In species where sociality and group cohesion are primarily determined by the maintenance of a reproductive division of labour and cooperative behaviours, the eusocial Damaraland mole-rat (Fukomys damarensis) presents a model which provides behavioural and endocrine distinctions between sex (males and females) and reproductive class (breeders and non-breeders). Although previous studies have demonstrated the endocrine aspects of reproductive suppression and behaviour in Damaraland mole-rats, they have focused on one hormone separately and on different conspecifics and samples across time. Unfortunately, this could introduce extrinsic biases when using these studies to compile complete hormonal profiles for comparisons. This study, therefore, set out to obtain a profile of the reproductive hormones from breeding and non-breeding male and female Damaraland mole-rats at a single point in time, from which circulating plasma prolactin and urinary progesterone, testosterone, and cortisol were measured. As expected, plasma prolactin and urinary cortisol did not differ between the breeders and non-breeders. However, breeders (both male and female) possessed increased urinary testosterone and progesterone concentrations compared to their non-breeding counterparts. These results, in conjunction with the variation in the expression of the respective hormonal receptors within the brains of breeders and non-breeders suggest that elevated testosterone and progesterone in breeders establish a neural dominance phenotype, which ultimately aids in controlling breeding activities. This study has emphasised the need for holistic, comprehensive profiling of reproductive endocrine systems.
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http://dx.doi.org/10.1016/j.ygcen.2022.114194 | DOI Listing |
Geroscience
December 2024
Department of Aging and Longevity Research, Kumamoto University, 2-2-1 Honjo, Chuo-Ku, Kumamoto, 860-0811, Japan.
The Damaraland mole-rat (DMR; Fukomys damarensis) is a long-lived (~ 20 years) Bathyergid rodent that diverged 26 million years ago from its close relative, the naked mole-rat (NMR). While the properties of NMR cultured fibroblasts have been extensively studied and have revealed several unusual features of this cancer-resistant, long-lived species, comparative DMR studies are extremely limited. We optimized conditions for successfully culturing primary DMR skin fibroblasts and also established immortalized DMR cells using simian virus 40 early region expression.
View Article and Find Full Text PDFBiol Lett
October 2024
Department of Zoology, University of Cambridge, Cambridge, UK.
Mating between closely related individuals can result in a reduction in offspring fitness, known as inbreeding depression. Here, we investigate whether breeding with close relatives affects the reproductive output of parents and the development of their offspring in Damaraland mole-rats (), a cooperatively breeding species where females avoid mating with familiar individuals. By cross-fostering litters of pups soon after birth, we were able to form breeding pairs from full siblings that were reared apart.
View Article and Find Full Text PDFProc Biol Sci
October 2024
Department of Zoology, University of Cambridge, Cambridge, UK.
Across taxa, breeding among close relatives is usually avoided because it incurs fitness costs to offspring. Incest is often averted through the dispersal of either sex from the natal area to breed. In some philopatric species, association among relatives extends into adulthood, and an ability to discriminate kin may be required for individuals to reduce inbreeding risk.
View Article and Find Full Text PDFJ Am Assoc Lab Anim Sci
November 2024
3Biologic Resources Laboratory, University of Illinois, Chicago, Illinois.
Mov Ecol
June 2024
School of Zoology, Faculty of Life Sciences, and the Steinhardt Museum of Natural History, Tel Aviv University, Tel Aviv, Israel.
The application of supervised machine learning methods to identify behavioural modes from inertial measurements of bio-loggers has become a standard tool in behavioural ecology. Several design choices can affect the accuracy of identifying the behavioural modes. One such choice is the inclusion or exclusion of segments consisting of more than a single behaviour (mixed segments) in the machine learning model training data.
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