Single-cell mapping of lineage and identity in direct reprogramming

Area of Science:

• Cell Biology
• Developmental Biology
• Genetics

Background:

• Direct lineage reprogramming converts cell identity, but heterogeneity complicates trajectory analysis.
• Existing single-cell technologies often lose crucial lineage information during processing.
• Reconstructing cellular trajectories requires methods that preserve both identity and clonal history.

Purpose of the Study:

• To develop a combinatorial cell-indexing method for simultaneous capture of clonal history and cell identity.
• To enable the construction of multi-level lineage trees during direct cellular reprogramming.
• To investigate the dynamics and heterogeneity of fibroblast to induced endoderm progenitor reprogramming.

Main Methods:

• Developed 'CellTagging', a combinatorial cell-indexing methodology using sequential cell labeling.
• Applied CellTagging for longitudinal tracking of fibroblast to induced endoderm progenitor reprogramming.
• Analyzed cell identity and clonal history to reconstruct lineage relationships.

Main Results:

• Identified two distinct reprogramming trajectories: one successful and one 'dead-end' state.
• Determined that trajectory paths are established in the early stages of lineage conversion.
• Found Mettl7a1 expression correlates with successful reprogramming and enhances induced endoderm progenitor yield when added to the reprogramming cocktail.

Conclusions:

• CellTagging effectively captures clonal history and cell identity, enabling detailed lineage tracing.
• The method reveals critical insights into the dynamics and heterogeneity of direct reprogramming processes.
• Mettl7a1 is identified as a key factor promoting successful direct lineage reprogramming.