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巴西的红信德牛:种群结构与分布

Red Sindhi cattle in Brazil: population structure and distribution.

作者信息

Panetto J C C, Silva M V G B, Leite R M H, Machado M A, Bruneli F A T, Reis D R L, Peixoto M G C D, Verneque R S

机构信息

Embrapa Gado de Leite, Juiz de Fora, MG, Brasil

Embrapa Gado de Leite, Juiz de Fora, MG, Brasil.

出版信息

Genet Mol Res. 2017 Mar 15;16(1):gmr-16-01-gmr.16019501. doi: 10.4238/gmr16019501.

DOI:10.4238/gmr16019501
PMID:28301672
Abstract

The Red Sindhi cattle breed was imported to Brazil in small numbers. Nowadays, the herds of this breed are distributed in the Northeast, Southeast and Midwest regions of the country. In this study, DNA samples of animals originating from 15 herds in the Northeast and Southeast regions have been analyzed to obtain the ancestry proportions, and to gain a better understanding of the current population structure of this breed in Brazil. Samples were genotyped using three different single nucleotide polymorphism (SNP) marker panels. Those markers have been used with the approach of unsupervised hierarchical clustering of individuals, and consequently, the ancestry of the population was divided into six different subpopulations. Three of those ancestry subpopulations were identified to be present in various different herds, while the other three were restricted to only one or two herds each. One of those herds has been kept isolated for more than 30 years, and it was identified to contain two almost exclusive subpopulations. To avoid important losses in the genetic diversity within the Red Sindhi breed in Brazil, we recommend the identification of superior sires from every subpopulation in the establishment of a breeding program for this breed.

摘要

红信德牛品种少量引进到了巴西。如今,该品种的牛群分布在该国的东北部、东南部和中西部地区。在本研究中,对来自东北部和东南部地区15个牛群的动物DNA样本进行了分析,以获得祖先比例,并更好地了解巴西该品种目前的种群结构。使用三种不同的单核苷酸多态性(SNP)标记面板对样本进行基因分型。这些标记已用于个体无监督层次聚类的方法,因此,该种群的祖先被分为六个不同的亚群。其中三个祖先亚群在不同的牛群中都有发现,而其他三个亚群则分别只限于一两个牛群。其中一个牛群已经隔离了30多年,并且被确定包含两个几乎独立的亚群。为避免巴西红信德牛品种内的遗传多样性出现重大损失,我们建议在为该品种建立育种计划时,从每个亚群中识别出优良种公牛。

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引用本文的文献

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Trop Anim Health Prod. 2020 Jan;52(1):273-281. doi: 10.1007/s11250-019-02009-7. Epub 2019 Aug 1.