Single-cell mapping of lineage and identity in direct reprogramming

Brent A. Biddy, Wenjun Kong, Kenji Kamimoto, Chuner Guo, Sarah E. Waye, Tao Sun and Samantha A. Morris ()
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Brent A. Biddy: Washington University School of Medicine in St Louis
Wenjun Kong: Washington University School of Medicine in St Louis
Kenji Kamimoto: Washington University School of Medicine in St Louis
Chuner Guo: Washington University School of Medicine in St Louis
Sarah E. Waye: Washington University School of Medicine in St Louis
Tao Sun: Washington University School of Medicine in St Louis
Samantha A. Morris: Washington University School of Medicine in St Louis

Nature, 2018, vol. 564, issue 7735, 219-224

Abstract: Abstract Direct lineage reprogramming involves the conversion of cellular identity. Single-cell technologies are useful for deconstructing the considerable heterogeneity that emerges during lineage conversion. However, lineage relationships are typically lost during cell processing, complicating trajectory reconstruction. Here we present ‘CellTagging’, a combinatorial cell-indexing methodology that enables parallel capture of clonal history and cell identity, in which sequential rounds of cell labelling enable the construction of multi-level lineage trees. CellTagging and longitudinal tracking of fibroblast to induced endoderm progenitor reprogramming reveals two distinct trajectories: one leading to successfully reprogrammed cells, and one leading to a ‘dead-end’ state, paths determined in the earliest stages of lineage conversion. We find that expression of a putative methyltransferase, Mettl7a1, is associated with the successful reprogramming trajectory; adding Mettl7a1 to the reprogramming cocktail increases the yield of induced endoderm progenitors. Together, these results demonstrate the utility of our lineage-tracing method for revealing the dynamics of direct reprogramming.

Keywords: Direct Lineage Reprogramming; Successful Reprogramming; Clonal History; Reprogramming Cocktail; Unique Molecular Identifiers (UMIs) (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (9)

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DOI: 10.1038/s41586-018-0744-4

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