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NeuroPAL (Neuronal Polychromatic Atlas of Landmarks) is a recently developed transgene that labels each of the 118 classes of neurons in C. elegans with various combinations of four fluorescent proteins. This neuron-type-specific labeling helps identify neurons that could otherwise be confused with neighboring neurons. Neuron identification enables researchers to combine new data that they generate on a C. elegans neuron with existing datasets on that same neuron, such as its synaptic connections, neurotransmitters, and transcriptome. An impediment to using NeuroPAL, however, is overcoming the steep learning curve for interpreting three-dimensional (3D) fluorescence images of crowded neural ganglia within which different neurons may be similarly colored, some neurons are only very faintly labeled, and the positions of some neurons are variable. Here, we provide protocols that allow researchers to learn to accurately identify neurons within 3D images of NeuroPAL-labeled animals. We provide 3D reference images that illustrate NeuroPAL labeling of each body region, and additional 3D images as training exercises to learn to accurately carry out C. elegans neuron identifications. We also provide tools to annotate images in 3D, and suggest that such 3D annotated images should be the standard for documenting C. elegans neuron identifications for publication. © 2022 Wiley Periodicals LLC. Basic Protocol 1: Using Imaris software to view and annotate images of NeuroPAL-labeled animals in 3D Alternate Protocol: Using FIJI/ImageJ software to view and annotate images of NeuroPAL-labeled animals in 3D Basic Protocol 2: Identifying tail neurons-an introduction to identifying neurons Basic Protocol 3: Identifying midbody neurons Basic Protocol 4: Identifying anterior head neurons Basic Protocol 5: Identifying posterior head neurons Basic Protocol 6: Identifying ventral head and retrovesicular ganglion neurons. |
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