Gene Co-expression Network Analysis to Identify Key Genes Involved in the Development of Root-knot Nematode Meloidogyne Incognita

Abstract

Plant-parasitic nematodes are a major cause of crop loss globally approximated at 150 billion dollars annually, and existing nematicides are toxic such that they offset the soil microbiome essential for crop growth. In order to develop eco-friendly mitigation tools, it is necessary to understand underlying molecular interactions driving the invasive phenotype of parasites. In this respect, a gene-gene co-expression network analysis of Meloidogyne incognita infecting Solanum lycopersicum was considered to be a good model for establishing a plant-nematode association. Transcriptomic data from five developmental stages of Meloidogyne incognita were obtained from the Sequence Read Archive (SRA) database of the National Centre for Biotechnology Information (NCBI). The data was pre-processed, generating a gene co-regulation count matrix. A systems biology tool, weighted gene co-expression network analysis (WGCNA) package, was used to describe gene correlation patterns across the development stages of M. incognita. The WGCNA tool was also utilised to detect clusters (modules) of highly correlated genes, summarise the modules using a module eigengene or an intramodular hub gene, connect modules, thus generating a gene-gene co-expression network of M. incognita. g:Profiler tool was used to perform functional enrichment on module genes establishing biological function to established gene co-expression network clusters. Multiple Expectation maximizations for Motif Elicitation (MEME) suite web tool were used to determine each module's highly abundant regulatory motifs. A total of 30,894 most varied genes and ten (10) modules were identified to be expressed during a 6-week developmental process of Meloidogyne incognita. Genes within the blue, darkslateblue, and plum1 modules were significantly related to perception and response to abiotic and biotic factors. The brown module was associated with altering the host’s transcriptional machinery. The darkseagreen3 module was responsible for producing peptide effector molecules facilitating parasite penetration into host tissues...