Lim, Elaine T.Chan, YingleongDawes, PepperErdin, SerkanReichert, Julia M.Burns, Mannix J.Church, George M.2022-08-232022-08-232022-06-102022-07-05<p>Lim ET, Chan Y, Dawes P, Guo X, Erdin S, Tai DJC, Liu S, Reichert JM, Burns MJ, Chan YK, Chiang JJ, Meyer K, Zhang X, Walsh CA, Yankner BA, Raychaudhuri S, Hirschhorn JN, Gusella JF, Talkowski ME, Church GM. Orgo-Seq integrates single-cell and bulk transcriptomic data to identify cell type specific-driver genes associated with autism spectrum disorder. Nat Commun. 2022 Jun 10;13(1):3243. doi: 10.1038/s41467-022-30968-3. PMID: 35688811; PMCID: PMC9187732. <a href="https://doi.org/10.1038/s41467-022-30968-3">Link to article on publisher's site</a></p>2041-1723 (Linking)10.1038/s41467-022-30968-335688811https://hdl.handle.net/20.500.14038/25958<p>Full author list omitted for brevity. For the full list of authors, see article.</p>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.en-USCopyright © The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.http://creativecommons.org/licenses/by/4.0/CRISPR-Cas9 genome editingData integrationExperimental models of diseaseGene expression profilingNeural stem cellsBioinformaticsComputational BiologyGenetics and GenomicsIntegrative BiologyNervous System DiseasesNeuroscience and NeurobiologyPsychiatrySystems BiologyJournal Articlehttps://escholarship.umassmed.edu/cgi/viewcontent.cgi?article=1180&amp;context=bioinformatics_pubs&amp;unstamped=1https://escholarship.umassmed.edu/bioinformatics_pubs/16930064398bioinformatics_pubs/169