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Single-nucleus multiomic atlas of frontal cortex in amyotrophic lateral sclerosis with a deep learning-based decoding of alternative polyadenylation mechanisms

View ORCID ProfilePaul M. McKeever, Aiden M. Sababi, View ORCID ProfileRaghav Sharma, Nicholas Khuu, Zhiyu Xu, Shu Yi Shen, Shangxi Xiao, View ORCID ProfilePhilip McGoldrick, Elias Orouji, View ORCID ProfileTroy Ketela, View ORCID ProfileChristine Sato, View ORCID ProfileDanielle Moreno, Naomi Visanji, Gabor G. Kovacs, Julia Keith, Lorne Zinman, View ORCID ProfileEkaterina Rogaeva, View ORCID ProfileHani Goodarzi, View ORCID ProfileGary D. Bader, View ORCID ProfileJanice Robertson
doi: https://doi.org/10.1101/2023.12.22.573083
Paul M. McKeever
1Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, ON, Canada
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Aiden M. Sababi
2Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
3The Donnelly Centre, University of Toronto, ON, Canada
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Raghav Sharma
1Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, ON, Canada
4Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
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Nicholas Khuu
5Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
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Zhiyu Xu
5Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
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Shu Yi Shen
4Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
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Shangxi Xiao
1Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, ON, Canada
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Philip McGoldrick
1Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, ON, Canada
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Elias Orouji
5Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
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Troy Ketela
5Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
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Christine Sato
1Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, ON, Canada
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Danielle Moreno
1Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, ON, Canada
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Naomi Visanji
1Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, ON, Canada
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Gabor G. Kovacs
1Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, ON, Canada
4Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
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Julia Keith
7Laboratory Medicine and Molecular Diagnostics, Division of Anatomical Pathology, Sunnybrook Health Sciences Centre, University of Toronto
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Lorne Zinman
8Department of Medicine, Division of Neurology, Sunnybrook Health Sciences Centre, University of Toronto
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Ekaterina Rogaeva
1Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, ON, Canada
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Hani Goodarzi
6Department of Biophysics & Biochemistry, University of California San Francisco, United States of America
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Gary D. Bader
2Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
3The Donnelly Centre, University of Toronto, ON, Canada
9Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada
10Department of Computer Science, University of Toronto, ON, Canada
11Princess Margaret Research Institute, University Health Network, Toronto, ON, Canada
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  • For correspondence: jan.robertson@utoronto.ca gary.bader@utoronto.ca
Janice Robertson
1Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, ON, Canada
4Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
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  • For correspondence: jan.robertson@utoronto.ca gary.bader@utoronto.ca
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Abstract

The understanding of how different cell types contribute to amyotrophic lateral sclerosis (ALS) pathogenesis is limited. Here we generated a single-nucleus transcriptomic and epigenomic atlas of the frontal cortex of ALS cases with C9orf72 (C9) hexanucleotide repeat expansions and sporadic ALS (sALS). Our findings reveal shared pathways in C9-ALS and sALS, characterized by synaptic dysfunction in excitatory neurons and a disease-associated state in microglia. The disease subtypes diverge with loss of astrocyte homeostasis in C9-ALS, and a more substantial disturbance of inhibitory neurons in sALS. Leveraging high depth 3’-end sequencing, we found a widespread switch towards distal polyadenylation (PA) site usage across ALS subtypes relative to controls. To explore this differential alternative PA (APA), we developed APA-Net, a deep neural network model that uses transcript sequence and expression levels of RNA-binding proteins (RBPs) to predict cell-type specific APA usage and RBP interactions likely to regulate APA across disease subtypes.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted December 23, 2023.
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Single-nucleus multiomic atlas of frontal cortex in amyotrophic lateral sclerosis with a deep learning-based decoding of alternative polyadenylation mechanisms
Paul M. McKeever, Aiden M. Sababi, Raghav Sharma, Nicholas Khuu, Zhiyu Xu, Shu Yi Shen, Shangxi Xiao, Philip McGoldrick, Elias Orouji, Troy Ketela, Christine Sato, Danielle Moreno, Naomi Visanji, Gabor G. Kovacs, Julia Keith, Lorne Zinman, Ekaterina Rogaeva, Hani Goodarzi, Gary D. Bader, Janice Robertson
bioRxiv 2023.12.22.573083; doi: https://doi.org/10.1101/2023.12.22.573083
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Single-nucleus multiomic atlas of frontal cortex in amyotrophic lateral sclerosis with a deep learning-based decoding of alternative polyadenylation mechanisms
Paul M. McKeever, Aiden M. Sababi, Raghav Sharma, Nicholas Khuu, Zhiyu Xu, Shu Yi Shen, Shangxi Xiao, Philip McGoldrick, Elias Orouji, Troy Ketela, Christine Sato, Danielle Moreno, Naomi Visanji, Gabor G. Kovacs, Julia Keith, Lorne Zinman, Ekaterina Rogaeva, Hani Goodarzi, Gary D. Bader, Janice Robertson
bioRxiv 2023.12.22.573083; doi: https://doi.org/10.1101/2023.12.22.573083

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