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Abstract 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.

The genetic relevance of Turkish sheep has recently been revealed by mtDNA analysis, which has led to the identification of a third maternal lineage in that species. We present here a study of the genetic variation of these breeds at a nuclear level from the analysis of 30 microsatellite loci. Parameters of variability indicated a high level of variation in the breeds analysed. Mean number of alleles per locus ranged from 7.8 to 10.4 and gene diversity varied between 0.69 and 0.74. Considerable differences were detected between breeds regarding the pattern of within-breed variability. Breed-specific alleles were detected at most loci and all breeds analysed, a total of 75 private variants being identified. The Hemsin sheep showed noticeably lower genetic variation in accordance with the present status of this breed. Percentages of shared alleles (from 54.8% to 69.5%) and gene flow estimates (from 5.98 to 28.32) gave information about the relative genetic differentiation of breeds. The results presented here for nuclear DNA complement those reported for mtDNA and bear out the need to preserve this invaluable genetic material. [ABSTRACT FROM AUTHOR]

Simple Summary: Parentage misassignments directly affect genetic gain in traditional breeding programs. The use of genetic markers facilitates parentage verification. In sheep, microsatellite markers and single nucleotide polymorphism (SNP) markers have been proposed by the International Society of Animal Sciences (ISAG) for parentage testing. Since the implementation of genomic selection, the microsatellite information used for parental testing in previous generations is gradually being replaced by SNPs. However, parentage verifications should all be performed using the same technology. A strategy for transitioning from microsatellites to SNP markers, while avoiding extra genotyping costs, is the imputation of microsatellite alleles from SNP haplotypes. This study aims to identify the optimum approach, using a minimum number of SNPs to accurately impute microsatellite markers and developing a low-density SNP chip for parentage verification in the Assaf sheep breed. The imputation approach described here reached high accuracies using a low number of SNP markers, which supports the development of a low-density SNP chip that could avoid the problems of genotyping with both technologies, being a cost-effective method for parentage testing. This study will help sheep breeders to perform parentage verification when different genotyping platforms have been used across generations. Transitioning from traditional to new genotyping technologies requires the development of bridging methodologies to avoid extra genotyping costs. This study aims to identify the optimum number of single nucleotide polymorphisms (SNPs) necessary to accurately impute microsatellite markers to develop a low-density SNP chip for parentage verification in the Assaf sheep breed. The accuracy of microsatellite marker imputation was assessed with three metrics: genotype concordance (C), genotype dosage (length r2), and allelic dosage (allelic r2), for all imputation scenarios tested (0.5–10 Mb microsatellite flanking SNP windows). The imputation accuracy for the three metrics analyzed for all haplotype lengths tested was higher than 0.90 (C), 0.80 (length r2), and 0.75 (allelic r2), indicating strong genotype concordance. The window with 2 Mb length provides the best accuracy for the imputation procedure and the design of an affordable low-density SNP chip for parentage testing. We additionally evaluated imputation performance under two null models, naive (imputing the most common allele) and random (imputing by randomly selecting the allele), which in comparison showed weak genotype concordances (0.41 and 0.15, respectively). Therefore, we describe a precise methodology in the present article to impute multiallelic microsatellite genotypes from a low-density SNP chip in sheep and solve the problem of parentage verification when different genotyping platforms have been used across generations. [ABSTRACT FROM AUTHOR]

Abstract: We have examined the genetic diversity and population structure of 149 Bolivian alpacas from eight different locations in Bolivia. The analysis of 22 microsatellite loci revealed high levels of genetic diversity, similar to the results reported in other alpaca populations. This high genetic variability was sustained by the identification of a total of 258 alleles; we identified between 4 and 18 alleles per locus with high levels of observed heterozygosity that ranged from 0.611 to 0.696. The inbreeding coefficients (Fis) were positive and significantly different from zero for all of the populations except for Turco. The genetic differentiation between populations (Fst) was low to moderate with pair-wise Fst estimates ranging from 0.008 for the Curahuara–Cosapa pair, to 0.077 for the Poopó–Ayopaya and Poopó–Ulla Ulla pairs. The analysis of molecular variance (AMOVA) indicated that the total variability observed between different populations was 3.86%, whereas 96.14% of the variation was found within the populations. The population structure analysis revealed that the eight studied populations could be assigned to five differentiated clusters. In agreement with the factorial analysis of correspondence, and supported through a bootstrapping analysis to adjust for differences in population sample size, this analysis suggested a genetic isolation of the Poopó population and the influence of the Turco population on the populations linked to the Cochabamba and the Pacajes-Sajama alpaquero systems. The Ulla Ulla population showed a clear subdivision into two clusters; in addition, these two clusters had an influence on the Challapata population and less impact on the rest of the populations. The Cosapa, Lagunas and Curahuara populations showed a clear common genetic background, whereas the Ayopaya population was influenced by the five defined clusters. Despite some sampling limitations and the need of confirming the results reported here through larger datasets, overall, this study provides the first survey of the genetic diversity in Bolivian alpaca populations, which may be of great value for the development of appropriate breeding strategies for these populations. [Copyright &y& Elsevier]