Identification of high utility SNPs for population assignment and traceability purposes in the pig using high-throughput sequencing

The objectives of this study were to develop breed-specific single nucleotide polymorphisms (SNPs) in five pig breeds sequenced with Illumina's Genome Analyzer and to investigate their usefulness for breed assignment purposes. DNA pools were prepared for Duroc, Landrace, Large White, Pietrain and Wild Boar. The total number of animals used for sequencing was 153. SNP discovery was performed by aligning the filtered reads against Build 7 of the pig genome. A total of 313,964 high confidence SNPs were identified and analysed for the presence of breed-specific SNPs (defined in this context as SNPs for which one of the alleles was detected in only one breed). There were 29,146 putative breed-specific SNPs identified, of which 4441 were included in the PorcineSNP60 beadchip. Upon re-examining the genotypes obtained using the beadchip, 193 SNPs were confirmed as being breed specific. These 193 SNPs were subsequently used to assign an additional 490 individuals from the same breeds, using the sequenced individuals as reference populations. In total, four breed assignment tests were performed. Results showed that for all methods tested 99% of the animals were correctly assigned, with an average probability of assignment of at least 99.2%, indicating the high utility of breed-specific markers for breed assignment and traceability. This study provides a blueprint for the way next-generation sequencing technologies can be used for the identification of breed-specific SNPs, as well as evidence that these SNPs may be a powerful tool for breed assignment and traceability of animal products to their breeds of origin.     

On the way to functional agro biodiversity: coat colour gene variability in goats

Functional agro biodiversity defines the exploitation of biodiversity to provide ecosystem services, support sustainable agricultural production and benefit the regional and global environment and the public at large (ELN-FAB, 2009; www.eln_fab.eu). Tracking of animal products back to the breed of origin based on their genetic make-up undoubtedly falls in this category. The aim of this paper was to identify and validate a set of single nucleotide polymorphisms (SNPs) in goat coat colour genes, most of which have not been investigated before, to trace five goat populations of the Italian Alps and their product. Several regions of 28 genes influencing coat colour pathways were amplified in eight animals (two per breed). Sequence comparison revealed 48 SNPs and three INDEL (INsertion DELetion). No breed-specific alleles were detected; however, several SNPs showed an uneven frequency distribution between breeds. In BIO, the genotype frequency distribution of a non-synonymous SNP suggested a possible role of TYRP1 in brown eumelanic goat coat colour. A total of 29 independent SNPs in 20 genes were selected and used to allocate 159 minimally related goat samples using STRUCTURE 2.2 and GeneClass 2 software. STRUCTURE 2.2 assigns 99% of individuals to the correct breed considering the prior information on putative breed of origin for each sample and 81% using only the genotypic data. The three algorithms available in GeneClass 2 performed with nearly equal efficiency, with 86% and 87% correct allocations. All the methods yielded an average probability of assignment >0.92 and a specificity index >0.86. Despite their coat colour variability, individuals belonging to ORO were fully assigned, showing that, in the absence of a breed-specific allele tied to coat colour, the best assignment resulted for the most genetically distinct breed. The lowest rate of correct assignment was observed in Verzaschese (73%), not ascertained in the breed panel used in the SNP discovery phase.     

Ultra-low-density genotype panels for breed assignment of Angus and Hereford cattle

Angus and Hereford beef is marketed internationally for apparent superior meat quality attributes; DNA-based breed authenticity could be a useful instrument to ensure consumer confidence on premium meat products. The objective of this study was to develop an ultra-low-density genotype panel to accurately quantify the Angus and Hereford breed proportion in biological samples. Medium-density genotypes (13 306 single nucleotide polymorphisms (SNPs)) were available on 54 703 commercial and 4042 purebred animals. The breed proportion of the commercial animals was generated from the medium-density genotypes and this estimate was regarded as the gold-standard breed composition. Ten genotype panels (100 to 1000 SNPs) were developed from the medium-density genotypes; five methods were used to identify the most informative SNPs and these included the Delta statistic, the fixation (F_st) statistic and an index of both. Breed assignment analyses were undertaken for each breed, panel density and SNP selection method separately with a programme to infer population structure using the entire 13 306 SNP panel (representing the gold-standard measure). Breed assignment was undertaken for all commercial animals (n=54 703), animals deemed to contain some proportion of Angus based on pedigree (n=5740) and animals deemed to contain some proportion of Hereford based on pedigree (n=5187). The predicted breed proportion of all animals from the lower density panels was then compared with the gold-standard breed prediction. Panel density, SNP selection method and breed all had a significant effect on the correlation of predicted and actual breed proportion. Regardless of breed, the Index method of SNP selection numerically (but not significantly) outperformed all other selection methods in accuracy (i.e. correlation and root mean square of prediction) when panel density was ⩾300 SNPs. The correlation between actual and predicted breed proportion increased as panel density increased. Using 300 SNPs (selected using the global index method), the correlation between predicted and actual breed proportion was 0.993 and 0.995 in the Angus and Hereford validation populations, respectively. When SNP panels optimised for breed prediction in one population were used to predict the breed proportion of a separate population, the correlation between predicted and actual breed proportion was 0.034 and 0.044 weaker in the Hereford and Angus populations, respectively (using the 300 SNP panel). It is necessary to include at least 300 to 400 SNPs (per breed) on genotype panels to accurately predict breed proportion from biological samples.     

Population structure and breed composition prediction in a multi-breed sheep population using genome-wide single nucleotide polymorphism genotypes

Knowledge of population structure and breed composition of a population can be advantageous for a number of reasons; these include designing optimal (cross)breeding strategies in order to maximise non-additive genetic effects, maintaining flockbook integrity by authenticating animals being registered and as a quality control measure in the genotyping process. The objectives of the present study were to 1) describe the population structure of 24 sheep breeds, 2) quantify the breed composition of both flockbook-recorded and crossbred animals using single nucleotide polymorphism BLUP (SNP-BLUP), and 3) quantify the accuracy of breed composition prediction from low-density genotype panels containing between 2000 and 6000 SNPs. In total, 9334 autosomal SNPs on 11 144 flockbook-recorded animals and 1172 crossbred animals were used. The population structure of all breeds was characterised by principal component analysis (PCA) as well as the pairwise breed fixation index (F_st). The total number of animals, all of which were purebred, included in the calibration population for SNP-BLUP was 2579 with the number of animals per breed ranging from 9 to 500. The remaining 9559 flockbook-recorded animals, composite breeds and crossbred animals represented the test population; three breeds were excluded from breed composition prediction. The breed composition predicted using SNP-BLUP with 9334 SNPs was considered the gold standard prediction. The pairwise breed F_st ranged from 0.040 (between the Irish Blackface and Scottish Blackface) to 0.282 (between the Border Leicester and Suffolk). Principal component analysis revealed that the Suffolk from Ireland and the Suffolk from New Zealand formed distinct, non-overlapping clusters. In contrast, the Texel from Ireland and that from New Zealand formed integrated, overlapping clusters. Composite animals such as the Belclare clustered close to its founder breeds (i.e., Finn, Galway, Lleyn and Texel). When all 9334 SNPs were used to predict breed composition, an animal that had a majority breed proportion predicted to be ≥0.90 was defined as purebred for the present study. As the panel density decreased, the predicted breed proportion threshold, used to identify animals as purebred, also decreased (≥0.85 with 6000 SNPs to ≥0.60 with 2000 SNPs). In all, results from the study suggest that breed composition for purebred and crossbred animals can be determined with SNP-BLUP using ≥5000 SNPs.     

A machine learning approach for the identification of population-informative markers from high-throughput genotyping data: application to several pig breeds

Single nucleotide polymorphisms (SNPs) able to describe population differences can be used for important applications in livestock, including breed assignment of individual animals, authentication of mono-breed products and parentage verification among several other applications. To identify the most discriminating SNPs among thousands of markers in the available commercial SNP chip tools, several methods have been used. Random forest (RF) is a machine learning technique that has been proposed for this purpose. In this study, we used RF to analyse PorcineSNP60 BeadChip array genotyping data obtained from a total of 2737 pigs of 7 Italian pig breeds (3 cosmopolitan-derived breeds: Italian Large White, Italian Duroc and Italian Landrace, and 4 autochthonous breeds: Apulo-Calabrese, Casertana, Cinta Senese and Nero Siciliano) to identify breed informative and reduced SNP panels using the mean decrease in the Gini Index and the Mean Decrease in Accuracy parameters with stability evaluation. Other reduced informative SNP panels were obtained using Delta, Fixation index and principal component analysis statistics, and their performances were compared with those obtained using the RF-defined panels using the RF classification method and its derived Out Of Bag rates and correct prediction proportions. Therefore, the performances of a total of six reduced panels were evaluated. The correct assignment of the animals to its breed was close to 100% for all tested approaches. Porcine chromosome 8 harboured the largest number of selected SNPs across all panels. Many SNPs were included in genomic regions in which previous studies identified signatures of selection or genes (e.g. ESR1, KITL and LCORL) that could contribute to explain, at least in part, phenotypically or economically relevant traits that might differentiate cosmopolitan and autochthonous pig breeds. Random forest used as preselection statistics highlighted informative SNPs that were not the same as those identified by other methods. This might be due to specific features of this machine learning methodology. It will be interesting to explore if the adaptation of RF methods for the identification of selection signature regions could be able to describe population-specific features that are not captured by other approaches.     

Breed assignment of Italian cattle using biallelic AFLP markers

The verification of the breed origin of animal products is relevant for food safety and authenticity. We assessed the suitability of AFLP molecular markers in the assignment of cattle individuals to their breed of origin. Three hundred and ninety-six animals belonging to 16 cattle breeds genotyped with 141 AFLP markers were used as reference data set. Assignment was performed with likelihood (aflpop) and Bayesian (structure) methods. The Bayesian approach was superior to the likelihood algorithm with respect to (i) the correct assignment of simulated individuals to their breed of origin (93% vs. 81% respectively), (ii) the correct assignment of 44 sampled Romagnola animals (91% vs. 45% respectively) and (iii) the correct classification of animals belonging to a breed that was not included within the reference dataset. Thus, AFLP profiling in combination with the Bayesian approach seems a useful tool for breed assignment.     

An empirical assessment of individual-based population genetic statistical techniques: application to British pig breeds

Recently developed Bayesian genotypic clustering methods for analysing genetic data offer a powerful tool to evaluate the genetic structure of domestic farm animal breeds. The unit of study with these approaches is the individual instead of the population. We aimed to empirically evaluate various individual-based population genetic statistical methods for characterization of genetic diversity and structure of livestock breeds. Eighteen British pig populations, comprising 819 individuals, were genotyped at 46 microsatellite markers. Three Bayesian genotypic clustering approaches, principle component analysis (PCA) and phylogenetic reconstruction were applied to individual multilocus genotypes to infer the genetic structure and diversity of the British pig breeds. Comparisons of the three Bayesian genotypic clustering methods (, and ) revealed some broad similarities but also some notable differences. Overall, the methods agreed that majority of the British pig breeds are independent genetic units with little evidence of admixture. The three Bayesian genotypic clustering methods provided complementary, biologically credible clustering solutions but at different levels of resolution. detected finer genetic differentiation and in some cases, populations within breeds. Consequently, it estimated a greater number of underlying genetic populations (K, in the notation of Bayesian clustering methods). Two of the Bayesian methods ( and ) and phylogenetic reconstruction provided similar success in assignment of individuals, supporting the use of these methods for breed assignment.     

Assessing SNP markers for assigning individuals to cattle populations

The effectiveness of single nucleotide polymorphisms (SNPs) for the assignment of cattle to their source breeds was investigated by analysing a panel of 90 SNPs assayed on 24 European breeds. Breed assignment was performed by comparing the Bayesian and frequentist methods implemented in the structure 2.2 and geneclass 2 software programs. The use of SNPs for the reallocation of known individuals to their breeds of origin and the assignment of unknown individuals was tested. In the reallocation tests, the methods implemented in structure 2.2 performed better than those in geneclass 2 , with 96% vs. 85% correct assignments respectively. In contrast, the methods implemented in geneclass 2 showed a greater correct assignment rate in allocating animals treated as unknowns to a reference dataset (62% vs. 51% and 80% vs. 65% in field tests 1 and 2 respectively). These results demonstrate that SNPs are suitable for the assignment of individuals to reference breeds. The results also indicate that structure 2.2 and geneclass 2 can be complementary tools to assess breed integrity and assignment. Our findings also stress the importance of a high-quality reference dataset in allocation studies.     

Population Growth in Planaria Dugesia tigrina (Gerard) : Regulation by the absolute number in the population

Planaria reproduce by transverse fission. Isolated worms increase in number exponentially, while social animals at the same density are inhibited in terms of numerical increase, but over a 25 day period undergo a larger increase in mass. Isolated posterior fission products reproduce faster than isolated anterior fission products. Regulation of population growth is independent of density over a 16-fold range and regulatory factors cannot be demonstrated in the medium. Regulation of population growth depends on direct contact between animals. Fission period varies from individual to individual and from period to period for a given individual. Doubling time is related to the absolute number of individuals comprising the population as follows: P_N = (P_M · N)/(K + N), where P_N is the doubling period of a population of N individuals, P_M is the doubling time of an infinitely large population, N is the number of individuals in the population, and K is the number of individuals in a population the period of which is one-half P_M. At 22°–24°C P_M is estimated to be 43.3 days and K is 1.87 individuals. A model system assumes that inhibitor flows through the population from animal to animal from the slowest to the fastest animal in the population thus acting to synchronize population increase as well as to determine the rate of population growth. A possible source of the inhibitor is discussed.     

Integration Analysis of Three Omics Data Using Penalized Regression Methods: An Application to Bladder Cancer

Omics data integration is becoming necessary to investigate the genomic mechanisms involved in complex diseases. During the integration process, many challenges arise such as data heterogeneity, the smaller number of individuals in comparison to the number of parameters, multicollinearity, and interpretation and validation of results due to their complexity and lack of knowledge about biological processes. To overcome some of these issues, innovative statistical approaches are being developed. In this work, we propose a permutation-based method to concomitantly assess significance and correct by multiple testing with the MaxT algorithm. This was applied with penalized regression methods (LASSO and ENET) when exploring relationships between common genetic variants, DNA methylation and gene expression measured in bladder tumor samples. The overall analysis flow consisted of three steps: (1) SNPs/CpGs were selected per each gene probe within 1Mb window upstream and downstream the gene; (2) LASSO and ENET were applied to assess the association between each expression probe and the selected SNPs/CpGs in three multivariable models (SNP, CPG, and Global models, the latter integrating SNPs and CPGs); and (3) the significance of each model was assessed using the permutation-based MaxT method. We identified 48 genes whose expression levels were significantly associated with both SNPs and CPGs. Importantly, 36 (75%) of them were replicated in an independent data set (TCGA) and the performance of the proposed method was checked with a simulation study. We further support our results with a biological interpretation based on an enrichment analysis. The approach we propose allows reducing computational time and is flexible and easy to implement when analyzing several types of omics data. Our results highlight the importance of integrating omics data by applying appropriate statistical strategies to discover new insights into the complex genetic mechanisms involved in disease conditions.     

Genetic relationships between Spanish Assaf (Assaf.E) and Spanish native dairy sheep breeds

At present, the Assaf is the main dairy sheep in Spain. The Spanish Assaf (Assaf.E) was formed by male-mediated absorption of native Spanish sheep. Here we assess the genetic relationships among the Assaf.E and major native Spanish dairy breeds using microsatellites to contribute to the knowledge of the formation and within-population genetic variability of the breed. Blood samples from 44 unrelated Assaf.E individuals from 23 different Assaf.E flocks spread throughout 6 different Spanish provinces were obtained and genotyped using 14 microsatellites. Up to 312 additional samples belonging to the Awassi and Milchschaf sheep breeds and to six native Spanish dairy sheep breeds (Castellana, Churra, Latxa, Manchega, and Rubia de El Molar) as well as samples from Merino individuals to be used as the outgroup were also analysed observed (H_o) and expected (H_e) heterozygosity, rarefacted number of alleles per locus and distances based on molecular coancestry information were computed. Probabilities of assignment of the Assaf.E individuals to native Spanish dairy sheep breeds and cryptic genetic structure in the whole dataset were also assessed. It can be concluded that the Assaf.E breed has low genetic variability and high genetic distance with respect native Spanish dairy sheep breeds. From our results, the formation of the Assaf.E breed basically occurred via the absorption of individuals belonging to the Entrefino type, particularly to the Castellana and Manchega populations. Furthermore, Churra individuals may have participated in the formation of the Assaf.E breed at an early moment of the introduction of the breed into Spain.     

Twenty years of artificial directional selection have shaped the genome of the Italian Large White pig breed

In this study, we investigated at the genome‐wide level if 20 years of artificial directional selection based on boar genetic evaluation obtained with a classical BLUP animal model shaped the genome of the Italian Large White pig breed. The most influential boars of this breed (n = 192), born from 1992 (the beginning of the selection program of this breed) to 2012, with an estimated breeding value reliability of >0.85, were genotyped with the Illumina Porcine SNP60 BeadChip. After grouping the boars in eight classes according to their year of birth, filtered single nucleotide polymorphisms (SNPs) were used to evaluate the effects of time on genotype frequency changes using multinomial logistic regression models. Of these markers, 493 had a P_Bonferroni < 0.10. However, there was an increasing number of SNPs with a decreasing level of allele frequency changes over time, representing a continuous profile across the genome. The largest proportion of the 493 SNPs was on porcine chromosome (SSC) 7, SSC2, SSC8 and SSC18 for a total of 204 haploblocks. Functional annotations of genomic regions, including the 493 shifted SNPs, reported a few Gene Ontology terms that might underly the biological processes that contributed to increase performances of the pigs over the 20 years of the selection program. The obtained results indicated that the genome of the Italian Large White pigs was shaped by a directional selection program derived by the application of methodologies assuming the infinitesimal model that captured a continuous trend of allele frequency changes in the boar population.     

What’s in a Name? Effect of Breed Perceptions & Labeling on Attractiveness,Adoptions & Length of Stay for Pit-Bull-Type Dogs

Previous research has indicated that certain breeds of dogs stay longer in shelters than others. However, exactly how breed perception and identification influences potential adopters'' decisions remains unclear. Current dog breed identification practices in animal shelters are often based upon information supplied by the relinquishing owner, or staff determination based on the dog''s phenotype. However, discrepancies have been found between breed identification as typically assessed by welfare agencies and the outcome of DNA analysis. In Study 1, the perceived behavioral and adoptability characteristics of a pit-bull-type dog were compared with those of a Labrador Retriever and Border Collie. How the addition of a human handler influenced those perceptions was also assessed. In Study 2, lengths of stay and perceived attractiveness of dogs that were labeled as pit bull breeds were compared to dogs that were phenotypically similar but were labeled as another breed at an animal shelter. The latter dogs were called "lookalikes." In Study 3, we compared perceived attractiveness in video recordings of pit-bull-type dogs and lookalikes with and without breed labels. Lastly, data from an animal shelter that ceased applying breed labeling on kennels were analyzed, and lengths of stay and outcomes for all dog breeds, including pit bulls, before and after the change in labeling practice were compared. In total, these findings suggest that breed labeling influences potential adopters'' perceptions and decision-making. Given the inherent complexity of breed assignment based on morphology coupled with negative breed perceptions, removing breed labels is a relatively low-cost strategy that will likely improve outcomes for dogs in animal shelters.     

Genetic diversity and population structure of Sicilian sheep breeds using microsatellite markers

Genetic diversity studies in domestic animals aim at evaluating genetic variation within and across breeds mainly for conservation purposes. In Sicily, dairy sheep production represents an important resource for hilly and mountain areas economy. Their milk is used for the production of traditional raw milk cheeses, sometimes protected designation of origin (PDO) cheeses. In some cases, the quality of these products is linked to a specific breed, i.e. mono-breed labelled cheeses and it is therefore important to be able to distinguish the milk of a breed from that of others, in order to guarantee both the consumer and the breed itself. In order to investigate the genetic structure and to perform an assignment test, a total of 331 individuals (Barbaresca, BAR n = 57, Comisana, COM n = 65, Pinzirita, PIN n = 75, Sarda, SAR n = 64, and Valle del Belice, VDB n = 70) were analysed using a panel of 20 microsatellite markers. A total of 259 alleles were observed with average polymorphic information content equal to 0.76, showing that the microsatellites panel used was highly informative. Estimates of observed heterozygosity ranged from 0.65 in the BAR breed to 0.75 in the COM breed. The low value of genetic differentiation among breeds (F_st = 0.049) may indicate that these breeds are little differentiated probably due to common history and breeding practices. The low F_is and F_it values indicated low level of inbreeding within and among breeds. The unrooted neighbor-joining dendrogram obtained from the Reynold's genetic distances, and factorial correspondence analysis revealed a separation between BAR and the other sheep breeds. Recent migration rates were estimated, showing that four out of the five breeds have not received a significant proportion of migrants. Only for the PIN breed a recent introgression rate from the VDB breed (7.2%) was observed. The Bayesian assignment test showed that BAR and SAR breeds had a more definite genetic structure (proportion of assignment of 92% and 86.6%, respectively), whereas the lowest assignment value was found in the PIN breed (67.1%). Our results indicated high genetic variability, low inbreeding and low genetic differentiation, except for BAR breed, and were in accordance with geographical location, history, and breeding practices. The low robustness of the assignment test makes it unfeasible for traceability purposes, due to the high level of admixture, in particular for COM, PIN and VDB.     

Use of the canonical discriminant analysis to select SNP markers for bovine breed assignment and traceability purposes

Several market research studies have shown that consumers are primarily concerned with the provenance of the food they eat. Among the available identification methods, only DNA‐based techniques appear able to completely prevent frauds. In this study, a new method to discriminate among different bovine breeds and assign new individuals to groups was developed. Bulls of three cattle breeds farmed in Italy – Holstein, Brown, and Simmental – were genotyped using the 50K SNP Illumina BeadChip. Multivariate canonical discriminant analysis was used to discriminate among breeds, and discriminant analysis (DA) was used to assign new observations. This method was able to completely identify the three groups at chromosome level. Moreover, a genome‐wide analysis developed using 340 linearly independent SNPs yielded a significant separation among groups. Using the reduced set of markers, the DA was able to assign 30 independent individuals to the proper breed. Finally, a set of 48 high discriminant SNPs was selected and used to develop a new run of the analysis. Again, the procedure was able to significantly identify the three breeds and to correctly assign new observations. These results suggest that an assay with the selected 48 SNP could be used to routinely track monobreed products.     

Genomic variation and population structure detected by single nucleotide polymorphism arrays in Corriedale,Merino and Creole sheep

The aim of this study was to investigate the genetic diversity within and among three breeds of sheep: Corriedale, Merino and Creole. Sheep from the three breeds (Merino n = 110, Corriedale n = 108 and Creole n = 10) were genotyped using the Illumina Ovine SNP50 beadchip^®. Genetic diversity was evaluated by comparing the minor allele frequency (MAF) among breeds. Population structure and genetic differentiation were assessed using STRUCTURE software, principal component analysis (PCA) and fixation index (F_ST). Fixed markers (MAF = 0) that were different among breeds were identified as specific breed markers. Using a subset of 18,181 single nucleotide polymorphisms (SNPs), PCA and STUCTURE analysis were able to explain population stratification within breeds. Merino and Corriedale divergent lines showed high levels of polymorphism (89.4% and 86% of polymorphic SNPs, respectively) and moderate genetic differentiation (F_ST = 0.08) between them. In contrast, Creole had only 69% polymorphic SNPs and showed greater genetic differentiation from the other two breeds (F_ST = 0.17 for both breeds). Hence, a subset of molecular markers present in the OvineSNP50 is informative enough for breed assignment and population structure analysis of commercial and Creole breeds.     

The evaluation of the usefulness of pedigree verification-dedicated SNPs for breed assignment in three polish cattle populations

The breed assignment in cattle is one of the issues of molecular genetics which needs further testing and development. Although several statistical approaches have been developed to enable such application, the obtained results strongly depend on specific populations differentiation and power of markers discrimination or their informativeness. Currently, all breeding animals are being tested for parentage with the use of panel of 12 microsatellite markers, which in near future probably will be replaced by about 100 single nucleotide polymorphisms (SNPs). Despite the fact that SNPs are mainly bi-allelic, the multilocus genotypes can reach the level of polymorphism of a panel of microsatellite markers. In this study we attempted to determine the breed of origin of 741 cattle by using 120 SNPs dedicated for parentage testing and included in the BovineSNP50 BeadChip genotyping assay (Illumina). The applied Bayesian and frequency-based methods allowed such differentiation, however, the reliability of the results was not completely satisfying, suggesting that the studied markers are not the best tool for breed assignment.     

Genetic diversity in the Churra tensina and Churra lebrijana endangered Spanish sheep breeds and relationship with other Churra group breeds and Spanish mouflon

The aim of the present study was to estimate the genetic intra-breed variability of Churra tensina and Churra lebrijana endangered breeds and to establish genetic relationships with Churra, Latxa and Merino breeds, as well as Spanish mouflon, by using 28 microsatellite markers, to provide useful information for their conservation. Allele frequencies and heterozygosity revealed high genetic variation in the two endangered breeds despite their small population size. Estimates of inbreeding coefficient (F_IS) were significant for all breeds studied, except for Churra lebrijana breed. The highest inbreeding coefficient (F_IS = 0.143) was found in the Spanish mouflon. Genetic differentiation tests (F_ST = 0.121) and assignment of individuals to populations indicated the existence of defined breed populations, and low genetic flow between these breeds. The highest pairwise Reynolds distance (D_R) values were observed between Mouflon and the domestic sheep breeds. Considering only domestic sheep breeds, the Churra lebrijana breed showed the highest pairwise D_R values_. The lowest values were found between Latxa and the other domestic sheep, except for Churra lebrijana. Results of pairwise D_R values, as well as phylogenetic tree and bottleneck analysis showed an important genetic isolation of the Churra lebrijana breed from the other Churra types, and genetic signatures of a demographic bottleneck. Finally, structure analysis of populations detected a population subdivision in the Latxa sheep breed. In conclusion, this study presents valuable insight into the existing genetic variability of two Spanish endangered breeds, as well as the first study in Spanish mouflon based on microsatellite analysis. The high degree of variability demonstrated in Churra tensina and Churra lebrijana implies that these populations are rich reservoirs of genetic diversity.     

Variation of cats under domestication: genetic assignment of domestic cats to breeds and worldwide random‐bred populations

Both cat breeders and the lay public have interests in the origins of their pets, not only in the genetic identity of the purebred individuals, but also in the historical origins of common household cats. The cat fancy is a relatively new institution with over 85% of its 40–50 breeds arising only in the past 75 years, primarily through selection on single‐gene aesthetic traits. The short, yet intense cat breed history poses a significant challenge to the development of a genetic marker–based breed identification strategy. Using different breed assignment strategies and methods, 477 cats representing 29 fancy breeds were analysed with 38 short tandem repeats, 148 intergenic and five phenotypic single nucleotide polymorphisms. Results suggest the frequentist method of Paetkau (single nucleotide polymorphisms = 0.78, short tandem repeats = 0.88) surpasses the Bayesian method of Rannala and Mountain (single nucleotide polymorphisms = 0.56, short tandem repeats = 0.83) for accurate assignment of individuals to the correct breed. Additionally, a post‐assignment verification step with the five phenotypic single nucleotide polymorphisms accurately identified between 0.31 and 0.58 of the misassigned individuals raising the sensitivity of assignment with the frequentist method to 0.89 and 0.92 for single nucleotide polymorphisms and short tandem repeats respectively. This study provides a novel multistep assignment strategy and suggests that, despite their short breed history and breed family groupings, a majority of cats can be assigned to their proper breed or population of origin, that is, race.     

Differentiation among Spanish sheep breeds using microsatellites

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 F_ST 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.