Data from: The oviposition of unfertilized eggs depends on the presence of potential mates in a kissing bug
Data files
Dec 16, 2025 version files 14.57 KB
Abstract
In most species, females face the risk of losing their oocytes if they remain unmated for a prolonged period. However, it remains unclear whether they have developed mechanisms to prevent the loss of fertilizable eggs according to the chances of finding a mate. We predict that virgin females will lay a lower proportion of their produced eggs when they perceive the presence of a male conspecific. We tested this prediction in the kissing bug Rhodnius prolixus, comparing the oviposition of virgin females randomly exposed to the presence of a potential mate or isolation over 10 days. We found that isolated females laid three times as many eggs as females exposed to the presence of a male. The dissection of females showed that both groups produced similar numbers of developed eggs, suggesting that differences in oviposition are due to changes in egg retention, rather than on egg production. We discuss the possible benefits of egg retention in virgin females, and how this process may contribute to their reproductive decision-making.
Dataset DOI: 10.5061/dryad.4qrfj6qr4
GENERAL INFORMATION
1. Paper Citation
The oviposition of unfertilized eggs depends on the presence of potential mates in a kissing bug
2. Brief abstract
Virgin female kissing bugs avoid losing their unfertilized eggs when potential mates are present.
Differences in the oviposition dynamics over time were observed between females exposed to a physically inaccessible male and those kept in isolation.
Isolated females laid approximately three times more eggs than those exposed to a male.
The mechanisms underlying these results may be related to differential egg retention associated with female reproductive decision-making.
3. Originators
Franco Divito, Lorena Pompilio and Gabriel Manrique
4. Contact information
Franco Divito (francodivito92@gmail.com; Gabriel Manrique (gabo@bg.fcen.uba.ar)
Laboratorio de Fisiología de Insectos
Departamento de Biodiversidad y Biología Experimental
Facultad de Ciencias Exactas y Naturales
Universidad de Buenos Aires
Instituto de Biodiversidad y Biología Experimental y Aplicada, IBBEA, UBA-CONICET
Ciudad Universitaria, Pabellón II, C1428EHA Buenos Aires
ARGENTINA
Lorena Pompilio (lopompilio@yahoo.com.ar) Dra. Lorena Pompilio
Laboratorio de Ecología y Comportamiento Animal
Departamento de Ecología, Genética y Evolución
Facultad de Ciencias Exactas y Naturales
Universidad de Buenos Aires
Instituto de Ecología, Genética y Evolución de Buenos Aires –IEGEBA, UBA-CONICET
Ciudad Universitaria, Pabellón II
Buenos Aires (C1428EHA)
ARGENTINA
5. Date of data collection
From 4/4/2023 to 5/8/2024
6. Geographic location(s) of data collection
All experiments were performed in Ciudad Universitaria, Buenos Aires (coordinates: 34°32′29″S 58°26′35″W).
7. Information about funding sources that supported the collection and curation of the
data
Agencia Nacional de Promoción Científica y Tecnológica (ANPCyT)(grant: PICT 2018-02634)
Universidad de Buenos Aires (grants UBACyT-20020170100571BA/ UBACyT-20020220100108BA)
Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)(grants:PIP 11220130100550CO/ PIP11220220100530CO)
ACCESS INFORMATION
1. Licenses/restrictions placed on the data
No licenses nor restrictions were placed on the data.
2. Data derived from other sources
No data used in this work was derived from other sources.
DATA FILES AND VARIABLES
All .csv files detailed here are semi-colon delimited with a comma decimal.
1. Laid_over_produced_eggs_Divito_et_al__2025.csv
This file contains the raw data used to calculate the percentage of laid over total produced eggs for each female.
The table shows the following variables:
- No_Assay: Number of assay performed (1 to 44).
- Treatment: Treatment conducted in a particular assay (M- or M+).
- M-: Absence of a potential mate.
- M+: Presence of a potential mate.
- Female_Weight: Weight of the female in milligrams (mg).
- Male_Weight: Weight of the male in milligrams (mg).
- Retained_Eggs: Number of retained eggs.
- Laid_Eggs: Number of laid eggs.
- Produced_Eggs: Number of produced eggs.
- Laid_Over_Produced_Eggs: Proportion of laid over produced eggs (conducted to obtain the percentage of laid over produced eggs).
2. Laid_eggs_per_day_interval_Divito_et_al__2025.csv
This file contains the raw data of the count of laid eggs for each female at every day interval.
The table shows the following variables:
- No_Assay: Number of assay performed (1 to 44).
- Treatment: Treatment conducted in a particular assay (M- or M+).
- M-: Absence of a potential mate.
- M+: Presence of a potential mate.
- Day: Day of the oviposition phase when eggs were counted.
- Day_Interval: Temporal intervals in which the daily oviposition data were grouped.
- Laid_Eggs: Number of laid eggs during each day interval.
3. Laid_eggs_per_day_Divito_et_al__2025.csv
This file contains the raw data of the count of laid eggs for each female at every day.
This data was used to determine the day intervals. The table shows the following variables:
- No_Assay: Number of assay performed (1 to 44).
- Treatment: Treatment conducted in a particular assay (M- or M+).
- M-: Absence of a potential mate.
- M+: Presence of a potential mate.
- Day: Day of the oviposition phase when eggs were counted.
- Laid_Eggs: Number of laid eggs during each day interval.
SOFTWARE VERSIONS
R Statistical Software (v4.2.0, R Core Team, 2022)
loaded packages:
- package: DHARMa (v0.4.7, Hartig, 2024)
REFERENCES
Hartig F. 2024. DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. R package version 0.4.7. URL https://CRAN.R-project.org/package=DHARMa.
R Core Team (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
Treatments
Virgin females were individually placed in one of the compartments of the experimental arena and then randomly assigned to one of the following treatments: M+, in which a male was present in the other compartment of the arena (n = 22); and M-, in which the other compartment was empty (n = 22). The transparent acrylic barrier separating the compartments allowed the female to perceive the male through visual and olfactory cues, although physical contact between the insects was prevented .
Data analysis
To analyze differences in the probability of laying of produced eggs, we used a generalized linear mixed model (GLMM) with a logit link and a binomial distribution, with the treatment (M+/M-) as the explanatory variable and the number of laid and retained eggs for each female as the dependent variable. As overdispersion in the data was detected using the DHARMa R package (Hartig 2024), we included observation-level random effects (OLRE) to account for it. The model was parameterized in R using the cbind() function, grouping the number of laid (successes) and retained (failures) eggs.
For the study of the oviposition dynamics, differences in the number of laid eggs over time within and between treatments were analyzed. Daily oviposition data were grouped into four temporal intervals (days 1, 2–4, 5–7, and 8–10). We used a GLMM with a repeated-measures design (RMD), with a log link and a Poisson distribution, with the treatment (M+/M-) and the oviposition days (1, 2-4, 5-7 and 8-10) as explanatory variables, the female as a random (intercept) variable and the number of laid eggs as a dependent variable. When the interaction between the main factors (treatment and time) was significant in the GLMM with repeated measures design (RMD), we analyzed the simple effects separately. Post-hoc Tukey’s tests were then used to compare treatments within each time interval and time intervals within each treatment that showed significant effects.
Differences in the total number of eggs produced between treatments were analyzed using a GLM with a log link and a negative binomial distribution, with treatment (M+/M-) as the explanatory variable and the total eggs produced as the response variable.
Additionally, to ascertain that females in both treatments had similar characteristics, we recorded their weight at the beginning of the experiment. No significant differences were found for the females’ weight between the treatments .The data were analyzed by means of parametric statistics after verification of the assumptions, i.e., normal distribution of residuals (Shapiro–Wilk’s test) and homogeneity of variances (Levene’s test). The distribution of female weights met the assumptions required for ANOVA. The weights of males in the M+ treatment followed a normal distribution.