Berthouly C, Do Ngoc D, Thévenon S, Bouchel D, Van T Nhu, Danes C, Grosbois V, Thanh H Hoang, Chi C Vu, Maillard J-C
CIRAD, UPR AGIRs, Campus International de Baillarguet, 34398 Montpellier Cedex 05, France.
Mol Ecol. 2009 Oct;18(19):3980-91. doi: 10.1111/j.1365-294X.2009.04342.x. Epub 2009 Sep 7.
Assessing how genes flow across populations is a key component of conservation genetics. Gene flow in a natural population depends on ecological traits and the local environment, whereas for a livestock population, gene flow is driven by human activities. Spatial organization, relationships between farmers and their husbandry practices will define the farmer's network and so determine farmer connectivity. It is thus assumed that farmer connectivity will affect the genetic structure of their livestock. To test this hypothesis, goats reared by four different ethnic groups in a Vietnamese province were genotyped using 16 microsatellites. A Bayesian approach and spatial multivariate analysis (spatial principal component analysis, sPCA) were used to identify subpopulations and spatial organization. Ethnic group frequencies, husbandry practices and altitude were used to create cost maps that were implemented in a least-cost path approach. Genetic diversity in the Vietnamese goat population was low (0.508) compared to other local Asian breeds. Using a Bayesian approach, three clusters were identified. sPCA confirmed these three clusters and also that the genetic structure showed a significant spatial pattern. The least-cost path analysis showed that genetic differentiation was significantly correlated (0.131-0.207) to ethnic frequencies and husbandry practices. In brief, the spatial pattern observed in the goat population was the result of complex gene flow governed by the spatial distribution of ethnic groups, ethnicity and husbandry practices. In this study, we clearly linked the livestock genetic pattern to farmer connectivity and showed the importance of taking into account spatial information in genetic studies.
评估基因如何在种群间流动是保护遗传学的关键组成部分。自然种群中的基因流动取决于生态特征和当地环境,而对于畜牧种群来说,基因流动则由人类活动驱动。空间组织、农民及其养殖方式之间的关系将界定农民网络,从而决定农民之间的连通性。因此可以假定,农民之间的连通性会影响其牲畜的遗传结构。为了验证这一假设,对越南一个省份中四个不同民族饲养的山羊进行了基因分型,使用了16个微卫星。采用贝叶斯方法和空间多变量分析(空间主成分分析,sPCA)来识别亚种群和空间组织。利用民族频率、养殖方式和海拔创建成本地图,并将其应用于最小成本路径法。与其他亚洲本地品种相比,越南山羊种群的遗传多样性较低(0.508)。采用贝叶斯方法,识别出了三个聚类。sPCA证实了这三个聚类,并且遗传结构呈现出显著的空间模式。最小成本路径分析表明,遗传分化与民族频率和养殖方式显著相关(0.131 - 0.207)。简而言之,在山羊种群中观察到的空间模式是由民族、种族和养殖方式的空间分布所支配的复杂基因流动的结果。在本研究中,我们明确地将牲畜的遗传模式与农民之间的连通性联系起来,并展示了在遗传研究中考虑空间信息的重要性。