Multi-condition and multi-modal temporal profile inference during mouse embryonic development.

Area of Science:

• Computational Biology
• Genomics
• Developmental Biology

Background:

• Single-cell time-series data offer insights into cellular dynamics but face challenges due to measurement disruption and mismatched time points across conditions and modalities.
• Integrating multi-condition and multi-modal single-cell data remains a significant hurdle in modeling cellular trajectories accurately.

Approach:

• We introduce Sunbear, a joint modeling framework designed for the integration of multi-condition and multi-modal single-cell profiles over time.
• Sunbear facilitates imputation of temporal profile changes, alignment of disparate datasets, and extrapolation of missing data modalities.

Key Points:

• Sunbear successfully revealed sex-biased transcription patterns during mouse embryonic development.
• The framework predicted dynamic relationships between epigenetic modifications and gene transcription, even with incomplete multi-modal data.
• It enables the projection of static single-cell snapshots into dynamic, multi-modal views of cellular progression.

Conclusions:

• Sunbear provides a robust computational approach for analyzing complex single-cell time-series data.
• This method enhances the ability to model and interpret cellular development across various conditions and data types.
• The framework has broad applications in developmental biology and precision medicine, facilitating deeper insights into cellular heterogeneity and dynamics.