Optimal-Transport Analysis of Single-Cell Gene Expression Identifies Developmental Trajectories in Reprogramming

Area of Science:

• Developmental Biology
• Computational Biology
• Genomics

Background:

• Understanding cell differentiation during development is crucial.
• Modeling regulatory programs guiding these processes remains challenging.

Purpose of the Study:

• Introduce Waddington-OT, a novel computational approach.
• Infer ancestor-descendant cell fates and model regulatory programs.
• Analyze developmental time courses using single-cell RNA sequencing data.

Main Methods:

• Applied Waddington-OT to reconstruct cell reprogramming landscapes.
• Utilized 315,000 single-cell RNA sequencing profiles across an 18-day time course.
• Identified transcription factors and paracrine signals influencing cell fates.

Main Results:

• Revealed a broader spectrum of developmental programs than previously known.
• Observed gradual cell adoption of terminal stromal or mesenchymal-to-epithelial transition states.
• Identified Obox6 and GDF9 as factors enhancing reprogramming efficiency.

Conclusions:

• Waddington-OT provides a framework for studying biological temporal processes.
• The study elucidates the process and outcomes of cell reprogramming.
• Identified specific molecular factors influencing developmental trajectories.