A GENETIC, GENOMIC, AND COMPUTATIONAL RESOURCE FOR EXPLORING NEURAL CIRCUIT FUNCTION. A GENETIC, GENOMIC, AND COMPUTATIONAL RESOURCE FOR EXPLORING NEURAL CIRCUIT FUNCTION

The anatomy of many neural circuits is being characterized with increasing resolution, but their molecular properties remain mostly unknown. Here, we characterize gene expression patterns in distinct neural cell types of the Drosophila visual system using genetic lines to access individual cell types, the TAPIN-seq method to measure their transcriptomes, and a probabilistic method to interpret these measurements. We used these tools to build a resource of high-resolution transcriptomes for 100 driver lines covering 67 cell types. Combining these transcriptomes with recently reported connectomes helps characterize how information is transmitted and processed across a range of scales, from individual synapses to circuit pathways. We describe examples that include identifying neurotransmitters, including cases of co-release, generating functional hypotheses based on receptor expression, as well as identifying strong commonalities between different cell types. Overall design: 266 RNA-seq samples including 242 nuclear RNA-seq libraries prepared from specific cell types using INTACT/TAPIN, 8 samples dissected from the optic lobe, and 16 control libraries to characterize the INTACT/TAPIN protocols.

尽管诸多神经环路的解剖结构解析分辨率正持续提升，但其分子特性仍大多未知。本研究借助可靶向单个神经元类群的遗传驱动品系、用于检测转录组的TAPIN-seq技术，以及用于解析实验数据的概率分析方法，对果蝇（Drosophila）视觉系统中不同神经元类群的基因表达模式进行了表征。我们依托上述工具，构建了覆盖67种神经元类群的100个驱动品系的高分辨率转录组数据集。将该转录组数据集与近期公布的神经连接组（connectome）相结合，有助于解析从单个突触到环路通路的多尺度信息传递与处理机制。本研究还展示了多项应用案例：包括鉴定神经递质（含共释放现象）、基于受体表达构建功能假说，以及识别不同神经元类群间的显著共性。实验整体设计：共包含266个RNA-seq样本，其中242个为利用INTACT/TAPIN技术从特定神经元类群中制备的细胞核RNA测序文库，8个为从视叶中解剖获得的样本，另有16个对照文库用于表征INTACT/TAPIN实验流程的性能。