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The dynamic changes of genes revealed that persistently overexpressed genes drive the evolution of cyflumetofen resistance in Tetranychus cinnabarinus.

Kaiyang FengJialu LiuMingyu ZhaoZhixin JiangPeilin LiuPeng WeiWei DouLin He
Published in: Insect science (2022)
Changes in gene expression are associated with the evolution of pesticide resistance in arthropods. In this study, transcriptome sequencing was performed in three different resistance levels (low, L; medium, M; and high, H) of cyflumetofen-resistant strain (YN-CyR). A total of 1 685 genes, including 97 detoxification enzyme genes, were upregulated in all three stages, of which 192 genes, including 11 detoxification enzyme genes, showed a continuous increase in expression level with resistance development (L to H). RNAi experiments showed that overexpression of 7 genes (CYP392A1, TcGSTd05, CCE06, CYP389A1, TcGSTz01, CCE59, and CYP389C2) is involved in the development of cyflumetofen resistance in Tetranychus cinnabarinus. The recombinant CYP392A1 can effectively metabolize cyflumetofen, while CCE06 can bind and sequester cyflumetofen in vitro. We compared two methods for rapid screening of resistance molecular markers, including short-term induction and one-time high-dose selection. Two detoxification enzyme genes were upregulated in the field susceptible strain (YN-S) by induction with LC 20 of cyflumetofen. However, 16 detoxification enzyme genes were upregulated by one-time selection with LC 80 of cyflumetofen. Interestingly, the 16 genes were overexpressed in all three resistance stages. These results indicated that 1 685 genes that were upregulated at the L stage constituted the basis of cyflumetofen resistance, of which 192 genes whose upregulation continued to increase were the main driving force for the development of resistance. Moreover, the one-time high-dose selection is an efficient way to rapidly obtain the resistance-related genes that can aid in the development of resistance markers and resistance management in mites. This article is protected by copyright. All rights reserved.
Keyphrases
  • genome wide
  • gene expression
  • bioinformatics analysis
  • high dose
  • genome wide identification
  • genome wide analysis
  • low dose
  • poor prognosis
  • rna seq