Unbiased Boolean analysis of public gene expression data for cell cycle gene identification

Mol Biol Cell. 2019 Jul 1;30(14):1770-1779. doi: 10.1091/mbc.E19-01-0013. Epub 2019 May 15.


Cell proliferation is essential for the development and maintenance of all organisms and is dysregulated in cancer. Using synchronized cells progressing through the cell cycle, pioneering microarray studies defined cell cycle genes based on cyclic variation in their expression. However, the concordance of the small number of synchronized cell studies has been limited, leading to discrepancies in definition of the transcriptionally regulated set of cell cycle genes within and between species. Here we present an informatics approach based on Boolean logic to identify cell cycle genes. This approach used the vast array of publicly available gene expression data sets to query similarity to CCNB1, which encodes the cyclin subunit of the Cdk1-cyclin B complex that triggers the G2-to-M transition. In addition to highlighting conservation of cell cycle genes across large evolutionary distances, this approach identified contexts where well-studied genes known to act during the cell cycle are expressed and potentially acting in nondivision contexts. An accessible web platform enables a detailed exploration of the cell cycle gene lists generated using the Boolean logic approach. The methods employed are straightforward to extend to processes other than the cell cycle.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Cell Cycle / genetics*
  • Databases, Genetic*
  • Drosophila / genetics
  • Gene Expression Regulation*
  • Humans
  • Mice
  • Plants / genetics