Taylor Jeremy F, Schnabel Robert D, Sutovsky Peter
Division of Animal Sciences, University of Missouri, Columbia, MO, 65211, USA.
Division of Animal Sciences, University of Missouri, Columbia, MO, 65211, USA.
Anim Reprod Sci. 2018 Jul;194:57-62. doi: 10.1016/j.anireprosci.2018.02.007. Epub 2018 Feb 10.
Whole genome sequencing has identified millions of bovine genetic variants; however, there is currently little understanding about which variants affect male fertility. It is imperative that we begin to link detrimental genetic variants to sperm phenotypes via the analysis of semen samples and measurement of fertility for bulls with alternate genotypes. Artificial insemination (AI) bulls provide a useful model system because of extensive fertility records, measured as sire conception rates (SCR). Genetic variants with moderate to large effects on fertility can be identified by sequencing the genomes of fertile and subfertile or infertile sires identified with high or low SCR as adult AI bulls or yearling bulls that failed Breeding Soundness Evaluation. Variants enriched in frequency in the sequences of subfertile/infertile bulls, particularly those likely to result in the loss of protein function or predicted to be severely deleterious to genes involved in sperm protein structure and function, semen quality or sperm morphology can be designed onto genotyping assays for validation of their effects on fertility. High throughput conventional and image-based flow cytometry, proteomics and cell imaging can be used to establish the functional effects of variants on sperm phenotypes. Integrating the genetic, fertility and sperm phenotype data will accelerate biomarker discovery and validation, improve routine semen testing in bull studs and identify new targets for cost-efficient AI dose optimization approaches such as semen nanopurification. This will maximize semen output from genetically superior sires and will increase the fertility of cattle. Better understanding of the relationships between male genotype and sperm phenotype may also yield new diagnostic tools and treatments for human male and idiopathic infertility.
全基因组测序已鉴定出数百万个牛的遗传变异;然而,目前对于哪些变异会影响雄性生育力却知之甚少。我们必须通过分析精液样本以及测量具有不同基因型公牛的生育力,将有害的遗传变异与精子表型联系起来。人工授精(AI)公牛提供了一个有用的模型系统,因为有广泛的生育力记录,以父本受胎率(SCR)来衡量。对生育力有中度至较大影响的遗传变异,可以通过对成年AI公牛或一岁公牛中,根据SCR高或低鉴定为可育和亚可育或不育的种公牛的基因组进行测序来识别。在亚可育/不育公牛的序列中频率富集的变异,特别是那些可能导致蛋白质功能丧失或预计对参与精子蛋白质结构和功能、精液质量或精子形态的基因有严重有害影响的变异,可以设计到基因分型检测中,以验证它们对生育力的影响。高通量传统流式细胞术和基于图像的流式细胞术、蛋白质组学和细胞成像可用于确定变异对精子表型的功能影响。整合遗传、生育力和精子表型数据将加速生物标志物的发现和验证,改善种公牛站的常规精液检测,并为精液纳米纯化等经济高效的AI剂量优化方法确定新靶点。这将使遗传上优良的种公牛的精液产量最大化,并提高牛的生育力。更好地理解男性基因型与精子表型之间的关系,也可能为人类男性和特发性不育症带来新的诊断工具和治疗方法。