Juvenile hormone regulates the maturation of sexually dimorphic naïve ethanol olfactory preference in Drosophila melanogaster
Data files
Aug 14, 2025 version files 229.18 KB
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genotypeNEOPdata.csv
76.56 KB
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glmm_model_summaries_highlighted_p_value.xlsx
30.33 KB
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glmmfigure2.R
9.29 KB
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NEOP.PREC.csv
47.24 KB
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NEOPdatafig1no1.csv
61.42 KB
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README.md
4.34 KB
Abstract
We have identified a sexually dimorphic behavior in adult Drosophila melanogaster that varies depending on age, sex, and mating status. Our results suggest that the rewarding neuropeptide Corazonin (Crz), the transcription factor Apontic, and juvenile hormone (JH) signaling regulate naïve ethanol olfactory preference (NEOP) responses during early stages of adulthood. Pharmacological blockade of JH via precocene increases NEOP in females and males, which is phenocopied by the knockdown of JH receptors Met and Gce globally in the nervous system, as well as specifically in the mushroom body. This suggests a novel role of JH in dimorphic ethanol behaviors. Mating decreases NEOP in males, likely acting through rewarding pathways such as Neuropeptide F (NPF) and Crz. Our study suggests an early evolutionary emergence of hormonal mechanisms regulating ethanol-dependent behaviors, as Crz and JH share similarities with the vertebrate gonadotropin-releasing hormone (GnRH) and thyroid hormones, respectively. The results described here pave the way for future studies to further investigate the mechanisms by which a non-reproductive, yet sexually dimorphic behavior matures using Drosophila as a model. The key molecular players identified to regulate this dimorphic behavior are conserved among species, advancing our fundamental understanding of sexual dimorphism and brain maturation in numerous species.
The dataset consists of the following files: genotypeNEOPdata.csv, NEOP.PREC.csv, and NEOPdatafig1no1.csv contain data collected from each T-maze trial of ~10 flies.
Each fly had the option to choose the ethanol chamber, the control chamber, or neither (staying in the starting chamber). These data were tallied as Experimental Stimulus, Control Stimulus, and No response, respectively. "Batch" refers to the specific maze being recorded, but was nested within the date for analysis. Each file has different column headers to denote the manipulation being used for the specific experiment. For example, genotypeNEOPdata.csv only with the inins genotype, while NEOP.PREC.csv also contains "Prec," which is the precocene concentration that animals were treated within that trial.
Variable Key:
- Batch: An ID number for each test
- Date: The date on which that test was run
- Genotype: The genotype of all flies in the test
- Sex: The sex of all the flies used in the test
- MS: The mating status (MS) of all the flies used in the test
- Experimental Stimulus: The number of flies counted on the side of the maze that contained the ethanol solution after the test was complete
- Control Stimulus: The number of flies counted on the side of the maze that contained the control solution after the test was complete
- No response: The number of flies that did not leave the starting chamber during the test
- glmm_model_summaries_highlighted_p_value.xlsx contains the output for the generalized linear mixed model (GLMM) used to make statements about, significantDryadcts of our predictor variables denoted above. An R script was used to output these data, titled glmmfigure2.R, within the Dryad repository, with minor differences depending on the dataset. The output is structured like so:
figure 2A <----denotes the figure that this model was used for
Metric Value
1 AIC 1307.93169 <-- Akaike Information Criterion value used to compare the quality of generated models
2 BIC 1356.549 <-- Bayesian Information Criterion value also used to compare the quality of generated models.
3 Log-Likelihood -640.965846 <-----log of the likelihood function at its maximum, used to compare the quality of generated models.
4 Deviance 187.840944 <---related to log-likelihood
5 Residual DF 311 <----related to log-likelihood
Group Name Variance StdDev: Batch (Intercept) 0.83863226 0.91576867 <---measures of the random deviation effect impact on the dataset. The variance is the estimated variance of the random effect, with "StdDev" being the standard of this variance.
Term Estimate StdError Zvalue Pvalue: (Intercept) -0.42535232 0.22069759 -1.92730843 0.053941204 <----the statistics of the reference level (always the mated reference genotype). The Estimate is the model's estimated effect size for this term on the log-odds scale, along with its StdError, which is the standard error of that estimate. The Z value is calculated as such: Estimate/StdError. The P value is the probability of observing this effect if the true effect were an estimate of 0. The maximum and minimum P values are highlighted in yellow.
GenotypeNPF1 <-----example group for statistics involving genotypic manipulations of the reference mating status (mated). Essentially, a pairwise comparison between the background genotype and the experimental genotype. The P value here denotes the probability of observing this estimate if the true effect was that of the reference level.
MSVirgin <----- statistics denoting the difference between the mating statuses in the background genotype.
Genotype774_167/+:MSVirgin <------interaction statistics, which denote how the two predictor variables can have effects that depend on each other.
Key: (Intercept) refers to the reference group, which is always the mated genetic background.
MSVirgin: MS is the abbreviation used for "Mating Status," which can be mated or virgin. MSVirgin is the virgin group and is listed when the effect of mating status is being assessed.
Batch: refers to the specific maze number, which is nested within "date," used as a random effect
GenotypeX: Genotype effect being assessed in the model, where X is the genotype