ArticleNucleic acids research2016
Network analysis of transcriptomics expands regulatory landscapes in Synechococcus sp. PCC 7002.
Article in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 28 citations in OpenAlex.
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- High-density CRISPRi screens reveal diverse routes to improved acclimation in cyanobacteria.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
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- Bioactive exometabolites drive maintenance competition in simple bacterial communities.mSystems · 2024Article
- Gene co-expression network analysis in zebrafish reveals chemical class specific modules.BMC genomics · 2021Article
- Enhancing photosynthetic production of glycogen-rich biomass for use as a fermentation feedstock.Frontiers in energy research · 2020Article
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- Unified feature association networks through integration of transcriptomic and proteomic data.PLoS computational biology · 2019Article
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- Effect of COFrontiers in microbiology · 2019Article
- Improving network inference algorithms using resampling methods.BMC bioinformatics · 2018Article
- Species-specific transcriptomic network inference of interspecies interactions.The ISME journal · 2018Article
- Distinct and redundant functions of three homologs of RNase III in the cyanobacterium Synechococcus sp. strain PCC 7002.Nucleic acids research · 2018Article
- Zn2+-Inducible Expression Platform for Synechococcus sp. Strain PCC 7002 Based on the smtA Promoter/Operator and smtB Repressor.Applied and environmental microbiology · 2017Article
- Small proteins in cyanobacteria provide a paradigm for the functional analysis of the bacterial micro-proteome.BMC microbiology · 2016Article
- Regulatory Tools for Controlling Gene Expression in Cyanobacteria.Advances in experimental medicine and biologyReview
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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