A 3D molecular atlas of the chick embryonic heart
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ABSTRACT:
SUBMITTER: Claire Anderson
PROVIDER: S-BIAD4 | bioimages | 2020-04-15
REPOSITORIES: bioimages
Similar Datasets
Project description:We performed a detailed analysis of gene expression in the 2-day (HH12) embryonic chick heart. RNA-seq of 13 microdissected heart regions reveals regionalised expression of about 15,000 genes (Dataset 1). Of these, 131 genes that are differentially expressed (FPKM ≥20, fold change ≥1.1-4.0) within a region compared to the other 12 regions were studied by in situ hybridisation (bold text in Dataset 1) and used to generate a 3D molecular map of the heart at this stage of development.
2019-10-02 | E-MTAB-7663 | biostudies-arrayexpress
Project description:A 3D molecular atlas of the chick embryonic heart
| PRJEB31198 | ENA
Project description:BACKGROUND:The developing mouse limb is widely used as a model system for studying tissue patterning. Despite this, few references are available that can be used for the correct identification of developing limb structures, such as muscles and tendons. Existing textual references consist of two-dimensional (2D) illustrations of the adult rat or mouse limb that can be difficult to apply when attempting to describe the complex three-dimensional (3D) relationship between tissues. RESULTS:To improve the resources available in the mouse model, we have generated a free, web-based, interactive reference of limb muscle, tendon, and skeletal structures at embryonic day (E) 14.5 http://www.nimr.mrc.ac.uk/3dlimb/. The Atlas was generated using mouse forelimb and hindlimb specimens stained using immunohistochemistry to detect muscle and tendon. Limbs were scanned using Optical Projection Tomography (OPT), reconstructed to make 3D models and annotated using computer-assisted segmentation tools in Amira 3D Visualisation software. The annotated dataset is visualised using Java, JAtlasView software. Users click on the names of structures and view their shape, position and relationship with other structures within the 3D model and also in 2D virtual sections. CONCLUSION:The Mouse Limb Anatomy Atlas provides a novel and valuable tool for researchers studying limb development and can be applied to a range of research areas, including the identification of abnormal limb patterning in transgenic lines and studies of models of congenital limb abnormalities. By using the Atlas for "virtual" dissection, this resource offers an alternative to animal dissection. The techniques we have developed and employed are also applicable to many other model systems and anatomical structures.
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Project description:One of the challenges of modern neuroscience is integrating voluminous data of diferent modalities derived from a variety of specimens. This task requires a common spatial framework that can be provided by brain atlases. The first atlases were limited to two-dimentional presentation of structural data. Recently, attempts at creating 3D atlases have been made to offer navigation within non-standard anatomical planes and improve capability of localization of different types of data within the brain volume. The 3D atlases available so far have been created using frameworks which make it difficult for other researchers to replicate the results. To facilitate reproducible research and data sharing in the field we propose an SVG-based Common Atlas Format (CAF) to store 2D atlas delineations or other compatible data and 3D Brain Atlas Reconstructor (3dBAR), software dedicated to automated reconstruction of three-dimensional brain structures from 2D atlas data. The basic functionality is provided by (1) a set of parsers which translate various atlases from a number of formats into the CAF, and (2) a module generating 3D models from CAF datasets. The whole reconstruction process is reproducible and can easily be configured, tracked and reviewed, which facilitates fixing errors. Manual corrections can be made when automatic reconstruction is not sufficient. The software was designed to simplify interoperability with other neuroinformatics tools by using open file formats. The content can easily be exchanged at any stage of data processing. The framework allows for the addition of new public or proprietary content.
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Project description:The locus and extent of brain damage in the event of vascular insult can be quantitatively established quickly and easily with vascular atlases. Although highly anticipated by clinicians and clinical researchers, no digital MRI arterial atlas is readily available for automated data analyses. We created a digital arterial territory atlas based on lesion distributions in 1,298 patients with acute stroke. The lesions were manually traced in the diffusion-weighted MRIs, binary stroke masks were mapped to a common space, probability maps of lesions were generated and the boundaries for each arterial territory was defined based on the ratio between probabilistic maps. The atlas contains the definition of four major supra- and infra-tentorial arterial territories: Anterior, Middle, Posterior Cerebral Arteries and Vertebro-Basilar, and sub-territories (thalamoperforating, lenticulostriate, basilar and cerebellar arterial territories), in two hierarchical levels. This study provides the first publicly-available, digital, 3D deformable atlas of arterial brain territories, which may serve as a valuable resource for large-scale, reproducible processing and analysis of brain MRIs of patients with stroke and other conditions.
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Project description:We present a new 3D digital brain atlas of the non-human primate, common marmoset monkey (Callithrix jacchus), with MRI and coregistered Nissl histology data. To the best of our knowledge this is the first comprehensive digital 3D brain atlas of the common marmoset having normalized multi-modal data, cortical and sub-cortical segmentation, and in a common file format (NIfTI). The atlas can be registered to new data, is useful for connectomics, functional studies, simulation and as a reference. The atlas was based on previously published work but we provide several critical improvements to make this release valuable for researchers. Nissl histology images were processed to remove illumination and shape artifacts and then normalized to the MRI data. Brain region segmentation is provided for both hemispheres. The data is in the NIfTI format making it easy to integrate into neuroscience pipelines, whereas the previous atlas was in an inaccessible file format. We also provide cortical, mid-cortical and white matter boundary segmentations useful for visualization and analysis.
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Project description:Defects in patterning during human embryonic development frequently result in craniofacial abnormalities. The gene regulatory programs that build the craniofacial complex are likely controlled by information located between genes and within intronic sequences. However, systematic identification of regulatory sequences important for forming the human face has not been performed. Here, we describe comprehensive epigenomic annotations from human embryonic craniofacial tissues and systematic comparisons with multiple tissues and cell types. We identified thousands of tissue-specific craniofacial regulatory sequences and likely causal regions for rare craniofacial abnormalities. We demonstrate significant enrichment of common variants associated with orofacial clefting in enhancers active early in embryonic development, while those associated with normal facial variation are enriched near the end of the embryonic period. These data are provided in easily accessible formats for both craniofacial researchers and clinicians to aid future experimental design and interpretation of noncoding variation in those affected by craniofacial abnormalities.
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Project description:This paper introduces a single-cell atlas for pivotal developmental stages in Xenopus, encompassing gastrulation, neurulation, and early tailbud. Notably surpassing its predecessors, the new atlas enhances gene mapping, read counts, and gene/cell type nomenclature. Leveraging the latest Xenopus tropicalis genome version, alongside advanced alignment pipelines and machine learning for cell type assignment, this release maintains consistency with previous cell type annotations while rectifying nomenclature issues. Employing an unbiased approach for cell type assignment proves especially apt for embryonic contexts, given the considerable number of non-terminally differentiated cell types. An alternative cell type attribution here adopts a fuzzy, non-deterministic stance, capturing the transient nature of early embryo progenitor cells by presenting an ensemble of types in superposition. The value of the new resource is emphasized through numerous examples, with a focus on previously unexplored germ cell populations where we uncover novel transcription onset features. Offering interactive exploration via a user-friendly web portal and facilitating complete data downloads, this atlas serves as a comprehensive and accessible reference.
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