Elucidation of gene interaction networks through time-lagged correlation analysis of transcriptional data.
The photosynthetic cyanobacterium Synechocystis sp. strain PCC 6803 uses a complex genetic program to control its physiological response to alternating light conditions. To study this regulatory program time-series experiments were conducted by exposing Synechocystis sp. to serial perturbations in light intensity. In each experiment whole-genome DNA microarrays were used to monitor gene transcription in 20-min intervals over 8- and 16-h periods. The data was analyzed using time-lagged correlation analysis, which identifies genetic interaction networks by constructing correlations between time-shifted transcription profiles with different levels of statistical confidence. These networks allow inference of putative cause-effect relationships among the organism's genes. Using light intensity as our initial input signal, we identified six groups of genes whose time-lagged profiles possessed significant correlation, or anti-correlation, with the light intensity. We expanded this network by using the average profile from each group of genes as a seed, and searching for other genes whose time-lagged profiles possessed significant correlation, or anti-correlation, with the group's average profile. The final network comprised 50 different groups containing 259 genes. Several of these gene groups possess known light-stimulated gene clusters, such as Synechocystis sp. photosystems I and II and carbon dioxide fixation pathways, while others represent novel findings in this work.
Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.
William A
WA
Schmitt
R Michael
RM
Raab
Gregory
G
Stephanopoulos
D000458:Cyanobacteria / Q000235:genetics*; D020869:Gene Expression Profiling; D015964:Gene Expression Regulation, Bacterial; D005798:Genes, Bacterial; D016680:Genome, Bacterial; D008027:Light; D008954:Models, Biological; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods; D013997:Time Factors