Vietnamese chickens: a gate towards Asian genetic diversity.

BACKGROUND: Chickens represent an important animal genetic resource and the conservation of local breeds is an issue for the preservation of this resource. The genetic diversity of a breed is mainly evaluated through its nuclear diversity. However, nuclear genetic diversity does not provide the same information as mitochondrial genetic diversity. For the species Gallus gallus, at least 8 maternal lineages have been identified. While breeds distributed westward from the Indian subcontinent usually share haplotypes from 1 to 2 haplogroups, Southeast Asian breeds exhibit all the haplogroups. The Vietnamese Ha Giang (HG) chicken has been shown to exhibit a very high nuclear diversity but also important rates of admixture with wild relatives. Its geographical position, within one of the chicken domestication centres ranging from Thailand to the Chinese Yunnan province, increases the probability of observing a very high genetic diversity for maternal lineages, and in a way, improving our understanding of the chicken domestication process. RESULTS: A total of 106 sequences from Vietnamese HG chickens were first compared to the sequences of published Chinese breeds. The 25 haplotypes observed in the Vietnamese HG population belonged to six previously published haplogroups which are: A, B, C, D, F and G. On average, breeds from the Chinese Yunnan province carried haplotypes from 4.3 haplogroups. For the HG population, haplogroup diversity is found at both the province and the village level (0.69).The AMOVA results show that genetic diversity occurred within the breeds rather than between breeds or provinces. Regarding the global structure of the mtDNA diversity per population, a characteristic of the HG population was the occurrence of similar pattern distribution as compared to G. gallus spadiceus. However, there was no geographical evidence of gene flow between wild and domestic populations as observed when microsatellites were used. CONCLUSIONS: In contrast to other chicken populations, the HG chicken population showed very high genetic diversity at both the nuclear and mitochondrial levels. Due to its past and recent history, this population accumulates a specific and rich gene pool highlighting its interest and the need for conservation.

How does farmer connectivity influence livestock genetic structure? A case-study in a Vietnamese goat population.

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.