Sign in
Molecular BiologybioRxiv
Preprint

PROTEOME DATA BASED IDENTIFICATION OF POTENTIAL RNAi TARGETS FOR COTTON MEALYBUG (Phenacoccus solenopsis Tinsley) POPULATION MANAGEMENT

Sanchita SinghiD, Somnath RahangdaleiD, Shivali Pandita, Manisha SinghiD, Gauri SaxenaiD, Gaurav Jain, Praveen Chandra VermaiD

Abstract

Background of the studyPhenacoccus solenopsis Tinsley (Hemiptera: Pseudococcidae), commonly known as cotton mealybug, regarded as an invasive pest worldwide, particularly in the tropics and subtropics. It is one of the major pests of cotton and other commercially important crops. Despite the significant economic losses caused by cotton mealybug the molecular aspects of this insect are under-studied. MethodsIn the present study, proteome data of four different developmental stages of cotton mealybug is generated. Differential expression of proteins (DEPs) was studied among six different groups of which, maximum DEPs (550 up-regulated and 1118 down-regulated) were obtained when the quantifiable proteins of Egg+first nymphal were compared with second nymphal instar (FC [≥] 2, P < 0.05). From this proteomics data fifteen potential target genes were predicted for insect pest management. Further, these fifteen genes were explored and evaluated the for RNAi based pest control and optimisation of dsRNA delivery system in cotton mealybug. The analysis of transient expression of target genes was performed. ResultsThe results signified that dsRNA of Ferritin caused [~]69% mortality hence, could be exploited as a promising candidate gene to design a sustainable method for cotton mealybug management. ConclusionThis study provides an urgently required, alternate green control strategy based on proteomics to identify potential RNAi targets for pest management.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISCedden '25Cedden '24Cedden '26Buer '24Güney '26Rauf '19
68% semantic matchZoology
Doğa Cedden, Gözde Güney, Michael Rostás+1 more·bioRxiv·Mar 23, 2025· 2 citations