RNA interference-mediated control of cigarette beetle, Lasioderma serricorne.
Jinmo KooShankar C R R ChereddySubba Reddy PalliPublished in: Archives of insect biochemistry and physiology (2020)
The cigarette beetle (CB; Lasioderma serricorne) is a pest on many stored products including tobacco. Fumigation is the common control method currently used. However, the options for controlling this pest are limited, due to resistance issues and phasing out of currently used chemical insecticides. Here, we evaluated RNA interference (RNAi) as a potential method for controlling the CB. RNA isolated from different stages was sequenced and assembled into a transcriptome. The CB RNA sequences showed the highest homology with those in the red flour beetle, Tribolium castaneum. Orthologs of proteins known to function in RNAi pathway were identified in the CB transcriptome, suggesting that RNAi may work well in this insect. Also, 32 P-labeled double-stranded RNA (dsRNA) injected into CB larvae and adults was processed to small interference RNAs. We selected 12 genes that were shown to be the effective RNAi targets in T. castaneum and other insects and identified orthologs of them in the CB by searching its transcriptome. Injection of dsRNA targeting genes coding for GAWKY, Kinesin, Sec23, SNF7, and 26S proteasome subunit 6B into the CB larvae caused 100% mortality. Feeding dsRNA targeting SNF7 and 26S proteasome subunit 6B by sucrose droplet assay induced more than 90% mortality, which is 1.8 times higher than the mortality induced by dsGFP control (53%). These data demonstrate an efficient RNAi response in CB, suggesting that RNAi could be developed as an efficient method to control this pest.
Keyphrases
- genome wide
- single cell
- cardiovascular events
- gene expression
- rna seq
- nucleic acid
- aedes aegypti
- high throughput
- risk factors
- cancer therapy
- smoking cessation
- dna methylation
- type diabetes
- oxidative stress
- climate change
- drug delivery
- risk assessment
- zika virus
- computed tomography
- artificial intelligence
- endothelial cells
- stress induced
- room temperature
- binding protein
- data analysis
- drosophila melanogaster
- deep learning