A phenotypically supervised single-cell analysis protocol to study within-cell-type heterogeneity of cultured mammalian cells
Year: 2021
Type: article
Abstract: Here, we describe a protocol combining functional metrics with genomic data to elucidate drivers of within-cell-type heterogeneity via the phenotype-to-genotype link. This technique involves using fluorescence tagging to label and isolate cells grown in 3D culture, enabling high-throughput enrichment of phenotypically defined cell subpopulations by fluorescence-activated cell sorting. We then perform a validated phenotypically supervised single-cell analysis pipeline to reveal unique functional cell states, including genes and pathways that contribute to cellular heterogeneity and were undetectable by unsupervised analysis. For complete details on the use and execution of this protocol, please refer to Chen et al. (2020).
Source: STAR Protocols
Institutions: University of California San Diego, Moores Cancer Center
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $1,500
Funders: National Science Foundation, Burroughs Wellcome Fund, National Sleep Foundation, Mark Foundation For Cancer Research, National Institutes of Health, University of California, San Diego, National Cancer Institute, National Institute of Neurological Disorders and Stroke, School of Medicine, University of California, San Diego
Awards: G1476237564, CAREER: A multi-scale, data-driven model of 3D cell motility, G1724392058, G3033040839, Illumina NovaSeq 6000 Sequencing System, GenePattern Notebooks for Cancer Research, Research Center for Cancer Systems Biology: Cancer Cell Map Initiative, G4256194535, G5601617290, University of California San Diego Neuroscience Microscopy Imaging Core, G64421039, G6671297155, Platform and portal development for accessible, reproducible cancer genomics research, Integrators of Metastatic Potential, G8027868358, GenePattern and GenePattern Notebook: Integrative 'Omic Analysis for Cancer Research, G8448096725, G872999976, G9000255603
OpenAlex ID: W3164947669