Good things come to those who mate: analysis of the mating behaviour in the menstruating rodent, Acomys cahirinus

Abstract Background The Egyptian spiny mouse (Acomys cahirinus) is the only known rodent to exhibit true, human-like menstruation and postpartum ovulation, and is an important new model for reproductive studies. Spiny mice do not produce a visible copulatory plug, and calculation of gestational age is therefore restricted by the need to use mated postpartum dams. The current inefficient method of monitoring until parturition to provide a subsequent estimate of gestational age increases study duration and costs. This study addressed this issue by comparing the mating behaviour of spiny mice across the menstrual cycle and proposes a more accurate method for staging and pairing animals that provides reliable estimates of gestational age. In experiment 1, mating behaviour was recorded overnight to collect data on mounting, intromission, and ejaculation (n = 5 pairs per stage) in spiny mice paired at menses and at early and late follicular and luteal phases of the menstrual cycle. In experiment 2, female spiny mice were paired at the follicular or luteal phases of the menstrual cycle to determine any effect on the pairing-birth interval (n = 10 pairs). Results We report a broad mating window of ~ 3 days during the follicular phase and early luteal phase of spiny mice. Males displayed a discrete ‘foot twitch’ behaviour during intromission and a brief copulatory lock during ejaculation. Litters were delivered after 40–43 days if pairing occurred during the mating window, compared with 46–48 days for spiny mice paired in the late luteal phase. When pairing occurred during the late luteal phase or menses no mating activity was observed during the recording period. Conclusion This study clearly demonstrates an effect of the menstrual cycle on mating behaviour and pregnancy in the spiny mouse and provides a reliable and more effective protocol for estimating gestational age without the need for postpartum dams.

Abstract licence: CC BY-NC-ND

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.