Cell lineage tracing: Methods, applications, and challenges.

Area of Science:

• Developmental Biology
• Cell Biology
• Genomics

Background:

• Cell lineage tracing is essential for understanding cell fate, development, regeneration, and disease.
• Methods have evolved from basic labeling to advanced genetic tools (e.g., CRISPR-Cas9) and computational analysis of single-cell data.

Purpose of the Study:

• To review and synthesize current experimental and computational cell lineage tracing methods.
• To highlight the strengths, limitations, and synergistic potential of different approaches.
• To identify future research directions and emerging technologies.

Main Methods:

• Review of experimental cell lineage tracing techniques, including genetic barcoding.
• Analysis of computational methods for reconstructing lineage relationships from high-dimensional omics data.
• Discussion of multi-omics integration and data analysis challenges.

Main Results:

• Experimental methods excel at cell labeling and tracking; computational methods reconstruct lineage and model dynamics.
• Current challenges include accuracy, resolution, multi-omics integration, and scalability.
• Synergies between experimental and computational approaches are crucial for comprehensive lineage analysis.

Conclusions:

• Significant progress has been made in cell lineage tracing, but challenges remain.
• Future advancements will likely involve improved experimental techniques and AI-enhanced computational methods.
• Enhanced cell lineage tracing holds promise for unraveling fundamental biological processes and disease mechanisms.