Modularly built, complete, coordinate- and template-free brain atlases

项目摘要 解剖地图集是组织/器官/脑中细胞的空间参考图，并提供结构 为广泛的生物分析提供信息。线虫神经系统的解剖图谱是 只有动物的整个神经系统的图谱，具有所有神经元类别的分辨率。然而，它是建立在 由于数据集和人工注释有限，标准图谱在捕捉生物多样性方面是不够的， 常规细胞鉴定不准确，难于使用，仅适用于野生型成人。虽然有几个 为了建立地图集，产生和成像标记菌株的英勇努力极大地改进了地图集，那里 仍然需要一条管道来建立准确的遗传背景特定(或实验条件特定) 地图集容易和便宜；此外，需要建立这样的地图集，可以使用而不专门 设备和尽可能少的遗传干扰。机器学习的最新发展 技术和分子转基因方法使体内报道和 能够大规模收集和处理高分辨率数据集的成像方法。这样做的目的是 应用是通过建立实验和计算相结合的方法来解决目前的瓶颈问题 模块化、完整、无坐标和无模板脑图谱的流水线 灵活使用。通过在大量活体动物身上成像标记，该项目将产生完整的 线虫神经系统的解剖图谱，捕捉了种群的变异性，这将极大地 在每种动物身上使用时，提高身份预测的准确性。该项目将生成一个集合 转基因动物表达部分重叠的体内标记，覆盖所有神经元并建立 汇编地图集的计算管道。此外，一些广泛适用的发展地图集作为 该项目的直接成果将展示管道和方法。重要的是，这些地图集并不寻求 为每个神经元类提供一组刚性坐标，而不是一组可用于 为每个新样本提供神经元同一性的最佳估计。这确保了准确性和适用性。 特定用例的地图集。全脑地图集的构建是从容易获得的部分 地图集，并可以根据需要进行众包。通过图像输入和神经元识别，将简化使用 预测输出。拟议的项目具有创新性，因为它将建立第一个完整的解剖地图集 使用从许多活体动物的活体标记中收集的大型数据集来描述神经系统；它使用关系 唯一适合于提供更准确任务的信息；它将捕获个体之间的差异 动物。拟议的这项工作意义重大，因为它将解决对准确、 易于使用和易于更新的地图集来管理大脑；此外，它还将开发和建立概念性的 在更复杂的解剖系统中进行类似工作的框架和技术。

Project Summary Anatomical atlases are spatial reference maps of cells in tissues/organs/brains and provide structure information for a wide range of biological analyses. The anatomical atlas of C. elegans nervous system is the only atlas for the entire nervous system of an animal with a resolution of all neuronal classes. However, built on a limited dataset and manual annotations, the standard atlas is insufficient in capturing biological variabilities, inaccurate and difficult to use for cell identification routinely, and only applicable for wildtype adult. While several heroic efforts of generating and imaging marker strains to build atlases have much improved the atlases, there is still a need for a pipeline to build accurate genetic-background-specific (or experimental-condition-specific) atlases easily and cheaply; further, there is a need to build such atlases that can be used without specialized equipment and with as few genetic perturbations as possible. Recent development of machine learning techniques and molecular transgenic approaches enabling the systematic production of in vivo reporters and imaging methods capable of collecting and processing high-resolution datasets at a large scale. The goal of this application is to address the current bottleneck by establishing a combined experimental and computational pipeline for modularly built, complete, coordinate- and template-free brain atlases for democratized and flexible uses. By imaging in vivo markers in a large number of live animals, the project will generate complete anatomical atlases for the C. elegans nervous system that capture variability in the population, which will greatly enhance the accuracy of identity predictions when used on each animal. The project will generate a collection of transgenic animals expressing partly overlapping in vivo markers that cover all neurons and build a computational pipeline to assemble the atlases. Further, a few widely applicable developmental atlases as a direct output of the project will showcase the pipeline and the approach. Importantly, the atlases do not seek to provide a set of rigid coordinates for each neuron class, but instead, a set of constraints that can be used to provide best estimates of neuron identities for each new sample. This ensures accuracy and applicability of the atlases to specific use case. The building of whole-brain atlases is piece-wise from easily-obtained partial atlases, and can be crowd-sourced if desired. The use will be streamlined with image input and neuron-identity prediction output. The proposed project is innovative, because it will build the first complete anatomical atlases of a nervous system using large datasets collected from in vivo markers of many live animals; it uses relational information uniquely suited to provide more accurate assignments; it will capture variabilities among individual animals. The proposed the work is significant, because it will address the urgent and unmet need for accurate, easy-to-use and easily updatable atlases to curate the brain; further, it will develop and establish conceptual framework and techniques for similar efforts in more complex anatomical systems.