Differentiation among Spanish sheep breeds using microsatellites
- 3k Downloads
Genetic variability at 18 microsatellites was analysed on the basis of individual genotypes in five Spanish breeds of sheep – Churra, Latxa, Castellana, Rasa-Aragonesa and Merino -, with Awassi also being studied as a reference breed. The degree of population subdivision calculated between Spanish breeds from FST diversity indices was around 7% of total variability. A high degree of reliability was obtained for individual-breed assignment from the 18 loci by using different approaches among which the Bayesian method provided to be the most efficient, with an accuracy for nine microsatellites of over 99%. Analysis of the Bayesian assignment criterion illustrated the divergence between any one breed and the others, which was highest for Awassi sheep, while no great differences were evident among the Spanish breeds. Relationships between individuals were analysed from the proportion of shared alleles. The resulting dendrogram showed a remarkable breed structure, with the highest level of clustering among members of the Spanish breeds in Latxa and the lowest in Merino sheep, the latter breed exhibiting a peculiar pattern of clustering, with animals grouped into several closely set nodes. Analysis of individual genotypes provided valuable information for understanding intra- and inter-population genetic differences and allowed for a discussion with previously reported results using populations as taxonomic units.
Keywordsmicrosatellites sheep breeds population assignment individual clustering analysis
(To access the full article, please see PDF)
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.