EXPERIMENT_TITLE: GSM8254190: K562 Hi-C rep2; Homo sapiens; Hi-C
EXPERIMENT_DESIGN_LIBRARY_DESCRIPTOR_LIBRARY_CONSTRUCTION_PROTOC: We performed Hi-C on wild-type K562 cells with the Arima Hi-C kit (A510008) according to the manufacturer's protocols (3 replicates, 870 million reads total).
STUDY_DESCRIPTOR_STUDY_ABSTRACT: Individual cells from isogenic populations often display large cell-to-cell differences in gene expression. This “noise” in expression derives from several sources, including the genomic and cellular environment in which a gene resides. Large-scale maps of genomic environments have revealed the effects of epigenetic modifications and transcription factor occupancy on mean expression levels, but leveraging such maps to explain expression noise will require new methods to assay how expression noise changes at locations across the genome.To address this gap, we present Single-cell Analysis of Reporter Gene Expression Noise and Transcriptome (SARGENT), a method that simultaneously measures the noisiness of reporter genes integrated throughout the genome and the global mRNA profiles of individual reporter-gene-containing cells. Using SARGENT, we perform the first comprehensive genome-wide survey of how genomic locations impact gene expression noise. We find that the mean and noise of expression correlate with different histone modifications. We quantify the intrinsic and extrinsic components of reporter gene noise and, using the associated mRNA profiles, assign the extrinsic component to differences between the CD24+ “stem-like” sub-state and the more “differentiated” sub-state. SARGENT also reveals the effects of transgene integrations on endogenous gene expression, which will help guide the search for “safe-harbor” loci. Overall design: We developed a high-throughput method to test the effects of genomic environments on the mean and noise of gene expression. Our goal was to integrate a common transgene across the genome and then, for individual cells, measure both the transcripts produced from the transgene and the global mRNA profile. This allows us to compute the mean and noise of reporter gene expression at each location, and correlate reporter gene expression with the cellular mRNA state of each cell. Because every unique integration contains the same transgene, the measured differences in the mean and noise of reporter gene expression are directly attributable to the influence of genomic environments or cellular states.
SAMPLE_TITLE: K562 Hi-C rep2
SAMPLE_SAMPLE_ATTRIBUTES_SAMPLE_ATTRIBUTE: [{"TAG": "source_name", "VALUE": "K562"}, {"TAG": "cell line", "VALUE": "K562"}, {"TAG": "geo_loc_name", "VALUE": "missing"}, {"TAG": "collection_date", "VALUE": "missing"}]
Pool_Member_@attributes_sample_title: K562 Hi-C rep2
RUN_SET_RUN_Pool_Member_@attributes_sample_title: K562 Hi-C rep2
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