对于波兰霍尔斯坦人群的牛奶产量和牛奶成分的多谱单阶段基因组预测
Hasan Önder1, Beata Sitskowska2, Burcu Kurnaz1
1Department of Animal Science, Ondokuz Mayis University, Samsun 55139, Türkiye.
Animals : an open access journal from MDPI
|October 14, 2023
概括
与单一特征模型相比,多特征基因组预测模型在波兰荷尔斯坦弗里西亚牛的遗传性和遗传相关性估计方面提供了更高的准确性. 这些模型对乳牛养殖有好处.
科学领域:
- 动物遗传学动物遗传学
- 量化遗传学 量化遗传学
- 乳制品科学 乳制品科学
背景情况:
- 基因组预测模型对于估计牲畜中的遗传参数至关重要.
- 了解遗传性和遗传相关性对于乳牛有效的繁殖计划至关重要.
- 波兰霍尔斯坦弗里西亚牛是乳制品生产研究的关键种群.
研究的目的:
- 评估多特征基因组预测模型的预测能力.
- 估计关键的牛奶生产特征的遗传性和遗传相关性.
- 为了比较多特征 (MT) 和单特征 (ST) 基因组预测方法.
主要方法:
- 利用了14742个SNP基因型记录,来自586只波兰霍尔斯坦弗里西亚奶牛.
- 采用了单段SSGBLUP (ST) 和多段SSGBLUP (MT) 方法.
- 分析了305天的牛奶产量 (MY),牛奶脂肪 (MF),牛奶蛋白 (MP),牛奶乳糖 (ML) 和牛奶干物质 (MDM) 的百分比.
主要成果:
- MT和ST模型显示可接受的预测准确度 (MT为0.7700.882,ST为0.7730.876).
- 牛奶蛋白的遗传性最高 (MP,0.3029),牛奶乳糖的遗传性最低 (ML,0.2171).
- 牛奶干物质 (MDM) 和牛奶脂肪 (MF) (0.4990) 之间是最强的遗传相关性;牛奶产量 (MY) 和ML (0.001) 之间是最弱的.
结论:
- 多特征基因组预测比单特征预测有潜在的好处.
- 牛奶产量和成分特征的遗传概率估计一般较低,正如预期的那样.
- 遗传相关性各不相同,有些特征表现出比其他特征更强烈的相互关系.
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