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# Predicting Male Fertility: From Decades of Semen Analysis to Future Perspectives

Eli Sellem

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## To cite this version:

Eli Sellem. Predicting Male Fertility: From Decades of Semen Analysis to Future Perspectives. AIVETS, EFFAB, Oct 2025, Budapest, Hungary. hal-05499465

HAL Id: hal-05499465

https://hal.science/hal-05499465v1

Submitted on 8 Feb 2026

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Distributed under a Creative Commons CC BY 4.0 - Attribution - International License
Predicting Male Fertility: From Decades of Semen Analysis to Future Perspectives

Valentin Costes<fnref n="1" />, Chrystelle Le Danvic<fnref n="1" />, Aurelie Bonnet<fnref n="1" />, Pritha Dey<fnref n="2" />, Helene Kiefer<fnref n="2" />, Eliaou Sellem<fnref n="2" />

Initially used as tools for population renewal, reproductive biotechnologies, such as artificial insemination, remain today the main drivers of genetic progress dissemination. Several million inseminations are performed each year in major livestock-producing countries, and the use of less fertile reproducers or ejaculates leads to a decrease in the overall efficiency of breeding schemes and, ultimately, to significant economic losses.

The development of genomic selection breeding programs has been a game changer, further reinforcing the need to control the fertility of disseminated ejaculates. Indeed, the selected bulls are younger aiming to shorten generation intervals, and they are disseminated without prior information on their fertilizing power. Thus, ensuring male fertility control still remains today a central challenge for breeding companies to optimally support the dissemination of genetic progress.

Initially based on male phenotypic traits, fertility prediction was then approached through semen quality assessment. For decades, numerous research teams have developed biomarkers reflecting the quality of the different sperm compartments. The prevailing paradigm of these approaches focused on the quality–functionality relationship<fnref n="1" />⁻³. A variant of this strategy addressed the multifactorial nature of in- or subfertility by combining several biomarkers to obtain a global comprehensive picture of sperm functionality and so an enhanced fertility prediction strength. With the development of new technologies that are more precise, automated, and miniaturized, phenotypes became more refined, objective, and measurable directly in the field rather than in specialized R&D laboratories⁴. Novel approaches have also explored the fine molecular composition of gametes through proteomics, glycomics, and lipidomics, highlighting biological pathways essential for sperm formation and normal function⁵⁻⁷. These results paved the road for studies investigating interactions between maturing male gametes and their local environment, particularly during epididymal transit or in contact with seminal plasma, revealing their essential role in the final sperm maturation⁸⁻¹⁰. These new insights have fostered the emergence of innovative research areas in reproductive biotechnologies, including the role of the sperm epigenome in sperm maturation and embryonic development, as well as the molecular study of environmental stress impacts on male gametes. The sperm DNA methylation pattern or the sperm-borne small non coding RNA profile expressions appeared¹¹⁻¹⁴. In parallel, with the rise of genomic selection approaches, SNP-fertility association studies have also been conducted, allowing a potential specific selection of this trait¹⁵⁻¹⁸. Altogether, these emerging approaches aim to improve our mechanistic and functional understanding of the biological pathways involved in reproductive biology and to develop relevant biomarkers to address livestock industry challenges, such as fertility prediction¹⁹.

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2. Sellem, E. et al. Use of combinations of in vitro quality assessments to predict fertility of bovine semen. *Theriogenology* **84**, 1447-1454.e5 (2015).

3. Singh, R. K. et al. Identification of suitable combinations of in vitro sperm-function test for the prediction of fertility in buffalo bull. *Theriogenology* **86**, 2263-2271.e1 (2016).

<footnote n="1">¹R&D Department, Eliance, 149 rue de Bercy, 75012, Paris, France</footnote>

<footnote n="2">2 UVSQ, INRAE, BREED, Université Paris Saclay, 78350, Jouy en Josas, France.</footnote>
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11. Sellem, E. et al. Dynamics of cattle sperm sncRNAs during maturation, from testis to ejaculated sperm. *Epigenetics Chromatin* **14**, 24 (2021).

12. Sellem, E., Jammes, H. & Schibler, L. Sperm-borne sncRNAs: potential biomarkers for semen fertility? *Reprod. Fertil. Dev.* **34**, 160–173 (2021).

13. Costes, V. et al. Predicting male fertility from the sperm methylome: application to 120 bulls with hundreds of artificial insemination records. *Clin. Epigenetics* **14**, 54 (2022).

14. Costes, V. et al. Multi-omics data integration for the identification of biomarkers for bull fertility. *PLOS ONE* **19**, e0298623 (2024).

15. de Carvalho, F. E. et al. Genetic parameters and genome-wide association studies including the X chromosome for various reproduction and semen quality traits in Nellore cattle. *BMC Genomics* **26**, 26 (2025).

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18. Ortega, M. S. et al. Association of single nucleotide polymorphisms in candidate genes previously related to genetic variation in fertility with phenotypic measurements of reproductive function in Holstein cows. *J. Dairy Sci.* **100**, 3725–3734 (2017).

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