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Cited by 82Single-cell and spatial transcriptomicsPluripotent Stem Cells ResearchGene Regulatory Network Analysis

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

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Jindal, Kunal, Adil, Mohd Tayyab, Yamaguchi, Naoto, Yang, Xue, Wang, Helen C., Kamimoto, Kenji, Rivera-Gonzalez, Guillermo C., Morris, Samantha A.·2024·Nature Biotechnology
DOI 10.1038/s41587-023-01931-4PMC PMC11180607
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Abstract

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. However, reliance on transcriptional profiling limits adaptation to other single-cell assays. With CellTag-multi, we present an approach that enables direct capture of heritable random barcodes expressed as polyadenylated transcripts, in both single-cell RNA sequencing and single-cell Assay for Transposase Accessible Chromatin using sequencing assays, allowing for independent clonal tracking of transcriptional and epigenomic cell states. We validate CellTag-multi to characterize progenitor cell lineage priming during mouse hematopoiesis. Additionally, in direct reprogramming of fibroblasts to endoderm progenitors, we identify core regulatory programs underlying on-target and off-target fates. Furthermore, we reveal the transcription factor Zfp281 as a regulator of reprogramming outcome, biasing cells toward an off-target mesenchymal fate. Our results establish CellTag-multi as a 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.

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  • Advanced primary cell models of hematopoietic differentiation allow measuring the activity of a large number of synthetic DNA constructs in a complex model of stemness and differentiation.

    “Advanced primary cell models of hematopoietic differentiation37,38,39 provide a unique opportunity to study this broadly relevant question, as they allow for measuring the activity of a large number of synthetic DNA constructs in a complex model of stemness and differentiation.”

    From Design principles of cell-state-specific enhancers in hematopoiesis (2025) · cites this paper as [39]

    The 'Benchmarking CellTag-multi using in vitro hematopoiesis' section describes a primary mouse bone-marrow cell model of multilineage differentiation. The paper measures gene expression and chromatin accessibility in that model, but the cited passages do not establish measurement of the activity of large numbers of synthetic DNA constructs. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

  • The adapted HSPC culture conditions permit the parallel differentiation of primary mouse HSCs into red blood cells, megakaryocytes, neutrophils, eosinophils, basophils, monocytes and dendritic cells.

    “We adapted culture conditions37,39 that permit the parallel differentiation of primary mouse HSCs into red blood cells, megakaryocytes, neutrophils, eosinophils, basophils, monocytes and dendritic cells.”

    From Design principles of cell-state-specific enhancers in hematopoiesis (2025) · cites this paper as [39]

    The Methods describe culturing LSK cells from adult mouse bone marrow in broad myeloid differentiation medium, and Fig. 2 identifies erythroid, megakaryocyte, neutrophil, eosinophil, basophil, monocyte and plasmacytoid dendritic-cell fates. The paper does not establish that the starting cells were purified HSCs rather than the broader LSK population, or that the erythroid cells became mature red blood cells. (LLM, conf=0.87)

    Experimental — accuracy not yet measured

  • All primary hematopoietic cells activate Trp53 upon lentiviral infection without affecting the differentiation of cells in the ex vivo system used here.

    “all primary hematopoietic cells activate Trp53 upon lentiviral infection87 without affecting the differentiation of cells in the ex vivo system used here.37,39”

    From Design principles of cell-state-specific enhancers in hematopoiesis (2025) · cites this paper as [39]

    In “Benchmarking CellTag-multi using in vitro hematopoiesis” (page unavailable), the paper reports that CellTag-labeled mouse hematopoietic cells produced all major lineages in culture. That supports differentiation occurring after lentiviral tagging, but it does not establish that infection left differentiation unaffected relative to uninfected cells. The Trp53 assertion is attached to a different citation in the citing sentence and is not judged here. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

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Cited by

Sorted by citations

Authors
Jindal, K., Adil, M. T., Yamaguchi, N., Yang, X., Wang, H. C., Kamimoto, K., Rivera-Gonzalez, G. C., & Morris, S. A.
Affiliations
Washington University in St. Louis (US)
Corresponding author
Morris, Samantha A.
ORCID
Venue
Nature Biotechnology
Publisher
Springer Science and Business Media LLC
Published
2023-09-25
Volume
42
Issue
6
Pages
946-959
ISSN
  • 0733-222X (ISSN-L)
  • 1087-0156
  • 1546-1696
DOI
10.1038/s41587-023-01931-4
PMC
PMC11180607
OpenAlex
W4387012711
Cited by
82
References
11
Citations by year
2026: 34 · 2025: 28 · 2024: 15 · 2023: 5
FWCI
7.31
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Biotechnology (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Digital Commons@Becker (Washington University School of Medicine) (submittedVersion, cc-by)
Funders
U.S. Department of Health and Human Services | NIH | National Institute of General Medical Sciences (R01 GM126112)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Pluripotent Stem Cells Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
Keywords
single-cell lineage tracing, polyadenylated transcripts, single-cell ATAC-seq, single-cell RNA sequencing, clonal tracking, hematopoiesis, transcription factor regulation, cell fate specification
MeSH terms
Animals, Cell Differentiation, Fibroblasts, Gene Expression Regulation, Hematopoiesis, Transcription Factors, Cell Lineage, Genomics, Mice, Single-Cell Analysis, Cellular Reprogramming

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