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Critical Analysis of Multi-Omic Data from a Strain of Plutella xylostella Resistant to Bacillus thuringiensis Cry1Ac Toxin.

Shi KangXun ZhuQingjun WuShaoli WangNeil CrickmoreYou-Jun ZhangZhaojiang Guo
Published in: Journal of agricultural and food chemistry (2022)
Rapid evolution of resistance in crop pests to Bacillus thuringiensis (Bt) products threatens their widespread use, especially as pests appear to develop resistance through a range of different physiological adaptations. With such a diverse range of mechanisms reported, researchers have resorted to multi-omic approaches to understand the molecular basis of resistance. Such approaches generate a lot of data making it difficult to establish where causal links between physiological changes and resistance exist. In this study, a combination of RNA-Seq and iTRAQ was used with a strain of diamondback moth, Plutella xylostella (L.), whose resistance mechanism is well understood. While some of the causal molecular changes in the resistant strain were detected, other previously verified changes were not detected. We suggest that while multi-omic studies have use in validating a proposed resistance mechanism, they are of limited value in identifying such a mechanism in the first place.
Keyphrases
  • electronic health record
  • rna seq
  • single cell
  • single molecule
  • artificial intelligence
  • big data