Abstract
BackgroundAs one of the most dominant bacterial groups on Earth, cyanobacteria play a pivotal role in the global carbon cycling and the Earth atmosphere composition. Understanding their molecular responses to environmental perturbations has important scientific and environmental values. Since important biological processes or networks are often evolutionarily conserved, the cross-species transcriptional network analysis offers a useful strategy to decipher conserved and species-specific transcriptional mechanisms that cells utilize to deal with various biotic and abiotic disturbances, and it will eventually lead to a better understanding of associated adaptation and regulatory networks.ResultsIn this study, the Weighted Gene Co-expression Network Analysis (WGCNA) approach was used to establish transcriptional networks for four important cyanobacteria species under metal stress, including iron depletion and high copper conditions. Cross-species network comparison led to discovery of several core response modules and genes possibly essential to metal stress, as well as species-specific hub genes for metal stresses in different cyanobacteria species, shedding light on survival strategies of cyanobacteria responding to different environmental perturbations.ConclusionsThe WGCNA analysis demonstrated that the application of cross-species transcriptional network analysis will lead to novel insights to molecular response to environmental changes which will otherwise not be achieved by analyzing data from a single species.
Highlights
As one of the most dominant bacterial groups on Earth, cyanobacteria play a pivotal role in the global carbon cycling and the Earth atmosphere composition
The analysis demonstrated that the application of crossspecies transcriptional network analysis could lead to novel insights into molecular response to environmental changes which will otherwise not be achieved by analyzing data from a single species
Analysis of the transcriptional networks showed that a total of 17, 21, 32 and 28 distinct transcriptional modules can be detected within the transcriptional networks of Prochlorococcus MIT9313 (PMT), PMM, SYG and Synechococcus WH 8102 (SYW), respectively (Additional file 2: Figure S2)
Summary
As one of the most dominant bacterial groups on Earth, cyanobacteria play a pivotal role in the global carbon cycling and the Earth atmosphere composition Understanding their molecular responses to environmental perturbations has important scientific and environmental values. WGCNA has been used in identifying functional clusters (modules) of highly correlated genes, summarizing such clusters using the module eigengene or an intramodular hub gene, relating modules to one another and to external sample traits (using eigengene network methodology), calculating module membership measures in many systems, and correlation network analysis can be used to determine biological correlated candidate biomarkers or disease therapeutic targets [11]. A recent comparative study of different network analysis methods indicated that WGCNA could be used for constructing gene networks, and for detecting modules/sub-networks, identifying hub genes and selecting candidate genes as biomarkers, using Escherichia coli as an empirical sample [18]
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