Global transcriptome analysis identifies critical functional modules associated with multiple abiotic stress responses in microalgae Chromochloris zofingiensis

Abstract

In the current study, systems biology approach was applied to get a deep insight regarding the regulatory mechanisms of Chromochloris zofingiensis under overall stress conditions. Meta-analysis was performed using p-values combination of differentially expressed genes. To identify the informative models related to stress conditions, two distinct weighted gene co-expression networks were constructed and preservation analyses were performed using medianRankand Zsummary algorithms. Moreover, functional enrichment analysis of non-preserved modules was performed to shed light on the biological performance of underlying genes in the non-preserved modules. In the next step, the gene regulatory networks between top hub genes of non-preserved modules and transcription factors were inferred using ensemble of trees algorithm. Results showed that the power of beta = 7 was the best soft-thresholding value to ensure a scale-free network, leading to the determination of 12 co-expression modules with an average size of 128 genes. Preservation analysis showed that the connectivity pattern of the six modules including the blue, black, yellow, pink, greenyellow, and turquoise changed during stress condition which defined as non-preserved modules. Examples of enriched pathways in non-preserved modules were Oxidative phosphorylation", "Vitamin B6 metabolism", and "Arachidonic acid metabolism". Constructed regulatory network between identified TFs and top hub genes of non-preserved module such as Cz06g10250, Cz03g12130 showed that some specific TFs such as C3H and SQUAMOSA promoter binding protein (SBP) specifically regulates the specific hubs. The current findings add substantially to our understanding of the stress responsive underlying mechanism of C. zofingiensis for future studies and metabolite production programs.

Fig 1. Step-by- step workflow of applied pipeline in current study.

Fig 2. The relationship of Soft Threshold (power) with Scale Free Topology (A) and Mean Connectivity (B).

The number showing the power threshold for each soft power corresponding to the SFT and connectivity mean.

Fig 3. Weighted gene co-expression network analysis of stress responses genes in Chromochloris zofingiensis.

(A) Determined functional modules based on hierarchical cluster tree of the Meta genes. (B) The sizes of determined modules based on the number of involved genes. (C) The module Eigen gene adjacency estimated by hierarchical clustering and shown by heat map. (B) Topological Overlap Matrix (TOM) value among the proteins of the network delimited in modules by the dynamic method.

Fig 4. Preservation analysis of co-expressed modules of control networks were tested in the stress condition based on the median rank (A) and Zsummary (B) algorithms.

Each dots indicated the corresponding modules which was defined based on WGCNA method.

Fig 5. Functional impact of non-preserved modules-based gene ontology (biological processes category).

Fig 6. Regulatory networks between Hubs and TFs of non-preserved co-expressed modules under stress condition.

Each dots indicated the genes involved in coexpressed modules. Here in we defined the dot as a node in the constructed network. Node colors represent correspondence module color of hub genes. TFs were shown with bigger red nodes.