Network analysis of transcriptomics expands regulatory landscapes in Synechococcus sp. PCC 7002.
Nucleic Acids Res
; 44(18): 8810-8825, 2016 Oct 14.
Article
em En
| MEDLINE
| ID: mdl-27568004
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 expansion of novel potential targets of both DNA binding proteins and sRNA regulators. These results offer a new perspective into the multi-level regulation that governs cellular adaptations of the fast-growing physiologically robust cyanobacterium Synechococcus sp. PCC 7002 to changing environmental variables. It also provides a methodological high-throughput approach to studying multi-scale regulatory mechanisms that operate in cyanobacteria. Finally, it provides valuable context for integrating systems-level data to enhance gene grouping based on annotated function, especially in organisms where traditional context analyses cannot be implemented due to lack of operon-based functional organization.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Regulação Bacteriana da Expressão Gênica
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Synechococcus
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Redes Reguladoras de Genes
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Transcriptoma
Tipo de estudo:
Prognostic_studies
Idioma:
En
Revista:
Nucleic Acids Res
Ano de publicação:
2016
Tipo de documento:
Article
País de afiliação:
Estados Unidos