Reproductive efficiency is crucial for animal agriculture. This economically important aspect can be influenced by environmental burdens, nutritional imbalance, and gonadal or gametic malformations of genetic origin. Successful implementation of genomic-driven selective breeding in cattle depends on the reproductive performance of artificial insemination (AI) sires with valuable genomic production traits. Reproduction is traditionally viewed as a complex set of polygenic traits that are negatively impacted by using a small number of often closely related sires selected for AI due to their superior genetics. Despite recent progress, it remains difficult to define relationships between sire genome and variation in sperm phenotypes, even though several types of heritable, non-compensable sperm defects have been identified. In this review, we discuss the concept of sperm quality biomarker discovery and genomics of male fertility. We also outline a multidisciplinary genome-to-phenome approach for investigating heritable mutations and their impacts on bull fertility, sperm phenotypes and paternal contributions to early pregnancy. High-precision phenotyping requires novel, state-of-the-art instrumentation for sperm quality evaluation and development of new biomarkers of sperm quality in farm animals, with potential for incorporation into andrology-specific machine learning protocols and translation to human andrology. We conclude that reproduction is a complex phenotype that can be deciphered and explored for more precise male fertility evaluation and higher reproductive efficiency.
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http://dx.doi.org/10.1016/j.anireprosci.2024.107636 | DOI Listing |
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