Objective: Artificial insemination (AI) success in cattle is strongly influenced by sperm cryotolerance, yet conventional semen evaluations often fail to predict fertility accurately.This study investigated enolase 1 (ENO1) as a candidate molecular marker associated with sperm cryotolerance, functional quality, and fertility in Bali bulls (Bos sondaicus) Methods: Cryopreserved semen from 20 bulls was classified into cryotolerant (CT) and cryosensitive (CS) groups based on post-thaw viability.Sperm functional parameters, including motility, kinematics (VCL, VAP, VSL), membrane integrity, mitochondrial membrane potential (MMP), and DNA fragmentation, were evaluated.Oxidative stress markers (malondialdehyde, MDA; aspartate aminotransferase, AST) were measured.ENO1 expression was quantified at mRNA (RT-qPCR) and protein (ELISA) levels.Field fertility was assessed using the first service conception rate (FSCR). Statistical analyses included t-tests, correlation, and linear regression.Results: CT sperm exhibited significantly higher (P < 0.05) motility, kinematic parameters, membrane integrity, MMP, and fertility rate compared to CS sperm.In contrast, DNA fragmentation, MDA levels, and AST activity were significantly lower in the CT group.ENO1 expression was markedly higher in CT bulls at both mRNA and protein levels (P < 0.05).Strong positive correlations were observed between ENO1 expression and sperm function, cryotolerance, and fertility (r ≈ 0.96-1.00),while strong negative correlations were found with oxidative stress and cellular damage markers (r ≈ -0.90 to -1.00).Regression analysis indicated strong associations between ENO1 abundance and sperm quality and fertility outcomes.Conclusion: ENO1 is closely associated with sperm cryotolerance, functional integrity, and fertility in Bali bulls.These findings support an association between ENO1 abundance and the cryotolerancefertility axis, highlighting its potential as a molecular biomarker for improving semen evaluation, sire selection, and cryopreservation strategies in bovine AI systems.
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Pardede et al. (2026) studied this question.
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