MoPS

MoPS identifies periodic fluctuations in time-series transcriptomic data using metabolic RNA labeling and comparative dynamic transcriptome analysis (cDTA) to quantify mRNA synthesis and degradation rates during processes such as the cell cycle.

Key Features:

• Metabolic RNA Labeling: Utilizes metabolic incorporation of labeled nucleotides into newly synthesized RNA to track mRNA synthesis over time.
• Comparative Dynamic Transcriptome Analysis (cDTA): Employs a comparative approach to analyze transcriptome snapshots at multiple time points to derive synthesis and degradation rates.
• Synthesis and Degradation Rate Estimation: Derives quantitative mRNA synthesis and degradation rates from labeled-RNA time-series data.
• High Temporal Resolution: Captures measurements at high temporal resolution, including sampling intervals as short as every 5 minutes.
• Statistical Modeling for Periodicity Detection: Incorporates a statistical model to identify genes with significant periodic changes in mRNA synthesis and degradation.
• Regulatory Inference: Links temporal patterns of synthesis and degradation to upstream DNA motifs, transcription factors, and core promoter properties.

Scientific Applications:

• Cell Cycle Analysis in Saccharomyces cerevisiae: Characterizes periodic mRNA dynamics across cell cycle phases in yeast.
• Gene Expression Dynamics: Identifies genes with periodic expression and dissects the temporal coordination of transcription and mRNA stability.
• Regulatory Mechanism Elucidation: Associates timing of mRNA synthesis with upstream DNA motifs, transcription factors, and core promoters to infer regulatory control.
• Systems Biology and Genomics: Provides temporal quantitative inputs for models of gene regulation and network dynamics in genomics studies.

Methodology:

Comparative dynamic transcriptome analysis (cDTA) compares labeled-RNA time-series to derive mRNA synthesis and degradation rates, and a statistical model identifies genes with significant periodic changes and associates timing with upstream DNA motifs, transcription factors, and core promoters.