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

ABSTRACT: This SuperSeries is composed of the SubSeries listed below.

ORGANISM(S): Mus musculus

PROVIDER: GSE216521 | GEO | 2023/07/24

REPOSITORIES: GEO

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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].

2023-07-25 | GSE216606 | GEO

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

2023-07-25 | GSE216518 | GEO

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

2023-07-25 | GSE216506 | GEO

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

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

| PRJNA894147 | ENA

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].

| PRJNA894151 | ENA

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].

| PRJNA894497 | ENA

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].

| PRJNA896969 | ENA

Single-Cell Proteomics Reveal that Quantitative Changes in Co-expressed Lineage-Specific Transcription Factors Determine Cell Fate.

Project description:Hematopoiesis provides an accessible system for studying the principles underlying cell-fate decisions in stem cells. Proposed models of hematopoiesis suggest that quantitative changes in lineage-specific transcription factors (LS-TFs) underlie cell-fate decisions. However, evidence for such models is lacking as TF levels are typically measured via RNA expression rather than by analyzing temporal changes in protein abundance. Here, we used single-cell mass cytometry and absolute quantification by mass spectrometry to capture the temporal dynamics of TF protein expression in individual cells during human erythropoiesis. We found that LS-TFs from alternate lineages are co-expressed, as proteins, in individual early progenitor cells and quantitative changes of LS-TFs occur gradually rather than abruptly to direct cell-fate decisions. Importantly, upregulation of a megakaryocytic TF in early progenitors is sufficient to deviate cells from an erythroid to a megakaryocyte trajectory, showing that quantitative changes in protein abundance of LS-TFs in progenitors can determine alternate cell fates.

| S-EPMC6886472 | biostudies-literature

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