Since the pioneering work by Parker, 1970, postcopulatory sexual selection has been recognized as an important driving force that shapes male sperm and female reproductive track characteristics. Post-copulatory sperm competition over gamete and cryptic female choice are equivalent to male-male competition and female choice in the pre-copulatory sexual selection. Sperm competition occurs when spermatozoa from more than one male coincide within the female reproductive tract in a time window where they have a chance to fertilize the same egg (Parker, 1970). The evolutionary consequences of the sperm competition for the male traits, including baculum complexity, sperm shape and behavior, are demonstrated in a wide range of animals from insects to mammals (Anderson et al., 2005; Lange et al., 2013; André et al., 2020). Such male adaptations secure sperm delivery to the female reproductive tract and influence the sequential mating of the already-mated female with other males. Cryptic female choice is a more complicated process to define as it is achieved at the various stages of the post-mating fertilization process that also occurs inside the female reproductive tract. However, post-copulatory cryptic female choice is evident where a female can exert an influence on ejaculates or even fertilized eggs that can influence the male’s reproductive success (Eberhard, 1996; Firman et al., 2017; Roberts et al., 2012).

Postcopulatory sexual selection results in the co-evolution of the male and female traits that impact the reproductive strategies of the opposite sex (Eberhard and Lehmann, 2019; Greff and Parker, 2000). For example, copulatory plugs formed by male semen hinder the sequential mating of the female with a second male and diminish the reproductive outcome of the second male (Mangels et al., 2016; Sutter and Lindholm, 2016). Females, on the other hand, by removing the copulatory plug, can counteract the male strategy (Koprowski, 1992). When fluid in female reproductive tract is spermicidal, male seminal fluid neutralises the spermicidal medium and secures sperm survival inside the female reproductive tract (Holman and Snook, 2008; Holman and Snook, 2006).

Among mammals, rodent species exhibit various sperm morphological and behavioral characteristics. A notable morphological feature of murine sperm is the apical hook resulting in an asymmetrical falciform head shape that is found in most of the murine rodents (Breed, 2004; Roldan et al., 1992). The functional significance of the sperm hook that causes head asymmetry is still under debate in the field of mouse reproductive ecology. Currently, two main hypotheses attempt to explain the function of the sperm hook. One is that the sperm hook plays a crucial role in sperm competition by aiding sperm linkage (sperm train formation) that enhances straighter and faster sperm forward progression – the sperm cooperation hypothesis (Fisher and Hoekstra, 2010; Moore et al., 2002). The other hypothesis is that the sperm hook facilitates sperm-epithelium interactions in the female reproductive tract, playing a significant role in sperm migration – the migration hypothesis (Smith and Yanagimachi, 1990; Firman and Simmons, 2009). The sperm cooperation hypothesis is supported by the pioneering discovery of sperm linkage known as sperm trains (Moore et al., 2002) and suggests that sperm trains facilitate faster or straighter sperm swimming (Fisher and Hoekstra, 2010; Moore et al., 2002). However, other studies could not find supporting evidence of sperm cooperation by the sperm train or morphological changes in sperm hooks concerning the degree of sperm competition (Firman and Simmons, 2009; Hook et al., 2021). These researchers rather suggest that the sperm hook plays a crucial role in sperm migration by interacting with epithelia in the female reproductive tract.

Since thick muscle layers comprise the outer part of the rodent female reproductive tract, direct observation of spermatozoa inside the female reproductive tract is a challenging feat. Therefore, previous studies focused on the oviduct where muscle layers are thin and transparent, using brightfield, fluorescence or confocal microscopy (Ishikawa et al., 2016; Qu et al., 2021; Suarez, 1987). In this study, we developed an ex-vivo observation system based on a custom-built two-photon microscope (Figure 1—figure supplement 1). This system enables the observation of spermatozoa and their behavior inside the live female reproductive tract. While two-photon microscopy is currently the method of choice for live imaging of deep tissues (Helmchen and Denk, 2005; Benninger and Piston, 2013; Keller, 2013), it has seldom been used for studying animal reproductive ecology. Here, we demonstrate high-resolution deep-tissue imaging that allows us to observe and track sperm movement inside the female reproductive tract, including the uterus, to realise real-time tracking of spermatozoa and their migration.

Using this technology, we report newly discovered sperm behavior and aggregation patterns that suggest various roles of the sperm hook in sperm migration inside the female reproductive tract. Based on live imaging of sperm dynamics inside the live female reproductive tract, we provide new observations and insights that suggest functions of the sperm hook that help sperm migration and cooperation. With our new observation system and results, we hope to contribute to the field of postcopulatory sexual selection in rodents by advancing methodological progress and stimulating discussion and future research on the function of sperm hook in murine rodents.

To observe mouse sperm behavior in the female reproductive tract, we mated wild-type Mus musculus (C57BL/6) females with transgenic male mice (Supplementary file 1a, b) that express DsRed at the sperm mid-piece (mitochondria) and eGFP in the sperm acrosome (Hasuwa et al., 2010). The female mice were euthanized between 0.5- and 3 hr post-mating, and their reproductive tract along with the copulatory plug was excised and transferred to a sterilized Petri dish. We then conducted ex-vivo imaging of the live reproductive tract using our two-photon microscope (Figure 1—figure supplement 1). Figure 1A is a diagram of the female reproductive tract that labels the name of each part of the tract. All observations were typically completed within 3 hr and did not exceed 6 hr post-euthanasia. Despite this observation period being longer than recommended for conventional rat transplantation surgery (Díaz-García et al., 2013), we noted live uterine movements throughout the entire observation period. When samples were transferred to incubators preheated to 37°C with 5% CO₂ following observation, uterine movement persisted even 24 hr post-excision. We used Fiji (Schindelin et al., 2012) and R 4.3.3 (R Development Core Team, 2024) for image processing and statistical analysis.

Figure 1 with 4 supplements see all

Download asset Open asset

Sperm anchoring and migration kinetics in the uterus

We observed that the sperm head was attaching to the epithelium of the CT and uterus (Figure 1—video 3A, B) when spermatozoa reached the CT. The sperm hook was affixed to the epithelium, thereby securing the spermatozoa on the epithelia. We defined this securing of the spermatozoa on the epithelia by the sperm hook as an anchor-like function of the hook (Figure 1—video 3A, B). This anchoring also helped prevent spermatozoa from being swept away by mucosal flow (Figure 1E; Figure 1—video 3B). When spermatozoa are attached to the CT and squeezed through other spermatozoa by hooking, the apical hook always faces the epithelium (Figure 1F; Figure 1—video 3A). Once spermatozoa successfully clung onto the CT, anchoring to the epithelia prevented them from being pushed out by competing spermatozoa or from being swept away by fluid flow (Figure 1—video 3B).

To compare sperm migration kinetics during sperm swimming relative to their distance from the uterine wall, we tracked sperm migration trajectories by employing the TrackMate plugin in ImageJ (Ershov et al., 2022; Tinevez et al., 2017). In total, we were able to track 694 sperm trajectories. After successful tracking using the customized tracking option in TrackMate, we computed various sperm kinetic parameters. These parameters included the curvilinear velocity (VCL), straight-line velocity (VSL), and linearity of forward progression (LIN), which are commonly used in computer-assisted sperm analysis, CASA (Amann and Waberski, 2014). Briefly, VCL was calculated as the total distance travelled divided by total travel time, VSL as the distance between initial and final positions of the sperm trajectory divided by total travel time, and LIN as the ratio of VSL to VCL, which can range from 0 to 100%, with 100% representing a perfectly straight line. We also introduced a new kinetic parameter called straight line-to-sideward movement ratio (SWR), defined as track displacement of a sperm trajectory divided by maximum sideward movement distance. Refer to Figure 2—figure supplement 1 for our definition of the uterus wall and a schematic description of the sperm migration kinetic parameters, as well as Methods for more details.

Our sperm tracking analysis revealed that spermatozoa located close to the uterine wall moved faster, exhibiting higher VCL and VSL (Figure 2A; Supplementary file 1c; Figure 1—video 1B, C). However, LIN and SWR did not significantly vary depending on the sperm’s distance from the uterus wall (Figure 2B). In contrast to the non-significant changes in LIN and SWR relative to the distance from the uterine wall, when spermatozoa swam parallel to the wall, they not only moved faster (higher VCL and VSL; Figure 2A), but also followed a straighter path (higher LIN and SWR; Figure 2B). Given that the internal fluid flow around the uterine wall is slower (Zaferani et al., 2019), and considering the hydrodynamic factors that attract spermatozoa to the wall when swimming near it (Alvarez et al., 2014; Elgeti et al., 2010), migration along the wall would be an efficient strategy for sperm movement within the uterus. We also examined the impact of both individual males (coded as ‘Male ID’) and females (coded as ‘Date’) on the sperm kinetic parameters in all models by visualizing the effects of these two random variables (Figure 2—figure supplement 2). We confirmed that the effects of the two random variables were consistent across all significant models, indicating the validity of our model estimations.

Figure 2 with 2 supplements see all

Download asset Open asset

Structure of UTJ and sperm behavior at the entrance of intramural UTJ (CT)

Upon sacrificing and optical clearing the tissue, we confirmed that the entrance to the intramural UTJ (CT) in the uterus consists of nearly closed narrow gaps between mucosal folds (Figure 3A). These narrow gaps extended to about 100 µm deeper from the entrance (Figure 3—video 1A, B), and only a few spermatozoa could pass through a gap at a time (Figure 3A; Figure 3—video 1C). We were not able to find evidence of passive sperm carriage, such as upsuck-like sperm carriage (Baker and Bellis, 1993), caused by peristaltic movement from the uterus into the UTJ in real-time live images (Figure 3—video 2A). Therefore, we concluded that fluid flow induced by uterine and oviduct contraction is not a major driving force for sperm entry to the UTJ through the CT.

Figure 3 with 3 supplements see all

Download asset Open asset

This conclusion raises a question about how spermatozoa enter the UTJ through the CT if the UTJ entrance is nearly closed. We found head-directional sliding of spermatozoa in the almost closed inter-luminal spaces between the uterus and intramural UTJ (Figure 3—video 2B). We did not observe any sliding of spermatozoa that were directs to the tail direction. This one-directional head-forward sliding in a very narrow inter-luminal space suggests the role of the sperm hook as an anchor that prevents backwards slipping by the squeezing movement from the contraction of the uterus. Such one-directional sliding is also a plausible way of sperm migration from the uterus to UTJ through the narrow gap at the CT. We also observed that when muscle contraction and relaxation occurred at the uterus and oviduct, the surfaces of two confronting mucosal folds in intramural UTJ slid against each other in opposite directions (Figure 3B; Figure 3—video 2B). Such an opposite directional movement of mucosal folds, for example, will occur when the uterus bends to the left due to muscle contraction on its left side and relaxation of its right side (Figure 3—figure supplement 1). As shown in Figure 3—video 2, the opposite movement of mucosal folds makes space between mucosal folds at the CT, providing an opportunity for nearby attached spermatozoa to enter the intramural UTJ (Figure 3—figure supplement 1). Although the application of further experimental approaches will be necessary, occasional fluctuations in the size of the luminal space between mucosal folds, caused by peristaltic movements, together with the head-directional sliding of the spermatozoa, may provide an opportunity for spermatozoa to pass through the CT.

We also observed unidirectional sperm clustering as a result of spontaneous sperm re-arrangement during sperm beating along the uterine wall (Figure 4A and Figure 4—video 1A, B). Such unidirectional sperm clustering and their successive beating resulted in synchronized sperm beating on some occasions (sperm self-organising behavior). We also found such self-organized sperm behavior on a large scale at the CT in which most of the clustered spermatozoa at the entrance of the intramural UTJ (CT) exhibited synchronized beating (Figure 4B; Figure 4—video 2). The synchronized sperm beating was observed to generate fluid flows strong enough to prevent other spermatozoa from attaching to the CT or directly pushing out other spermatozoa, thereby preventing other spermatozoa from entering the UTJ (Figure 4—video 1; S7).

Figure 4 with 2 supplements see all

Download asset Open asset

Sperm linkage and their migration kinetics

Unlike the sperm trains found in wood mice (Apodemus sylvaticus; Moore et al., 2002) and deer mice (Peromyscus maniculatus; Fisher and Hoekstra, 2010), most of the spermatozoa in this study did not form functional sperm trains (linked spermatozoa) (Figure 5A; Figure 5—video 1). Active sperm linkage or clusters were indeed observed but were rare (only three identifiable cases during over 100 hr of imaging). For the house mouse, the observed sperm trains did not move faster or slower than unlinked single spermatozoa (Figure 5B; Figure 5—video 1). Their VCL, VSL, and LIN were not faster nor higher than those of unlinked single spermatozoa as shown in Figure 5B. Although their SWR may be higher than that of unlinked single spermatozoa, due to the rare number of observed events, further experiments will be necessary to clarify whether the sperm train formation is advantageous in the house mouse.

Figure 5 with 1 supplement see all

Download asset Open asset

Sperm migration and accumulation in the oviduct

After entering the UTJ, spermatozoa continued migration through the narrow UTJ lumen. In the UTJ, spermatozoa interact with epithelia with their hook and penetrate their thin head into a narrow space (Figure 6—video 1A). Contraction of the UTJ reduced the width of the UTJ lumen and prevented sperm migration (Figure 6—video 1B). However, some spermatozoa could pass through the narrow luminal space by putting their thin hook (Figure 6A and B; Figure 6—video 1B). During UTJ lumen contraction, both swimming and beating of spermatozoa therein were physically suppressed. When the UTJ lumen dilates, the suppressed spermatozoa started beating and swimming again (Figure 6C; Figure 6—video 1B). We also found sperm accumulations in the oviduct, including UTJ and isthmus (Figure 6D). However, as these sperm accumulations were arranged irregularly and consisted of spermatozoa that were mostly acrosome reacted and inactive, they were considered inactive entangled spermatozoa rather than actively linked spermatozoa (or sperm trains). These entangled spermatozoa filled the narrow oviductal lumen, creating an obstruction for the migration of other spermatozoa (Figure 6—video 1C). If sperm hook facilitates such entanglement of inactive spermatozoa in the UTJ and isthmus, it can play a role in sperm competition by obstructing migration of the other spermatozoa including those from a second male.

Figure 6 with 2 supplements see all

Download asset Open asset

Sperm beating rates of the epithelia-attached spermatozoa were observed to change over time according to the changes in widths of the UTJ lumen (Figure 6—video 2). Although such a change in beating rates may simply reflect luminal flow speed or luminal width related to physical space for beating, it may also assist in attaching spermatozoa to the epithelium by providing propulsive forces (Kantsler et al., 2014). Fluid flow in the UTJ and isthmus can damage unattached spermatozoa, particularly when they get entangled with inactive entangled spermatozoa that are moving back and forth by the flow (Figure 6—video 1C). If such beating prevents epithelium-attached spermatozoa from being swept away by the flow, sperm beating corresponding to the fluid flow will be advantageous. The oviductal fluid gradually flows upward while continuously repeating back-and-forth directional changes and such flow is assumed to aid sperm migration from UTJ to ampulla (Hino and Yanagimachi, 2019). However, given our observation of the resistant (anchoring) behavior of spermatozoa to the flow in the UTJ, passive sperm transfer may not always be beneficial for healthy spermatozoa. Additionally, such passive transfer can cause physical damage to the spermatozoa by the collision with other entangled spermatozoa or epithelia of the narrow lumen. Further experiments will be necessary to clarify the role of the rapid upward flow in the oviduct in the fertilization process in mice.

Our real-time deep tissue imaging enabled by two-photon microscopy shows that the mouse sperm hook (i) facilitates sperm interaction with the epithelium for better navigation and (ii) provides an anchor-like role that assists the attachment of sperm to the epithelium. These results suggest that the sperm hook in house mice functions to facilitate sperm migration by interacting with the female reproductive tract (Firman and Simmons, 2009; Suarez, 1987; Tourmente et al., 2016). We also showed that when spermatozoa swim along the uterine wall, their apical hook interacts with the epithelia and determines sperm travelling direction upon encountering uterine epithelium. This finding implies that the sperm hook functions as a pivot when spermatozoa reach the uterine epithelium, and help spermatozoa migrate along the uterine wall by assisting in pro-wall-hook sperm orientation. Additionally, the sperm hook plays an important role in resisting endogenous fluid flow in the female reproductive tract by providing an anchor-like function. We did not observe a linkage of spermatozoa (sperm trains) that enables faster and straighter swimming of the sperm train in the uterus or oviduct. Instead, we found instances of the entanglement of inactive spermatozoa in the oviduct. Such aggregates of inactive spermatozoa appear to obstruct the migration of other spermatozoa. However, the role that these entangled spermatozoa play in sperm competition within the oviduct is a subject that necessitates further investigation.

Previous studies using various murine rodents suggest that acquiring the ability to form sperm train is a relatively rare evolutionary event in this taxon (Tourmente et al., 2016; Varea-Sánchez et al., 2016). Instead of finding evidence that the sperm hook aids in sperm train formation, those studies showed that variations in the length of the sperm hook, and asymmetry of sperm head influenced by the sperm hook are two important variables that reflect the degree of the sperm competition in murine rodents. One study even suggested that the sperm train formation (sperm linkage) is independent of the existence of sperm hook (Tourmente et al., 2016). Therefore, it is questionable whether acquiring the sperm hook in the murine rodents has evolved in general for a better sperm linkage. In line with the previous studies, our current study also showed that sperm hook plays a pivotal role in sperm-epithelium interactions by aiding sperm attachment to the uterine and oviductal epithelium and influencing sperm orientation during migration inside the female reproductive tract (Figure 1E and F; Figure 1—video 3A, B). Such a role of the sperm hook suggests that the hook facilitates interactions between sperm and epithelia of the female reproductive tract and supports the migration hypothesis.

As we did not observe any passive sperm transfer by the internal fluid flow from the uterus to intramural UTJ through the CT, it is puzzling how spermatozoa enter the intramural UTJ. Although we proposed a hypothetical model of sperm passage through the CT in which the sperm hook plays an important role by providing an anchor-like role that prevents backward movement but allows head-forward sliding, further investigation with new experimental and observational tools will be necessary. Nevertheless, our findings suggest that the CT is a key female anatomical structure that controls sperm entry to the UTJ and influences sperm competition. If sperm passage through the CT is too easy, associated risks such as polyspermy or pathogen transmission that incur fitness costs for females also increase (Firman and Simmons, 2013; Mahabir et al., 2008). Therefore, the number of sperm passing through the CT should be balanced by the conflict between the two sexes depending on species-specific mating systems and the degree of promiscuity. This conflict then gives rise to an evolutionary arms race, with the male’s sperm fertilization ability on one side, which includes aspects such as sperm swimming speed, and the female’s sperm selection process on the other, which encompasses elements like physio-chemical barriers in the female reproductive tract (Firman et al., 2017; Lüpold and Pitnick, 2018; Simmons and Wedell, 2020). Therefore, species variations in the length of the sperm hook and head asymmetry in rodents suggested in the previous studies (Tourmente et al., 2016; Varea-Sánchez et al., 2016) will also reflect the mechanical and structural characteristics of the CT and lumen in the intramural UTJ.

In the current study, we could not confirm evidence of sperm cooperation via sperm train formation that aids faster sperm swimming. Instead, we discovered a new form of potential sperm cooperation – synchronized sperm beating that resulted from spontaneous unidirectional sperm clustering. Based on these observations, we propose that the asymmetry of the mouse sperm head with an apical hook plays a crucial role in synchronized sperm beating (sperm cooperation) by facilitating unidirectional sperm re-arrangement at the uterine wall. The asymmetrical head shape in the house mouse, therefore, may have evolved not only to facilitate sperm migration but also to facilitate such sperm self-organized behaviors including unidirectional clustering and following beating synchrony. Under this scenario, sperm cooperation in house mice is not only mediated by sperm train formation as in some rodent species (Fisher and Hoekstra, 2010; Moore et al., 2002), but mediated by the synchronized sperm beating that obstructs migration of other spermatozoa in the uterus. Unidirectional sperm clustering and its potential role in sperm migration were also suggested in a previous study using fixed and tissue-cleared samples with in-vitro live sperm analysis (Qu et al., 2021). We could not find any supporting evidence that such clustering helps sperm passage through the CT. However, our observations regarding self-organized sperm behavior provide insights into the evolution of the asymmetrical structure of the sperm head in rodent species. These findings present an opportunity to reconcile two hypotheses: the cooperation hypothesis (Fisher and Hoekstra, 2010; Immler et al., 2007; Moore et al., 2002) and the migration hypothesis (Firman and Simmons, 2009; Smith and Yanagimachi, 1990).

The evolution of sperm characteristics, including the sperm hook, is a complex process influenced by several factors. For instance, sperm competition between ejaculates is a significant driving force influencing sperm head morphology and behavior in rodents (Fisher et al., 2014; Immler et al., 2007; Tourmente et al., 2016; Varea-Sánchez et al., 2016). Cryptic female choice also plays a crucial role in the evolution of sperm head shape and sperm kinetic characteristics (Birkhead, 1998; Eberhard and Lehmann, 2019; Firman et al., 2017). Further investigation of sperm behavior inside the female reproductive tract or tissue mimicking microfluidic devices with real-time deep tissue imaging as in the current study, will provide valuable opportunities for a more comprehensive examination of both sperm-sperm and sperm-epithelium interactions in the female reproductive tract. While we have focused on observing sperm interactions for only naturally healthy mice in this study, future works employing specifically targeted genetically modified knockout animal models will further elucidate and confirm the exact genetic and functional mechanisms that guide these interactions. This will help us better understand not only sperm competition and cryptic female choice in mice, but also those in other animals, including humans. While current assessments of sperm health generally involve measuring sperm count, movement, and shape, the current study suggests that analysing interactions between spermatozoa and the female reproductive tract is important and warrants further exploration. Given the significance of sperm health for fertility, this work not only highlights the importance of interactions between male sperm and female reproductive tract in successful migration, but also opens new avenues for understanding different causes of infertility and possible targets for treatment.

Raw data on sperm trajectories in the female reproductive track are available at figshare. Custom codes for sperm tracking data analysis written with Matlab (version R2019b) are available at GitHub (copy archived at Jeong, 2023).

1. 1. Ryu H
   2. Nam K
   3. Lee BE
   4. Jeong Y
   5. Lee S
   6. Kim J
   7. Hyun YM
   8. Kim JI
   9. Park JH

   (2024) figshare

   Data from: Mouse sperm hook facilitates sperm anchoring and probing for successful migration.

   https://doi.org/10.6084/m9.figshare.22878230

1. 1. Alvarez L
   2. Friedrich BM
   3. Gompper G
   4. Kaupp UB

   (2014) The computational sperm cell

   Trends in Cell Biology 24:198–207.

   https://doi.org/10.1016/j.tcb.2013.10.004

   • PubMed
   • Google Scholar
2. 1. Amann RP
   2. Waberski D

   (2014) Computer-assisted sperm analysis (CASA): capabilities and potential developments

   Theriogenology 81:5–17.

   https://doi.org/10.1016/j.theriogenology.2013.09.004

   • PubMed
   • Google Scholar
3. 1. Anderson MJ
   2. Nyholt J
   3. Dixson AF

   (2005) Sperm competition and the evolution of sperm midpiece volume in mammals

   Journal of Zoology 267:135–142.

   https://doi.org/10.1017/S0952836905007284

   • Google Scholar
4. 1. André GI
   2. Firman RC
   3. Simmons LW

   (2020) Baculum shape and paternity success in house mice: evidence for genital coevolution

   Philosophical Transactions of the Royal Society B 375:20200150.

   https://doi.org/10.1098/rstb.2020.0150

   • Google Scholar
5. 1. Baker RR
   2. Bellis MA

   (1993) Human sperm competition: ejaculate manipulation by females and a function for the female orgasm

   Animal Behaviour 46:887–909.

   https://doi.org/10.1006/anbe.1993.1272

   • Google Scholar
6. 1. Benninger RKP
   2. Piston DW

   (2013) Two-photon excitation microscopy for the study of living cells and tissues

   Current Protocols in Cell Biology Chapter 4:4.

   https://doi.org/10.1002/0471143030.cb0411s59

   • PubMed
   • Google Scholar
7. 1. Birkhead TR

   (1998) Cryptic female choice: Criteria for establishing female sperm choice

   Evolution; International Journal of Organic Evolution 52:1212–1218.

   https://doi.org/10.1111/j.1558-5646.1998.tb01848.x

   • PubMed
   • Google Scholar
8. 1. Breed WG

   (2004) The spermatozoon of Eurasian murine rodents: Its morphological diversity and evolution

   Journal of Morphology 261:52–69.

   https://doi.org/10.1002/jmor.10228

   • PubMed
   • Google Scholar
9. 1. Byers SL
   2. Wiles MV
   3. Dunn SL
   4. Taft RA

   (2012) Mouse estrous cycle identification tool and images

   PLOS ONE 7:e35538.

   https://doi.org/10.1371/journal.pone.0035538

   • PubMed
   • Google Scholar
10. 1. Dana H
    2. Novak O
    3. Guardado-Montesino M
    4. Fransen JW
    5. Hu A
    6. Borghuis BG
    7. Guo C
    8. Kim DS
    9. Svoboda K

    (2018) Thy1 transgenic mice expressing the red fluorescent calcium indicator jRGECO1a for neuronal population imaging in vivo

    PLOS ONE 13:e0205444.

    https://doi.org/10.1371/journal.pone.0205444

    • PubMed
    • Google Scholar
11. 1. Díaz-García C
    2. Akhi SN
    3. Martínez-Varea A
    4. Brännström M

    (2013) The effect of warm ischemia at uterus transplantation in a rat model

    Acta Obstetricia et Gynecologica Scandinavica 92:152–159.

    https://doi.org/10.1111/aogs.12027

    • PubMed
    • Google Scholar
12. Book

    1. Eberhard WG

    (1996) Female Control: Sexual Selection by Cryptic Female Choice

    Princeton University Press.

    https://doi.org/10.2307/j.ctvs32rx1

    • Google Scholar
13. 1. Eberhard WG
    2. Lehmann GUC

    (2019) Demonstrating sexual selection by cryptic female choice on male genitalia: What is enough?

    Evolution; International Journal of Organic Evolution 73:2415–2435.

    https://doi.org/10.1111/evo.13863

    • PubMed
    • Google Scholar
14. 1. Elgeti J
    2. Kaupp UB
    3. Gompper G

    (2010) Hydrodynamics of sperm cells near surfaces

    Biophysical Journal 99:1018–1026.

    https://doi.org/10.1016/j.bpj.2010.05.015

    • PubMed
    • Google Scholar
15. 1. Ershov D
    2. Phan MS
    3. Pylvänäinen JW
    4. Rigaud SU
    5. Le Blanc L
    6. Charles-Orszag A
    7. Conway JRW
    8. Laine RF
    9. Roy NH
    10. Bonazzi D
    11. Duménil G
    12. Jacquemet G
    13. Tinevez JY

    (2022) TrackMate 7: integrating state-of-the-art segmentation algorithms into tracking pipelines

    Nature Methods 19:829–832.

    https://doi.org/10.1038/s41592-022-01507-1

    • PubMed
    • Google Scholar
16. 1. Firman RC
    2. Simmons LW

    (2009) Sperm competition and the evolution of the sperm hook in house mice

    Journal of Evolutionary Biology 22:2505–2511.

    https://doi.org/10.1111/j.1420-9101.2009.01867.x

    • PubMed
    • Google Scholar
17. 1. Firman RC
    2. Simmons LW

    (2013) Sperm competition risk generates phenotypic plasticity in ovum fertilizability

    Proceedings. Biological Sciences 280:20132097.

    https://doi.org/10.1098/rspb.2013.2097

    • PubMed
    • Google Scholar
18. 1. Firman RC
    2. Gasparini C
    3. Manier MK
    4. Pizzari T

    (2017) Postmating female control: 20 years of cryptic female choice

    Trends in Ecology & Evolution 32:368–382.

    https://doi.org/10.1016/j.tree.2017.02.010

    • PubMed
    • Google Scholar
19. 1. Fisher HS
    2. Hoekstra HE

    (2010) Competition drives cooperation among closely related sperm of deer mice

    Nature 463:801–803.

    https://doi.org/10.1038/nature08736

    • PubMed
    • Google Scholar
20. 1. Fisher HS
    2. Giomi L
    3. Hoekstra HE
    4. Mahadevan L

    (2014) The dynamics of sperm cooperation in a competitive environment

    Proceedings. Biological Sciences 281:20140296.

    https://doi.org/10.1098/rspb.2014.0296

    • PubMed
    • Google Scholar
21. 1. Greff JM
    2. Parker GA

    (2000) Spermicide by females: what should males do?

    Proceedings of the Royal Society of London. Series B 267:1759–1763.

    https://doi.org/10.1098/rspb.2000.1207

    • Google Scholar
22. 1. Hasuwa H
    2. Muro Y
    3. Ikawa M
    4. Kato N
    5. Tsujimoto Y
    6. Okabe M

    (2010) Transgenic mouse sperm that have green acrosome and red mitochondria allow visualization of sperm and their acrosome reaction in vivo

    Experimental Animals 59:105–107.

    https://doi.org/10.1538/expanim.59.105

    • PubMed
    • Google Scholar
23. 1. Helmchen F
    2. Denk W

    (2005) Deep tissue two-photon microscopy

    Nature Methods 2:932–940.

    https://doi.org/10.1038/nmeth818

    • PubMed
    • Google Scholar
24. 1. Hino T
    2. Yanagimachi R

    (2019) Active peristaltic movements and fluid production of the mouse oviduct: their roles in fluid and sperm transport and fertilization†

    Biology of Reproduction 101:40–49.

    https://doi.org/10.1093/biolre/ioz061

    • PubMed
    • Google Scholar
25. 1. Holman L
    2. Snook RR

    (2006) Spermicide, cryptic female choice and the evolution of sperm form and function

    Journal of Evolutionary Biology 19:1660–1670.

    https://doi.org/10.1111/j.1420-9101.2006.01112.x

    • PubMed
    • Google Scholar
26. 1. Holman L
    2. Snook RR

    (2008) A sterile sperm caste protects brother fertile sperm from female-mediated death in Drosophila pseudoobscura

    Current Biology 18:292–296.

    https://doi.org/10.1016/j.cub.2008.01.048

    • PubMed
    • Google Scholar
27. 1. Hook KA
    2. Wilke LM
    3. Fisher HS

    (2021) Apical sperm hook morphology is linked to sperm swimming performance and sperm aggregation in Peromyscus mice

    Cells 10:2279.

    https://doi.org/10.3390/cells10092279

    • PubMed
    • Google Scholar
28. 1. Immler S
    2. Moore HDM
    3. Breed WG
    4. Birkhead TR

    (2007) By hook or by crook? Morphometry, competition and cooperation in rodent sperm

    PLOS ONE 2:e170.

    https://doi.org/10.1371/journal.pone.0000170

    • PubMed
    • Google Scholar
29. 1. Ishikawa Y
    2. Usui T
    3. Yamashita M
    4. Kanemori Y
    5. Baba T

    (2016) Surfing and swimming of ejaculated sperm in the mouse oviduct

    Biology of Reproduction 94:89.

    https://doi.org/10.1095/biolreprod.115.135418

    • PubMed
    • Google Scholar
30. Software

    1. Jeong Y

    (2023) Sperm_tracking, version swh:1:rev:de5cedb0ac79fc772524ab61c09e5be2528b94d8

    Software Heritage.

    https://archive.softwareheritage.org/swh:1:dir:ce27959954ed5ce3654fc1e3a2bce9d15cd6fa46;origin=https://github.com/YundonJeong/Sperm_tracking;visit=swh:1:snp:ccf199c6b22f4ace23cff3cb4653cfb68abe69dc;anchor=swh:1:rev:de5cedb0ac79fc772524ab61c09e5be2528b94d8
31. 1. Kantsler V
    2. Dunkel J
    3. Blayney M
    4. Goldstein RE

    (2014) Rheotaxis facilitates upstream navigation of mammalian sperm cells

    eLife 3:e02403.

    https://doi.org/10.7554/eLife.02403

    • PubMed
    • Google Scholar
32. 1. Keller PJ

    (2013) Imaging morphogenesis: technological advances and biological insights

    Science 340:1234168.

    https://doi.org/10.1126/science.1234168

    • PubMed
    • Google Scholar
33. 1. Koprowski JL

    (1992) Removal of copulatory plugs by female tree squirrels

    Journal of Mammalogy 73:572–576.

    https://doi.org/10.2307/1382026

    • Google Scholar
34. 1. Lange R
    2. Reinhardt K
    3. Michiels NK
    4. Anthes N

    (2013) Functions, diversity, and evolution of traumatic mating

    Biological Reviews of the Cambridge Philosophical Society 88:585–601.

    https://doi.org/10.1111/brv.12018

    • PubMed
    • Google Scholar
35. 1. Lüpold S
    2. Pitnick S

    (2018) Sperm form and function: What do we know about the role of sexual selection?

    Reproduction 155:R229–R243.

    https://doi.org/10.1530/REP-17-0536

    • PubMed
    • Google Scholar
36. 1. Mahabir E
    2. Bauer B
    3. Schmidt J

    (2008) Rodent and germplasm trafficking: Risks of microbial contamination in a high-tech biomedical world

    ILAR Journal 49:347–355.

    https://doi.org/10.1093/ilar.49.3.347

    • PubMed
    • Google Scholar
37. 1. Mangels R
    2. Tsung K
    3. Kwan K
    4. Dean MD

    (2016) Copulatory plugs inhibit the reproductive success of rival males

    Journal of Evolutionary Biology 29:2289–2296.

    https://doi.org/10.1111/jeb.12956

    • PubMed
    • Google Scholar
38. 1. Moore H
    2. Dvoráková K
    3. Jenkins N
    4. Breed W

    (2002) Exceptional sperm cooperation in the wood mouse

    Nature 418:174–177.

    https://doi.org/10.1038/nature00832

    • PubMed
    • Google Scholar
39. 1. Nakanishi T
    2. Isotani A
    3. Yamaguchi R
    4. Ikawa M
    5. Baba T
    6. Suarez SS
    7. Okabe M

    (2004) Selective passage through the uterotubal junction of sperm from a mixed population produced by chimeras of calmegin-knockout and wild-type male mice

    Biology of Reproduction 71:959–965.

    https://doi.org/10.1095/biolreprod.104.028647

    • PubMed
    • Google Scholar
40. 1. Parker GA

    (1970) Sperm competition and its evolutionary consequences in the insects

    Biological Reviews 45:525–567.

    https://doi.org/10.1111/j.1469-185X.1970.tb01176.x

    • Google Scholar
41. 1. Parkhurst CN
    2. Yang G
    3. Ninan I
    4. Savas JN
    5. Lafaille JJ
    6. Hempstead BL
    7. Littman DR
    8. Gan WB

    (2013) Microglia promote learning-dependent synapse formation through brain-derived neurotrophic factor

    Cell 155:1596–1609.

    https://doi.org/10.1016/j.cell.2013.11.030

    • Google Scholar
42. 1. Pologruto TA
    2. Sabatini BL
    3. Svoboda K

    (2003) ScanImage: flexible software for operating laser scanning microscopes

    Biomedical Engineering Online 2:13.

    https://doi.org/10.1186/1475-925X-2-13

    • PubMed
    • Google Scholar
43. 1. Qu Y
    2. Chen Q
    3. Guo S
    4. Ma C
    5. Lu Y
    6. Shi J
    7. Liu S
    8. Zhou T
    9. Noda T
    10. Qian J
    11. Zhang L
    12. Zhu X
    13. Lei X
    14. Cao Y
    15. Li W
    16. Li W
    17. Plachta N
    18. Matzuk MM
    19. Ikawa M
    20. Duan E
    21. Zhang Y
    22. Wang H

    (2021) Cooperation-based sperm clusters mediate sperm oviduct entry and fertilization

    Protein & Cell 12:810–817.

    https://doi.org/10.1007/s13238-021-00825-y

    • PubMed
    • Google Scholar
44. Software

    1. R Development Core Team

    (2023) R: A language and environment for statistical computing

    R Foundation for Statistical Computing, Vienna, Austria.

    https://www.r-project.org
45. Software

    1. R Development Core Team

    (2024) R: A language and environment for statistical computing

    R Foundation for Statistical Computing, Vienna, Austria.

    https://www.r-project.org
46. 1. Roberts EK
    2. Lu A
    3. Bergman TJ
    4. Beehner JC

    (2012) A Bruce effect in wild geladas

    Science 335:1222–1225.

    https://doi.org/10.1126/science.1213600

    • PubMed
    • Google Scholar
47. 1. Roldan ERS
    2. Gomendio M
    3. Vitullo AD

    (1992) The evolution of eutherian spermatozoa and underlying selective forces: female selection and sperm competition

    Biological Reviews of the Cambridge Philosophical Society 67:551–593.

    https://doi.org/10.1111/j.1469-185x.1992.tb01193.x

    • PubMed
    • Google Scholar
48. 1. Schindelin J
    2. Arganda-Carreras I
    3. Frise E
    4. Kaynig V
    5. Longair M
    6. Pietzsch T
    7. Preibisch S
    8. Rueden C
    9. Saalfeld S
    10. Schmid B
    11. Tinevez JY
    12. White DJ
    13. Hartenstein V
    14. Eliceiri K
    15. Tomancak P
    16. Cardona A

    (2012) Fiji: an open-source platform for biological-image analysis

    Nature Methods 9:676–682.

    https://doi.org/10.1038/nmeth.2019

    • PubMed
    • Google Scholar
49. 1. Simmons LW
    2. Wedell N

    (2020) Fifty years of sperm competition: the structure of a scientific revolution

    Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 375:20200060.

    https://doi.org/10.1098/rstb.2020.0060

    • PubMed
    • Google Scholar
50. 1. Smith TT
    2. Yanagimachi R

    (1990) The viability of hamster spermatozoa stored in the isthmus of the oviduct: the importance of sperm-epithelium contact for sperm survival

    Biology of Reproduction 42:450–457.

    https://doi.org/10.1095/biolreprod42.3.450

    • PubMed
    • Google Scholar
51. 1. Suarez SS

    (1987) Sperm transport and motility in the mouse oviduct: observations in situ

    Biology of Reproduction 36:203–210.

    https://doi.org/10.1095/biolreprod36.1.203

    • PubMed
    • Google Scholar
52. 1. Sutter A
    2. Lindholm AK

    (2016) The copulatory plug delays ejaculation by rival males and affects sperm competition outcome in house mice

    Journal of Evolutionary Biology 29:1617–1630.

    https://doi.org/10.1111/jeb.12898

    • PubMed
    • Google Scholar
53. 1. Tayama K
    2. Fujita H
    3. Takahashi H
    4. Nagasawa A
    5. Yano N
    6. Yuzawa K
    7. Ogata A

    (2006) Measuring mouse sperm parameters using a particle counter and sperm quality analyzer: a simple and inexpensive method

    Reproductive Toxicology 22:92–101.

    https://doi.org/10.1016/j.reprotox.2005.11.009

    • PubMed
    • Google Scholar
54. 1. Thévenaz P
    2. Ruttimann UE
    3. Unser M

    (1998) A pyramid approach to subpixel registration based on intensity

    IEEE Transactions on Image Processing 7:27–41.

    https://doi.org/10.1109/83.650848

    • PubMed
    • Google Scholar
55. 1. Tinevez JY
    2. Perry N
    3. Schindelin J
    4. Hoopes GM
    5. Reynolds GD
    6. Laplantine E
    7. Bednarek SY
    8. Shorte SL
    9. Eliceiri KW

    (2017) TrackMate: An open and extensible platform for single-particle tracking

    Methods 115:80–90.

    https://doi.org/10.1016/j.ymeth.2016.09.016

    • Google Scholar
56. 1. Tourmente M
    2. Zarka-Trigo D
    3. Roldan ERS

    (2016) Is the hook of muroid rodent’s sperm related to sperm train formation?

    Journal of Evolutionary Biology 29:1168–1177.

    https://doi.org/10.1111/jeb.12857

    • PubMed
    • Google Scholar
57. 1. Varea-Sánchez M
    2. Tourmente M
    3. Bastir M
    4. Roldan ERS

    (2016) Unraveling the sperm bauplan: Relationships between sperm head morphology and sperm function in rodents

    Biology of Reproduction 95:1–9.

    https://doi.org/10.1095/biolreprod.115.138008

    • PubMed
    • Google Scholar
58. 1. Yu SX
    2. Wu Y
    3. Luo H
    4. Liu Y
    5. Chen YC
    6. Wang YJ
    7. Liu W
    8. Tang J
    9. Shi H
    10. Gao H
    11. Jing G
    12. Liu YJ

    (2023) Escaping behavior of sperms on the biomimetic oviductal surface

    Analytical Chemistry 95:2366–2374.

    https://doi.org/10.1021/acs.analchem.2c04338

    • PubMed
    • Google Scholar
59. 1. Zaferani M
    2. Palermo GD
    3. Abbaspourrad A

    (2019) Strictures of a microchannel impose fierce competition to select for highly motile sperm

    Science Advances 5:eaav2111.

    https://doi.org/10.1126/sciadv.aav2111

    • PubMed
    • Google Scholar

Author details

1. Heungjin Ryu

   1. Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea
   2. Department of Social Informatics, Kyoto University, Kyoto, Japan

   Contribution

   Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Visualization, Methodology, Writing – original draft, Writing – review and editing

   Contributed equally with

   Kibum Nam, Byeong Eun Lee and Yundon Jeong

   For correspondence

   ryu.heungjin.26v@kyoto-u.jp

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-1048-9519

2. Kibum Nam

   Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea

   Contribution

   Investigation, Methodology

   Contributed equally with

   Heungjin Ryu, Byeong Eun Lee and Yundon Jeong

   Competing interests

   No competing interests declared

3. Byeong Eun Lee

   Department of Biological Sciences, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea

   Contribution

   Investigation

   Contributed equally with

   Heungjin Ryu, Kibum Nam and Yundon Jeong

   Competing interests

   No competing interests declared

4. Yundon Jeong

   Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea

   Contribution

   Software, Investigation, Visualization, Methodology

   Contributed equally with

   Heungjin Ryu, Kibum Nam and Byeong Eun Lee

   Competing interests

   No competing interests declared

5. Seunghun Lee

   Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea

   Contribution

   Methodology

   Competing interests

   No competing interests declared

6. Jeongmo Kim

   Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea

   Contribution

   Methodology

   Competing interests

   No competing interests declared

7. Young-Min Hyun

   Department of Anatomy, Yonsei University College of Medicine, Seoul, Republic of Korea

   Contribution

   Methodology

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-0567-2039

8. Jae-Ick Kim

   Department of Biological Sciences, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea

   Contribution

   Supervision, Funding acquisition, Project administration, Writing – review and editing

   For correspondence

   jikim220@unist.ac.kr

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-9705-0394

9. Jung-Hoon Park

   Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea

   Contribution

   Conceptualization, Supervision, Funding acquisition, Investigation, Visualization, Methodology, Writing – original draft, Project administration, Writing – review and editing

   For correspondence

   jh.park@unist.ac.kr

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-5316-1690

• 517

  views

• 21

  downloads

• 0

  citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.