Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2016 Nov 21:7:206.
doi: 10.3389/fgene.2016.00206. eCollection 2016.

A Network Approach of Gene Co-expression in the Zea mays/ Aspergillus flavus Pathosystem to Map Host/Pathogen Interaction Pathways

Affiliations

A Network Approach of Gene Co-expression in the Zea mays/ Aspergillus flavus Pathosystem to Map Host/Pathogen Interaction Pathways

Bryan M Musungu et al. Front Genet. .

Abstract

A gene co-expression network (GEN) was generated using a dual RNA-seq study with the fungal pathogen Aspergillus flavus and its plant host Zea mays during the initial 3 days of infection. The analysis deciphered novel pathways and mapped genes of interest in both organisms during the infection. This network revealed a high degree of connectivity in many of the previously recognized pathways in Z. mays such as jasmonic acid, ethylene, and reactive oxygen species (ROS). For the pathogen A. flavus, a link between aflatoxin production and vesicular transport was identified within the network. There was significant interspecies correlation of expression between Z. mays and A. flavus for a subset of 104 Z. mays, and 1942 A. flavus genes. This resulted in an interspecies subnetwork enriched in multiple Z. mays genes involved in the production of ROS. In addition to the ROS from Z. mays, there was enrichment in the vesicular transport pathways and the aflatoxin pathway for A. flavus. Included in these genes, a key aflatoxin cluster regulator, AflS, was found to be co-regulated with multiple Z. mays ROS producing genes within the network, suggesting AflS may be monitoring host ROS levels. The entire GEN for both host and pathogen, and the subset of interspecies correlations, is presented as a tool for hypothesis generation and discovery for events in the early stages of fungal infection of Z. mays by A. flavus.

Keywords: Aspergillus flavus; RNA-sequencing; Zea mays; gene co-expression analysis; networks.

PubMed Disclaimer

Figures

FIGURE 1
FIGURE 1
Principal component analysis (PCA) of RNA-seq. Transcriptomic (global gene expression) data from each of the time points of (A) Zea mays and (B) Aspergillus flavus were analyzed by principal component analysis using R statistical language. Colored dots represent individual biological replicates harvested at different time points during the infection. These were grouped based on similarity of infection by hpi (hours post-inoculation).
FIGURE 2
FIGURE 2
Histogram distribution of Pearson correlations. Histogram shows the correlation between differentially expressed genes identified in an in vivo simultaneous RNA-seq experiment with A. flavus and Z. mays. The histogram includes all differentially expressed genes along with their Pearson correlation distribution for (Z. mays vs. Z. mays), (A. flavus vs. A. flavus), and (Z. mays vs. A. flavus). The correlations that were found to be significant in the analysis were greater >0.95 Pearson correlation.
FIGURE 3
FIGURE 3
Interspecific Z. mays and A. flavus co-expression network Pearson correlation analysis was performed on Z. mays and A. flavus genes to generate a cytoscape network. The network contains edges (lines implying linkage) which had a Pearson correlation >0.95. Blue nodes (Z. mays) and yellow nodes (A. flavus) are found within the network. Within the network (A) represents the Z. mays genes that were found to be co-expressed with at least one A. flavus gene. (B) (GRMZM2G420988) Solute Carrier Protein which was found to be associated with 421 A. flavus genes. (C) Shows a subnetwork with the co-regulator for the aflatoxin cluster AflS.
FIGURE 4
FIGURE 4
(A) Mcode Analysis of the Z. mays to Z. mays subnetwork from the gene co-expression network (GEN) was performed. (B,D) Shows subnetworks and the functionally enriched terms present within each of subnets that had greater than two interactions. (C,E) Show the genes that had the largest clustering coefficient in the subnetworks. (C) Represents the mcode analysis of (B,E,F) represents (D). For the tables show expression of the columns were order by a relative to the abundance of A. flavus. The gene ontology values were calculated using gprofiler and only significant terms were kept in the table (FDR <0.1).
FIGURE 5
FIGURE 5
Gene co-expression and interactome overlap network. Genes found in the interspecies co-expression network (baits) were mined in the predicted maize interactome (PiZeaM) to determine novel interacting protein partners (preys). Triangles indicate that a gene is a bait gene from the static co-expression network and rectangles indicate first neighbors within the interactome.

Similar articles

Cited by

References

    1. Abdel-Hadi A., Schmidt-Heydt M., Parra R., Geisen R., Magan N. (2012). A systems approach to model the relationship between aflatoxin gene cluster expression, environmental factors, growth and toxin production by Aspergillus flavus. J. R. Soc. Interface 9 757–767. 10.1098/rsif.2011.0482 - DOI - PMC - PubMed
    1. Amare M. G., Keller N. P. (2014). Molecular mechanisms of Aspergillus flavus secondary metabolism and development. Fungal Genet. Biol. 66 11–18. 10.1016/j.fgb.2014.02.008 - DOI - PubMed
    1. Bader G. D., Hogue C. W. (2003). An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinformatics 4:1 10.1186/1471-2105-4-1 - DOI - PMC - PubMed
    1. Bhardwaj N., Lu H. (2005). Correlation between gene expression profiles and protein–protein interactions within and across genomes. Bioinformatics 21 2730–2738. 10.1093/bioinformatics/bti398 - DOI - PubMed
    1. Borad V., Sriram S. (2008). Pathogenesis-related proteins for the plant protection. Asian J. Exp. Sci. 22 189–196.