Network analysis of transcriptomics expands regulatory landscapes in Synechococcus sp. PCC 7002.

ABSTRACT: Cyanobacterial regulation of gene expression must contend with a genome organization that lacks apparent functional context, as the majority of cellular processes and metabolic pathways are encoded by genes found at disparate locations across the genome and relatively few transcription factors exist. In this study, global transcript abundance data from the model cyanobacterium Synechococcus sp. PCC 7002 grown under 42 different conditions was analyzed using Context-Likelihood of Relatedness (CLR). The resulting network, organized into 11 modules, provided insight into transcriptional network topology as well as grouping genes by function and linking their response to specific environmental variables. When used in conjunction with genome sequences, the network allowed identification and exp

SUBMITTER: McClure RS 

PROVIDER: S-EPMC5062996 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature