Modular inflammation network discovery from large-scale phenotypic screening in genetically heterogeneous mouse brains

通过对遗传异质性小鼠脑进行大规模表型筛选,发现模块化炎症网络

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作者:Monica Xiong #,Lisa A Miosge #,Carolina Correa-Ospina,Claudia M Y Yan,Tiffany Cripps,Stefan Bauernfried,Yuanyuan Wang,Maggie Crow,Lucy X Morris,T Daniel Andrews,Andrew Trujillo,Mitchell G Rezzonico,Yuxin Liang,Qixin Bei,Zora Modrusan,Kimberly L Stark,Tracy J Yuen,Brad A Friedman,Jesse E Hanson,Edward M Bertram,Christopher J Bohlen

Abstract

The central nervous system (CNS) represents a uniquely immune-privileged environment, with inflammatory responses involving several resident CNS-specific cell types. While stereotyped cellular and transcriptional responses recur across varied diseases, relevant signaling pathways and regulatory networks are not fully understood. Here, we investigate multi-modal inflammatory gene networks at large scale by developing a high-throughput RNA-seq screening and analysis workflow. As proof-of-concept, we investigate genetically heterogeneous mice from a large-scale chemical mutagenesis screen to identify novel functionally relevant variants in six genes previously linked to human CNS disorders: Nrros, Ctsd, Smpd1, Idua, Nlrp1a, and Inpp5d. We leverage the readily interpretable data from our large-scale study to demarcate distinct inflammatory states arising from each mutation. In all, our work provides a validated analysis framework for identifying discrete gene expression modules that are engaged divergently across disease contexts, which can be used to discover novel regulators of CNS neuroimmune homeostasis.

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