermore, the model inferred that PU.1, considered a master regulator of all white-blood cell lineages, is upregulated during neutrophil development by two other proteins, Cebpa and Gfi1. We validated this prediction by showing that Cebpa and Gfi1 expression precedes that of PU.1 in single-cell gene expression data from mouse bone marrow. These results revise the architecture of the gene network and the causality of regulatory events guiding hematopoiesis. The results also show that combining machine learning approaches with time course data can help resolve causality during development.

The early Drosophila embryo as a model system for quantitative biology

With the rise of new tools, from controlled genetic manipulations and optogenetics to improved microscopy, it is now possible to make clear, quantitative and reproducible measurements of biological processes. The humble fruit fly Drosophila melanogaster, with its ease of genetic manipulation combined with excellent imaging accessibility, has become a major model system for performing quantitative in vivo measurements. Such measurements are driving a new wave of interest from physicists and engineers, who are developing a range of testable dynamic models of active systems to understand fundamental biological processes. The reproducibility of the early Drosophila embryo has been crucial for understanding how biological systems are robust to unavoidable noise during development. Insights from quantitative in vivo experiments in the Drosophila embryo are having an impact on our understanding of critical biological processes, such as how cells make decisions and how complex tissue shape emerges. Here, to highlight the power of using Drosophila embryogenesis for quantitative biology, I focus on three main areas: (1) formation and robustness of morphogen gradients; (2) how gene regulatory networks ensure precise boundary formation; and (3) how mechanical interactions drive packing and tissue folding. I further discuss how such data has driven advances in modelling.

Dynamic regulation of anterior-posterior patterning genes in living Drosophila embryos

Expression of the gap and pair-rule genes plays an essential role in body segmentation during Drosophila embryogenesis.^1-5 However, it remains unclear how precise expression patterns of these key developmental genes arise from stochastic transcriptional activation at the single-cell level. Here, I employed genome-editing and live-imaging approaches to comprehensively visualize regulation of the gap and pair-rule genes at the endogenous loci. Quantitative image analysis revealed that the total duration of active transcription (transcription period) is a major determinant of spatial patterning of gene expression in early embryos. The length of the transcription period is determined by the continuity of bursting activities in individual nuclei, with the core expression domain producing more bursts than boundary regions. Each gene exhibits a distinct rate of nascent RNA production during transcriptional bursting, which contributes to gene-to-gene variability in the total output. I also provide evidence for "enhancer interference," wherein a distal weak enhancer interferes with transcriptional activation by a strong proximal enhancer to downregulate the length of the transcription period without changing the transcription rate. Analysis of the endogenous hunchback (hb) locus revealed that the removal of the distal shadow enhancer induces strong ectopic transcriptional activation, which suppresses refinement of the initial broad expression domain into narrower stripe patterns at the anterior part of embryos. This study provides key insights into the link between transcriptional bursting, enhancer-promoter interaction, and spatiotemporal patterning of gene expression during animal development.

Selenic Acid Etching Assisted Vacancy Engineering for Designing Highly Active Electrocatalysts toward the Oxygen Evolution Reaction

Oxygen evolution electrocatalysts are central to overall water splitting, and they should meet the requirements of low cost, high activity, high conductivity, and stable performance. Herein, a general, selenic-acid-assisted etching strategy is designed from a metal-organic framework as a precursor to realize carbon-coated 3d metal selenides M_m Se_n (Co_0.85 Se_{1- x} , NiSe_{2- x} , FeSe_{2- x} ) with rich Se vacancies as high-performance precious metal-free oxygen evolution reaction (OER) electrocatalysts. Specifically, the as-prepared Co_0.85 Se_{1- x} @C nanocages deliver an overpotential of only 231 mV at a current density of 10 mA cm^-2 for the OER and the corresponding full water-splitting electrolyzer requires only a cell voltage of 1.49 V at 10 mA cm^-2 in alkaline media. Density functional theory calculation reveals the important role of abundant Se vacancies for improving the catalytic activity through improving the conductivity and reducing reaction barriers for the formation of intermediates. Although phase change after long-term operation is observed with the formation of metal hydroxides, catalytic activity is not obviously affected, which strengthens the important role of the carbon network in the operating stability. This study provides a new opportunity to realize high-performance OER electrocatalysts by a general strategy on selenic acid etching assisted vacancy engineering.

Boranyl-Functionalized [Ge9 ] Clusters: Providing the Idea of Intramolecular Ge/B Frustrated Lewis Pairs

The unique three-dimensional structure of spherical, homoatomic nine-atom germanium clusters opens various possibilities for the spatial arrangement of functional groups. Ligands comprising lone pairs have recently been introduced in the cluster sphere, and we now report the addition of a boranyl group to the cluster featuring a Ge-B exo-cluster bond. The reaction of the twofold-silylated cluster [Ge9 {Si(TMS)3 }2 ]2- (TMS=trimethylsilyl) with 2-chloro-1,3,2-diazaborolidines DABR -Cl leads to the first boranyl-functionalized [Ge9 ] clusters [Ge9 {Si(TMS)3 }2 DABR ]- (R=methyl (1 a), iso-propyl (2 a), ortho-tolyl (3 a)). The anions 2 a and 3 a were structurally characterized as [NHCDipp Cu]+ complexes (NHCDipp =1,3-di(2,6-diisopropylphenyl)imidazolylidine) through single crystal X-ray structure determination. Quantum-chemical calculations manifest the frustrated Lewis pair (FLP) character of the boranyl-functionalized cluster [Ge9 {Si(TMS)3 }2 BCy2 ]- (4 a).

Dynamic patterning by morphogens illuminated by cis-regulatory studies

Morphogen concentration changes in space as well as over time during development. However, how these dynamics are interpreted by cells to specify fate is not well understood. Here, we focus on two morphogens: the maternal transcription factors Bicoid and Dorsal, which directly regulate target genes to pattern Drosophila embryos. The actions of these factors at enhancers has been thoroughly dissected and provides a rich platform for understanding direct input by morphogens and their changing roles over time. Importantly, Bicoid and Dorsal do not work alone; we also discuss additional inputs that work with morphogens to control spatiotemporal gene expression in embryos.

Dynamic Modeling of Transcriptional Gene Regulatory Networks

Diverse cellular phenotypes are determined by groups of transcription factors (TFs) and other regulators that influence each others' gene expression, forming transcriptional gene regulatory networks (GRNs). In many biological contexts, especially in development and associated diseases, the expression of the genes in GRNs is not static but evolves in time. Modeling the dynamics of GRN state is an important approach for understanding diverse cellular phenomena such as cell-fate specification, pluripotency and cell-fate reprogramming, oncogenesis, and tissue regeneration. In this protocol, we describe how to model GRNs using a data-driven dynamic modeling methodology, gene circuits. Gene circuits do not require knowledge of the GRN topology and connectivity but instead learn them from training data, making them very general and applicable to diverse biological contexts. We utilize the MATLAB-based gene circuit modeling software Fast Inference of Gene Regulation (FIGR) for training the model on quantitative gene expression data and simulating the GRN. We describe all the steps in the modeling life cycle, from formulating the model, training the model using FIGR, simulating the GRN, to analyzing and interpreting the model output. This protocol highlights these steps with the example of a dynamical model of the gap gene GRN involved in Drosophila segmentation and includes example MATLAB statements for each step.

Integrating cellular dimensions with cell differentiation during early development

Early embryo development is characterized by alteration of cellular dimensions and fating of blastomeres. An emerging concept is that cell size and shape drive cellular differentiation during early embryogenesis in a variety of model organisms. In this review, we summarize recent advances that elucidate the contribution of the physical dimensions of a cell to major embryonic transitions and cell fate specification in vivo. We also highlight techniques and newly evolving methods for manipulating the sizes and shapes of cells and whole embryos in situ and ex vivo. Finally, we provide an outlook for addressing fundamental questions in the field and more broadly uncovering how changes to cell size control decision making in a variety of biological contexts.

Embryonic geometry underlies phenotypic variation in decanalized conditions

During development, many mutations cause increased variation in phenotypic outcomes, a phenomenon termed decanalization. Phenotypic discordance is often observed in the absence of genetic and environmental variations, but the mechanisms underlying such inter-individual phenotypic discordance remain elusive. Here, using the anterior-posterior (AP) patterning of the Drosophila embryo, we identified embryonic geometry as a key factor predetermining patterning outcomes under decanalizing mutations. With the wild-type AP patterning network, we found that AP patterning is robust to variations in embryonic geometry; segmentation gene expression remains reproducible even when the embryo aspect ratio is artificially reduced by more than twofold. In contrast, embryonic geometry is highly predictive of individual patterning defects under decanalized conditions of either increased bicoid (bcd) dosage or bcd knockout. We showed that the phenotypic discordance can be traced back to variations in the gap gene expression, which is rendered sensitive to the geometry of the embryo under mutations.

A matter of time: Formation and interpretation of the Bicoid morphogen gradient

Spatially distributed signaling molecules, known as morphogens, provide spatial information during development. A host of different morphogens have now been identified, from subcellular gradients through to morphogens that act across a whole embryo. These gradients form over a wide-range of timescales, from seconds to hours, and their time windows for interpretation are also highly variable; the processes of morphogen gradient formation and interpretation are highly dynamic. The morphogen Bicoid (Bcd), present in the early Drosophila embryo, is essential for setting up the future Drosophila body segments. Due to its accessibility for both genetic perturbations and imaging, this system has provided key insights into how precise patterning can occur within a highly dynamic system. Here, we review the temporal scales of Bcd gradient formation and interpretation. In particular, we discuss the quantitative evidence for different models of Bcd gradient formation, outline the time windows for Bcd interpretation, and describe how Bcd temporally adapts its own ability to be interpreted. The utilization of temporal information in morphogen readout may provide crucial inputs to ensure precise spatial patterning, particularly in rapidly developing systems.

Classification-Based Inference of Dynamical Models of Gene Regulatory Networks

Cell-fate decisions during development are controlled by densely interconnected gene regulatory networks (GRNs) consisting of many genes. Inferring and predictively modeling these GRNs is crucial for understanding development and other physiological processes. Gene circuits, coupled differential equations that represent gene product synthesis with a switch-like function, provide a biologically realistic framework for modeling the time evolution of gene expression. However, their use has been limited to smaller networks due to the computational expense of inferring model parameters from gene expression data using global non-linear optimization. Here we show that the switch-like nature of gene regulation can be exploited to break the gene circuit inference problem into two simpler optimization problems that are amenable to computationally efficient supervised learning techniques. We present FIGR (Fast Inference of Gene Regulation), a novel classification-based inference approach to determining gene circuit parameters. We demonstrate FIGR’s effectiveness on synthetic data generated from random gene circuits of up to 50 genes as well as experimental data from the gap gene system of Drosophila melanogaster, a benchmark for inferring dynamical GRN models. FIGR is faster than global non-linear optimization by a factor of 600 and its computational complexity scales much better with GRN size. On a practical level, FIGR can accurately infer the biologically realistic gap gene network in under a minute on desktop-class hardware instead of requiring hours of parallel computing. We anticipate that FIGR would enable the inference of much larger biologically realistic GRNs than was possible before.

Detection and Quantification of the Bicoid Concentration Gradient in Drosophila Embryos

We describe methods for detecting and quantifying the concentration gradient of the morphogenetic protein Bicoid through fluorescent immunostaining in fixed Drosophila embryos. We introduce image-processing steps using MATLAB functions, and discuss how the measured signal intensities can be analyzed to extract quantitative information. The described procedures permit robust detection of the endogenous Bicoid concentration gradient at a cellular resolution.

[Cp*RhIII ]/Ionic Liquid as a Highly Efficient and Recyclable Catalytic Medium for C-H Amidation

A [Cp*Rh^III ]-catalyzed direct C-H amidation is carried out in ionic liquid. Both C(sp² )-H bonds of (hetero)arenes and alkenes and unactivated C(sp³ )-H bonds can be easily amidated with high functional-group tolerance and excellent yields under these conditions. Notably, using [Cp*Rh^III ]/[BMIM]BF₄ (BMIM=1-butyl-3-methylimidazolium) as the green and recyclable medium is environmentally benign, in light of characteristics such as the reusability of the expensive rhodium catalyst, avoidance of highly toxic organic solvents, and mild reaction conditions, as well as a short reaction time.

Network and Pathway Analysis of Toxicogenomics Data

Toxicogenomics is the study of the molecular effects of chemical, biological and physical agents in biological systems, with the aim of elucidating toxicological mechanisms, building predictive models and improving diagnostics. The vast majority of toxicogenomics data has been generated at the transcriptome level, including RNA-seq and microarrays, and large quantities of drug-treatment data have been made publicly available through databases and repositories. Besides the identification of differentially expressed genes (DEGs) from case-control studies or drug treatment time series studies, bioinformatics methods have emerged that infer gene expression data at the molecular network and pathway level in order to reveal mechanistic information. In this work we describe different resources and tools that have been developed by us and others that relate gene expression measurements with known pathway information such as over-representation and gene set enrichment analyses. Furthermore, we highlight approaches that integrate gene expression data with molecular interaction networks in order to derive network modules related to drug toxicity. We describe the two main parts of the approach, i.e., the construction of a suitable molecular interaction network as well as the conduction of network propagation of the experimental data through the interaction network. In all cases we apply methods and tools to publicly available rat in vivo data on anthracyclines, an important class of anti-cancer drugs that are known to induce severe cardiotoxicity in patients. We report the results and functional implications achieved for four anthracyclines (doxorubicin, epirubicin, idarubicin, and daunorubicin) and compare the information content inherent in the different computational approaches.

Dynamic Maternal Gradients Control Timing and Shift-Rates for Drosophila Gap Gene Expression

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.

Animal development is a highly dynamic process. Biochemical or environmental signals can cause the rules that shape it to change over time. We know little about the effects of such changes. For the sake of simplicity, we usually leave them out of our models and experimental assays. Here, we do exactly the opposite. We characterise precisely those aspects of pattern formation caused by changing signalling inputs to a gene regulatory network, the gap gene system of Drosophila melanogaster. Gap genes are involved in determining the body segments of flies and other insects during early development. Gradients of maternal morphogens activate the expression of the gap genes. These gradients are highly dynamic themselves, as they decay while being read out. We show that this decay controls the peak concentration of gap gene products, produces smooth boundaries of gene expression, and slows down the observed positional shifts of gap domains in the posterior of the embryo, thereby stabilising the spatial pattern. Our analysis demonstrates that the dynamics of gene regulation not only affect the timing, but also the positioning of gene expression. This suggests that we must pay closer attention to transient dynamic aspects of development than is currently the case.

Scaling of pattern formations and morphogen gradients

The concentration gradient of morphogens provides positional information for an embryo and plays a pivotal role in pattern formation of tissues during the developmental processes. Morphogen-dependent pattern formations show robustness despite various perturbations. Although tissues usually grow and dynamically change their size during histogenesis, proper patterns are formed without the influence of size variations. Furthermore, even when the blastula embryo of Xenopus laevis is bisected into dorsal and ventral halves, the dorsal half of the embryo leads to proportionally patterned half-sized embryos. This robustness of pattern formation despite size variations is termed as scaling. In this review, I focused on the morphogen-dependent dorsal-ventral axis formation in Xenopus and described how morphogens form a proper gradient shape according to the embryo size.

Gene expression boundary scaling and organ size regulation in the Drosophila embryo

How the shape and size of tissues and organs is regulated during development is a major question in developmental biology. Such regulation relies upon both intrinsic cues (such as signaling networks) and extrinsic inputs (such as from neighboring tissues). Here, we focus on pattern formation and organ development during Drosophila embryogenesis. In particular, we outline the importance of both biochemical and mechanical tissue-tissue interactions in size regulation. We describe how the Drosophila embryo can potentially provide novel insights into how shape and size are regulated during development. We focus on gene expression boundary scaling in the early embryo and how size is regulated in three organs (hindgut, trachea, and ventral nerve cord) later in development, with particular focus on the role of tissue-tissue interactions. Overall, we demonstrate that Drosophila embryogenesis provides a suitable model system for studying spatial and temporal scaling and size control in vivo.

Spinal Cords Built to Scale

An outstanding question in embryogenesis is how different-sized animals maintain similarly proportioned body plans. In this issue of Developmental Cell, Uygur et al. (2016) tackle this issue in the context of neural tube patterning, discovering that differential sensitivity to the Hedgehog pathway may provide one answer to this fundamental issue.

Maternal AP determinants in the Drosophila oocyte and embryo

An animal embryo cannot initiate its journey of forming a new life on its own. It must rely on maternally provided resources and inputs to kick-start its developmental process. In Drosophila, the initial polarities of the embryo along both the anterior-posterior (AP) and dorsal-ventral (DV) axes are also specified by maternal determinants. Over the past several decades, genetic and molecular studies have identified and characterized such determinants, as well as the zygotic genetic regulatory networks that control patterning in the early embryo. Extensive studies of oogenesis have also led to a detailed knowledge of the cellular and molecular interactions that control the formation of a mature egg. Despite these efforts, oogenesis and embryogenesis have been studied largely as separate problems, except for qualitative aspects with regard to maternal regulation of the asymmetric localization of maternal determinants. Can oogenesis and embryogenesis be viewed from a unified perspective at a quantitative level, and can that improve our understanding of how robust embryonic patterning is achieved? Here, we discuss the basic knowledge of the regulatory mechanisms controlling oogenesis and embryonic patterning along the AP axis. We explore properties of the maternal Bicoid gradient in relation to embryo size in search for a unified framework for robust AP patterning. WIREs Dev Biol 2016, 5:562-581. doi: 10.1002/wdev.235 For further resources related to this article, please visit the WIREs website.

Stepwise Progression of Embryonic Patterning

It is long established that the graded distribution of Dorsal transcription factor influences spatial domains of gene expression along the dorsoventral (DV) axis of Drosophila melanogaster embryos. However, the more recent realization that Dorsal levels also change with time raises the question of whether these dynamics are instructive. An overview of DV axis patterning is provided, focusing on new insights identified through quantitative analysis of temporal changes in Dorsal target gene expression from one nuclear cycle to the next ('steps'). Possible roles for the stepwise progression of this patterning program are discussed including (i) tight temporal regulation of signaling pathway activation, (ii) control of gene expression cohorts, and (iii) ensuring the irreversibility of the patterning and cell fate specification process.

Time to move on: Modeling transcription dynamics during an embryonic transition away from maternal control

In a recent study, we investigated the regulation of hunchback (hb) transcription dynamics in Drosophila embryos. Our results suggest that shutdown of hb transcription at early nuclear cycle (nc) 14 is an event associated with the global changes taking place during the mid-blastula transition (MBT). Here we have developed a simple model of hb transcription dynamics during this transition time. With kinetic parameters estimated from our published experimental data, the model describes the dynamical processes of hb gene transcription and hb mRNA accumulation. With two steps, transcription onset upon exiting the previous mitosis followed by a sudden impact that blocks gene activation, the model recapitulates the observed dynamics of hb transcription during the nc14 interphase. The timing of gene inactivation is essential, as its alterations lead to changes in both hb transcription dynamics and hb mRNA levels. Our model provides a clear dynamical picture of hb transcription regulation as one of the many, actively regulated events concurrently taking place during the MBT.