Proximity analysis of native proteomes reveals phenotypic modifiers in a mouse model of autism and related neurodevelopmental conditions

One of the main drivers of autism spectrum disorder is risk alleles within hundreds of genes, which may interact within shared but unknown protein complexes. Here we develop a scalable genome-editing-mediated approach to target 14 high-confidence autism risk genes within the mouse brain for proximity-based endogenous proteomics, achieving the identification of high-specificity spatial proteomes. The resulting native proximity proteomes are enriched for human genes dysregulated in the brain of autistic individuals, and reveal proximity interactions between proteins from high-confidence risk genes with those of lower-confidence that may provide new avenues to prioritize genetic risk. Importantly, the datasets are enriched for shared cellular functions and genetic interactions that may underlie the condition. We test this notion by spatial proteomics and CRISPR-based regulation of expression in two autism models, demonstrating functional interactions that modulate mechanisms of their dysregulation. Together, these results reveal native proteome networks in vivo relevant to autism, providing new inroads for understanding and manipulating the cellular drivers underpinning its etiology.

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Publication Details

Journal
Nature Communications
Published
2024-08-09
DOI
https://doi.org/10.1038/s41467-024-51037-x
Citations
23
Primary Topic
Genetics and Neurodevelopmental Disorders
Type
article
Field-Weighted Citation Impact
12.66

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article

Proximity analysis of native proteomes reveals phenotypic modifiers in a mouse model of autism and related neurodevelopmental conditions

S. Alexandra Garcia-Moreno, Jieqing Zhao, Matthew Trn, William C. Wetsel et al.
23 citations
Nature Communications
Genetics and Neurodevelopmental Disorders
12.66
article

Proximity analysis of native proteomes reveals phenotypic modifiers in a mouse model of autism and related neurodevelopmental conditions

S. Alexandra Garcia-Moreno, Jieqing Zhao, Matthew Trn, William C. Wetsel, Joseph D. Buxbaum, Laura Sloofman, Erik J. Soderblom, Yong‐hui Jiang, Dmitry Velmeshev, Daichi Shonai, Géraldine Dawson, Charles A. Gersbach, Scott H. Soderling, Yudong Gao
article en
23 citations

Abstract

One of the main drivers of autism spectrum disorder is risk alleles within hundreds of genes, which may interact within shared but unknown protein complexes. Here we develop a scalable genome-editing-mediated approach to target 14 high-confidence autism risk genes within the mouse brain for proximity-based endogenous proteomics, achieving the identification of high-specificity spatial proteomes. The resulting native proximity proteomes are enriched for human genes dysregulated in the brain of autistic individuals, and reveal proximity interactions between proteins from high-confidence risk genes with those of lower-confidence that may provide new avenues to prioritize genetic risk. Importantly, the datasets are enriched for shared cellular functions and genetic interactions that may underlie the condition. We test this notion by spatial proteomics and CRISPR-based regulation of expression in two autism models, demonstrating functional interactions that modulate mechanisms of their dysregulation. Together, these results reveal native proteome networks in vivo relevant to autism, providing new inroads for understanding and manipulating the cellular drivers underpinning its etiology.

Nature CommunicationsVol. 15(1)
Allen Institute for Brain Science (US), Duke University (US), Baylor College of Medicine (US), Yale University (US), Child Health and Development Institute (US), Duke Medical Center (US), Applied Genetic Technologies (United States) (US), Icahn School of Medicine at Mount Sinai (US)
National Institutes of Health, National Institute of Mental Health
Zero hunger
Openalex Percentile: Top 1%
Genetics and Neurodevelopmental Disorders
12.66
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