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bioRxiv2022

Developmental staging of the complete life cycle of the model marine tubeworm Hydroides elegans

BackgroundThe biofouling marine tube worm, Hydroides elegans, is an indirect developing polychaete with significance as a model organism for questions in developmental biology and the evolution of host-microbe interactions. However, a complete description of the life cycle from fertilization through sexual maturity remains scattered in the literature, and lacks standardization. ResultsHere we present a unified staging scheme detailing the major morphological changes that occur during the entire life cycle of the animal. These data represent a complete record of the life cycle, and serve as a foundation for connecting molecular changes with morphology. ConclusionsThe present descriptions and associated staging scheme are especially timely as this system gains traction within research communities. Characterizing the Hydroides life cycle is essential for investigating the molecular mechanisms that drive major developmental transitions, like metamorphosis, in response to bacteria.

developmental biology↗

bioRxiv2026

Transforming avian to mammalian modes of digit patterning

How a conserved embryonic organiser--the Sonic hedgehog (Shh)-expressing Zone of Polarising Activity (ZPA)--generates diverse limb architectures in amniotes remains a central problem in evolutionary and developmental biology. The principal difference across species lies in the number of digits produced from ZPA tissue: two in mammals1, one in the chick leg2 and none in the chick wing2. Here we show that this divergence is governed by a Shh-p27Kip1 pathway operating in avian, but not mammalian ZPAs. In chick wing ZPA explants, attenuation of this pathway reveals an intrinsic digit-forming programme, enabling cells to self-organise signalling networks and generate digits after grafting into a host wing bud. Guided by these findings, we redirected the chick leg, which retains stem amniote digit identities, to follow a mammalian-like developmental trajectory. Precise temporal restriction of Shh signalling transforms chick legs into pentadactyl limbs with digit identities characteristic of mammals and their therapsid ancestors, with two digits arising from the ZPA. These findings establish a unifying framework for how Shh controls both digit number and identity across amniotes.

developmental biology↗

bioRxiv2018

Wnt/β-catenin regulates an ancient signaling network during zebrafish scale development

Understanding how patterning influences cell behaviors to generate three dimensional morphologies is a central goal of developmental biology. Additionally, comparing these regulatory mechanisms among morphologically diverse tissues allows for rigorous testing of evolutionary hypotheses. Zebrafish skin is endowed with a coat of precisely patterned bony scales. We use in-toto live imaging during scale development and manipulations of cell signaling activity to elucidate core features of scale patterning and morphogenesis. These analyses show that scale development requires the concerted activity of Wnt/{beta}-catenin, Ectodysplasin (Eda) and Fibroblast growth factor (Fgf) signaling. This regulatory module coordinates Hedgehog (HH) dependent collective cell migration during epidermal invagination, a cell behavior not previously implicated in skin appendage morphogenesis. Our analyses demonstrate the utility of zebrafish scale development as a tractable system in which to elucidate mechanisms of developmental patterning and morphogenesis, and suggest a single, ancient origin of skin appendage patterning mechanisms in vertebrates.

developmental biology↗

bioRxiv2023

Mutant analysis of Kcng4b reveals how the different functional states of the voltage-gated potassium channel regulate ear development

The voltage gated (Kv) slow-inactivating delayed rectifier channel regulates the development of hollow organs of the zebrafish. The functional tetramer consists of an electrically active subunit (Kcnb1, Kv2.1) and a modulatory silent subunit (Kcng4b, Kv6.4). The two mutations in zebrafish kcng4b - kcng4b-C1 and kcng4b-C2 (Gasanov et al., 2021) - have been studied during ear development using electrophysiology, developmental biology and in silico structural modelling. kcng4b-C1 mutation causes a C-terminal truncation characterized by mild Kcng4b loss-of-function (LOF) manifested by failure of kinocilia to extend and formation of ectopic otoliths. In contrast, the kcng4b-C2-/- mutation causes the C-terminal domain to elongate and the ectopic seventh transmembrane (TM) domain to form, converting the intracellular C-terminus to an extracellular one. Kcng4b-C2 acts as a Kcng4b gain-of-function (GOF) allele. Otoliths fail to develop and kinocilia are reduced in kcng4b-C2-/-. These results show that different mutations of the silent subunit Kcng4 can affect the activity of the Kv channel and cause a wide range of developmental defects.

developmental biology↗

bioRxiv2024

A timed epigenetic switch balances T and ILC lineage proportions in the thymus

How stem and progenitor cells give rise to multiple cell types in defined numbers and proportions is a central question in developmental biology. Epigenetic switches, acting at single gene loci, can generate extended delays in the activation timing of lineage-specifying genes, and thereby impact lineage decisions and cell type output of progenitors. Here, we analyzed a timed epigenetic switch controlling Bcl11b, a transcription factor that drives T cell lineage commitment, but only after a long multi-day time delay in expression. To investigate roles for this delay in controlling lineage decision making, we analyzed progenitors with a deletion in a distal Bcl11b enhancer, that further extends this delay by [~]3 days. Strikingly, delaying Bcl11b activation reduces T cell output but enhances ILC generation in the thymus, and does so by redirecting progenitors to the ILC lineages at the T and ILC developmental branchpoint. Mechanistically, delaying Bcl11b activation promoted ILC redirection by up-regulating a PLZF-dependent ILC transcriptional program in progenitors. Despite up-regulating PLZF, committed ILC progenitors were still capable of later activating Bcl11b, which is also needed for specification of type 2 ILCs. These results show that epigenetic switches, by controlling the activation timing and order of lineage-specifying genes within regulatory networks, can modulate population sizes and proportions of differentiated cell types.

developmental biology↗

bioRxiv2020

Asymmetric histone inheritance regulates stem cell fate in Drosophila midgut

A fundamental question in developmental biology is how distinct cell fates are established and maintained through epigenetic mechanisms in multicellular organisms. Here, we report that preexisting (old) and newly synthesized (new) histones H3 and H4 are asymmetrically inherited by the distinct daughter cells during asymmetric division of Drosophila intestinal stem cells (ISCs). By contrast, in symmetrically dividing ISCs that produce two self-renewed stem cells, old and new H3 and H4 show symmetric inheritance patterns. These results indicate that asymmetric histone inheritance is tightly associated with the distinct daughter cell fates. To further understand the biological significance of this asymmetry, we express a mutant histone that compromises asymmetric histone inheritance pattern. We find increased symmetric ISC division and ISC tumors during aging under this condition. Together, our results demonstrate that asymmetric histone inheritance is important for establishing distinct cell identities in a somatic stem cell lineage, consistent with previous findings in asymmetrically dividing male germline stem cells in Drosophila. Therefore, this work sheds light on the principles of histone inheritance in regulating stem cell fate in vivo.

developmental biology↗

bioRxiv2023

Polycomb safeguards imaginal disc specification through control of the Vestigial-Scalloped complex

A fundamental goal of developmental biology is to understand how cell and tissue fates are specified. The imaginal discs of Drosophila are excellent model systems for addressing this paradigm as their fate can be redirected when discs regenerate after injury or when key selector genes are mis-regulated. Here, we show that when Polycomb expression is reduced, the wing selector gene vestigial is ectopically activated. This leads to the inappropriate formation of the Vestigial-Scalloped complex which forces the eye to transform into a wing. We further demonstrate that disrupting this complex does not simply block wing formation or restore eye development. Instead, immunohistochemistry and high throughput genomic analysis show that the eye-antennal disc unexpectedly undergoes hyperplastic growth with multiple domains being organized into other imaginal discs and tissues. These findings provide insight into the complex developmental landscape that tissues must navigate before adopting their final fate. Summary StatementHere we describe a novel mechanism by which Pc promotes an eye fate during normal development and how the eye is reprogrammed into a wing in its absence.

developmental biology↗

bioRxiv2024

ARHGEF3 Regulates Hair Follicle Morphogenesis

During embryogenesis, cells arrange into precise patterns that enable tissues and organs to develop specialized functions. Despite its critical importance, the molecular choreography behind these collective cellular behaviors remains elusive, posing a major challenge in developmental biology and limiting advances in regenerative medicine. By using the mouse hair follicle as a mini-organ system to study the formation of bud-like structures during embryonic development, our work uncovers a crucial role for the Rho GTPase regulator ARHGEF3 in hair follicle morphogenesis. We demonstrate that Arhgef3 expression is upregulated at the onset of hair follicle placode formation. In Arhgef3 knockout animals, we observed defects in placode compaction, leading to impaired hair follicle downgrowth. Through cell culture models, we show that ARHGEF3 promotes F-actin accumulation at the cell cortex and P-cadherin enrichment at cell-cell junctions. Collectively, our study identifies ARHGEF3 as a new regulator of cell shape rearrangements during hair placode morphogenesis, warranting further exploration of its role in other epithelial appendages that arise from similar developmental processes.

developmental biology↗

bioRxiv2025

Automated, high-throughput in-situ hybridization of Lytechinus pictus embryos

Despite the reach of in situ hybridization (ISH) in developmental biology, it has rarely been used at scale. The major limitation has been the throughput of the assay, which typically relies upon labor intensive manual steps. The goal of this study was to develop a fully automated hybridization chain reaction (HCR) pipeline capable of large-scale gene expression pattern profiling, with dramatically reduced cost and effort, in the sea urchin Lytechinus pictus. Our resulting pipeline, which we term high throughput (HT)-HCR, can process 192 gene probe sets on whole-mount embryos within 32 hours. The unique qualities of the sea urchin embryo enabled us to automate the entire HCR assay in a 96-well plate format, and utilize highly miniaturized reaction volumes, a general purpose robotic liquid handler, and automated confocal microscopy. From this approach we produced high quality localization data for 101 target genes across three developmental stages of L. pictus. The results reveal the localization of previously undescribed physiological genes, as well as canonical developmental transcription factors. HT-HCR represents a log order increase in the rate at which spatial transcriptomic data can be resolved in the sea urchin. This study paves the way for localization of understudied genes and for sophisticated perturbation analysis. Summary StatementWe developed an automated high-throughput HCR pipeline to rapidly map expression of 101 genes in sea urchin embryos, enabling large-scale discovery of novel developmental gene expression patterns.

developmental biology↗

bioRxiv2017

Brain Development: Machine Learning Analysis Of Individual Stem Cells In Live 3D Tissue

A major challenge in cell and developmental biology is the automated identification and quantitation of cells in complex multilayered tissues. We developed CytoCensus: an easily deployed implementation of supervised machine learning that extends convenient 2D \"point- and-click\" user training to 3D detection of cells in challenging datasets with ill-defined cell boundaries. In tests on these datasets, CytoCensus outperforms other freely available image analysis software in accuracy and speed of cell detection. We used CytoCensus to count stem cells and their progeny, and to quantify individual cell divisions from time-lapse movies of explanted Drosophila larval brains, comparing wild-type and mutant phenotypes. We further illustrate the general utility and future potential of CytoCensus by analysing the 3D organisation of multiple cell classes in Zebrafish retinal organoids and cell distributions in mouse embryos. CytoCensus opens the possibility of straightforward and robust automated analysis of developmental phenotypes in complex tissues.\n\nSummaryHailstone et al. develop CytoCensus, a \"point-and-click\" supervised machine-learning image analysis software to quantitatively identify defined cell classes and divisions from large multidimensional data sets of complex tissues. They demonstrate its utility in analysing challenging developmental phenotypes in living explanted Drosophila larval brains, mammalian embryos and zebrafish organoids. They further show, in comparative tests, a significant improvement in performance over existing easy-to-use image analysis software.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=198 HEIGHT=200 SRC=\"FIGDIR/small/137406v4_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (93K):\norg.highwire.dtl.DTLVardef@68912corg.highwire.dtl.DTLVardef@11300bdorg.highwire.dtl.DTLVardef@95810corg.highwire.dtl.DTLVardef@14b77a6_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LICytoCensus: machine learning quantitation of cell types in complex 3D tissues\nC_LIO_LISingle cell analysis of division rates from movies of living Drosophila brains in 3D\nC_LIO_LIDiverse applications in the analysis of developing vertebrate tissues and organoids\nC_LIO_LIOutperforms other image analysis software on challenging, low SNR datasets tested\nC_LI

developmental biology↗

bioRxiv2020

A deep learning approach for staging embryonic tissue isolates with small data

Machine learning approaches are becoming increasingly widespread and are now present in most areas of research. Their recent surge can be explained in part due to our ability to generate and store enormous amounts of data with which to train these models. The requirement for large training sets is also responsible for limiting further potential applications of machine learning, particularly in fields where data tend to be scarce such as developmental biology. However, recent research seems to indicate that machine learning and Big Data can sometimes be decoupled to train models with modest amounts of data. In this work we set out to train a CNN-based classifier to stage zebrafish tail buds at four different stages of development using small information-rich data sets. Our results show that two and three dimensional convolutional neural networks can be trained to stage developing zebrafish tail buds based on both morphological and gene expression confocal microscopy images, achieving in each case up to 100% test accuracy scores. Importantly, we show that high accuracy can be achieved with data set sizes of under 100 images, much smaller than the typical training set size for a convolutional neural net. Furthermore, our classifier shows that it is possible to stage isolated embryonic structures without the need to refer to classic developmental landmarks in the whole embryo, which will be particularly useful to stage 3D culture in vitro systems such as organoids. We hope that this work will provide a proof of principle that will help dispel the myth that large data set sizes are always required to train CNNs, and encourage researchers in fields where data are scarce to also apply ML approaches. Author summaryThe application of machine learning approaches currently hinges on the availability of large data sets to train the models with. However, recent research has shown that large data sets might not always be required. In this work we set out to see whether we could use small confocal microscopy image data sets to train a convolutional neural network (CNN) to stage zebrafish tail buds at four different stages in their development. We found that high test accuracies can be achieved with data set sizes of under 100 images, much smaller than the typical training set size for a CNN. This work also shows that we can robustly stage the embryonic development of isolated structures, without the need to refer back to landmarks in the tail bud. This constitutes an important methodological advance for staging organoids and other 3D culture in vitro systems. This work proves that prohibitively large data sets are not always required to train CNNs, and we hope will encourage others to apply the power of machine learning to their areas of study even if data are scarce.

developmental biology↗

bioRxiv2022

TubULAR: Tracking deformations of dynamic tissues and interfaces in 3D

A common motif in biology is the arrangement of cells into tube-like sheets, which further transform into more complex shapes. Traditionally, analysis of the dynamic surfaces of growing tissues has relied on inspecting static snapshots, live imaging of cross-sections, or tracking isolated cells in 3D. However, capturing the interplay between in-plane and out-of-plane behaviors requires following the full surface as it deforms and integrating cell-scale motions into collective, tissue-scale deformations. The advent of methods for whole-organ live imaging ushers the need for in toto analysis methods to understand these collective tissue dynamics. Here, we introduce an approach that builds in toto maps of surface deformation by following tissue parcels in the material frame of reference. Mapping the full 3D surface to 2D images such that the tissue motion in 2D is minimal enables the user to easily follow the tissue and discern its 3D motion. We then provide a computational framework for linking in-plane and out-of-plane behaviors and decomposing complex deformation maps into elementary contributions. The Tube-like sUrface Lagrangian Analysis Resource (TubULAR) provides an open-source MATLAB implementation whose functionality is accessible either as a standalone toolkit or as an extension of the ImSAnE package used in the developmental biology community. We underscore the power of our approach by analyzing shape change in the embryonic Drosophila midgut and beating zebrafish heart. Following deformations in the tissue/material frame reveals the signatures of tissue flow and a reduced-dimensional mode decomposition of the dynamics. The method naturally generalizes to in vitro and synthetic systems and provides ready access to the mechanical mechanisms relating genetic patterning to organ shape change.

developmental biology↗

bioRxiv2025

Dpp Scaling is Not the Key to Robust Wing Patterning in Drosophila

Individuals within a population can vary dramatically in body and trait size in response to environmental factors such as developmental nutrition, temperature, and oxygen level, a phenomenon called phenotypic plasticity. Despite this variation, morphological pattern across the body and within traits are largely maintained, an example of developmental robustness. Consequently, the same trait can display both plastic and robust phenotypes. A fundamental yet unanswered question in developmental biology is: how do organs achieve plasticity in size while maintaining the robustness of pattern? This question is often answered using the French flag model of cell fate specification1-4. The model argues that cells receive positional information from a gradient of signaling molecules (morphogens) that diffuse from a single location in undifferentiated tissue. Specifically, the model argues that if the gradient is dynamically scale invariant, such that the gradient adjusts proportionally to the size of the tissue as it grows, then pattern is maintained regardless of the tissue size. However, while dynamic scale invariance has been demonstrated in several systems5,6, and explicitly2 or implicitly7,8 used to explain the robustness of pattern when tissue size varies due to environmental factors, this hypothesis has not yet been tested. We used the developing Drosophila wing as a model to test this hypothesis, under environmental conditions that reduce (low developmental oxygen level) and increase (low developmental temperature) adult wing size. We found that scale invariance of morphogen gradients is not observed under non-standard environmental conditions and is therefore not an explanation for robust patterning in the Drosophila wing with environmental variation in wing size.

developmental biology↗

bioRxiv2026

Longitudinal, Non-Invasive Imaging of the Developing Chick Heart, Vasculature, and Chorioallantoic Membrane (CAM)

The chick embryo is a widely used vertebrate model for developmental biology, cardiovascular, and bioengineering research. We present an automated laser speckle contrast imaging (LSCI) platform for non-invasive, longitudinal, label-free imaging of the developing heart and extraembryonic vasculature of the chick embryo through the intact eggshell. The platform can detect blood vessels as small as 70 +/- 17 um in diameter and enable repeated imaging from day 0 to day 8 of incubation without disturbing normal embryonic development. It provides both structural (a map of growing extraembryonic blood vessels) and functional (blood flow dynamics and heart rate) information. Using this system, we generated the first continuous, non-invasive, time-lapse recordings of the early functioning chick heart and its extraembryonic vessels. Longitudinal imaging was performed on 15 embryos from different chicken breeds with eggshell colors white, brown and green. Analysis revealed slight variability in early cardiac and vascular morphogenesis across breeds and shell types and shows its potential for automated developmental staging. Finally, for the first time, the growing vasculature of the yolk sac and the chorioallantoic (CAM) membrane was imaged from day 4 to 8. The heart rate and growth of the extraembryonic blood vessels were quantified automatically during imaging.

developmental biology↗

bioRxiv2026

Comparative Biology at Single-Cell Resolution: Rigorous Matching of Atlases for Cross-Species Analysis

Single-cell transcriptomics has revolutionised developmental biology by providing an unprecedented, fine-grained view of cellular lineages. However, our ability to compare species and distinguish universal from species-specific developmental principles remains limited by biological and technical variability. To address this, we introduce RIMA (RIgorous Matching of Atlases), a method for quantitatively comparing transcriptomic atlases across species at near-single-cell resolution. RIMA uses a novel computational approach to identify matching cell states across atlases and leverages this to enable quantitative comparative analyses. Applied to gastrulation in mouse, rabbit, and macaque, RIMA recapitulates a developmental hourglass pattern, identifying a molecular similarity bottleneck at the onset of organogenesis. It further uncovers conserved developmental programmes, including a core set of transcription factors driving epithelial-mesenchymal transition, and highlights transcriptional boosts of erythroid differentiation genes that are conserved across species but exhibit shifted onset timing. Furthermore, RIMA enables cross-species prediction of gene expression, augmenting sparse atlases and correcting differences between model and target organisms. Beyond cross-species comparisons, RIMAs framework extends naturally to any setting where large systematic differences exist across datasets, including in vitro to in vivo comparisons, opening new avenues for improving biological models and advancing translational research.

bioinformatics↗

bioRxiv2022

mBeRFP, a versatile fluorescent tool to enhance multichannel live imaging and its applications

Cell and developmental biology increasingly require live imaging of protein dynamics in cells, tissues or living organisms. Thanks to the discovery and the development of a panel of fluorescent proteins over the last decades, live imaging has become a powerful and commonly used approach. However, multicolor live imaging remains challenging. The generation of long Stokes shift red fluorescent proteins, such as mBeRFP, offers interesting new perspectives to bypass this limitation. Here, we constructed a set of mBeRFP-expressing vectors and provided a detailed characterization of this fluorescent protein for in vivo live imaging and its applications in Drosophila. Briefly, we showed that a single illumination source is sufficient to simultaneously stimulate mBeRFP and GFP. We demonstrated that mBeRFP can be easily combined with classical green and red fluorescent protein without any crosstalk. We also showed that the low photobleaching of mBeRFP is suitable for live imaging, and that this protein can be used for quantitative applications such as FRAP or laser ablation. Finally, we believe that this fluorescent protein, with the set of new possibilities it offers, constitutes an important tool for cell, developmental and mechano biologists in their current research.

developmental biology↗

bioRxiv2025

The Network Basis of Pattern Formation: A Topological Atlas of Multifunctional Turing Networks

Understanding how genetic networks can drive different self-organizing spatial behaviors remains a significant challenge. Here, we use an automated algebraic method to systematically screen for Turing networks capable of generating diverse spatial patterns from noise, including periodic static waves, traveling waves and noise-amplifying patterns. We organize these networks into a topological atlas--a higher-level graph where nodes represent Turing networks linked together when they differ by only one regulatory interaction. In this atlas, Turing networks are arranged into distinct clusters showing a remarkable correspondence between network topology and self-organizing behaviors. Using an analytical approach, we identify the specific regulatory feedbacks that characterize each behavior. Moreover, we discover that different clusters are interconnected by multifunctional networks that can transition between behaviors upon feedback modulation. Among these networks, we find a new class of multiphase Turing networks capable of altering the phase of periodic wave patterns depending on the parameters, and networks that can transition between static and oscillatory Turing behaviors. The atlas further highlights the crucial role of feedback on immobile nodes in regulating pattern formation speed and precision by canalizing system noise. Overall, our study provides a novel framework to study the evolution and development of multicellular self-organization through changes in network topology and feedback modulation. This offers insights into how genetic regulatory networks can be tuned to drive pattern formation in developmental biology and in stem cell systems like embryoids and organoids. Significance StatementBy employing an automated algebraic method, Regueria and Marcon construct a topological atlas that categorizes Turing networks based on their ability to produce periodic patterns, traveling waves, or noise amplifying patterns. The atlas identifies distinct topological clusters linked by multi-functional networks that can transition between behaviors through feedback modulation. Key findings highlight how modulation of regulatory cycle strength in time or space can promote transition between static and oscillatory periodic pattern. The study also reveals the importance of feedback on immobile nodes in managing noise and influencing pattern formation. Overall the topological atlas offers a new framework for examining the evolution and development of multicellular self-organization.

developmental biology↗

bioRxiv2017

Pericyte ontogeny: the use of chimeras to track a cell lineage of diverse germ line origins

The goal of lineage tracing is to understand body formation over time by discovering which cells are the progeny of a specific, identified, ancestral progenitor. Subsidiary questions include unequivocal identification of what they have become, how many descendants develop, whether they live or die, and where they are located in the tissue or body at the end of the window examined. A classical approach in experimental embryology, lineage tracing continues to be used in developmental biology, stem cell and cancer research, wherever cellular potential and behavior need to be studied in multiple dimensions, of which one is time. Each technical approach has its advantages and drawbacks. This chapter, with some previously unpublished data, will concentrate non-exclusively on the use of interspecies chimeras to explore the origins of perivascular (or mural) cells, of which those adjacent to the vascular endothelium are termed pericytes for this purpose. These studies laid the groundwork for our understanding that pericytes derive from progenitor mesenchymal pools of multiple origins in the vertebrate embryo, some of which persist into adulthood. The results obtained through xenografting, like in the methodology described here, complement those obtained through genetic lineage tracing techniques within a given species.

developmental biology↗