Semen quality analysis plays a pivotal role in the global pig industry to enhance animal production efficiency, and artificial insemination (AI) is employed in animal husbandry to disseminate the genetic benefits of superior sires [1,2]. In Canada, Denmark, the Netherlands, Norway, and the USA, semen quality accounts for approximately 30% of the reasons for sire replacement in AI units, ranking second only to genetic factors [3]. Thus, selecting superior sires that produce high-quality semen is crucial in the swine industry as pregnancy failures cause significant economic losses [4,5].

Traditional semen analyses primarily focus on assessing semen quality parameters such as basic sperm motility, sperm counts, and visual sperm morphological analysis [[6], [7], [8], [9]]. However, conventional parameters based on microscopic assessment cannot clearly address sperm function, posing limitations in predicting male fertility through these parameters [10]. Several researchers have previously reported that the conventional semen analysis parameters are inadequate for distinguishing semen with high fecundability from those with low fecundability [11,12]. The difficulty in making accurate predictions of fertilization arises from the fact that the currently used traditional semen analyses cannot estimate factors that contribute further to fertilization, such as sperm-female reproductive tract interaction [9]. Nonetheless, these conventional methods have limitations when evaluating fertility, it served as reference standards for sperm quality evaluation in the animal industry, human clinics, hospitals, and beyond. Hence, in incorporating current semen analyses, the need for more accurate and comprehensive sperm evaluation methods has been emphasized [12,13].

Recent advancements have prompted the discovery of various fertility-related biomarkers, aiming to overcome the constraints of conventional semen analysis [[14], [15], [16]]. These research efforts have illuminated the molecular mechanisms underlying male fertility and the potential for diagnosing and predicting male fertility using diverse protein biomarkers [14,15,[17], [18], [19], [20]]. Nonetheless, further studies are required to comprehensively understand the male reproductive mechanisms and to ensure accurate diagnostic and prognostic analysis of male fertility. Additionally, more research is needed to identify highly effective fertility-related biomarkers and elucidate the causes of infertility in idiopathic cases. Hence, the current study was designed to assess the utility of three sperm function-specific proteins [axonemal dynein light intermediate polypeptide 1 (DNALI1), radial spoke head protein 9 homolog (RSPH9), and cytochrome b5 domain-containing protein 1 (CYB5D1)] as fertility-related biomarkers. Within this investigation, we evaluated the physiological disparities based on sperm motion parameters and assessed the potential fertility biomarker proteins associated with these parameters. Moreover, statistical analysis was conducted to select the most pertinent fertility-related biomarkers for the prognosis and diagnosis of male fertility.