Data from: Population-specific gene expression patterns underlying differential sensitivity to deltamethrin in Culex pipiens in Blida Province, Northern Algeria
Data files
Sep 25, 2026 version files 26.90 KB
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Metadata_Bochra__2nd_MS.xlsx
22.08 KB
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README.md
4.81 KB
Abstract
Insecticide resistance in mosquitoes poses a major challenge for vector control and the prevention of mosquito-borne diseases. This study investigated resistance to the pyrethroid deltamethrin and associated gene expression responses in Culex pipiens populations from Blida Province, Northern Algeria. Larvae were collected from two urban sites (Mouzaia and 13-May) and one rural site (Hammam Melouane), and susceptibility bioassays were conducted using fourth-instar larvae following WHO guidelines. Marked differences in susceptibility were observed among populations. The rural population was highly susceptible (LC₅₀ = 0.00002 ppm), whereas urban populations exhibited strong resistance, with resistance ratios reaching up to 1000-fold. To explore underlying molecular responses, larvae were exposed to LC₂₅, LC₅₀, and LC₇₅ concentrations of deltamethrin, and expression of detoxification, mitochondrial, and digestive enzyme genes was quantified by RT-qPCR. CYP6F1 expression was strongly associated with resistance in the highly resistant urban population, suggesting an important role in metabolic detoxification. In contrast, the susceptible rural population showed pronounced inducible expression of CYP6F1, mitochondrial genes (cytochrome b and COXI), chymotrypsin, and acetylcholinesterase following insecticide exposure, indicating a generalized stress response. These findings reveal population-specific physiological responses to deltamethrin and highlight the complex interplay between detoxification pathways, mitochondrial activity, and protease functions in shaping insecticide responses. The high resistance levels detected in urban populations underscore the need for continuous resistance monitoring and improved vector management strategies.
Dataset DOI: 10.5061/dryad.5mkkwh7mn
Description of the data and file structure
This dataset supports the study investigating population-specific molecular responses associated with differential susceptibility to the pyrethroid insecticide deltamethrin in Culex pipiens populations from Blida Province, Northern Algeria. Mosquito larvae were collected from three geographically distinct populations (two urban and one rural) and reared under standardized laboratory conditions to establish first-generation (F1) colonies.
Fourth-instar larvae were subjected to WHO-standard larval susceptibility bioassays to determine lethal concentrations (LC₂₅, LC₅₀, and LC₇₅) of deltamethrin for each population. Following 24-hour exposure, surviving larvae were collected for gene expression analyses. Total RNA was extracted from biological replicates, reverse transcribed into cDNA, and analyzed using quantitative real-time PCR (RT-qPCR). The expression of genes associated with insecticide detoxification (CYP6F1), target-site response (AChE), mitochondrial function (cytochrome b and COXI), and digestive physiology (chymotrypsin) was quantified using β-actin as the reference gene.
The dataset includes raw mortality data from insecticide bioassays, concentration–response data used for LC estimation, RT-qPCR Ct values, relative gene expression values calculated using the 2^-ΔΔCt method, and statistical outputs used to compare gene expression among mosquito populations and treatment concentrations. These data provide the basis for evaluating differences in deltamethrin susceptibility and the associated transcriptional responses among field populations of Culex pipiens.
Files and variables
File: Metadata_Bochra__2nd_MS.xlsx
Description: This Excel workbook contains all raw and processed data generated in this study. The data are organized into separate worksheets corresponding to the different analyses.
Worksheets
Sheet 1 – LC50
- Contains raw mortality data and dose–response data used for LC₅₀ estimation.
- Variables include mosquito population, deltamethrin concentration (ppm), total number of larvae tested, and number of dead larvae.
Sheet 2 – CYP6F1
- Contains RT-qPCR data and relative expression values for the CYP6F1 gene.
- Variables include population, treatment (Control, LC₂₅, LC₅₀, LC₇₅), biological replicate, technical replicate, gene expression (2^-ΔΔCt), and log2.
Sheet 3 – AChE
- Contains RT-qPCR data and relative expression values for the AChE gene.
- Variables are the same as those described for Sheet 2.
Sheet 4 – COXI
- Contains RT-qPCR data and relative expression values for the COXI gene.
- Variables are the same as those described for Sheet 2.
Sheet 5 – Cytochrome b
- Contains RT-qPCR data and relative expression values for the cytochrome b gene.
- Variables are the same as those described for Sheet 2.
Sheet 6 – Chymotrypsin
- Contains RT-qPCR data and relative expression values for the chymotrypsin gene.
- Variables are the same as those described for Sheet 2.
Abbreviations
- LC₂₅, LC₅₀, LC₇₅ = lethal concentrations causing 25%, 50%, and 75% mortality.
Missing values
Missing values are indicated as NA.
Code/software
The dataset is provided as a Microsoft Excel workbook (.xlsx), which can be viewed using Microsoft Excel (2016 or later), LibreOffice Calc (version 7.0 or later), or other spreadsheet software compatible with the XLSX format.
Statistical analyses were performed using R (version 4.4.0; R Core Team, 2024) in RStudio. Dose–response analyses and LC₅₀ estimation were conducted using the drc package. Gene expression analyses were performed using the ARTool, emmeans, and car packages. Data manipulation and visualization were carried out using the tidyverse suite of packages.
The workflow consisted of: (1) importing the raw bioassay and RT-qPCR data from the Excel workbook into R; (2) correcting mortality using Abbott's formula; (3) fitting three-parameter log-logistic dose–response models to estimate LC₂₅, LC₅₀, and LC₇₅ values; (4) calculating relative gene expression using the 2^-ΔΔCt method; (5) log₂-transforming gene expression data; (6) performing two-way ANOVA or aligned rank transformation (ART) analyses where appropriate; and (7) conducting Tukey-adjusted post hoc comparisons using estimated marginal means. No custom scripts are included with this data submission.