Systematic identification of yeast cell cycle transcription factors using multiple data sources

Area of Science:

• Molecular Biology
• Systems Biology
• Genomics

Background:

• Eukaryotic cell cycle progression is a complex, highly regulated process.
• Cell cycle-specific genes are often transcriptionally controlled, expressed precisely when needed.
• Identifying cell cycle transcription factors (TFs) is crucial for understanding gene regulation.

Purpose of the Study:

• To develop and validate a computational method for identifying cell cycle TFs in yeast.
• To identify novel cell cycle-regulated genes and TFs.
• To elucidate the regulatory roles and temporal dynamics of TFs within the cell cycle.

Main Methods:

• Integrated ChIP-chip, mutant, transcription factor binding site (TFBS), and gene expression data.
• Developed a novel computational approach to predict cell cycle TFs and their target genes.
• Validated predictions against existing literature and experimental data.

Main Results:

• Identified 17 cell cycle TFs in yeast, including 12 known and 5 putative novel TFs (Ash1, Rlm1, Ste12, Stp1, Tec1).
• Determined specific cell cycle phases of function and regulatory time lags for identified TFs.
• Discovered 178 novel cell cycle-regulated genes, including 59 with previously unknown functions.

Conclusions:

• The developed method is effective for identifying yeast cell cycle TFs and regulated genes.
• Integration of multiple data sources provides a powerful approach for studying complex biological systems.
• The findings offer a validated resource for further research into cell cycle mechanisms.