Linking Fertility-Associated Gene Polymorphisms to Aberrant Sperm Phenotypes

萨托夫斯基，彼得-警察局 摘要 本项目与RFA PAR-13-204的目标直接相关，具有双重用途和双重效益：研究 使用农业上重要的家养物种的生物医学和农业。这将是第一个系统地 将影响男性生育能力的遗传特征与人类/动物精液样本中容易测量的精子表型联系起来。 全基因组测序发现了大量可能影响男性的基因多态。 人类和牲畜的生育能力。然而，对于这些多态如何影响 精子表型、受精能力及其对胚胎前期发育和早期胚胎的影响 损失。我们假设，在精子发生和精子发生前阶段表达的基因的独特突变/多态 胚胎发育(更进一步的“生育相关基因”)是导致男性亚生育和早期胚胎丧失的原因。 在怀孕期间。我们的目标是将这些遗传特征与精液样本中可测量的精子表型联系起来 通过雄性在体内和体外的生育能力来反映。我们选择人工授精(AI)公牛作为模型系统是因为 他们的基因类型是公众可以接触到的，他们有大量的人工智能服务的生育记录，他们在体内的生育能力 与他们的体外受精率有关。我们已经确定了3601个功能丧失的候选生育相关基因 代表18个品种的219头公牛全基因组序列的Lof)多态性 对几个候选基因产物的分析表明，可生育但表现不佳的基因产品之间存在显著差异 AI生育力不太令人满意的公牛和AI生育力最高的顶级公牛。这两个基因也显示出非同义词 人类的多态现象。 该项目的目标1将使用基因分型和电子搜索来识别可生育和可生育的基因差异 不育公牛，包括与人工智能中高/低受孕率相关的多态，以及在 未通过繁殖健康评估(BSE)的一岁公牛。我们假设有生育能力的公牛落在相反的两端 由于控制精子发生的相对较少的基因存在可识别的多态而导致的生育范围 表型和精子功能。目标2将使用蛋白质组学和细胞生物学方法的组合，包括 不仅限于创新的基于图像的流式细胞术(IBFC)，将遗传生育特征与精子表型联系起来 在精液样本中很容易测量到。基于只表达或主要表达于 携带影响生育能力的突变，我们将开发基于多重、流式细胞术的高通量精液 用于现场人工智能常规使用的质量分析。我们假设，控制基因的非同义变化 精子发生或精子功能会通过改变精子的数量、定位和/或改变精子表型 该基因编码的精子或胚胎蛋白的功能，从而影响携带该基因的男性的生育能力。 总之，我们希望识别和验证由生育相关多态编码的精子表型生物标记物。 并通过基因选择和客观、自动化的精液评估来改进父本管理。这个项目 还将产生治疗人类男性和特发性不育症的新方法和潜在的新疗法。这一领域 通过更好地了解男性基因型和精子之间的联系，生殖生物学将得到进一步发展 表型。

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.