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National Science ReviewNeurosciencePeer-reviewed journal article

Organization of mouse prefrontal cortex subnetwork revealed by spatial single-cell multi-omic analysis of SPIDER-Seq

Leqiang SuniD, Hu ZhengiD, Yayu Huang, Xuehuan Huang, Keji YaniD, Zhongchao WangiD, Liyao Yang, Yiping Yue, Xiaojuan Gou, Guohua Du, Yang Wang, Xiaofeng Wu, Huazhen Liu, Hang CheniD, Daqing MaiD, Yunyun HaniD, Jinxia DaiiD, Gang CaoiD

PDFDOIPreprint

Abstract

Deciphering the connectome, anatomy, transcriptome and spatial-omics integrated multi-modal brain atlas and the underlying organization principles remains a great challenge. We developed a Single-cell Projectome-transcriptome In situ Deciphering Sequencing (SPIDER-Seq) technique by combining viral barcoding tracing with single-cell sequencing and spatial-omics. This empowers us to delineate a integrated single-cell spatial molecular, cellular, anatomic and projectomic atlas of mouse prefrontal cortex (PFC). The projectomic and transcriptomic cell clusters display distinct modular organization principles, but are coordinately configured in the PFC. The projection neurons gradiently occupied different territories in the PFC aligning with their wiring patterns. Importantly, they show higher co-projection probability to the downstream nuclei with reciprocal circuit connections. Moreover, we integrated projectomic atlas with their distinct spectrum of neurotransmitter/neuropeptide and the receptors-related gene profiles and depicted PFC neural signal transmission network. By which, we uncovered potential mechanisms underlying the complexity and specificity of neural transmission. Finally, leveraging machine learning, we predicted neuron projections with high accuracy by combining gene profiles and spatial information. As a proof of concept, we used this model to predict projections of fear recall engram neurons. This study facilitates our understanding of brain multi-modal network and neural computation.

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