Abstract
Recent technological developments have led to widespread applications of large-scale transcriptomics-based sequencing methods to identify genotype-to-cell type associations. Here we describe a fluorescence-activated cell sorting (FACS)-based sequencing method to utilize CRISPR/Cas9 edited mosaic cerebral organoids to identify or validate genotype-to-cell type associations. Our approach is high-throughput and quantitative and uses internal controls to enable comparisons of the results across different antibody markers and experiments.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Macosko EZ, Basu A, Satija R et al (2015) Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161:1202–1214
Klein AM, Mazutis L, Akartuna I et al (2015) Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell 161:1187–1201
Zheng GX, Terry JM, Belgrader P et al (2017) Massively parallel digital transcriptional profiling of single cells. Nat Commun 8:14049
Stahl PL, Salmen F, Vickovic S et al (2016) Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. Science 353:78–82
Rodriques SG, Stickels RR, Goeva A et al (2019) Slide-seq: a scalable technology for measuring genome-wide expression at high spatial resolution. Science 363:1463–1467
Chen A, Liao S, Cheng M et al Large field of view-spatially resolved transcriptomics at nanoscale resolution. bioRxiv 2021:2021.2001.2017.427004
Lim ET, Chan Y, Dawes P et al (2022) Orgo-Seq integrates single-cell and bulk transcriptomic data to identify cell type specific-driver genes associated with autism spectrum disorder. Nat Commun 13:3243
Dawes P, Murray LF, Olson MN et al (2023) oFlowSeq: a quantitative approach to identify protein coding mutations affecting cell type enrichment using mosaic CRISPR-Cas9 edited cerebral organoids. Hum Genet. https://doi.org/10.1007/s00439-023-02534-4
Kosuri S, Goodman DB, Cambray G et al (2013) Composability of regulatory sequences controlling transcription and translation in Escherichia coli. Proc Natl Acad Sci U S A 110:14024–14029
Raveh-Sadka T, Levo M, Shabi U et al (2012) Manipulating nucleosome disfavoring sequences allows fine-tune regulation of gene expression in yeast. Nat Genet 44:743–750
Sharon E, Kalma Y, Sharp A et al (2012) Inferring gene regulatory logic from high-throughput measurements of thousands of systematically designed promoters. Nat Biotechnol 30:521–530
Lancaster MA, Knoblich JA (2014) Generation of cerebral organoids from human pluripotent stem cells. Nat Protoc 9:2329–2340
Acknowledgments
We thank George Church, Mohammed Uddin, ChangHui Pak, and members of their labs, as well as members in the Program in Bioinformatics & Integrative Biology at UMass Chan Medical School, for their expertise, advice, and suggestions in developing the oFlowSeq method. This study was supported by the National Institutes of Health grants (NHGRI RM1HG008525 to George Church; NIMH R01MH113279 to George Church), Robert Wood Johnson Foundation grant (74178 to George Church), and startup funds by UMass Chan Medical School (Elaine Lim and Yingleong Chan).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature
About this protocol
Cite this protocol
Murray, L., Olson, M.N., Barton, N., Dawes, P., Chan, Y., Lim, E.T. (2023). FACS-Based Sequencing Approach to Evaluate Cell Type to Genotype Associations Using Cerebral Organoids. In: Huang, YW.A., Pak, C. (eds) Stem Cell-Based Neural Model Systems for Brain Disorders. Methods in Molecular Biology, vol 2683. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-3287-1_15
Download citation
DOI: https://doi.org/10.1007/978-1-0716-3287-1_15
Published:
Publisher Name: Humana, New York, NY
Print ISBN: 978-1-0716-3286-4
Online ISBN: 978-1-0716-3287-1
eBook Packages: Springer Protocols