Orgo-Seq integrates single-cell and bulk transcriptomic data to identify cell type specific-driver genes associated with autism spectrum disorder

Elaine T. Lim (), Yingleong Chan, Pepper Dawes, Xiaoge Guo, Serkan Erdin, Derek J. C. Tai, Songlei Liu, Julia M. Reichert, Mannix J. Burns, Ying Kai Chan, Jessica J. Chiang, Katharina Meyer, Xiaochang Zhang, Christopher A. Walsh, Bruce A. Yankner, Soumya Raychaudhuri, Joel N. Hirschhorn, James F. Gusella, Michael E. Talkowski and George M. Church ()
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Elaine T. Lim: University of Massachusetts Chan Medical School
Yingleong Chan: University of Massachusetts Chan Medical School
Pepper Dawes: University of Massachusetts Chan Medical School
Xiaoge Guo: Harvard Medical School
Serkan Erdin: Massachusetts General Hospital
Derek J. C. Tai: Massachusetts General Hospital
Songlei Liu: Harvard Medical School
Julia M. Reichert: University of Massachusetts Chan Medical School
Mannix J. Burns: University of Massachusetts Chan Medical School
Ying Kai Chan: Harvard Medical School
Jessica J. Chiang: Harvard Medical School
Katharina Meyer: Harvard Medical School
Xiaochang Zhang: The University of Chicago
Christopher A. Walsh: Broad Institute of MIT and Harvard
Bruce A. Yankner: Harvard Medical School
Soumya Raychaudhuri: Broad Institute of MIT and Harvard
Joel N. Hirschhorn: Harvard Medical School
James F. Gusella: Harvard Medical School
Michael E. Talkowski: Massachusetts General Hospital
George M. Church: Harvard Medical School

Nature Communications, 2022, vol. 13, issue 1, 1-14

Abstract: Abstract Cerebral organoids can be used to gain insights into cell type specific processes perturbed by genetic variants associated with neuropsychiatric disorders. However, robust and scalable phenotyping of organoids remains challenging. Here, we perform RNA sequencing on 71 samples comprising 1,420 cerebral organoids from 25 donors, and describe a framework (Orgo-Seq) to integrate bulk RNA and single-cell RNA sequence data. We apply Orgo-Seq to 16p11.2 deletions and 15q11–13 duplications, two loci associated with autism spectrum disorder, to identify immature neurons and intermediate progenitor cells as critical cell types for 16p11.2 deletions. We further applied Orgo-Seq to identify cell type-specific driver genes. Our work presents a quantitative phenotyping framework to integrate multi-transcriptomic datasets for the identification of cell types and cell type-specific co-expressed driver genes associated with neuropsychiatric disorders.

Date: 2022
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DOI: 10.1038/s41467-022-30968-3

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