Cell tracing reveals a dorsoventral lineage restriction plane in the mouse limb bud mesenchyme.

Regionalization of embryonic fields into independent units of growth and patterning is a widespread strategy during metazoan development. Compartments represent a particular instance of this regionalization, in which unit coherence is maintained by cell lineage restriction between adjacent regions. Lineage compartments have been described during insect and vertebrate development. Two common characteristics of the compartments described so far are their occurrence in epithelial structures and the presence of signaling regions at compartment borders. Whereas Drosophila compartmental organization represents a background subdivision of embryonic fields that is not necessarily related to anatomical structures, vertebrate compartment borders described thus far coincide with, or anticipate, anatomical or cell-type discontinuities. Here, we describe a general method for clonal analysis in the mouse and use it to determine the topology of clone distribution along the three limb axes. We identify a lineage restriction boundary at the limb mesenchyme dorsoventral border that is unrelated to any anatomical discontinuity, and whose lineage restriction border is not obviously associated with any signaling center. This restriction is the first example in vertebrates of a mechanism of primordium subdivision unrelated to anatomical boundaries. Furthermore, this is the first lineage compartment described within a mesenchymal structure in any organism, suggesting that lineage restrictions are fundamental not only for epithelial structures, but also for mesenchymal field patterning. No lineage compartmentalization was found along the proximodistal or anteroposterior axes, indicating that patterning along these axes does not involve restriction of cell dispersion at specific axial positions.S

Automatic reconstruction from serial sections

In many experiments in biological and medical research, serial sectioning of biological material is the only way to reveal the three dimensional (3D) structure and function. For a number of reasons other 3D imaging techniques, such as CT, MRI, and confocal microscopy, are not always adequate because they cannot provide the necessary resolution or contrast, or because the specimen is too large, or because the staining techniques require sectioning. Therefore for the foreseeable future reconstruction from serial sections will remain the only method for 3D investigations in many biomedical fields. Reconstruction is a difficult problem due to the loss of 3D alignment as the sections are cut and, more seriously, the systematic and random distortion caused by the sectioning and preparation processes.Many authors have reported how serial sections can be registered by means of fiducial markers or otherwise, but there have been only a few studies of automated correction of the sectioning distortions. In this thesis solutions to the registration problem are reviewed and discussed, and a solution to the warping problem, based on image pro¬ cessing techniques and the finite element method (FEM), is presented. The aim of this project was to develop a fully automatic method of reconstruction in order to provide a 3D atlas of mouse development as part of a gene expression database. For this purpose it is not necessary to warp the object so that it is identical to the original object, but to correct local distortions in the sections in order to produce a smooth representative mouse embryo. Furthermore the use of fiducial markers was not possible because the reconstructions were from already sectioned material.In this thesis we demonstrate a new method for warping serial sections. The sections are warped by applying forces to each section, where each section is modelled as a thin elastic plate. The deformation forces are determined from correspondences between sections which are calculated by combining match strengths and positional information. The equilibrium state which represents the reconstructed 3D image is calculated using the finite element method. Results of the application of these methods to paraffin wax and resin embedded sections of the mouse embryo are presented

Mechanical Coupling Coordinates the Co-elongation of Axial and Paraxial Tissues in Avian Embryos.

Tissues undergoing morphogenesis impose mechanical effects on one another. How developmental programs adapt to or take advantage of these effects remains poorly explored. Here, using a combination of live imaging, modeling, and microsurgical perturbations, we show that the axial and paraxial tissues in the forming avian embryonic body coordinate their rates of elongation through mechanical interactions. First, a cell motility gradient drives paraxial presomitic mesoderm (PSM) expansion, resulting in compression of the axial neural tube and notochord; second, elongation of axial tissues driven by PSM compression and polarized cell intercalation pushes the caudal progenitor domain posteriorly; finally, the axial push drives the lateral movement of midline PSM cells to maintain PSM growth and cell motility. These interactions form an engine-like positive feedback loop, which sustains a shared elongation rate for coupled tissues. Our results demonstrate a key role of inter-tissue forces in coordinating distinct body axis tissues during their co-elongation

Quantifying heart development

This thesis presents a series of papers on quantified heart development. It contains an atlas of human embryonic heart development, covering the first 8 weeks after conception. This atlas gives graphs of growth in size and volume of the various cardiac compartments. Such measures are still scarce in literature as illustrated in a review about ventricular wall development. The atlas also shows that by quantification of growth, new insights in developmental processes, such as sinus venosus incorporation can be gained. It, together with a series of ventricular wall growth curves covering foetal development, illustrates that a hypertrabeculated ventricle is the result of differential growth rather than a failure of compaction as has been presumed to underlie left ventricular non-compaction cardiomyopathy. Additionally, this thesis shows that trabecular myocardium is not necessarily weaker or ill-adapted to force generation compared to the compact wall as is assumed to be the case in aforementioned cardiomyopathy. Furthermore, quantification of atrioventricular canal growth on foetal ultrasounds lend support to the theory that aberrant atrioventricular canal development can lead to tricuspid valve agenesis. Finally, this thesis shows that there is a role for comparative anatomy, in a broader sense than just mouse and chicken, in understanding mammalian and human heart development by comparing a series of bird hearts from different species

A Computational Framework for Learning from Complex Data: Formulations, Algorithms, and Applications

Many real-world processes are dynamically changing over time. As a consequence, the observed complex data generated by these processes also evolve smoothly. For example, in computational biology, the expression data matrices are evolving, since gene expression controls are deployed sequentially during development in many biological processes. Investigations into the spatial and temporal gene expression dynamics are essential for understanding the regulatory biology governing development. In this dissertation, I mainly focus on two types of complex data: genome-wide spatial gene expression patterns in the model organism fruit fly and Allen Brain Atlas mouse brain data. I provide a framework to explore spatiotemporal regulation of gene expression during development. I develop evolutionary co-clustering formulation to identify co-expressed domains and the associated genes simultaneously over different temporal stages using a mesh-generation pipeline. I also propose to employ the deep convolutional neural networks as a multi-layer feature extractor to generate generic representations for gene expression pattern in situ hybridization (ISH) images. Furthermore, I employ the multi-task learning method to fine-tune the pre-trained models with labeled ISH images. My proposed computational methods are evaluated using synthetic data sets and real biological data sets including the gene expression data from the fruit fly BDGP data sets and Allen Developing Mouse Brain Atlas in comparison with baseline existing methods. Experimental results indicate that the proposed representations, formulations, and methods are efficient and effective in annotating and analyzing the large-scale biological data sets

Cyberinfrastructure for the digital brain:spatial standards for integrating rodent brain atlases

Biomedical research entails capture and analysis of massive data volumes and new discoveries arise from data-integration and mining. This is only possible if data can be mapped onto a common framework such as the genome for genomic data. In neuroscience, the framework is intrinsically spatial and based on a number of paper atlases. This cannot meet today’s data-intensive analysis and integration challenges. A scalable and extensible software infrastructure that is standards based but open for novel data and resources, is required for integrating information such as signal distributions, gene-expression, neuronal connectivity, electrophysiology, anatomy, and developmental processes. Therefore, the International Neuroinformatics Coordinating Facility (INCF) initiated the development of a spatial framework for neuroscience data integration with an associated Digital Atlasing Infrastructure (DAI). A prototype implementation of this infrastructure for the rodent brain is reported here. The infrastructure is based on a collection of reference spaces to which data is mapped at the required resolution, such as the Waxholm Space (WHS), a 3D reconstruction of the brain generated using high-resolution, multi-channel microMRI. The core standards of the digital atlasing service-oriented infrastructure include Waxholm Markup Language (WaxML): XML schema expressing a uniform information model for key elements such as coordinate systems, transformations, points of interest (POI)s, labels, and annotations; and Atlas Web Services: interfaces for querying and updating atlas data. The services return WaxML-encoded documents with information about capabilities, spatial reference systems and structures, and execute coordinate transformations and POI-based requests. Key elements of INCF-DAI cyberinfrastructure have been prototyped for both mouse and rat brain atlas sources, including the Allen Mouse Brain Atlas, UCSD Cell-Centered Database, and Edinburgh Mouse Atlas Project

Using cilia mutants to study left-right asymmetry in zebrafish

A thesis submitted in fulfillment of the requirements for the degree of the Masters in Molecular Genetics and BiomedicineIn vertebrates, internal organs are positioned asymmetrically across the left-right (L-R) body axis. Events determining L-R asymmetry occur during embryogenesis, and are regulated by the coordinated action of genetic mechanisms. Embryonic motile cilia are essential in this process by generating a directional fluid flow inside the zebrafish organ of asymmetry, called Kupffer’s vesicle ﴾KV). A correct L-R formation is highly dependent on signaling pathways downstream of such flow, however detailed characterization of how its dynamics modulates these mechanisms is still lacking. In this project, fluid flow measurements were achieved by a non-invasive method, in four genetic backgrounds: Wild-type (WT), deltaD-/- mutants, Dnah7 morphants (MO) and control-MO embryos. Knockdown of Dnah7, a heavy chain inner axonemal dynein, renders cilia completely immotile and depletes the KV directional fluid flow, which we characterize here for the first time. By following the development of each embryo, we show that flow dynamics in the KV is already asymmetric and provides a very good prediction of organ laterality. Through novel experiments, we characterized a new population of motile cilia, an immotile population, a range of cilia beat frequencies and lengths, KV volumes and cilia numbers in live embryos. These data were crucial to perform fluid dynamics simulations, which suggested that the flow in embryos with 30 or more cilia reliably produces left situs; with fewer cilia, left situs is sometimes compromised through disruption of the dorsal anterior clustering of motile cilia. A rough estimate based upon the 30 cilium threshold and statistics of cilium number predicts 90% and 60% left situs in WT and deltaD-/- respectively, as observed experimentally. Cilia number and clustering are therefore critical to normal situs via robust asymmetric flow. Thus, our results support a model in which asymmetric flow forces registered in the KV pattern organ laterality in each embryo