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Single-cell lineage capture across genomic modalities with CellTag-multi reveals fate-specific gene regulatory changes.

ABSTRACT: Single-cell lineage capture across genomic modalities with CellTag-multi reveals fate-specific gene regulatory changes.

PROVIDER: PRJNA894147 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR22033415.fastq.gz	Fastqsanger.gz
	SRR22033415_1.fastq.gz	Fastqsanger.gz
	SRR22033415_2.fastq.gz	Fastqsanger.gz
	SRR22033416.fastq.gz	Fastqsanger.gz
	SRR22033416_1.fastq.gz	Fastqsanger.gz

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Single-cell lineage capture across genomic modalities with CellTag-multi reveals fate-specific gene regulatory changes [scATAC-seq - iEP].

Project description:Complex gene regulatory mechanisms underlie differentiation and reprogramming. Contemporary single-cell lineage tracing (scLT) methods use expressed, heritable DNA barcodes to combine cell lineage readout with single-cell transcriptomics enabling high-resolution analysis of cell states while preserving lineage relationships. However, reliance on transcriptional profiling limits their adaptation to an ever-expanding tool kit of multiomic single-cell assays. With CellTag-multi, we present a novel approach for profiling lineage barcodes with single-cell chromatin accessibility without relying on co-assay of transcriptional state, paving the way for truly multiomic lineage tracing. We validate CellTag-multi in mouse hematopoiesis, characterizing transcriptional and epigenomic lineage priming across progenitor cell populations. In direct reprogramming of fibroblasts to endoderm progenitors, we use CellTag-multi to comprehensively link early cell state with reprogramming outcomes, identifying core regulatory programs underlying on-target and off-target reprogramming. Further, we reveal the Transcription Factor (TF) Zfp281 as a novel regulator of reprogramming outcome, biasing cells towards an off-target mesenchymal fate via its regulation of TGF-β signaling. Together, these results establish CellTag-multi as a novel lineage tracing method compatible with multiple single-cell modalities and demonstrate its utility in revealing fate-specifying gene regulatory changes across diverse paradigms of differentiation and reprogramming.

2023-07-25 | GSE217119 | GEO

Single-cell lineage capture across genomic modalities with CellTag-multi reveals fate-specific gene regulatory changes [scRNA-seq - LSK].

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Single-cell lineage capture across genomic modalities with CellTag-multi reveals fate-specific gene regulatory changes [scRNA-seq - iEP].

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Single-cell lineage capture across genomic modalities with CellTag-multi reveals fate-specific gene regulatory changes [scATAC-seq - LSK].

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Single-cell lineage capture across genomic modalities with CellTag-multi reveals fate-specific gene regulatory changes [scATAC-seq - LSK].

Project description:Single-cell lineage capture across genomic modalities with CellTag-multi reveals fate-specific gene regulatory changes [scATAC-seq - LSK].

| PRJNA894125 | ENA

Single-cell lineage capture across genomic modalities with CellTag-multi reveals fate-specific gene regulatory changes [scRNA-seq - iEP].

Project description:Single-cell lineage capture across genomic modalities with CellTag-multi reveals fate-specific gene regulatory changes [scRNA-seq - iEP].

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Single-cell lineage capture across genomic modalities with CellTag-multi reveals fate-specific gene regulatory changes [scRNA-seq - LSK].

Project description:Single-cell lineage capture across genomic modalities with CellTag-multi reveals fate-specific gene regulatory changes [scRNA-seq - LSK].

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Single-cell lineage capture across genomic modalities with CellTag-multi reveals fate-specific gene regulatory changes [scATAC-seq - iEP].

Project description:Single-cell lineage capture across genomic modalities with CellTag-multi reveals fate-specific gene regulatory changes [scATAC-seq - iEP].

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Single-cell lineage capture across genomic modalities with CellTag-multi reveals fate-specific gene regulatory changes.

Project description:This SuperSeries is composed of the SubSeries listed below.

2023-07-24 | GSE216521 | GEO

CellTag Indexing: genetic barcode-based sample multiplexing for single-cell genomics

Project description:High-throughput single-cell assays increasingly require special consideration in experimental design, sample multiplexing, batch effect removal, and data interpretation. Here, we describe a lentiviral barcode-based multiplexing approach, CellTag Indexing, which uses predefined genetic barcodes that are also heritable, enabling cell populations to be tagged, pooled, and tracked over time in the same experimental replicate. We demonstrate the utility of CellTag Indexing by sequencing transcriptomes using a variety of cell types, including long-term tracking of cell engraftment and differentiation in vivo. Together, this presents CellTag Indexing as a broadly applicable genetic multiplexing tool that is complementary with existing single-cell technologies.

2019-04-20 | GSE130065 | GEO

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