Annotation of cell identity is an essential process in neuroscience that allows comparison of cells, including that of neural activities across different animals. In Caenorhabditis elegans, although unique identities have been assigned to all neurons, the number of annotatable neurons in an intact animal has been limited due to the lack of quantitative information on the location and identity of neurons. Here, we present a dataset that facilitates the annotation of neuronal identities, and demonstrate its application in a comprehensive analysis of whole-brain imaging. We systematically identified neurons in the head region of 311 adult worms using 35 cell-specific promoters and created a dataset of the expression patterns and the positions of the neurons. We found large positional variations that illustrated the difficulty of the annotation task. We investigated multiple combinations of cell-specific promoters driving distinct fluorescence and generated optimal strains for the annotation of most head neurons in an animal. We also developed an automatic annotation method with human interaction functionality that facilitates annotations needed for whole-brain imaging. Our neuron ID dataset and optimal fluorescent strains enable the annotation of most neurons in the head region of adult C. elegans, both in full-automated fashion and a semi-automated version that includes human interaction functionalities. Our method can potentially be applied to model species used in research other than C. elegans, where the number of available cell-type-specific promoters and their variety will be an important consideration.

中文翻译：

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神经元ID数据集有助于对秀丽隐杆线虫的全脑活动成像进行神经元注释

细胞身份的注释是神经科学中的一个基本过程，可以比较细胞，包括不同动物的神经活动。在秀丽隐杆线虫中，尽管已为所有神经元分配了唯一的身份，但由于缺乏有关神经元位置和身份的定量信息，因此完整动物中可注释的神经元的数量受到限制。在这里，我们提出了一个便于注释神经元身份的数据集，并展示了其在全脑成像综合分析中的应用。我们使用35个细胞特异性启动子系统地鉴定了311只成虫的头部神经元，并创建了表达模式和神经元位置的数据集。我们发现大量的位置变化说明了注释任务的难度。我们研究了驱动特异性荧光的细胞特异性启动子的多种组合，并产生了用于注释动物中大多数头部神经元的最佳菌株。我们还开发了一种具有人机交互功能的自动注释方法，该方法可简化全脑成像所需的注释。我们的神经元ID数据集和最佳荧光菌株能够以全自动方式和包括人机交互功能的半自动版本对成人秀丽隐杆线虫头部区域中的大多数神经元进行注释。我们的方法可以潜在地应用于秀丽隐杆线虫以外的用于研究的模型物种，在该物种中，可用的细胞类型特异性启动子的数量及其种类将是重要的考虑因素。