Co-Expression Network Analysis: A Future Approach for Pest Control Target Discovery.
Zaihui ZhouZhuotian YaoMostafa AbouzaidJ Joe HullWeihua MaHongxia HuaYongjun LinPublished in: Journal of agricultural and food chemistry (2023)
The striped stem borer (SSB, Chilo suppressalis Walker ) is a major pest of rice worldwide. Double-stranded RNAs (dsRNAs) targeting essential genes can trigger a lethal RNA interference (RNAi) response in insect pests. In this study, we applied a Weighted Gene Co-expression Network Analysis (WGCNA) to diet-based RNA-Seq data as a method to facilitate the discovery of novel target genes for pest control. Nieman-Pick type c 1 homolog b ( NPC1b ) was identified as the gene with the highest correlation values to hemolymph cholesterol levels and larval size. Functional characterization of the gene supported CsNPC1b expression with dietary cholesterol uptake and insect growth. This study revealed the critical role of NPC1b for intestinal cholesterol absorption in lepidopteran insects and highlights the utility of the WGCNA approach for identifying new pest management targets.
Keyphrases
- network analysis
- genome wide
- poor prognosis
- rna seq
- genome wide identification
- single cell
- small molecule
- copy number
- binding protein
- dna methylation
- genome wide analysis
- low density lipoprotein
- magnetic resonance
- gene expression
- machine learning
- high throughput
- computed tomography
- long non coding rna
- artificial intelligence