(221) Investigating the Genetic Origins of Sperm Nuclear Vacuoles and Their Impact on Bovine Reproductive Outcomes

Filip Tirpak¹; Lauren Hamilton¹; Tasrin Sultana¹; Robert Schnabel¹; Jacob Rissman¹; Karl Kerns²; Michal Zigo¹; Miriam Sutovsky¹; Peter Sutovsky^1,3

1. Division of Animal Sciences, University of Missouri, Columbia, MO, USA

2. Department of Animal Science, Iowa State University, Ames, IA, USA

3. Department of Obstetrics, Gynecology and Women’s Health, University of Missouri, Columbia, MO, USA

Abstract Text:

Artificial insemination (AI) has dramatically transformed cattle breeding strategies since its implementation. While significant improvements in production traits have been achieved, the neglect of reproductive traits has led to increased inbreeding and a subsequent decline in fertility. Breeding management that incorporates reproductive traits has generally improved fertility, however rare, homozygous single nucleotide polymorphisms, often associated with sperm morphological abnormalities, are harbored in the cattle population genomes. Tackling the complexity of cattle AI, we employ a genome-to-phenome (G2P) approach to identify mutations inherited from the past generations. Our goal is to identify biomarkers of paternally derived factors affecting reproductive outcomes. Based on extensive insemination and pregnancy records, along with genome sequencing, we have identified 85 subfertile bulls carrying alternative gene variants related to sperm quality and preimplantation embryo development. Our research focuses particularly on spermatozoa exhibiting a nuclear vacuole (NV) phenotype at a frequency of >20% spermatozoa in an ejaculate, within a sub-cohort of five NV bulls that share mutations in fertility-associated genes—MSL3, PIR, PEG3, EP400, and TDRD9. In addition to a possible role in the NV pathology, these genes are involved in chromatin and DNA dynamics and are developmentally regulated during spermatogenesis and preimplantation embryo development. Using our high-throughput phenotyping pipeline, which includes epifluorescence microscopy, image-based flow cytometry (IBFC), and proteomic analyses, we identified differential protein immunolocalization and abundance compared to spermatozoa from wild-type (for said gene mutations) sires. We also confirmed the nuclear localization of candidate proteins in wild-type bull spermatids. These findings are being translated to automated, label-free semen analysis by integrating machine learning with advanced IBFC techniques—essentially, putting the AI (artificial intelligence) into AI, a concept we refer to as AI². The results of this study will deepen our understanding of spermatogenesis, link idiopathic infertility and pregnancy failure to inherited paternal factors, and elevate the efficiency of livestock breeding strategies while opening new horizons for the identification and treatment of human infertility. This study was supported by grant 2023-67015-39262 from USDA NIFA Animal Breeding, Genetics and Genomics Program. Seed funding was provided by University of Missouri College of Agriculture, Food and Natural Resources. In-kind contributions were received from Genex Cooperative and Select Sires Inc.