The distribution of Dishevelled in convergently extending mesoderm

Convergent extension (CE) is a conserved morphogenetic movement that drives axial lengthening of the primary body axis and depends on the planar cell polarity (PCP) pathway. In Drosophila epithelia, a polarised subcellular accumulation of PCP core components, such as Dishevelled (Dvl) protein, is associated with PCP function. Dvl has long been thought to accumulate in the mediolateral protrusions in Xenopus chordamesoderm cells undergoing CE. Here we present a quantitative analysis of Dvl intracellular localisation in Xenopus chordamesoderm cells. We find that, surprisingly, accumulations previously observed at mediolateral protrusions of chordamesodermal cells are not protrusion-specific but reflect yolk-free cytoplasm and are quantitatively matched by the distribution of the cytoplasm-filling lineage marker dextran. However, separating cell cortex-associated from bulk Dvl signal reveals a statistical enrichment of Dvl in notochord–somite boundary-(NSB)-directed protrusions, which is dependent upon NSB proximity. Dvl puncta were also observed, but only upon elevated overexpression. These puncta showed no statistically significant spatial bias, in contrast to the strongly posteriorly-enriched GFP-Dvl puncta previously reported in zebrafish. We propose that Dvl distribution is more subtle and dynamic than previously appreciated and that in vertebrate mesoderm it reflects processes other than protrusion as such

Contour Extraction of Drosophila Embryos Using Active Contours in Scale Space

Contour extraction of Drosophila embryos is an important step to build a computational system for pattern matching of embryonic images which aids in the discovery of genes. Automatic contour extraction of embryos is challenging due to several image variations such as size, shape, orientation and neigh- boring embryos such as touching and non-touching embryos. In this thesis, we introduce a framework for contour extraction based on the connected components in the gaussian scale space of an embryonic image. The active contour model is applied on the images to refine embryo contours. Data cleaning methods are applied to smooth the jaggy contours caused by blurred embryo boundaries. The scale space theory is applied to improve the performance of the result. The active contour adjusts better to the object for finer scales. The proposed framework contains three components. In the first component, we find the connected components of the image. The second component is to find the largest component of the image. Finally, we analyze the largest component across scales by selecting the optimal scale corresponding to the largest component having largest area. The optimal scale at which maximum area is attained is assumed to give information about the feature being extracted. We tested the proposed framework on BDGP images, and the results achieved promising accuracy in extracting the targeting embryo

Differential expression of conserved germ line markers and delayed segregation of male and female primordial germ cells in a hermaphrodite, the leech helobdella.

In sexually reproducing animals, primordial germ cells (PGCs) are often set aside early in embryogenesis, a strategy that minimizes the risk of genomic damage associated with replication and mitosis during the cell cycle. Here, we have used germ line markers (piwi, vasa, and nanos) and microinjected cell lineage tracers to show that PGC specification in the leech genus Helobdella follows a different scenario: in this hermaphrodite, the male and female PGCs segregate from somatic lineages only after more than 20 rounds of zygotic mitosis; the male and female PGCs share the same (mesodermal) cell lineage for 19 rounds of zygotic mitosis. Moreover, while all three markers are expressed in both male and female reproductive tissues of the adult, they are expressed differentially between the male and female PGCs of the developing embryo: piwi and vasa are expressed preferentially in female PGCs at a time when nanos is expressed preferentially in male PGCs. A priori, the delayed segregation of male and female PGCs from somatic tissues and from one another increases the probability of mutations affecting both male and female PGCs of a given individual. We speculate that this suite of features, combined with a capacity for self-fertilization, may contribute to the dramatically rearranged genome of Helobdella robusta relative to other animals

SPEX2: automated concise extraction of spatial gene expression patterns from Fly embryo ISH images

Motivation: Microarray profiling of mRNA abundance is often ill suited for temporal–spatial analysis of gene expressions in multicellular organisms such as Drosophila. Recent progress in image-based genome-scale profiling of whole-body mRNA patterns via in situ hybridization (ISH) calls for development of accurate and automatic image analysis systems to facilitate efficient mining of complex temporal–spatial mRNA patterns, which will be essential for functional genomics and network inference in higher organisms

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

Three-dimensional morphology and gene expression in the Drosophila blastoderm at cellular resolution I: data acquisition pipeline

BACKGROUND: To model and thoroughly understand animal transcription networks, it is essential to derive accurate spatial and temporal descriptions of developing gene expression patterns with cellular resolution. RESULTS: Here we describe a suite of methods that provide the first quantitative three-dimensional description of gene expression and morphology at cellular resolution in whole embryos. A database containing information derived from 1,282 embryos is released that describes the mRNA expression of 22 genes at multiple time points in the Drosophila blastoderm. We demonstrate that our methods are sufficiently accurate to detect previously undescribed features of morphology and gene expression. The cellular blastoderm is shown to have an intricate morphology of nuclear density patterns and apical/basal displacements that correlate with later well-known morphological features. Pair rule gene expression stripes, generally considered to specify patterning only along the anterior/posterior body axis, are shown to have complex changes in stripe location, stripe curvature, and expression level along the dorsal/ventral axis. Pair rule genes are also found to not always maintain the same register to each other. CONCLUSION: The application of these quantitative methods to other developmental systems will likely reveal many other previously unknown features and provide a more rigorous understanding of developmental regulatory networks

Three-dimensional morphology and gene expression in the Drosophila blastoderm at cellular resolution I: data acquisition pipeline

BACKGROUND: To model and thoroughly understand animal transcription networks, it is essential to derive accurate spatial and temporal descriptions of developing gene expression patterns with cellular resolution. RESULTS: Here we describe a suite of methods that provide the first quantitative three-dimensional description of gene expression and morphology at cellular resolution in whole embryos. A database containing information derived from 1,282 embryos is released that describes the mRNA expression of 22 genes at multiple time points in the Drosophila blastoderm. We demonstrate that our methods are sufficiently accurate to detect previously undescribed features of morphology and gene expression. The cellular blastoderm is shown to have an intricate morphology of nuclear density patterns and apical/basal displacements that correlate with later well-known morphological features. Pair rule gene expression stripes, generally considered to specify patterning only along the anterior/posterior body axis, are shown to have complex changes in stripe location, stripe curvature, and expression level along the dorsal/ventral axis. Pair rule genes are also found to not always maintain the same register to each other. CONCLUSION: The application of these quantitative methods to other developmental systems will likely reveal many other previously unknown features and provide a more rigorous understanding of developmental regulatory networks