Kinematic subpopulation structure variations in cryopreserved semen from dairy cattle
DOI:
https://doi.org/10.15517/am.2025.63141Keywords:
Semen quality, animal science, bulls, sperm motility, artificial insemination, spermatozoaAbstract
Introduction. In the dairy industry, frozen-thawed semen is crucial for artificial insemination and genetic improvement of livestock. Objective. To evaluate the variation in the kinematic subpopulation structure of frozen-thawed semen in Jersey and Holstein breeds using a CASA-mot system. Materials and methods. The study was carried out from April to November 2023, at the Animal Reproduction Laboratory (AndroTEC), located at the Campus Tecnológico Local San Carlos, Alajuela, Costa Rica. Eight animals from the Holstein and Jersey breeds were used, and nine doses of frozen-thawed semen per animal were analyzed for each breed. A total of 72 semen doses from eight bulls (four from each breed) were thawed at 37° C for 30 s. Sperm motility and kinematic variables were analyzed using CASA-mot (Computer-Assisted Semen Analysis) technology. Results. The Jersey breed showed higher percentages of total motile, progressive motile, and rapid spermatozoa compared to the Holstein breed (P < 0.05). Principal component analysis revealed two significant factors explaining 87.5 % of the total variance in kinematic variables. The kinematics variables between sperm subpopulations (SPs) showed differences (P < 0.05) in both breeds. The subpopulation SP2 was the fastest, with higher values in curvilinear speed (VCL), straight-line speed (VSL) and average trajectory speed (VAP) for Holstein and Jersey bulls. Conclusions. Kinematics differences were found between the subpopulations identified for both breeds. The kinematic patterns of the subpopulations present in the ejaculate could influence fertility and reproductive performance.
Downloads
References
Araya-Zúñiga, I., Sevilla, F., Molina-Montero, R., Roldan, E. R. S., Barrientos-Morales, M., Silvestre, M. A., & Valverde, A. (2024). Kinematic and morphometric assessment of fresh semen, before, during and after mating period in brahman bulls. Animals, 14(1), Article 132. https://doi.org/10.3390/ANI14010132
Barbas, J. P., Leahy, T., Horta, A. E., & García-Herreros, M. (2018). Sperm kinematics and subpopulational responses during the cryopreservation process in caprine ejaculates. Cryobiology, 82, 137–147. https://doi.org/10.1016/J.CRYOBIOL.2018.03.005
Barquero, V., Roldan, E. R. S., Soler, C., Yániz, J. L., Camacho, M., & Valverde, A. (2021). Predictive capacity of boar sperm morphometry and morphometric sub-populations on reproductive success after artificial insemination. Animals, 11(4), Article 920. https://doi.org/10.3390/ANI11040920
Barquero, V., Soler, C., Sevilla, F., Calderón-Calderón, J., & Valverde, A. (2021). A Bayesian analysis of boar spermatozoa kinematics and head morphometrics and their relationship with litter size fertility variables. Reproduction in Domestic Animals, 56(7), 1024–1033. https://doi.org/10.1111/RDA.13946
Barquero, V., Víquez, L., Calderón, J. C., & Valverde, A. (2021). Optimal frame rate to evaluate boar sperm kinematic with a CASA-Mot system. Agronomía Mesoamericana, 32(1), 1–18. https://doi.org/10.15517/am.v32i1.41928
Bompart, D., García-Molina, A., Valverde, A., Caldeira, C., Yániz, J., Núñez de Murga, M., & Soler, C. (2018). CASA-Mot technology: how results are affected by the frame rate and counting chamber. Reproduction, Fertility and Development, 30(6), 810–819. https://doi.org/10.1071/RD17551
Bompart, D., Vázquez, R., Gómez, R., Valverde, A., Roldán, E., García-Molina, A., & Soler, C. (2019). Combined effects of type and depth of counting chamber, and rate of image frame capture, on bull sperm motility and kinematics. Animal Reproduction Science, 209, Article106169. https://doi.org/10.1016/J.ANIREPROSCI.2019.106169
Botta, D., de Arruda, R. P., Watanabe, Y. F., de Carvalho Balieiro, J. C., Romanello, N., do Nascimento Barreto, A., de Andrade Pantoja, M. H., Giro, A., de Carvalho, C. P. T., de Sousa Oliveira, A., & Garcia, A. R. (2019). Influence of post-thawing thermal environment on bovine sperm characteristics and in vitro fertility. Andrologia, 51(6), Article e13266. https://doi.org/10.1111/AND.13266
Butler, S. T. (2014). Nutritional management to optimize fertility of dairy cows in pasture-based systems. Animal, 8(Supp. 1), 15–26. https://doi.org/10.1017/S1751731114000834
Caldeira, C., García-Molina, A., Valverde, A., Bompart, D., Hassane, M., Martin, P., & Soler, C. (2018). Comparison of sperm motility subpopulation structure among wild anadromous and farmed male Atlantic salmon (Salmo salar) parr using a CASA system. Reproduction, Fertility and Development, 30(6), 897–906. https://doi.org/10.1071/RD17466
Caldeira, C., Hernández-Ibáñez, S., Valverde, A., Martin, P., Herranz-Jusdado, J. G., Gallego, V., Asturiano, J. F., Dzyuba, B., Pšenička, M., & Soler, C. (2019). Standardization of sperm motility analysis by using CASA-Mot for Atlantic salmon (Salmo salar), European eel (Anguilla anguilla) and Siberian sturgeon (Acipenser baerii). Aquaculture, 502, 223–231. https://doi.org/10.1016/j.aquaculture.2018.12.001
Chicaiza-Cabezas, N., Garcia-Herreros, M., & Aponte, P. M. (2023). Germplasm cryopreservation in bulls: Effects of gonadal tissue type, cryoprotectant agent, and freezing-thawing rates on sperm quality parameters. Cryobiology, 110, 24–35. https://doi.org/10.1016/J.CRYOBIOL.2023.01.001
Cucho, H., Gallegos, M., Ccoiso, R., Meza, A., Ampuero, E., Ordóñez, C., & Valverde, A. (2021). Morphometry and subpopulation of llama (Lama glama) sperm using the ISAS® CASA-Morph system. Revista de Investigaciones Veterinarias Del Peru, 32(1), Article e19506. https://doi.org/10.15381/RIVEP.V32I1.19506
Cucho, H., Nina, G., Meza, A., Ccalta, R., Ordóñez, C., & Valverde, A. (2022). Subpoblaciones morfométricas de espermatozoides epididimarios del venado de cola blanca (Odocoileus virginianus peruvianus). Agronomy Mesoamerican, 33(2), Article 46938. https://doi.org/10.15517/AM.V33I2.46938
Gacem, S., Catalán, J., Valverde, A., Soler, C., & Miró, J. (2020). Optimization of Casa-mot analysis of donkey sperm: Optimum frame rate and values of kinematic variables for different counting chamber and fields. Animals, 10(11), Article 1993. https://doi.org/10.3390/ani10111993
Gacem, S., Valverde, A., Catalán, J., Yánez Ortiz, I., Soler, C., & Miró, J. (2021). A New Approach of Sperm Motility Subpopulation Structure in Donkey and Horse. Frontiers in Veterinary Science, 8, Article 424. https://doi.org/10.3389/FVETS.2021.651477
Gallagher, M. T., Smith, D. J., & Kirkman-Brown, J. C. (2018). CASA: tracking the past and plotting the future. Reproduction, Fertility and Development, 30(6), 867–874. https://doi.org/10.1071/RD17420
Gallego, V., Vílchez, M. C., Peñaranda, D. S., Pérez, L., Herráez, M. P., Asturiano, J. F., & Martínez-Pastor, F. (2015). Subpopulation pattern of eel spermatozoa is affected by post-activation time, hormonal treatment and the thermal regimen. Reproduction, Fertility and Development, 27(3), 529–543. https://doi.org/10.1071/RD13198
García-Herreros, M. (2016). Sperm subpopulations in avian species: a comparative study between the rooster (Gallus domesticus) and Guinea fowl (Numida meleagris). Asian Journal of Andrology, 18(6), 889–894. https://doi.org/10.4103/1008-682X.188448
García-Molina, A., Navarro, N., Valverde, A., Bompart, D., Caldeira, C., Vendrell, A., & Soler, C. (2022). Human kinematic and morphometric sperm subpopulation analysis using CASA technology: A new approach to spermatozoa classification. Revista Internacional de Andrología, 20(4), 257–265. https://doi.org/10.1016/J.ANDROL.2021.05.003
García-Molina, A., Navarro, N., Valverde, A., Sadeghi, S., Garrido, N., & Soler, C. (2023). Optimization of human semen analysis using CASA-Mot technology. Systems Biology in Reproductive Medicine, 69(2), 166–174. https://doi.org/10.1080/19396368.2023.2170297
García-Molina, A., Valverde, A., Bompart, D., Caldeira, C., Vendrell, A., & Soler, C. (2020). Updating semen analysis: a subpopulation approach. Asian Journal of Andrology, 22(1), 118–119. https://doi.org/10.4103/aja.aja_33_19
Gomes, F. P., Park, R., Viana, A. G., Fernandez-Costa, C., Topper, E., Kaya, A., Memili, E., Yates, J. R., & Moura, A. A. (2020). Protein signatures of seminal plasma from bulls with contrasting frozen-thawed sperm viability. Scientific, 10, Article 14661. https://doi.org/10.1038/s41598-020-71015-9
Hidalgo, M. M. T., Almeida, A. B. M. de, Moraes, F. L. Z. de, Marubayashi, R. Y. P., Souza, F. F. de, Barreiros, T. R. R., & Martins, M. I. M. (2021). Sperm subpopulations influence the pregnancy rates in cattle. Reproduction in Domestic Animals, 56(8), 1117–1127. https://doi.org/10.1111/RDA.13955
Hoflack, G., Opsomer, G., Van Soom, A., Maes, D., de Kruif, A., & Duchateau, L. (2006). Comparison of sperm quality of Belgian Blue and Holstein Friesian bulls. Theriogenology, 66(8), 1834–1846. https://doi.org/10.1016/J.THERIOGENOLOGY.2006.05.007
Holt, W. V., & Satake, N. (2018). Making the most of sperm activation responses: experiments with boar spermatozoa and bicarbonate. Reproduction, Fertility and Development, 30(6), 842–849. https://doi.org/10.1071/RD17476
Ibănescu, I., Leiding, C., & Bollwein, H. (2018). Cluster analysis reveals seasonal variation of sperm subpopulations in extended boar semen. Journal of Reproduction and Development, 64(1), 33–39. https://doi.org/10.1262/jrd.2017-083
Ibanescu, I., Siuda, M., & Bollwein, H. (2020). Motile sperm subpopulations in bull semen using different clustering approaches – Associations with flow cytometric sperm characteristics and fertility. Animal Reproduction Science, 215, Article 106329. https://doi.org/10.1016/j.anireprosci.2020.106329
Kathiravan, P., Kalatharan, J., Karthikeya, G., Rengarajan, K., & Kadirvel, G. (2011). Objective sperm motion analysis to assess dairy bull fertility using computer-aided system - A review. Reproduction in Domestic Animals, 46(1), 165–172. https://doi.org/10.1111/j.1439-0531.2010.01603.x
Koch, J., Weber, L. P., Heppelmann, M., Freise, F., Klingelmann, M., & Bachmann, L. (2022). Effect of different Thawing methods for frozen bull semen and additional factors on the conception rate of dairy cows in Artificial Insemination. Animals, 12(18), Article 2330. https://doi.org/10.3390/ANI12182330
Layek, S. S., Mohanty, T. K., Kumaresan, A., & Parks, J. E. (2016). Cryopreservation of bull semen: Evolution from egg yolk based to soybean based extenders. Animal Reproduction Science, 172, 1–9. https://doi.org/10.1016/J.ANIREPROSCI.2016.04.013
Martínez-Pastor, F. (2021). What is the importance of sperm subpopulations? Animal Reproduction Science, 246, Article 106844. https://doi.org/10.1016/J.ANIREPROSCI.2021.106844
Martínez-Pastor, F., Tizado, E., Garde, J., Anel, L., & de Paz, P. (2011). Statistical Series: Opportunities and challenges of sperm motility subpopulation analysis. Theriogenology, 75(5), 783–795. https://doi.org/10.1016/J.THERIOGENOLOGY.2010.11.034
Morrell, J. M., Valeanu, A. S., Lundeheim, N., & Johannisson, A. (2018). Sperm quality in frozen beef and dairy bull semen. Acta Veterinaria Scandinavica, 60, Article 41. https://doi.org/10.1186/S13028-018-0396-2
Mortimer, S. T., & De Jonge, C. J. (2018). CASA—Computer-Aided Sperm Analysis. In M. Skinner (Ed.), Encyclopedia of Reproduction (pp. 59–63). Elsevier. https://doi.org/10.1016/b978-0-12-801238-3.64935-8
Pichardo-Matamoros, D., Sevilla, F., Elizondo-Salazar, J., Jiménez-Sánchez, C., Roldan, E. R. S., Soler, C., Gacem, S., & Valverde, A. (2023). Exploration of semen quality analyzed by casa-mot systems of brahman bulls infected with BLV and BHV-1. Scientific Reports, 13, Article 18659. https://doi.org/10.1038/s41598-023-45981-9
Quintero-Moreno, A., Miró, J., Teresa Rigau, A., & Rodríguez-Gil, J. E. (2003). Identification of sperm subpopulations with specific motility characteristics in stallion ejaculates. Theriogenology, 59(9), 1973–1990. https://doi.org/10.1016/s0093-691x(02)01297-9
Quintero-Moreno, A., Rigau, T., & Rodríguez-Gil, J. (2007). Multivariate cluster analysis regression procedures as tools to identify motile sperm subpopulations in rabbit semen and to predict semen fertility and litter size. Reproduction in Domestic Animals, 42(3), 312–319. https://doi.org/10.1111/j.1439-0531.2006.00785.x
Ramón, M., & Martínez-Pastor, F. (2018). Implementation of novel statistical procedures and other advanced approaches to improve analysis of CASA data. Reproduction, Fertility and Development, 30(6), 860–866. https://doi.org/10.1071/RD17479
Schulze, M., Jakop, U., Jung, M., & Cabezón, F. (2019). Influences on thermo-resistance of boar spermatozoa. Theriogenology, 127, 15–20. https://doi.org/10.1016/J.THERIOGENOLOGY.2018.12.022
Selvaraju, S., Parthipan, S., Somashekar, L., Binsila, B. K., Kolte, A. P., Arangasamy, A., Ravindra, J. P., & Krawetz, S. A. (2018). Current status of sperm functional genomics and its diagnostic potential of fertility in bovine (Bos taurus). Systems Biology in Reproductive Medicine, 64(6), 484–501. https://doi.org/10.1080/19396368.2018.1444816
Shojaei, H., Kroetsch, T., Wilde, R., Blondin, P., Kastelic, J. P., & Thundathil, J. C. (2012). Moribund sperm in frozen-thawed semen, and sperm motion end points post-thaw and post-swim-up, are related to fertility in Holstein AI bulls. Theriogenology, 77(5), 940–951. https://doi.org/10.1016/J.THERIOGENOLOGY.2011.09.026
Sitko, E. M., Laplacette, A., Duhatschek, D., Rial, C., Perez, M. M., Tompkins, S., Kerwin, A. L., & Giordano, J. O. (2024). Reproductive physiological outcomes of dairy cows with different genomic merit for fertility: biomarkers, uterine health, endocrine status, estrus features, and response to ovarian synchronization. Journal of Dairy Science, 107(10), 8670-8687. https://doi.org/10.3168/JDS.2023-24376
Soler, C., Alambiaga, A., Martí, M. A., García-Molina, A., Valverde, A., Contell, J., & Campos, M. (2017). Dog sperm head morphometry: its diversity and evolution. Asian Journal of Andrology, 19(2), 149–153. https://doi.org/10.4103/1008-682X.189207
Soler, C., Contell, J., Bori, L., Sancho, M., García-Molina, A., Valverde, A., & Segarvall, J. (2017). Sperm kinematic, head morphometric and kinetic-morphometric subpopulations in the blue fox (Alopex lagopus). Asian Journal of Andrology, 19(2), 154–159. https://doi.org/10.4103/1008-682X.188445
Soler, C., Valverde, A., Bompart, D., Fereidounfar, S., Sancho, M., Yániz, J., Garcia-Molina, A., & Korneenko-Zhilyaev, Yu. A. (2017). New methods of semen analysis by casa. Sel’skokhozyaistvennaya Biologiya (Agricultural Biology), 52(2), 232-241. https://doi.org/10.15389/agrobiology.2017.2.232eng
Solís, J. M., Sevilla, F., Silvestre, M. A., Araya-Zúñiga, I., Roldan, E. R. S., Saborío-Montero, A., & Valverde, A. (2024). Effect of thawing procedure and thermo-resistance test on sperm motility and kinematics patterns in two bovine breeds. Animals, 14(19), Article 2768. https://doi.org/10.3390/ANI14192768
Stefanska, B., Sobolewska, P., Fievez, V., Pruszynska-Oszmałek, E., Purwin, C., & Nowak, W. (2024). The effect of heat stress on performance, fertility, and adipokines involved in regulating systemic immune response during lipolysis of early lactating dairy cows. Journal of Dairy Science, 107(4), 2111–2128. https://doi.org/10.3168/JDS.2023-23804
Valverde, A., Arenán, H., Sancho, M., Contell, J., Yániz, J., Fernández, A., & Soler, C. (2016). Morphometry and subpopulation structure of Holstein bull spermatozoa: variations in ejaculates and cryopreservation straws. Asian Journal of Andrology, 18(6), 851–857. https://doi.org/10.4103/1008-682X.187579
Valverde, A., Arnau, S., García‐Molina, A., Bompart, D., Campos, M., Roldán, E., & Soler, C. (2019). Dog sperm swimming parameters analysed by computer‐assisted semen analysis of motility reveal major breed differences. Reproduction in Domestic Animals, 54(5), 795–803. https://doi.org/10.1111/rda.13420
Valverde, A., Barquero, V., & Soler, C. (2020). The application of computer-assisted semen analysis (CASA) technology to optimise semen evaluation. A review. Journal of Animal and Feed Sciences, 29(3), 189–198. https://doi.org/10.22358/jafs/127691/2020
Valverde, A., Castro-Morales, O., Madrigal-Valverde, M., Camacho, M., Barquero, V., Soler, C., & Roldan, E. R. S. (2021). Sperm kinematic subpopulations of the American crocodile (Crocodylus acutus). PLOS ONE, 16(3), Article e0248270. https://doi.org/10.1371/journal.pone.0248270
Valverde, A., Castro-Morales, O., Madrigal-Valverde, M., & Soler, C. (2019). Sperm kinematics and morphometric subpopulations analysis with CASA systems: A review. Revista de Biología Tropical, 67(6), 1473–1487. https://doi.org/10.15517/rbt.v67i6.35151
Valverde, A., Madrigal, M., Caldeira, C., Bompart, D., de Murga, J. N., Arnau, S., & Soler, C. (2019). Effect of frame rate capture frequency on sperm kinematic parameters and subpopulation structure definition in boars, analysed with a CASA-Mot system. Reproduction in Domestic Animals, 54(2), 167–175. https://doi.org/10.1111/rda.13320
Valverde, A., Madrigal-Valverde, M., Castro-Morales, O., Gadea-Rivas, A., Johnston, S., & Soler, C. (2019). Kinematic and head morphometric characterisation of spermatozoa from the Brown Caiman (Caiman crocodilus fuscus). Animal Reproduction Science, 207, 9–20. https://doi.org/10.1016/j.anireprosci.2019.06.011
van der Horst, G. (2020). Computer Aided Sperm Analysis (CASA) in domestic animals: Current status, three D tracking and flagellar analysis. Animal Reproduction Science, 220, Article 106350. https://doi.org/10.1016/j.anireprosci.2020.106350
Vázquez, A. J. F., Cedillo, M. J., Quezada, V. J., Rivas, A. C., Morales, E. C. L., Ayala, E. M. E., Hernández, M. J., González, R. A., & Aragón, M. A. (2015). Effects of repeated electroejaculations on kinematic sperm subpopulations and quality markers of Mexican creole goats. Animal Reproduction Science, 154, 29–38. https://doi.org/10.1016/j.anireprosci.2014.12.009
Víquez, L., Barquero, V., Soler, C., Roldan, E. R. S., & Valverde, A. (2020). Kinematic sub-populations in bull spermatozoa: A comparison of classical and Bayesian approaches. Biology, 9(6), Article 138. https://doi.org/10.3390/biology9060138
Víquez, L., Barquero, V., & Valverde, A. (2021). Optimal conditions for the kinematic analysis in fresh semen of Brahman bulls with a CASA-Mot system. Agronomía Mesoamericana, 32(3), 920–938. https://doi.org/10.15517/AM.V32I3.42768
Winters, R. A., Hamilton, D. N., Bhatnagar, A. S., Fitzgerald, R., Bovin, N., & Miller, D. J. (2018). Porcine sperm binding to oviduct cells and glycans as supplements to traditional laboratory semen analysis. Journal of Animal Science, 96(12), 5265–5275. https://doi.org/10.1093/jas/sky372
Yánez-Ortiz, I., Catalán, J., Rodríguez-Gil, J. E., Miró, J., & Yeste, M. (2022). Advances in sperm cryopreservation in farm animals: Cattle, horse, pig and sheep. Animal Reproduction Science, 246, Article 106904. https://doi.org/10.1016/J.ANIREPROSCI.2021.106904
Yániz, J., Palacín, I., Caycho, K., Soler, C., Silvestre, M., & Santolaria, P. (2018). Determining the relationship between bull sperm kinematic subpopulations and fluorescence groups using an integrated sperm quality analysis technique. Reproduction, Fertility and Development, 30(6), 919–923. https://doi.org/10.1071/RD17441
Yániz, J., Palacín, I., Vicente-Fiel, S., Sánchez-Nadal, J., & Santolaria, P. (2015). Sperm population structure in high and low field fertility rams. Animal Reproduction Science, 156, 128–134. https://doi.org/10.1016/j.anireprosci.2015.03.012
Yániz, J., Silvestre, M., Santolaria, P., & Soler, C. (2018). CASA-Mot in mammals: an update. Reproduction, Fertility, and Development, 30(6), 799–809. https://doi.org/10.1071/RD17432
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Juan M. Solís, Francisco Sevilla, Ignacio Araya-Zúñiga, Kenneth Matamoros, Laura Murillo, Patricia Cervantes, Antonio Hernández, Anthony Valverde
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
1. Proposed policy for open access journals
Authors who publish in this journal accept the following conditions:
a. Authors retain the copyright and assign to the journal the right to the first publication, with the work registered under the attribution, non-commercial and no-derivative license from Creative Commons, which allows third parties to use what has been published as long as they mention the authorship of the work and upon first publication in this journal, the work may not be used for commercial purposes and the publications may not be used to remix, transform or create another work.
b. Authors may enter into additional independent contractual arrangements for the non-exclusive distribution of the version of the article published in this journal (e.g., including it in an institutional repository or publishing it in a book) provided that they clearly indicate that the work was first published in this journal.
c. Authors are permitted and encouraged to publish their work on the Internet (e.g. on institutional or personal pages) before and during the review and publication process, as it may lead to productive exchanges and faster and wider dissemination of published work (see The Effect of Open Access).
