BackgroundAmong the European countries, Italy counts the largest number of local goat breeds. Thanks to the recent availability of a medium-density SNP (single nucleotide polymorphism) chip for goat, the genetic diversity of Italian goat populations was characterized by genotyping samples from 14 Italian goat breeds that originate from different geographical areas with more than 50 000 SNPs evenly distributed on the genome.ResultsAnalysis of the genotyping data revealed high levels of genetic polymorphism and an underlying North–south geographic pattern of genetic diversity that was highlighted by both the first dimension of the multi-dimensional scaling plot and the Neighbour network reconstruction. We observed a moderate and weak population structure in Northern and Central-Southern breeds, respectively, with pairwise FST values between breeds ranging from 0.013 to 0.164 and 7.49 % of the total variance assigned to the between-breed level. Only 2.11 % of the variance explained the clustering of breeds into geographical groups (Northern, Central and Southern Italy and Islands).ConclusionsOur results indicate that the present-day genetic diversity of Italian goat populations was shaped by the combined effects of drift, presence or lack of gene flow and, to some extent, by the consequences of traditional management systems and recent demographic history. Our findings may constitute the starting point for the development of marker-assisted approaches, to better address future breeding and management policies in a species that is particularly relevant for the medium- and long-term sustainability of marginal regions.Electronic supplementary materialThe online version of this article (doi:10.1186/s12711-015-0140-6) contains supplementary material, which is available to authorized users.

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Domestic species such as cattle (Bos taurus taurus and B. t. indicus) represent attractive biological models to characterize the genetic basis of short‐term evolutionary response to climate pressure induced by their post‐domestication history. Here, using newly generated dense SNP genotyping data, we assessed the structuring of genetic diversity of 21 autochtonous cattle breeds from the whole Mediterranean basin and performed genome‐wide association analyses with covariables discriminating the different Mediterranean climate subtypes. This provided insights into both the demographic and adaptive histories of Mediterranean cattle. In particular, a detailed functional annotation of genes surrounding variants associated with climate variations highlighted several biological functions involved in Mediterranean climate adaptation such as thermotolerance, UV protection, pathogen resistance or metabolism with strong candidate genes identified (e.g., NDUFB3, FBN1, METTL3, LEF1, ANTXR2 and TCF7). Accordingly, our results suggest that main selective pressures affecting cattle in Mediterranean area may have been related to variation in heat and UV exposure, in food resources availability and in exposure to pathogens, such as anthrax bacteria (Bacillus anthracis). Furthermore, the observed contribution of the three main bovine ancestries (indicine, European and African taurine) in these different populations suggested that adaptation to local climate conditions may have either relied on standing genomic variation of taurine origin, or adaptive introgression from indicine origin, depending on the local breed origins. Taken together, our results highlight the genetic uniqueness of local Mediterranean cattle breeds and strongly support conservation of these populations.

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BackgroundThe detection of regions that affect quantitative traits (QTL), to implement selection assisted by molecular information, remains of particular interest in dairy sheep for which genetic gain is constrained by the high costs of large-scale phenotype and pedigree recording. QTL detection based on the combination of linkage disequilibrium and linkage analysis (LDLA) is the most suitable approach in family-structured populations. The main issue in performing LDLA mapping is the handling of the identity-by-descent (IBD) probability matrix. Here, we propose the use of principal component analysis (PCA) to perform LDLA mapping for milk traits in Sarda dairy sheep.MethodsA resource population of 3731 ewes belonging to 161 sire families and genotyped with the OvineSNP50 Beadchip was used to map genomic regions that affect five milk traits. The paternally and maternally inherited gametes of genotyped individuals were reconstructed and IBD probabilities between them were defined both at each SNP position and at the genome level. A QTL detection model fitting fixed effects of principal components that summarize IBD probabilities was tested at each SNP position. Genome-wide (GW) significance thresholds were determined by within-trait permutations.ResultsPCA resulted in substantial dimensionality reduction, in fact 137 and 32 (on average) principal components were able to capture 99% of the IBD variation at the locus and genome levels, respectively. Overall, 2563 positions exceeded the 0.05 GW significance threshold for at least one trait, which clustered into 75 QTL regions most of which affected more than one trait. The strongest signal was obtained for protein content on Ovis aries (OAR) chromosome 6 and overlapped with the region that harbours the casein gene cluster. Additional interesting positions were identified on OAR4 for fat content and on OAR11 for the three yield traits.ConclusionsPCA is a good strategy to summarize IBD probabilities. A large number of regions associated to milk traits were identified. The outputs provided by the proposed method are useful for the selection of candidate genes, which need to be further investigated to identify causative mutations or markers in strong LD with them for application in selection programs assisted by molecular information.