Three-dimensional morphology and gene expression in the Drosophila blastoderm at cellular resolution II: dynamics

Single-cell transcriptome atlas of Drosophila gastrula 2.0

During development, positional information directs cells to specific fates, leading them to differentiate with their own transcriptomes and express specific behaviors and functions. However, the mechanisms underlying these processes in a genome-wide view remain ambiguous, partly because the single-cell transcriptomic data of early developing embryos containing accurate spatial and lineage information are still lacking. Here, we report a single-cell transcriptome atlas of Drosophila gastrulae, divided into 77 transcriptomically distinct clusters. We find that the expression profiles of plasma-membrane-related genes, but not those of transcription-factor genes, represent each germ layer, supporting the nonequivalent contribution of each transcription-factor mRNA level to effector gene expression profiles at the transcriptome level. We also reconstruct the spatial expression patterns of all genes at the single-cell stripe level as the smallest unit. This atlas is an important resource for the genome-wide understanding of the mechanisms by which genes cooperatively orchestrate Drosophila gastrulation.

The epithelial polarity genes frazzled and GUK-holder adjust morphogen gradients to coordinate changes in cell position with cell fate specification

Morphogenetic gradients specify distinct cell populations within tissues. Originally, morphogens were conceived as substances that act on a static field of cells, yet cells usually move during development. Thus, the way cell fates are defined in moving cells remains a significant and largely unsolved problem. Here, we investigated this issue using spatial referencing of cells and 3D spatial statistics in the Drosophila blastoderm to reveal how cell density responds to morphogenetic activity. We show that the morphogen decapentaplegic (DPP) attracts cells towards its peak levels in the dorsal midline, whereas dorsal (DL) stalls them ventrally. We identified frazzled and GUK-holder as the downstream effectors regulated by these morphogens that constrict cells and provide the mechanical force necessary to draw cells dorsally. Surprisingly, GUKH and FRA modulate the DL and DPP gradient levels and this regulation creates a very precise mechanism of coordinating cell movement and fate specification.

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.

A timer gene network is spatially regulated by the terminal system in the Drosophila embryo

In insect embryos, anteroposterior patterning is coordinated by the sequential expression of the 'timer' genes caudal, Dichaete, and odd-paired, whose expression dynamics correlate with the mode of segmentation. In Drosophila, the timer genes are expressed broadly across much of the blastoderm, which segments simultaneously, but their expression is delayed in a small 'tail' region, just anterior to the hindgut, which segments during germband extension. Specification of the tail and the hindgut depends on the terminal gap gene tailless, but beyond this the regulation of the timer genes is poorly understood. We used a combination of multiplexed imaging, mutant analysis, and gene network modelling to resolve the regulation of the timer genes, identifying 11 new regulatory interactions and clarifying the mechanism of posterior terminal patterning. We propose that a dynamic Tailless expression gradient modulates the intrinsic dynamics of a timer gene cross-regulatory module, delineating the tail region and delaying its developmental maturation.

An integrated microfluidic device for multiplexed imaging of spatial gene expression patterns of Drosophila embryos

To reveal the underlying mechanism of the biological function of multicellular systems, it is important to obtain comprehensive spatial gene expression profiles. Among the emerging single-cell spatial-omics techniques, immunofluorescence (IF)-based iterative multiplexed imaging is a promising approach. However, the conventional method is usually costly, time-consuming, labor-intensive, and has low throughput. Moreover, it has yet to be demonstrated in intact multicellular organisms. Here, we developed an integrated microfluidic system to overcome these challenges for quantitatively measuring multiple protein profiles sequentially in situ in the same Drosophila embryo. We designed an array of hydrodynamic trapping sites to automatically capture over ten Drosophila embryos with orientation selectivity at more than 90% trapping rates. We also optimized the geometry of confinement and the on-chip IF protocol to achieve the same high signal-to-noise ratio as the off-chip traditional IF experiments. Moreover, we developed an efficient de-staining protocol by combining on-chip antibody stripping and fluorophore bleaching. Using the same secondary antibody to sequentially stain different genes, we confirmed that the de-stained genes have no detectable interference with the subsequently stained genes, and the gene expression profiles are preserved after multiple cycles of staining and de-staining processes. This preliminary test shows that our newly developed integrated microfluidic system can be a powerful tool for multiplexed imaging of Drosophila embryos. Our work opens a new avenue to design microfluidic chips for multicellular organisms and single-cell spatial-omics techniques.

Attractive internuclear force drives the collective behavior of nuclear arrays in Drosophila embryos

The collective behavior of the nuclear array in Drosophila embryos during nuclear cycle (NC) 11 to NC14 is crucial in controlling cell size, establishing developmental patterns, and coordinating morphogenesis. After live imaging on Drosophila embryos with light sheet microscopy, we extract the nuclear trajectory, speed, and internuclear distance with an automatic nuclear tracing method. We find that the nuclear speed shows a period of standing waves along the anterior-posterior (AP) axis after each metaphase as the nuclei collectively migrate towards the embryo poles and partially move back. And the maximum nuclear speed dampens by 28-45% in the second half of the standing wave. Moreover, the nuclear density is 22-42% lower in the pole region than the middle of the embryo during the interphase of NC12-14. To find mechanical rules controlling the collective motion and packing patterns of the nuclear array, we use a deep neural network (DNN) to learn the underlying force field from data. We apply the learned spatiotemporal attractive force field in the simulations with a particle-based model. And the simulations recapitulate nearly all the observed characteristic collective behaviors of nuclear arrays in Drosophila embryos.

Time and space in segmentation

Arthropod segmentation and vertebrate somitogenesis are leading fields in the experimental and theoretical interrogation of developmental patterning. However, despite the sophistication of current research, basic conceptual issues remain unresolved. These include: (i) the mechanistic origins of spatial organization within the segment addition zone (SAZ); (ii) the mechanistic origins of segment polarization; (iii) the mechanistic origins of axial variation; and (iv) the evolutionary origins of simultaneous patterning. Here, I explore these problems using coarse-grained models of cross-regulating dynamical processes. In the morphogenetic framework of a row of cells undergoing axial elongation, I simulate interactions between an 'oscillator', a 'switch' and up to three 'timers', successfully reproducing essential patterning behaviours of segmenting systems. By comparing the output of these largely cell-autonomous models to variants that incorporate positional information, I find that scaling relationships, wave patterns and patterning dynamics all depend on whether the SAZ is regulated by temporal or spatial information. I also identify three mechanisms for polarizing oscillator output, all of which functionally implicate the oscillator frequency profile. Finally, I demonstrate significant dynamical and regulatory continuity between sequential and simultaneous modes of segmentation. I discuss these results in the context of the experimental literature.

Implications of diffusion and time-varying morphogen gradients for the dynamic positioning and precision of bistable gene expression boundaries

The earliest models for how morphogen gradients guide embryonic patterning failed to account for experimental observations of temporal refinement in gene expression domains. Following theoretical and experimental work in this area, dynamic positional information has emerged as a conceptual framework to discuss how cells process spatiotemporal inputs into downstream patterns. Here, we show that diffusion determines the mathematical means by which bistable gene expression boundaries shift over time, and therefore how cells interpret positional information conferred from morphogen concentration. First, we introduce a metric for assessing reproducibility in boundary placement or precision in systems where gene products do not diffuse, but where morphogen concentrations are permitted to change in time. We show that the dynamics of the gradient affect the sensitivity of the final pattern to variation in initial conditions, with slower gradients reducing the sensitivity. Second, we allow gene products to diffuse and consider gene expression boundaries as propagating wavefronts with velocity modulated by local morphogen concentration. We harness this perspective to approximate a PDE model as an ODE that captures the position of the boundary in time, and demonstrate the approach with a preexisting model for Hunchback patterning in fruit fly embryos. We then propose a design that employs antiparallel morphogen gradients to achieve accurate boundary placement that is robust to scaling. Throughout our work we draw attention to tradeoffs among initial conditions, boundary positioning, and the relative timescales of network and gradient evolution. We conclude by suggesting that mathematical theory should serve to clarify not just our quantitative, but also our intuitive understanding of patterning processes.

Three-dimensional multi-gene expression maps reveal cell fate changes associated with laterality reversal of zebrafish habenula

The conserved bilateral habenular nuclei (HA) in vertebrate diencephalon develop into compartmentalized structures containing neurons derived from different cell lineages. Despite extensive studies demonstrated that zebrafish larval HA display distinct left-right (L-R) asymmetry in gene expression and connectivity, the spatial gene expression domains were mainly obtained from two-dimensional (2D) snapshots of colorimetric RNA in situ hybridization staining which could not properly reflect different HA neuronal lineages constructed in three-dimension (3D). Combing the tyramide-based fluorescent mRNA in situ hybridization, confocal microscopy and customized imaging processing procedures, we have created spatial distribution maps of four genes for 4-day-old zebrafish and in sibling fish whose L-R asymmetry was spontaneously reversed. 3D volumetric analyses showed that ratios of cpd2, lov, ron, and nrp1a expression in L-R reversed HA were reversed according to the parapineal positions. However, the quantitative changes of gene expression in reversed larval brains do not mirror the gene expression level in the obverse larval brains. There were a total 87.78% increase in lov⁺ nrp1a⁺ and a total 12.45% decrease in lov⁺ ron⁺ double-positive neurons when the L-R asymmetry of HA was reversed. Thus, our volumetric analyses of the 3D maps indicate that changes of HA neuronal cell fates are associated with the reversal of HA laterality. These changes likely account for the behavior changes associated with HA laterality alterations.

Kinetic sculpting of the seven stripes of the Drosophila even-skipped gene

We used live imaging to visualize the transcriptional dynamics of the Drosophila melanogaster even-skipped gene at single-cell and high-temporal resolution as its seven stripe expression pattern forms, and developed tools to characterize and visualize how transcriptional bursting varies over time and space. We find that despite being created by the independent activity of five enhancers, even-skipped stripes are sculpted by the same kinetic phenomena: a coupled increase of burst frequency and amplitude. By tracking the position and activity of individual nuclei, we show that stripe movement is driven by the exchange of bursting nuclei from the posterior to anterior stripe flanks. Our work provides a conceptual, theoretical and computational framework for dissecting pattern formation in space and time, and reveals how the coordinated transcriptional activity of individual nuclei shapes complex developmental patterns.

Arthropod segmentation

There is now compelling evidence that many arthropods pattern their segments using a clock-and-wavefront mechanism, analogous to that operating during vertebrate somitogenesis. In this Review, we discuss how the arthropod segmentation clock generates a repeating sequence of pair-rule gene expression, and how this is converted into a segment-polarity pattern by ‘timing factor’ wavefronts associated with axial extension. We argue that the gene regulatory network that patterns segments may be relatively conserved, although the timing of segmentation varies widely, and double-segment periodicity appears to have evolved at least twice. Finally, we describe how the repeated evolution of a simultaneous (Drosophila-like) mode of segmentation within holometabolan insects can be explained by heterochronic shifts in timing factor expression plus extensive pre-patterning of the pair-rule genes.

Hunchback is counter-repressed to regulate even-skipped stripe 2 expression in Drosophila embryos

Hunchback is a bifunctional transcription factor that can activate and repress gene expression in Drosophila development. We investigated the regulatory DNA sequence features that control Hunchback function by perturbing enhancers for one of its target genes, even-skipped (eve). While Hunchback directly represses the eve stripe 3+7 enhancer, we found that in the eve stripe 2+7 enhancer, Hunchback repression is prevented by nearby sequences-this phenomenon is called counter-repression. We also found evidence that Caudal binding sites are responsible for counter-repression, and that this interaction may be a conserved feature of eve stripe 2 enhancers. Our results alter the textbook view of eve stripe 2 regulation wherein Hb is described as a direct activator. Instead, to generate stripe 2, Hunchback repression must be counteracted. We discuss how counter-repression may influence eve stripe 2 regulation and evolution.

A damped oscillator imposes temporal order on posterior gap gene expression in Drosophila

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.

Different insect species exhibit one of two distinct modes of determining their body segments (known as segmentation) during development: they either use a molecular oscillator to position segments sequentially, or they generate segments simultaneously through a hierarchical gene-regulatory cascade. The sequential mode is ancestral, while the simultaneous mode has been derived from it independently several times during evolution. In this paper, we present evidence suggesting that simultaneous segmentation also involves an oscillator in the posterior end of the embryo of the vinegar fly, Drosophila melanogaster. This surprising result indicates that both modes of segment determination are much more similar than previously thought. Such similarity provides an important step towards our understanding of the frequent evolutionary transitions observed between sequential and simultaneous segmentation.

Speed regulation of genetic cascades allows for evolvability in the body plan specification of insects

During the anterior-posterior fate specification of insects, anterior fates arise in a nonelongating tissue (called the "blastoderm"), and posterior fates arise in an elongating tissue (called the "germband"). However, insects differ widely in the extent to which anterior-posterior fates are specified in the blastoderm versus the germband. Here we present a model in which patterning in both the blastoderm and germband of the beetle Tribolium castaneum is based on the same flexible mechanism: a gradient that modulates the speed of a genetic cascade of gap genes, resulting in the induction of sequential kinematic waves of gap gene expression. The mechanism is flexible and capable of patterning both elongating and nonelongating tissues, and hence converting blastodermal to germband fates and vice versa. Using RNAi perturbations, we found that blastodermal fates could be shifted to the germband, and germband fates could be generated in a blastoderm-like morphology. We also suggest a molecular mechanism underlying our model, in which gradient levels regulate the switch between two enhancers: One enhancer is responsible for sequential gene activation, and the other is responsible for freezing temporal rhythms into spatial patterns. This model is consistent with findings in Drosophila melanogaster, where gap genes were found to be regulated by two nonredundant "shadow" enhancers.

Dynamic patterning by the Drosophila pair-rule network reconciles long-germ and short-germ segmentation

Drosophila segmentation is a well-established paradigm for developmental pattern formation. However, the later stages of segment patterning, regulated by the "pair-rule" genes, are still not well understood at the system level. Building on established genetic interactions, I construct a logical model of the Drosophila pair-rule system that takes into account the demonstrated stage-specific architecture of the pair-rule gene network. Simulation of this model can accurately recapitulate the observed spatiotemporal expression of the pair-rule genes, but only when the system is provided with dynamic "gap" inputs. This result suggests that dynamic shifts of pair-rule stripes are essential for segment patterning in the trunk and provides a functional role for observed posterior-to-anterior gap domain shifts that occur during cellularisation. The model also suggests revised patterning mechanisms for the parasegment boundaries and explains the aetiology of the even-skipped null mutant phenotype. Strikingly, a slightly modified version of the model is able to pattern segments in either simultaneous or sequential modes, depending only on initial conditions. This suggests that fundamentally similar mechanisms may underlie segmentation in short-germ and long-germ arthropods.

Odd-paired controls frequency doubling in Drosophila segmentation by altering the pair-rule gene regulatory network

The Drosophila embryo transiently exhibits a double-segment periodicity, defined by the expression of seven 'pair-rule' genes, each in a pattern of seven stripes. At gastrulation, interactions between the pair-rule genes lead to frequency doubling and the patterning of 14 parasegment boundaries. In contrast to earlier stages of Drosophila anteroposterior patterning, this transition is not well understood. By carefully analysing the spatiotemporal dynamics of pair-rule gene expression, we demonstrate that frequency-doubling is precipitated by multiple coordinated changes to the network of regulatory interactions between the pair-rule genes. We identify the broadly expressed but temporally patterned transcription factor, Odd-paired (Opa/Zic), as the cause of these changes, and show that the patterning of the even-numbered parasegment boundaries relies on Opa-dependent regulatory interactions. Our findings indicate that the pair-rule gene regulatory network has a temporally modulated topology, permitting the pair-rule genes to play stage-specific patterning roles.

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.

Predicting Ancestral Segmentation Phenotypes from Drosophila to Anopheles Using In Silico Evolution

Molecular evolution is an established technique for inferring gene homology but regulatory DNA turns over so rapidly that inference of ancestral networks is often impossible. In silico evolution is used to compute the most parsimonious path in regulatory space for anterior-posterior patterning linking two Dipterian species. The expression pattern of gap genes has evolved between Drosophila (fly) and Anopheles (mosquito), yet one of their targets, eve, has remained invariant. Our model predicts that stripe 5 in fly disappears and a new posterior stripe is created in mosquito, thus eve stripe modules 3+7 and 4+6 in fly are homologous to 3+6 and 4+5 in mosquito. We can place Clogmia on this evolutionary pathway and it shares the mosquito homologies. To account for the evolution of the other pair-rule genes in the posterior we have to assume that the ancestral Dipterian utilized a dynamic method to phase those genes in relation to eve.

The last common ancestor of the fruit fly (Drosophila) and mosquito (Anopheles) lived more than 200 Million years ago. Can we use available data on insects alive today to infer what their ancestor looked like? In this manuscript, we focus on early embryonic development, when stripes of genetic expression appear and define the location of insect segments (“segmentation”). We use an evolutionary algorithm to reconstruct and predict dynamics of genes controlling stripes in the last common ancestor of fly and mosquito. We predict a new and different combinatorial logic of stripe formation in mosquito compared to fly, which is fully consistent with development of intermediate species such as moth-fly (Clogmia). Our simulations further suggest that the dynamics of gene expression in this last common ancestor were similar to other insects, such as wasps (Nasonia). Our method illustrates how computational methods inspired by machine learning and non-linear physics can be used to infer gene dynamics in species that disappeared millions of years ago.

A gene expression atlas of a bicoid-depleted Drosophila embryo reveals early canalization of cell fate

In developing embryos, gene regulatory networks drive cells towards discrete terminal fates, a process called canalization. We studied the behavior of the anterior-posterior segmentation network in Drosophila melanogaster embryos by depleting a key maternal input, bicoid (bcd), and measuring gene expression patterns of the network at cellular resolution. This method results in a gene expression atlas containing the levels of mRNA or protein expression of 13 core patterning genes over six time points for every cell of the blastoderm embryo. This is the first cellular resolution dataset of a genetically perturbed Drosophila embryo that captures all cells in 3D. We describe the technical developments required to build this atlas and how the method can be employed and extended by others. We also analyze this novel dataset to characterize the degree and timing of cell fate canalization in the segmentation network. We find that in two layers of this gene regulatory network, following depletion of bcd, individual cells rapidly canalize towards normal cell fates. This result supports the hypothesis that the segmentation network directly canalizes cell fate, rather than an alternative hypothesis whereby cells are initially mis-specified and later eliminated by apoptosis. Our gene expression atlas provides a high resolution picture of a classic perturbation and will enable further computational modeling of canalization and gene regulation in this transcriptional network.

Shadow enhancers enable Hunchback bifunctionality in the Drosophila embryo

Hunchback (Hb) is a bifunctional transcription factor that activates and represses distinct enhancers. Here, we investigate the hypothesis that Hb can activate and repress the same enhancer. Computational models predicted that Hb bifunctionally regulates the even-skipped (eve) stripe 3+7 enhancer (eve3+7) in Drosophila blastoderm embryos. We measured and modeled eve expression at cellular resolution under multiple genetic perturbations and found that the eve3+7 enhancer could not explain endogenous eve stripe 7 behavior. Instead, we found that eve stripe 7 is controlled by two enhancers: the canonical eve3+7 and a sequence encompassing the minimal eve stripe 2 enhancer (eve2+7). Hb bifunctionally regulates eve stripe 7, but it executes these two activities on different pieces of regulatory DNA--it activates the eve2+7 enhancer and represses the eve3+7 enhancer. These two "shadow enhancers" use different regulatory logic to create the same pattern.

Imaging the dorsal-ventral axis of live and fixed Drosophila melanogaster embryos

Optimal imaging conditions are of critical importance in developmental biology, as much of the data in the discipline is acquired through microscopy. However, imaging deep sections of tissue, especially live tissue, can be a technical challenge due to light scattering and difficulties in mounting the sample. In particular, capturing high-quality images of dorsal-ventral cross sections requires "end-on" mounting to orient the anterior-posterior axis vertically. Here we present methods to mount and image dorsal-ventral cross sections of both live and fixed Drosophila melanogaster embryos. Our methods have the advantages of being rapid, allowing deep optical sections, and not requiring expensive, specialized equipment.

A computational model of nuclear self-organisation in syncytial embryos

Syncytial embryos develop through cycles of nuclear division and rearrangement within a common cytoplasm. A paradigm example is Drosophila melanogaster in which nuclei form an ordered array in the embryo surface over cell cycles 10-13. This ordering process is assumed to be essential for subsequent cellularisation. Using quantitative tissue analysis, it has previously been shown that the regrowth of actin and microtubule networks after nuclear division generates reordering forces that counteract its disordering effect (Kanesaki et al., 2011). We present here an individual-based computer simulation modelling the nuclear dynamics. In contrast to similar modelling approaches e.g. epithelial monolayers or tumour spheroids, we focus not on the spatial dependence, but rather on the time-dependence of the interaction laws. We show that appropriate phenomenological inter-nuclear force laws reproduce the experimentally observed dynamics provided that the cytoskeletal network regrows sufficiently quickly after mitosis. Then repulsive forces provided by the actin system are necessary and sufficient to regain the observed level of order in the system, after the strong disruption resulting from cytoskeletal network disassembly and spindle formation. We also observe little mixing of nuclei through cell cycles. Our study highlights the importance of the dynamics of cytoskeletal forces during this critical phase of syncytial development and emphasises the need for real-time experimental data at high temporal resolution.

Bioimage Informatics in the context of Drosophila research

Modern biological research relies heavily on microscopic imaging. The advanced genetic toolkit of Drosophila makes it possible to label molecular and cellular components with unprecedented level of specificity necessitating the application of the most sophisticated imaging technologies. Imaging in Drosophila spans all scales from single molecules to the entire populations of adult organisms, from electron microscopy to live imaging of developmental processes. As the imaging approaches become more complex and ambitious, there is an increasing need for quantitative, computer-mediated image processing and analysis to make sense of the imagery. Bioimage Informatics is an emerging research field that covers all aspects of biological image analysis from data handling, through processing, to quantitative measurements, analysis and data presentation. Some of the most advanced, large scale projects, combining cutting edge imaging with complex bioimage informatics pipelines, are realized in the Drosophila research community. In this review, we discuss the current research in biological image analysis specifically relevant to the type of systems level image datasets that are uniquely available for the Drosophila model system. We focus on how state-of-the-art computer vision algorithms are impacting the ability of Drosophila researchers to analyze biological systems in space and time. We pay particular attention to how these algorithmic advances from computer science are made usable to practicing biologists through open source platforms and how biologists can themselves participate in their further development.

A quantitative atlas of Even-skipped and Hunchback expression in Clogmia albipunctata (Diptera: Psychodidae) blastoderm embryos

Background

Comparative studies of developmental processes are one of the main approaches to evolutionary developmental biology (evo-devo). Over recent years, there has been a shift of focus from the comparative study of particular regulatory genes to the level of whole gene networks. Reverse-engineering methods can be used to computationally reconstitute and analyze the function and dynamics of such networks. These methods require quantitative spatio-temporal expression data for model fitting. Obtaining such data in non-model organisms remains a major technical challenge, impeding the wider application of data-driven mathematical modeling to evo-devo.

Results

We have raised antibodies against four segmentation gene products in the moth midge Clogmia albipunctata, a non-drosophilid dipteran species. We have used these antibodies to create a quantitative atlas of protein expression patterns for the gap gene hunchback (hb), and the pair-rule gene even-skipped (eve). Our data reveal differences in the dynamics of Hb boundary positioning and Eve stripe formation between C. albipunctata and Drosophila melanogaster. Despite these differences, the overall relative spatial arrangement of Hb and Eve domains is remarkably conserved between these two distantly related dipteran species.

Conclusions

We provide a proof of principle that it is possible to acquire quantitative gene expression data at high accuracy and spatio-temporal resolution in non-model organisms. Our quantitative data extend earlier qualitative studies of segmentation gene expression in C. albipunctata, and provide a starting point for comparative reverse-engineering studies of the evolutionary and developmental dynamics of the segmentation gene system.

Automated annotation of gene expression image sequences via non-parametric factor analysis and conditional random fields

Motivation: Computational approaches for the annotation of phenotypes from image data have shown promising results across many applications, and provide rich and valuable information for studying gene function and interactions. While data are often available both at high spatial resolution and across multiple time points, phenotypes are frequently annotated independently, for individual time points only. In particular, for the analysis of developmental gene expression patterns, it is biologically sensible when images across multiple time points are jointly accounted for, such that spatial and temporal dependencies are captured simultaneously.

Methods: We describe a discriminative undirected graphical model to label gene-expression time-series image data, with an efficient training and decoding method based on the junction tree algorithm. The approach is based on an effective feature selection technique, consisting of a non-parametric sparse Bayesian factor analysis model. The result is a flexible framework, which can handle large-scale data with noisy incomplete samples, i.e. it can tolerate data missing from individual time points.

Results: Using the annotation of gene expression patterns across stages of Drosophila embryonic development as an example, we demonstrate that our method achieves superior accuracy, gained by jointly annotating phenotype sequences, when compared with previous models that annotate each stage in isolation. The experimental results on missing data indicate that our joint learning method successfully annotates genes for which no expression data are available for one or more stages.

Contact: uwe.ohler@duke.edu

Automated cellular annotation for high-resolution images of adult Caenorhabditis elegans

Motivation: Advances in high-resolution microscopy have recently made possible the analysis of gene expression at the level of individual cells. The fixed lineage of cells in the adult worm Caenorhabditis elegans makes this organism an ideal model for studying complex biological processes like development and aging. However, annotating individual cells in images of adult C.elegans typically requires expertise and significant manual effort. Automation of this task is therefore critical to enabling high-resolution studies of a large number of genes.

Results: In this article, we describe an automated method for annotating a subset of 154 cells (including various muscle, intestinal and hypodermal cells) in high-resolution images of adult C.elegans. We formulate the task of labeling cells within an image as a combinatorial optimization problem, where the goal is to minimize a scoring function that compares cells in a test input image with cells from a training atlas of manually annotated worms according to various spatial and morphological characteristics. We propose an approach for solving this problem based on reduction to minimum-cost maximum-flow and apply a cross-entropy–based learning algorithm to tune the weights of our scoring function. We achieve 84% median accuracy across a set of 154 cell labels in this highly variable system. These results demonstrate the feasibility of the automatic annotation of microscopy-based images in adult C.elegans.

Contact:saerni@cs.stanford.edu

Design principles for generating robust gene expression patterns in dynamic engineered tissues

Recapitulating native tissue organization is a central challenge in regenerative medicine as it is critical for generating functional tissues. One strategy to generate engineered tissues with predictable and appropriate organization is to mimic the gene expression patterning process that organizes tissues in the developing embryo. In a developing embryo, correct organization is accomplished by tissue patterning via the generation of temporal and spatial patterns of gene expression coupled with, and leading to, extensive cellular re-organization. Methods to pattern gene expression in vitro could therefore provide both better models for understanding the cellular and molecular events taking place during tissue morphogenesis and novel strategies for engineering tissues with more realistic and complex architectures. While a few attempts have been made to genetically pattern tissues in vitro, these do not produce sharp predictable patterning. In both the embryo and an in vitro tissue, patterning often occurs during extensive cell re-organization but how the dynamics of gene induction and cell re-distribution interact to impact the final outcome of patterning and ultimately tissue organization is not known. Understanding this relationship and the system parameters that dictate robust pattern formation is critical for engineering genetic patterning in vitro to organize artificial tissues. We set out to identify key requirements for pattern formation by patterning gene expression in vitro in sheets of re-distributing cells using a drug-inducible gene expression system and patterned drug delivery to mimic morphogen gene induction. Based on our experimental observations, we develop a mathematical model that allows us to identify and experimentally verify the conditions under which generation of sharp gene expression patterns is possible in vitro. Our results highlight the importance of coordinating gene induction dynamics and cellular movement in order to achieve robust pattern formation.

Towards 3D in silico modeling of the sea urchin embryonic development

Embryogenesis is a dynamic process with an intrinsic variability whose understanding requires the integration of molecular, genetic, and cellular dynamics. Biological circuits function over time at the level of single cells and require a precise analysis of the topology, temporality, and probability of events. Integrative developmental biology is currently looking for the appropriate strategies to capture the intrinsic properties of biological systems. The "-omic" approaches require disruption of the function of the biological circuit; they provide static information, with low temporal resolution and usually with population averaging that masks fast or variable features at the cellular scale and in a single individual. This data should be correlated with cell behavior as cells are the integrators of biological activity. Cellular dynamics are captured by the in vivo microscopy observation of live organisms. This can be used to reconstruct the 3D + time cell lineage tree to serve as the basis for modeling the organism's multiscale dynamics. We discuss here the progress that has been made in this direction, starting with the reconstruction over time of three-dimensional digital embryos from in toto time-lapse imaging. Digital specimens provide the means for a quantitative description of the development of model organisms that can be stored, shared, and compared. They open the way to in silico experimentation and to a more theoretical approach to biological processes. We show, with some unpublished results, how the proposed methodology can be applied to sea urchin species that have been model organisms in the field of classical embryology and modern developmental biology for over a century.

Cellular resolution models for even skipped regulation in the entire Drosophila embryo

Transcriptional control ensures genes are expressed in the right amounts at the correct times and locations. Understanding quantitatively how regulatory systems convert input signals to appropriate outputs remains a challenge. For the first time, we successfully model even skipped (eve) stripes 2 and 3+7 across the entire fly embryo at cellular resolution. A straightforward statistical relationship explains how transcription factor (TF) concentrations define eve's complex spatial expression, without the need for pairwise interactions or cross-regulatory dynamics. Simulating thousands of TF combinations, we recover known regulators and suggest new candidates. Finally, we accurately predict the intricate effects of perturbations including TF mutations and misexpression. Our approach imposes minimal assumptions about regulatory function; instead we infer underlying mechanisms from models that best fit the data, like the lack of TF-specific thresholds and the positional value of homotypic interactions. Our study provides a general and quantitative method for elucidating the regulation of diverse biological systems. DOI:http://dx.doi.org/10.7554/eLife.00522.001.

Evaluating thermodynamic models of enhancer activity on cellular resolution gene expression data

With the advent of high throughput sequencing and high resolution transcriptomic technologies, there exists today an unprecedented opportunity to understand gene regulation at a quantitative level. State of the art models of the relationship between regulatory sequence and gene expression have shown great promise, but also suffer from some major shortcomings. In this paper, we identify and address methodological challenges pertaining to quantitative modeling of gene expression from sequence, and test our models on the anterior-posterior patterning system in the Drosophila embryo. We first develop a framework to process cellular resolution three-dimensional gene expression data from the Drosophila embryo and create data sets on which quantitative models can be trained. Next we propose a new score, called 'weighted pattern generating potential' (w-PGP), to evaluate model predictions, and show its advantages over the two most common scoring schemes in use today. The model building exercise uses w-PGP as the evaluation score and adopts a systematic strategy to increase a model's complexity while guarding against over-fitting. Our model identifies three transcription factors--ZELDA, SLOPPY-PAIRED, and NUBBIN--that have not been previously incorporated in quantitative models of this system, as having significant regulatory influence. Finally, we show how fitting quantitative models on data sets comprising a handful of enhancers, as reported in earlier work, may lead to unreliable models.

Variation in the dorsal gradient distribution is a source for modified scaling of germ layers in Drosophila

Specification of germ layers along the dorsoventral axis by morphogenetic gradients is an ideal model to study scaling properties of gradients and cell fate changes during evolution. Classical anatomical studies in divergent insects (e.g., flies and grasshoppers) revealed that the neuroectodermal size is conserved and originates similar numbers of neuroblasts of homologous identity. In contrast, mesodermal domains vary significantly in closely related Drosophila species. To further investigate the underlying mechanisms of scaling of germ layers across Drosophila species, we quantified the Dorsal (Dl)/NF-κB gradient, the main morphogenetic gradient that initiates separation of the mesoderm, neuroectoderm, and ectoderm. We discovered a variable range of Toll activation across species and found that Dl activates mesodermal genes at the same threshold levels in melanogaster sibling species. We also show that the Dl gradient distribution can be modulated by nuclear size and packing densities. We propose that variation in mesodermal size occurs at a fast evolutionary rate and is an important mechanism to define the ventral boundary of the neuroectoderm.

Accurate measurements of dynamics and reproducibility in small genetic networks

Quantification of gene expression has become a central tool for understanding genetic networks. In many systems, the only viable way to measure protein levels is by immunofluorescence, which is notorious for its limited accuracy. Using the early Drosophila embryo as an example, we show that careful identification and control of experimental error allows for highly accurate gene expression measurements. We generated antibodies in different host species, allowing for simultaneous staining of four Drosophila gap genes in individual embryos. Careful error analysis of hundreds of expression profiles reveals that less than ∼20% of the observed embryo-to-embryo fluctuations stem from experimental error. These measurements make it possible to extract not only very accurate mean gene expression profiles but also their naturally occurring fluctuations of biological origin and corresponding cross-correlations. We use this analysis to extract gap gene profile dynamics with ∼1 min accuracy. The combination of these new measurements and analysis techniques reveals a twofold increase in profile reproducibility owing to a collective network dynamics that relays positional accuracy from the maternal gradients to the pair-rule genes.

The importance of geometry in mathematical models of developing systems

Understanding the interaction between the spatial variation of extracellular signals and the interpretation of such signals in embryonic development is difficult without a mathematical model, but the inherent limitations of a model can have a profound impact on its utility. A central issue is the level of abstraction needed, and here we focus on the role of geometry in models and how the choice of the spatial dimension can influence the conclusions reached. A widely studied system in which the proper choice of geometry is critical is embryonic development of Drosophila melanogaster, and we discuss recent work in which 3D embryo-scale modeling is used to identify key modes of transport, analyze gap gene expression, and test BMP-mediated positive feedback mechanisms.

A segmentation clock operating in blastoderm and germband stages of Tribolium development

In Drosophila, all segments form in the blastoderm where morphogen gradients spanning the entire anterior-posterior axis of the embryo provide positional information. However, in the beetle Tribolium castaneum and most other arthropods, a number of anterior segments form in the blastoderm, and the remaining segments form sequentially from a posterior growth zone during germband elongation. Recently, the cyclic nature of the pair-rule gene Tc-odd-skipped was demonstrated in the growth zone of Tribolium, indicating that a vertebrate-like segmentation clock is employed in the germband stage of its development. This suggests that two mechanisms might function in the same organism: a Drosophila-like mechanism in the blastoderm, and a vertebrate-like mechanism in the germband. Here, we show that segmentation at both blastoderm and germband stages of Tribolium is based on a segmentation clock. Specifically, we show that the Tribolium primary pair-rule gene, Tc-even-skipped (Tc-eve), is expressed in waves propagating from the posterior pole and progressively slowing until they freeze into stripes; such dynamics are a hallmark of clock-based segmentation. Phase shifts between Tc-eve transcripts and protein confirm that these waves are due to expression dynamics. Moreover, by tracking cells in live embryos and by analyzing mitotic profiles, we found that neither cell movement nor oriented cell division could explain the observed wave dynamics of Tc-eve. These results pose intriguing evolutionary questions, as Drosophila and Tribolium segment their blastoderms using the same genes but different mechanisms.

Medium-throughput processing of whole mount in situ hybridisation experiments into gene expression domains

Understanding the function and evolution of developmental regulatory networks requires the characterisation and quantification of spatio-temporal gene expression patterns across a range of systems and species. However, most high-throughput methods to measure the dynamics of gene expression do not preserve the detailed spatial information needed in this context. For this reason, quantification methods based on image bioinformatics have become increasingly important over the past few years. Most available approaches in this field either focus on the detailed and accurate quantification of a small set of gene expression patterns, or attempt high-throughput analysis of spatial expression through binary pattern extraction and large-scale analysis of the resulting datasets. Here we present a robust, “medium-throughput” pipeline to process in situ hybridisation patterns from embryos of different species of flies. It bridges the gap between high-resolution, and high-throughput image processing methods, enabling us to quantify graded expression patterns along the antero-posterior axis of the embryo in an efficient and straightforward manner. Our method is based on a robust enzymatic (colorimetric) in situ hybridisation protocol and rapid data acquisition through wide-field microscopy. Data processing consists of image segmentation, profile extraction, and determination of expression domain boundary positions using a spline approximation. It results in sets of measured boundaries sorted by gene and developmental time point, which are analysed in terms of expression variability or spatio-temporal dynamics. Our method yields integrated time series of spatial gene expression, which can be used to reverse-engineer developmental gene regulatory networks across species. It is easily adaptable to other processes and species, enabling the in silico reconstitution of gene regulatory networks in a wide range of developmental contexts.

Learning sparse representations for fruit-fly gene expression pattern image annotation and retrieval

Background

Fruit fly embryogenesis is one of the best understood animal development systems, and the spatiotemporal gene expression dynamics in this process are captured by digital images. Analysis of these high-throughput images will provide novel insights into the functions, interactions, and networks of animal genes governing development. To facilitate comparative analysis, web-based interfaces have been developed to conduct image retrieval based on body part keywords and images. Currently, the keyword annotation of spatiotemporal gene expression patterns is conducted manually. However, this manual practice does not scale with the continuously expanding collection of images. In addition, existing image retrieval systems based on the expression patterns may be made more accurate using keywords.

Results

In this article, we adapt advanced data mining and computer vision techniques to address the key challenges in annotating and retrieving fruit fly gene expression pattern images. To boost the performance of image annotation and retrieval, we propose representations integrating spatial information and sparse features, overcoming the limitations of prior schemes.

Conclusions

We perform systematic experimental studies to evaluate the proposed schemes in comparison with current methods. Experimental results indicate that the integration of spatial information and sparse features lead to consistent performance improvement in image annotation, while for the task of retrieval, sparse features alone yields better results.

Three-dimensional morphology and gene expression mapping for the Drosophila blastoderm

To properly understand the transcriptional network of animals, we must have full quantitative comprehension of the spatial and temporal expression patterns of transcription factors and their targets. Visual inspection of embryos stained to reveal the patterns of genes shows levels of expression that change from cell to cell in a complex manner. With our current wealth of knowledge regarding the basic biology of animal genomes and the components of their transcriptional regulatory networks, combined with current technologies in optical microscopy, computing, and image and vision analysis, we should be able to capture quantitative, three-dimensional (3D) information about the transcriptional network (all factors and targets) for an entire animal at cellular resolution. It should also be possible to assemble these data into a single computationally analyzable database--an atlas--that could be the basis for uncovering new biology governing regulatory gene networks. This article describes progress toward realizing these goals, with the focus on Drosophila melanogaster. It describes a suite of high-throughput methods that have been used to create the first quantitative 3D description of gene expression and morphology at cellular resolution in a whole animal, and it presents some of the new biology that has been revealed by this quantitative atlas.

Analysis of gap gene regulation in a 3D organism-scale model of the Drosophila melanogaster embryo

The axial bodyplan of Drosophila melanogaster is determined during a process called morphogenesis. Shortly after fertilization, maternal bicoid mRNA is translated into Bicoid (Bcd). This protein establishes a spatially graded morphogen distribution along the anterior-posterior (AP) axis of the embryo. Bcd initiates AP axis determination by triggering expression of gap genes that subsequently regulate each other's expression to form a precisely controlled spatial distribution of gene products. Reaction-diffusion models of gap gene expression on a 1D domain have previously been used to infer complex genetic regulatory network (GRN) interactions by optimizing model parameters with respect to 1D gap gene expression data. Here we construct a finite element reaction-diffusion model with a realistic 3D geometry fit to full 3D gap gene expression data. Though gap gene products exhibit dorsal-ventral asymmetries, we discover that previously inferred gap GRNs yield qualitatively correct AP distributions on the 3D domain only when DV-symmetric initial conditions are employed. Model patterning loses qualitative agreement with experimental data when we incorporate a realistic DV-asymmetric distribution of Bcd. Further, we find that geometry alone is insufficient to account for DV-asymmetries in the final gap gene distribution. Additional GRN optimization confirms that the 3D model remains sensitive to GRN parameter perturbations. Finally, we find that incorporation of 3D data in simulation and optimization does not constrain the search space or improve optimization results.

A conserved developmental patterning network produces quantitatively different output in multiple species of Drosophila

Differences in the level, timing, or location of gene expression can contribute to alternative phenotypes at the molecular and organismal level. Understanding the origins of expression differences is complicated by the fact that organismal morphology and gene regulatory networks could potentially vary even between closely related species. To assess the scope of such changes, we used high-resolution imaging methods to measure mRNA expression in blastoderm embryos of Drosophila yakuba and Drosophila pseudoobscura and assembled these data into cellular resolution atlases, where expression levels for 13 genes in the segmentation network are averaged into species-specific, cellular resolution morphological frameworks. We demonstrate that the blastoderm embryos of these species differ in their morphology in terms of size, shape, and number of nuclei. We present an approach to compare cellular gene expression patterns between species, while accounting for varying embryo morphology, and apply it to our data and an equivalent dataset for Drosophila melanogaster. Our analysis reveals that all individual genes differ quantitatively in their spatio-temporal expression patterns between these species, primarily in terms of their relative position and dynamics. Despite many small quantitative differences, cellular gene expression profiles for the whole set of genes examined are largely similar. This suggests that cell types at this stage of development are conserved, though they can differ in their relative position by up to 3–4 cell widths and in their relative proportion between species by as much as 5-fold. Quantitative differences in the dynamics and relative level of a subset of genes between corresponding cell types may reflect altered regulatory functions between species. Our results emphasize that transcriptional networks can diverge over short evolutionary timescales and that even small changes can lead to distinct output in terms of the placement and number of equivalent cells.

For a gene to function properly, it must be active in the right place, at the right time, and in the right amount. Changes in any of these features can lead to observable differences between individuals and species and in some cases can lead to disease. We do not currently understand how the position, timing, and amount of gene expression is encoded in DNA sequence. One approach to this problem is to compare how gene expression differs between species and to try to relate changes in DNA sequence to changes in gene expression. Here, we take the first step by comparing gene expression patterns at high spatial and temporal resolution between embryos of three species of fruit flies. We develop methods for comparing gene expression in individual cells, which allow us to control for variation in the size, shape, and number of nuclei between embryos. We find measurable quantitative differences in the patterns for all individual genes that we have examined. However, by considering all genes in our dataset at once, we show that many genes are changing together, leading to largely equivalent types of cells in these three species.

Mathematical modeling of gene expression: a guide for the perplexed biologist

The detailed analysis of transcriptional networks holds a key for understanding central biological processes, and interest in this field has exploded due to new large-scale data acquisition techniques. Mathematical modeling can provide essential insights, but the diversity of modeling approaches can be a daunting prospect to investigators new to this area. For those interested in beginning a transcriptional mathematical modeling project, we provide here an overview of major types of models and their applications to transcriptional networks. In this discussion of recent literature on thermodynamic, Boolean, and differential equation models, we focus on considerations critical for choosing and validating a modeling approach that will be useful for quantitative understanding of biological systems.

Scaling of the Bicoid morphogen gradient by a volume-dependent production rate

An important feature of development is the formation of patterns that are proportional to the overall size of the embryo. But how such proportionality, or scaling, is achieved mechanistically remains poorly understood. Furthermore, it is currently unclear whether organisms utilize similar or distinct mechanisms to achieve scaling within a species and between species. Here we investigate within-species scaling mechanisms for anterior-posterior (A-P) patterning in Drosophila melanogaster, focusing specifically on the properties of the Bicoid (Bcd) morphogen gradient. Using embryos from lines artificially selected for large and small egg volume, we show that large embryos have higher nuclear Bcd concentrations in the anterior than small embryos. This anterior difference leads to scaling properties of the Bcd gradient profiles: in broad regions of the large and small embryos along the A-P axis, normalizing their positions to embryo length reduces the differences in both the nuclear Bcd concentrations and Bcd-encoded positional information. We further trace the origin of Bcd gradient scaling by showing directly that large embryos have more maternally deposited bcd mRNA than small embryos. Our results suggest a simple model for how within-species Bcd gradient scaling can be achieved. In this model, the Bcd production rate, which is dependent on the total number of bcd mRNA molecules in the anterior, is scaled with embryo volume.

Gene expression in time and space: additive vs hierarchical organization of cis-regulatory regions

In higher eukaryotes, individual genes are often intermingled with other genes and spread out across tens to hundreds of kilobases, even though only small portions of their sequence are devoted to protein coding. Yet, in this seemingly extended and tangled mess, the cell is able to precisely regulate gene expression in both time and space. Over the past few decades, numerous elements, like enhancers, silencers and insulators have been found that shed some light on how the precise control of gene expression is achieved. Through these discoveries, an additive model of gene expression was envisioned, where the addition of the patterning details imparted by regulatory elements would create the final pattern of gene expression. Although many genes can be described using this model, recent work in the Drosophila bithorax complex suggests that this model may be somewhat simplistic and, in fact, regulatory elements sometimes seem to communicate with each other to form a functional hierarchy that is far from additive.

The gap gene network

Gap genes are involved in segment determination during the early development of the fruit fly Drosophila melanogaster as well as in other insects. This review attempts to synthesize the current knowledge of the gap gene network through a comprehensive survey of the experimental literature. I focus on genetic and molecular evidence, which provides us with an almost-complete picture of the regulatory interactions responsible for trunk gap gene expression. I discuss the regulatory mechanisms involved, and highlight the remaining ambiguities and gaps in the evidence. This is followed by a brief discussion of molecular regulatory mechanisms for transcriptional regulation, as well as precision and size-regulation provided by the system. Finally, I discuss evidence on the evolution of gap gene expression from species other than Drosophila. My survey concludes that studies of the gap gene system continue to reveal interesting and important new insights into the role of gene regulatory networks in development and evolution.

Artificial selection on egg size perturbs early pattern formation in Drosophila melanogaster

Pattern formation in Drosophila embryogenesis has been widely investigated as a developmental and evolutionary model of robustness. To ask whether genetic variation for pattern formation is suppressed in this system, artificial selection for divergent egg size was used to challenge the scaling of even-skipped (eve) pattern formation in mitotic cycle 14 (stage 5) embryos of Drosophila melanogaster. Three-dimensional confocal imaging revealed shifts in the allometry of eve pair-rule stripes along both anterior–posterior (A–P) and dorsoventral (D–V) axes as a correlated response to egg size selection, indicating the availability of genetic variation for this buffered trait. Environmental perturbation was not required for the manifestation of this variation. The number of nuclei at the cellular blastoderm stage also changed in response to selection, with large-egg selected lines having more than 1000 additional nuclei relative to small-egg lines. This increase in nuclear number in larger eggs does not scale with egg size, however, as nuclear density is inversely correlated with egg length. Nuclear density varies along the A–P axis but does not correlate with the shift in eve stripe allometry between the selection treatments. Despite its macroevolutionary conservation, both eve stripe patterning and blastoderm cell number vary genetically both within and between closely related species.

Shaping a morphogen gradient for positional precision

Morphogen gradients, which provide positional information to cells in a developing tissue, could in principle adopt any nonuniform profile. To our knowledge, how the profile of a morphogen gradient affects positional precision has not been well studied experimentally. Here, we compare the positional precision provided by the Drosophila morphogenetic protein Bicoid (Bcd) in wild-type (wt) embryos with embryos lacking an interacting cofactor. The Bcd gradient in the latter case exhibits decreased positional precision around mid-embryo compared with its wt counterpart. The domain boundary of Hunchback (Hb), a target activated by Bcd, becomes more variable in mutant embryos. By considering embryo-to-embryo, internal, and measurement fluctuations, we dissect mathematically the relevant sources of fluctuations that contribute to the error in positional information. Using this approach, we show that the defect in Hb boundary positioning in mutant embryos is directly reflective of an altered Bcd gradient profile with increasing flatness toward mid-embryo. Furthermore, we find that noise in the Bcd input signal is dominated by internal fluctuations but, due to time and spatial averaging, the spatial precision of the Hb boundary is primarily affected by embryo-to-embryo variations. Our results demonstrate that the positional information provided by the wt Bcd gradient profile is highly precise and necessary for patterning precision.

Distance measurements via the morphogen gradient of Bicoid in Drosophila embryos

BACKGROUND

Patterning along the anterior-posterior (A-P) axis in Drosophila embryos is instructed by the morphogen gradient of Bicoid (Bcd). Despite extensive studies of this morphogen, how embryo geometry may affect gradient formation and target responses has not been investigated experimentally.

RESULTS

In this report, we systematically compare the Bcd gradient profiles and its target expression patterns on the dorsal and ventral sides of the embryo. Our results support a hypothesis that proper distance measurement and the encoded positional information of the Bcd gradient are along the perimeter of the embryo. Our results also reveal that the dorsal and ventral sides of the embryo have a fundamentally similar relationship between Bcd and its target Hunchback (Hb), suggesting that Hb expression properties on the two sides of the embryo can be directly traced to Bcd gradient properties. Our 3-D simulation studies show that a curvature difference between the two sides of an embryo is sufficient to generate Bcd gradient properties that are consistent with experimental observations.

CONCLUSIONS

The findings described in this report provide a first quantitative, experimental evaluation of embryo geometry on Bcd gradient formation and target responses. They demonstrate that the physical features of an embryo, such as its shape, are integral to how pattern is formed.

Deciphering the genome's regulatory code: the many languages of DNA

The generation of patterns and the diversity of cell types in a multicellular organism require differential gene regulation. At the heart of this process are enhancers or cis-regulatory modules (CRMs), genomic regions that are bound by transcription factors (TFs) that control spatio-temporal gene expression in developmental networks. To date, only a few CRMs have been studied in detail and the underlying cis-regulatory code is not well understood. Here, we review recent progress on the genome-wide identification of CRMs with chromatin immunoprecipitation of TF-DNA complexes followed by microarrays (ChIP-on-chip). We focus on two computational approaches that have succeeded in predicting the expression pattern driven by a CRM either based on TF binding site preferences and their expression levels, or quantitative analysis of CRM occupancy by key TFs. We also discuss the current limits of these methods and highlight some of the key problems that have to be solved to gain a more complete understanding of the structure and function of CRMs.