Gene Co-Expression Network Analysis Reveals Key Regulatory Genes in Metisa plana Hormone Pathways.
Vinothienii VengatharajulooHoe-Han GohMaizom HassanNisha GovenderSuhaila SulaimanNor Afiqah-AlengSarahani HarunZeti Azura Mohamed HusseinPublished in: Insects (2023)
Metisa plana Walker (Lepidoptera: Psychidae) is a major oil palm pest species distributed across Southeast Asia. M. plana outbreaks are regarded as serious ongoing threats to the oil palm industry due to their ability to significantly reduce fruit yield and subsequent productivity. Currently, conventional pesticide overuses may harm non-target organisms and severely pollute the environment. This study aims to identify key regulatory genes involved in hormone pathways during the third instar larvae stage of M. plana gene co-expression network analysis. A weighted gene co-expression network analysis (WGCNA) was conducted on the M. plana transcriptomes to construct a gene co-expression network. The transcriptome datasets were obtained from different development stages of M. plana , i.e., egg, third instar larvae, pupa, and adult. The network was clustered using the DPClusO algorithm and validated using Fisher's exact test and receiver operating characteristic (ROC) analysis. The clustering analysis was performed on the network and 20 potential regulatory genes (such as MTA1-like , Nub , Grn , and Usp ) were identified from ten top-most significant clusters. Pathway enrichment analysis was performed to identify hormone signalling pathways and these pathways were identified, i.e., hormone-mediated signalling, steroid hormone-mediated signalling, and intracellular steroid hormone receptor signalling as well as six regulatory genes Hnf4 , Hr4 , MED14 , Usp , Tai , and Trr . These key regulatory genes have a potential as important targets in future upstream applications and validation studies in the development of biorational pesticides against M. plana and the RNA interference (RNAi) gene silencing method.
Keyphrases
- network analysis
- genome wide
- genome wide identification
- transcription factor
- poor prognosis
- copy number
- genome wide analysis
- dna methylation
- risk assessment
- binding protein
- computed tomography
- bioinformatics analysis
- machine learning
- gene expression
- inflammatory response
- current status
- fatty acid
- high resolution
- drosophila melanogaster
- young adults
- deep learning
- magnetic resonance
- data analysis
- aedes aegypti
- human health
- immune response