Global analysis of phase locking in gene expression during cell cycle: the potential in network modeling

Area of Science:

• Systems Biology
• Computational Biology
• Genomics

Background:

• Synchrony via oscillation and frequency modulation coordinates modules in dynamic systems.
• Frequency modulation is increasingly recognized in transcription regulation.
• Synchrony patterns can infer biological interactions.

Purpose of the Study:

• Investigate phase locking analysis for transcription network modeling.
• Assess its utility with time-course gene expression data.
• Develop a novel phase locking metric for network reconstruction.

Main Methods:

• Applied phase locking analysis to yeast cell cycle gene expression data.
• Compared phase locking with correlation for identifying gene interactions.
• Proposed a new phase locking metric for network reconstruction.

Main Results:

• Significant phase locking observed between transcription factors and targets, interacting gene pairs, and cell cycle genes.
• Phase locking identified interacting gene pairs more efficiently than correlation.
• The method automatically handles time lags and different dynamic scales.
• Observed higher-order locking and phase lags between gene pairs.

Conclusions:

• Phase locking analysis shows significant potential for transcription network modeling.
• The findings highlight the importance of dynamic gene expression patterns.
• The proposed metric effectively identifies biologically relevant network modules.