Identification of genomic variants causing sperm abnormalities and reduced male fertility.
Identification of genomic variants causing sperm abnormalities and reduced male fertility.
复制标题
鉴定基因组变异，导致精子异常和雄性生育能力降低。
DOI：
10.1016/j.anireprosci.2018.02.007
复制
发表时间：
2018-07
影响因子：
2.2
通讯作者：
Sutovsky P
中科院分区：
文献类型：
--
作者：
Taylor JF;Schnabel RD;Sutovsky P
全基因组测序已鉴定出数百万个牛基因变异；然而，目前人们对哪些变异影响男性生育能力知之甚少。我们必须开始通过分析精液样本和测量具有替代基因型的公牛的生育力，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，因为有大量的生育记录（以公牛受孕率 (SCR) 衡量）。通过对具有高或低 SCR 鉴定为未通过育种健全性评估的成年 AI 公牛或一岁公牛的可育和低生育力或不育公牛的基因组进行测序，可以识别对生育力具有中度至大影响的遗传变异。低生育力/不育公牛序列中频率丰富的变体，特别是那些可能导致蛋白质功能丧失或预测对涉及精子蛋白质结构和功能、精液质量或精子形态的基因严重有害的变体，可以设计用于基因分型测定，以验证其对生育力的影响。高通量传统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，改进公牛种马的常规精液测试，并确定精液纳米纯化等具有成本效益的人工智能剂量优化方法的新目标。这将最大限度地提高遗传优越的公牛的精液产量，并提高牛的生育能力。更好地了解男性基因型和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。
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.
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