Linking Fertility-Associated Gene Polymorphisms to Aberrant Sperm Phenotypes

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Sutovsky, Peter - PD SUMMARY The present project is directly relevant to the goals of RFA PAR-13-204, Dual Purpose with Dual Benefit: Research in Biomedicine and Agriculture Using Agriculturally Important Domestic Species. It will be the first project to systematically link the genetic traits affecting male fertility to sperm phenotypes easily measurable in a human/animal semen sample. Whole genome sequencing has identified a large number of gene polymorphisms with the potential to affect male fertility in humans and livestock. However, there is very little understanding of how these polymorphisms may affect the phenotypes of spermatozoa, their fertilizing ability and their influence on pre-embryo development and early embryo loss. We hypothesize that unique mutations/polymorphisms in genes expressed during spermatogenesis and pre- embryo development (further “fertility associated genes”) are responsible for male subfertility and for early embryo loss during pregnancy. Our goal is to link these genetic traits to sperm phenotypes measurable in a semen sample and reflected by the males’ fertility in vivo and in vitro. We chose artificial insemination (AI) bulls as model system because their genotypes are publically accessible, they have extensive fertility records from AI services, and their fertility in vivo correlates with their in vitro fertility. We have identified 3,601 candidate fertility-related genes with loss-of-function LOF) polymorphisms in the whole genome sequences of 219 bulls representing 18 breeds and performed phenotype analysis on several candidate gene products that revealed significant differences between fertile but under-performing bulls with less than satisfactory AI fertility and top bulls with highest AI fertility. Both genes also show non-synonymous polymorphisms in humans. AIM 1 of this project will employ genotyping and in silico search to identify genetic differences between fertile and subfertile bulls, including polymorphisms associated with high/low conception rates in AI, as well as those prevalent in yearling bulls that failed Breeding Soundness Evaluation (BSE). We hypothesize that fertile bulls fall on the opposite ends of fertility range due to identifiable polymorphisms in relatively few genes controlling spermatogenesis, sperm phenotype and sperm function. AIM 2 will use a combination of proteomic and cell biological approaches, including but not limited to innovative image based flow cytometry (IBFC), to link genetic fertility traits to the sperm phenotypes easily measurable in a semen sample. Based on the identification of sperm antigens expressed only or predominantly by carriers of the fertility-affecting mutations, we will develop multiplex, flow cytometry-based high throughput semen quality assays for routine use in field AI. We hypothesize that a non-synonymous change in a gene controlling spermatogenesis or sperm function will alter the sperm phenotype via change in the quantity, localization and/or function of a sperm or embryo protein encoded by this gene, thus influencing fertility of the carrier male. Altogether, we expect to identify and validate sperm phenotype biomarkers encoded by fertility associated polymorphic genes, and to improve sire management by genetic selection and objective, automated semen evaluation. This project will also yield new methods and potentially new treatments for human male and idiopathic infertility. The field of reproductive biology will be advanced through better understanding of the link between male genotype and sperm phenotype.