Gateway analysis reveals transient molecular programs at cell-fate transitions

Area of Science:

• Computational Biology
• Genomics
• Developmental Biology

Background:

• Single-cell atlases offer insights into cell identity but struggle to resolve rare, transient cell states during cell fate transitions.
• Identifying molecular programs driving lineage changes is challenging due to the low abundance of these intermediate cells.

Purpose of the Study:

• To develop a computational framework, gateway analysis, for identifying rare cell populations at fate boundaries.
• To pinpoint specific genes (bell and valley genes) that characterize these transient cell states.

Main Methods:

• Gateway analysis defines cell neighborhoods using binary mutual information (BMI) from gene expression patterns.
• A regularized latent model preserves neighborhood structure to identify boundary cells.
• The framework was applied to four diverse single-cell datasets.

Main Results:

• Gateway analysis successfully identified rare boundary populations and their associated transient gene expression programs across reprogramming, gastrulation, pancreatic endocrinogenesis, and kidney injury datasets.
• Key biological processes like epithelial remodeling, gastrulation regulation, endocrine differentiation signaling, and proteostasis were identified at specific transition points.
• These transition signals were not detected by standard comparisons of stable cell populations.

Conclusions:

• Gateway analysis provides a robust method for detecting rare transition-state cells and their defining molecular signatures in large single-cell atlases.
• This framework enhances the understanding of dynamic cellular processes and cell fate decisions.
• The identified bell and valley genes offer novel insights into the mechanisms governing cell transitions.