Abstract
Penicillium echinulatum 2HH and Penicillium oxalicum 114-2 are well-known cellulase fungal producers. However, few studies addressing global mechanisms for gene regulation of these two important organisms are available so far. A recent finding that the 2HH wild-type is closely related to P. oxalicum leads to a combined study of these two species. Firstly, we provide a global gene regulatory network for P. echinulatum 2HH and P. oxalicum 114-2, based on TF-TG orthology relationships, considering three related species with well-known regulatory interactions combined with TFBSs prediction. The network was then analyzed in terms of topology, identifying TFs as hubs, and modules. Based on this approach, we explore numerous identified modules, such as the expression of cellulolytic and xylanolytic systems, where XlnR plays a key role in positive regulation of the xylanolytic system. It also regulates positively the cellulolytic system by acting indirectly through the cellodextrin induction system. This remarkable finding suggests that the XlnR-dependent cellulolytic and xylanolytic regulatory systems are probably conserved in both P. echinulatum and P. oxalicum. Finally, we explore the functional congruency on the genes clustered in terms of communities, where the genes related to cellular nitrogen, compound metabolic process and macromolecule metabolic process were the most abundant. Therefore, our approach allows us to confer a degree of accuracy regarding the existence of each inferred interaction.
Highlights
The connectivity between biological data facilitates the inference of networks
We propose the inference of gene regulatory network (GRN) for P. echinulatum 2HH and P. oxalicum 114-2, based on transcription factors (TFs)-target genes (TGs) orthology relationships of three related species with well-known regulatory interactions, combined with transcription factor binding sites (TFBSs) prediction
We identified that the networks are structured into a single giant component in which there is a path between each pair of nodes. Taking these data into account, we identified that 1,404 nodes in P. echinulatum and 1,776 nodes in P. oxalicum are regulated by only one TF, i.e., they have an input degree of 1; while the BrlA (PDE_00087) and its orthologous PECH_007435 are regulated by 24 TFs in P. oxalicum and P. echinulatum, respectively, making them the most regulated genes
Summary
The connectivity between biological data facilitates the inference of networks. These graphs are made up of nodes and connections between them, comprising a flexible model that can capture the complexity and interconnectivity of biological information (Huber et al, 2007). The elucidation of regulatory relationships between transcription regulators and their target genes is essential to understand various biological processes. These processes range from cell growth and division, cell differentiation in multicellular organisms and cell response to environmental changes. A gene regulatory network (GRN) is a directed graph in which gene regulators are connected to target genes (TGs) by interaction edges (Karlebach and Shamir, 2008). GRNs combined with knowledge mining has a major potential to improve omics data interpretation, allowing the discovery of how transcription regulation may control biological processes, phenotypes, and diseases (Hassani-Pak and Rawlings, 2017)
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