Co-expression network analysis: a future approach for pest control target discovery

Authors: ZHOU, ZAIHUI - Huazhong Agricultural University; YAO, ZHUOTIAN - Huazhong Agricultural University; ABOUZAID, MOSTAFA - Huazhong Agricultural University; Hull, Joe; MA, WEIHUA - Huazhong Agricultural University; HUA, HONGXIA - Huazhong Agricultural University; LIN, YONGJUN - Huazhong Agricultural University

Submitted to: Journal of Agriculture and Food Chemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/14/2023
Publication Date: 5/5/2023
Citation: Zhou, Z., Yao, Z., Abouzaid, M., Hull, J.J., Ma, W., Hua, H., Lin, Y. 2023. Co-expression network analysis: a future approach for pest control target discovery. Journal of Agriculture and Food Chemistry. https://doi.org/10.1021/acs.jafc.3c00113.
DOI: https://doi.org/10.1021/acs.jafc.3c00113

Interpretive Summary: The advantage of applying correlation networks to functional bioinformatics applications is the identification of genes with potentially intriguing biological relevance that had been overlooked in previous analyses. The weighted gene co-expression network analysis (WGCNA) is one such correlational program designed to infer relationships in RNA-seq samples. Using an RNA-seq dataset consisting of 60 libraries, a number of transcripts correlated with larvae size and cholesterol content were identified in the striped stem borer. PCR-based expression profiling and RNAi-mediated knockdown assays of a subset of the transcripts revealed a critical role for Nieman pick type c 1 homolog b (NPC1b) in the uptake and utilization of cholesterol during striped stem borer development. The study highlights the utility of correlational networks and suggests that NPC1b homologs may be good candidates for targeted disruption in other insect pests.

Technical Abstract: 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.