PDF(Pubmed)
Abstract：
OBJECTIVE: This study aims to investigate the genetic structure and characteristics of the Angus cattle population in Hungary. The survey was performed with the assistance of the Hungarian Hereford, Angus, Galloway Association (HHAGA).
METHODS: Genetic parameters of 1,369 animals from 16 Angus herds were analyzed using the genotyping results of 12 microsatellite markers with the aid of PowerMarker, Genalex, GDA-NT2021, and STRUCTURE software. Genotyping of DNA was performed using an automated genetic analyzer. Based on pairwise identity by state values of animals, the Python networkx 2.3 library was used for network analysis of the breed and to identify the central animals.
RESULTS: The observed numbers of alleles on the 12 loci under investigation ranged from 11 to 18. The average effective number of alleles was 3.201. The overall expected heterozygosity was 0.659 and the observed heterozygosity was 0.710. Four groups were detected among the 16 Angus herds. The breeders\' information validated the grouping results and facilitated the comparison of birth weight, age at first calving, number of calves born and productive lifespan data between the four groups, revealing significant differences. We identified the central animals/herd of the Angus population in Hungary. The match of our group descriptions with the phenotypic data provided by the breeders further underscores the value of cooperation between breeders and researchers.
CONCLUSIONS: The observation that significant differences in the measured traits occurred among the identified groups paves the way to further enhancement of breeding efficiency. Our findings have the potential to aid the development of new breeding strategies and help breeders keep the Angus populations in Hungary under genetic supervision. Based on our results the efficient use of an upcoming genomic selection can, in some cases, significantly improve birth weight, age at first calving, number of calves born and the productive lifespan of animals.
METHODS: Genetic parameters of 1,369 animals from 16 Angus herds were analyzed using the genotyping results of 12 microsatellite markers with the aid of PowerMarker, Genalex, GDA-NT2021, and STRUCTURE software. Genotyping of DNA was performed using an automated genetic analyzer. Based on pairwise identity by state values of animals, the Python networkx 2.3 library was used for network analysis of the breed and to identify the central animals.
RESULTS: The observed numbers of alleles on the 12 loci under investigation ranged from 11 to 18. The average effective number of alleles was 3.201. The overall expected heterozygosity was 0.659 and the observed heterozygosity was 0.710. Four groups were detected among the 16 Angus herds. The breeders\' information validated the grouping results and facilitated the comparison of birth weight, age at first calving, number of calves born and productive lifespan data between the four groups, revealing significant differences. We identified the central animals/herd of the Angus population in Hungary. The match of our group descriptions with the phenotypic data provided by the breeders further underscores the value of cooperation between breeders and researchers.
CONCLUSIONS: The observation that significant differences in the measured traits occurred among the identified groups paves the way to further enhancement of breeding efficiency. Our findings have the potential to aid the development of new breeding strategies and help breeders keep the Angus populations in Hungary under genetic supervision. Based on our results the efficient use of an upcoming genomic selection can, in some cases, significantly improve birth weight, age at first calving, number of calves born and the productive lifespan of animals.
摘要：
目的：本研究旨在调查匈牙利安格斯牛种群的遗传结构和特征。这项调查是在匈牙利人赫里福德的协助下进行的，安格斯,加洛韦协会（HHAGA）。
方法：在PowerMarker的帮助下，使用12个微卫星标记的基因分型结果，分析了来自16个安格斯牛群的1,369只动物的遗传参数，Genalex,GDA-NT2021和STRUCTURE软件。使用自动遗传分析仪进行DNA的基因分型。基于动物状态值的成对身份，Pythonnetworkx2.3库用于品种的网络分析和识别中心动物。
结果：在研究的12个基因座上观察到的等位基因数量范围为11至18。平均有效等位基因数为3.201。总体预期杂合性为0.659,观测杂合性为0.710。在16个安格斯牛群中检测到四组。育种者的信息验证了分组结果，并促进了出生体重的比较，第一次产牛的年龄，四组之间出生的小牛数量和生产寿命数据，揭示了显著的差异。我们确定了匈牙利安格斯种群的中心动物/畜群。我们的小组描述与育种者提供的表型数据的匹配进一步强调了育种者与研究人员之间合作的价值。
结论：所确定的群体之间测量性状的显着差异为进一步提高育种效率铺平了道路。我们的发现有可能帮助开发新的育种策略，并帮助育种者将匈牙利的安格斯种群保持在遗传监督下。根据我们的结果，有效利用即将到来的基因组选择可以，在某些情况下,显著提高出生体重，第一次产牛的年龄，出生的小牛数量和动物的生产寿命。
方法：在PowerMarker的帮助下，使用12个微卫星标记的基因分型结果，分析了来自16个安格斯牛群的1,369只动物的遗传参数，Genalex,GDA-NT2021和STRUCTURE软件。使用自动遗传分析仪进行DNA的基因分型。基于动物状态值的成对身份，Pythonnetworkx2.3库用于品种的网络分析和识别中心动物。
结果：在研究的12个基因座上观察到的等位基因数量范围为11至18。平均有效等位基因数为3.201。总体预期杂合性为0.659,观测杂合性为0.710。在16个安格斯牛群中检测到四组。育种者的信息验证了分组结果，并促进了出生体重的比较，第一次产牛的年龄，四组之间出生的小牛数量和生产寿命数据，揭示了显著的差异。我们确定了匈牙利安格斯种群的中心动物/畜群。我们的小组描述与育种者提供的表型数据的匹配进一步强调了育种者与研究人员之间合作的价值。
结论：所确定的群体之间测量性状的显着差异为进一步提高育种效率铺平了道路。我们的发现有可能帮助开发新的育种策略，并帮助育种者将匈牙利的安格斯种群保持在遗传监督下。根据我们的结果，有效利用即将到来的基因组选择可以，在某些情况下,显著提高出生体重，第一次产牛的年龄，出生的小牛数量和动物的生产寿命。
