Faculty Collaboration Database

Global analysis of phase locking in gene expression during cell cycle: the potential in network modeling. BMC Syst Biol 2010 Dec 03;4:167

Date

12/07/2010

Pubmed ID

21129191

Pubmed Central ID

PMC3017040

DOI

10.1186/1752-0509-4-167

Scopus ID

2-s2.0-78649564171 (requires institutional sign-in at Scopus site)   9 Citations

Abstract

BACKGROUND: In nonlinear dynamic systems, synchrony through oscillation and frequency modulation is a general control strategy to coordinate multiple modules in response to external signals. Conversely, the synchrony information can be utilized to infer interaction. Increasing evidence suggests that frequency modulation is also common in transcription regulation.

RESULTS: In this study, we investigate the potential of phase locking analysis, a technique to study the synchrony patterns, in the transcription network modeling of time course gene expression data. Using the yeast cell cycle data, we show that significant phase locking exists between transcription factors and their targets, between gene pairs with prior evidence of physical or genetic interactions, and among cell cycle genes. When compared with simple correlation we found that the phase locking metric can identify gene pairs that interact with each other more efficiently. In addition, it can automatically address issues of arbitrary time lags or different dynamic time scales in different genes, without the need for alignment. Interestingly, many of the phase locked gene pairs exhibit higher order than 1:1 locking, and significant phase lags with respect to each other. Based on these findings we propose a new phase locking metric for network reconstruction using time course gene expression data. We show that it is efficient at identifying network modules of focused biological themes that are important to cell cycle regulation.

CONCLUSIONS: Our result demonstrates the potential of phase locking analysis in transcription network modeling. It also suggests the importance of understanding the dynamics underlying the gene expression patterns.

Author List

Gao S, Hartman JL 4th, Carter JL, Hessner MJ, Wang X

Author

Martin J. Hessner PhD Professor in the Pediatrics department at Medical College of Wisconsin

MESH terms used to index this publication - Major topics in bold

Cell Cycle
Gene Expression Profiling
Gene Regulatory Networks
Models, Genetic
Nonlinear Dynamics
Reproducibility of Results
Transcription Factors