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

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Authors: Leqiang Sun, Hu Zheng, Yayu Huang, Xuehuan Huang, Keji Yan, Zhongchao Wang, Liyao Yang, Yiping Yue, Xiaojuan Gou, Guohua Du, Yang Wang, Xiaofeng Wu
+6 more Huazhen Liu, Hang Chen, Daqing Ma, Yunyun Han, Jinxia Dai, Gang Cao
Cited by: 0
References: 52

Abstract

Deciphering the connectome, anatomy, transcriptome and spatial-omics integrated multi-modal brain atlas and its 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 an integrated single-cell spatial molecular, cellular, anatomic and projectomic atlas of the 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 the projectomic atlas with its distinct spectrum of neurotransmitters/neuropeptides with their receptor-related gene profiles in order to demonstrate the PFC neural signal transmission network, by which means 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 the brain multi-modal network and neural computation.

Fields of Study & Subjects

Single-cell and spatial transcriptomics Neuroscience and Neuropharmacology Research Memory and Neural Mechanisms

Publication details

Journal / source
National Science Review
Volume
13
Issue
5
Pages
nwag004–nwag004
Publication date
15 January 2026
Language
EN