Population structure and genomic diversity of the Einsiedler horse.

The breeding history of the Einsiedler horse is closely connected with the Benedictine cloister Einsiedeln. In the mid-nineteenth century, it was decided to use European Warmblood stallions for cross-breeding and to abandon the selection of stallions. Since that time, it has only been possible to trace back the origin of Einsiedler horses using maternal ancestry information. Here, we collected high-density genotype data for European Warmblood horses (Selle Français, Swiss Warmblood and Einsiedler) and Franches-Montagnes horses, the last native Swiss horse breed, to unravel the current population structure of the Einsiedler horse. Using commonly applied methods to ascertain fine-scale population structures, it was not possible to clearly differentiate the Einsiedler from other European Warmblood horses. However, by means of runs of homozygosity (ROH) we were able to detect breed-specific ROH islands for the Einsiedler horse, including genes involved in domestication and adaptation to high altitude. Therefore, future breeding activities should involve the screening of these breed-specific ROH segments, the revival of cryopreserved sperm and the selection of Einsiedler stallions.

Genetic analysis of geometric morphometric 3D visuals of French jumping horses.

BACKGROUND: For centuries, morphology has been the most commonly selected trait in horses. A 3D video recording enabled us to obtain the coordinates of 43 anatomical landmarks of 2089 jumping horses. Generalized Procrustes analysis provided centered and scaled coordinates that were independent of volume, i.e., centroid size. Genetic analysis of these coordinates (mixed model; 17,994 horses in the pedigree) allowed us to estimate a variance-covariance matrix. New phenotypes were then defined: the "summarized shapes". They were obtained by linear combinations of Procrustes coordinates with, as coefficients, the eigenvectors of the genetic variance-covariance matrix. These new phenotypes were used in genome-wide association analyses (GWAS) and multitrait genetic analysis that included judges' scores and competition results of the horses. RESULTS: We defined ten shapes that represented 86% of the variance, with heritabilities ranging from 0.14 to 0.42. Only one of the shapes was found to be genetically correlated with competition success (rg = - 0.12, standard error = 0.07). Positive and negative genetic correlations between judges' scores and shapes were found. This means that the breeding objective defined by judges involves improvement of anatomical parts of the body that are negatively correlated with each other. Known single nucleotide polymorphisms (SNPs) on chromosomes 1 and 3 for height at withers were significant for centroid size but not for any of the shapes. As these SNPs were not associated with the shape that distinguished rectangular horses from square horses (with height at withers greater than body length), we hypothesize that these SNPs play a role in the overall development of horses, i.e. in height, width, and length but not in height at withers when standardized to unit centroid size. Several other SNPs were found significant for other shapes. CONCLUSIONS: The main application of 3D morphometric analysis is the ability to define the estimated breeding value (EBV) of a sire based on the shape of its potential progeny, which is easier for breeders to visualize in a single synthetic image than a full description based on linear profiling. However, the acceptance of these new phenotypes by breeders and the complex nature of summarized shapes may be challenging. Due to the low genetic correlations of the summarized shapes with jumping performance, the methodology did not allow indirect performance selection criteria to be defined.

An improved transmissibility model to detect transgenerational transmitted environmental effects.

BACKGROUND: Evolutionary studies have reported that non-genetic information can be inherited across generations (epigenetic marks, microbiota, cultural inheritance). Non-genetic information is considered to be a key element to explain the adaptation of wild species to environmental constraints because it lies at the root of the transgenerational transmission of environmental effects. The "transmissibility model" was proposed several years ago to better predict the transmissible potential of each animal by taking these diverse sources of inheritance into account in a global transmissible potential. We propose to improve this model to account for the influence of the environment on the global transmissible potential as well. This extension of the transmissibility model is the "transmissibility model with environment" that considers a covariance between transmissibility samplings of animals sharing the same environment. The null hypothesis of "no transmitted environmental effect" can be tested by comparing the two models using a likelihood ratio test (LRT). RESULTS: We performed simulations that mimicked an experimental design consisting of two lines of animals with one exposed to a particular environment at a given generation. This enabled us to evaluate the performances of the transmissibility model with environment so as to detect and quantify transgenerational transmitted environmental effects. The power and the realized type I error of the LRT were compared to those of a T-test comparing the phenotype of the two lines, three generations after the environmental exposure for different sets of parameters. The power of the LRT ranged from 45 to 94%, whereas that of the T-test was always lower than 26%. In addition, the realized type I error of the T-test was 15% and that of the LRT was 5%, as expected. Variances, the covariance between transmissibility samplings, and path coefficients of transmission estimated with the transmissibility model with environment were close to their true values for all sets of parameters. CONCLUSIONS: The transmissibility model with environment is effective in modeling vertical transmission of environmental effects.

Quality of breeding value predictions from longitudinal analyses, with application to residual feed intake in pigs.

BACKGROUND: An important goal in animal breeding is to improve longitudinal traits. The objective of this study was to explore for longitudinal residual feed intake (RFI) data, which estimated breeding value (EBV), or combination of EBV, to use in a breeding program. Linear combinations of EBV (summarized breeding values, SBV) or phenotypes (summarized phenotypes) derived from the eigenvectors of the genetic covariance matrix over time were considered, and the linear regression method (LR method) was used to facilitate the evaluation of their prediction accuracy. RESULTS: Weekly feed intake, average daily gain, metabolic body weight, and backfat thickness measured on 2435 growing French Large White pigs over a 10-week period were analysed using a random regression model. In this population, the 544 dams of the phenotyped animals were genotyped. These dams did not have own phenotypes. The quality of the predictions of SBV and breeding values from summarized phenotypes of these females was evaluated. On average, predictions of SBV at the time of selection were unbiased, slightly over-dispersed and less accurate than those obtained with additional phenotypic information. The use of genomic information did not improve the quality of predictions. The use of summarized instead of longitudinal phenotypes resulted in predictions of breeding values of similar quality. CONCLUSIONS: For practical selection on longitudinal data, the results obtained with this specific design suggest that the use of summarized phenotypes could facilitate routine genetic evaluation of longitudinal traits.

Copula miss-specification in REML multivariate genetic animal model estimation.

BACKGROUND: In animal genetics, linear mixed models are used to deal with genetic and environmental effects. The variance and covariance terms of these models are usually estimated by restricted maximum likelihood (REML), which provides unbiased estimators. A strong hypothesis of REML estimation is the multi-normality of the response variables. However, in practice, even if the marginal distributions of each phenotype are normal, the multi-normality assumption may be violated by non-normality of the cross-sectional dependence structure, that is to say when the copula of the multivariate distribution is not Gaussian. This study uses simulations to evaluate the impact of copula miss-specification in a bivariate animal model on REML estimations of variance components. RESULT: Bivariate phenotypes were simulated for populations undergoing selection, considering different copulas for the dependence structure between the error components. Two multi-trait situations were considered: two phenotypes were measured on the selection candidates, or only one phenotype was measured on the selection candidates. Three generations with random selection and five generations with truncation selection based on estimated breeding values were simulated. When selection was performed at random, no significant differences were observed between the REML estimations of variance components and the true parameters even for the non-Gaussian distributions. For the truncation selections, when two phenotypes were measured on candidates, biases were systematically observed in the variance components for high residual dependence in the case of non-Gaussian distributions, especially in the case of a heavy-tailed or asymmetric distribution when the two traits were measured. Conversely, when only one phenotype was measured on candidates, no difference was observed between the Gaussian and non-Gaussian distributions in REML estimations. CONCLUSIONS: This study confirms that REML can be used by geneticists to evaluate breeding values in the multivariate case even if the multivariate phenotypes deviate from normality in the situation of random selection or if one trait is not measured for the candidate under selection. Nevertheless, when the two traits are measured, the violation of the normality assumption may lead to non-negligible biases in the REML estimations of the variance-covariance components.

DPF3, A Putative Candidate Gene For Melanoma Etiopathogenesis in Gray Horses.

Melanoma prevalence in gray horses reaches up to 50% and more. Several studies have documented a genetic melanoma predisposition which is referred to the 4.6 kb duplication in intron 6 of STX17 and its surrounding haplotype. However, the genetic background and mechanisms responsible for differences in etiopathogenesis of equine dermal melanomatosis still remain unknown. In the current study, we performed a genome wide association analysis in 141 Lipizzan horses and subsequently identified one candidate gene on chromosome 24 putatively involved in melanoma pathogenesis in gray horses. The associated SNP was located in the intronic region of DPF3, a gene which is involved in humans in cell growth, proliferation, apoptosis and motility of cancer cells. The replication study in 1210 horses from seven breeds demonstrated, that the G/G genotype of the DPF3 associated SNP exhibits putative melanoma suppression effects. As a conclusion DPF3 represents a candidate gene, which might play an essential role for gray horses coping with high genetic melanoma related tumor load.

Equine vitiligo-like depigmentation in grey horses is related to genes involved in immune response and tumor metastasis.

BACKGROUND: In horses, the autoimmune disease vitiligo is characterized by the loss of melanocytes and results in patchy depigmentation of the skin around the eyes, muzzle and the perianal region. Vitiligo-like depigmentation occurs predominantly in horses displaying the grey coat colour and is observed at a prevalence level of 26.0-67.0% in grey horses compared with only 0.8-3.5% in non-grey horses. While the polygenetic background of this complex disease is well documented in humans, the underlying candidate genes for this skin disorder in horses remain unknown. In this study we aim to perform a genome-wide association study (GWAS) for identifying putative candidate loci for vitiligo-like depigmentation in horses. METHODS: In the current study, we performed a GWAS analysis using high-density 670 k single nucleotide polymorphism (SNP) data from 152 Lipizzan and 104 Noriker horses, which were phenotyped for vitiligo-like depigmentation by visual inspection. After quality control 376,219 SNPs remained for analyses, the genome-wide Bonferroni corrected significance level was p < 1.33e-7. RESULTS: We identified seven candidate genes on four chromosomes (ECA1, ECA13, ECA17, ECA20) putatively involved in vitiligo pathogenesis in grey horses. The highlighted genes PHF11, SETDB2, CARHSP1 and LITAFD, are associated with the innate immune system, while the genes RCBTB1, LITAFD, NUBPL, PTP4A1, play a role in tumor suppression and metastasis. The antagonistic pathogenesis of vitiligo in relation to cancer specific enhanced cell motility and/or metastasis on typical melanoma predilection sites underlines a plausible involvement of RCBTB1, LITAFD, NUBPL, and PTP4A1. CONCLUSIONS: The proposed candidate genes for equine vitiligo-like depigmentation, indicate an antagonistic relation between vitiligo and tumor metastasis in a horse population with higher incidence of melanoma. Further replication and expression studies should lead to a better understanding of this skin disorder in horses.

Genomic Correlations Between the Gaits of Young Horses Measured by Accelerometry and Functional Longevity in Jumping Competition.

Functional longevity is essential for the well-being of horses and the satisfaction of riders. Conventional selection using longevity breeding values calculated from competition results is not efficient because it takes too long to obtain reliable information. Therefore, the objective was to identify early criteria for selection. We assessed two types of early criteria: gait traits of young horses and QTLs. Thus, our aim was to estimate the genetic correlation between gait traits and longevity and to perform a genome-wide association study (GWAS) for longevity. Measurements of gaits by accelerometry were recorded on 1,477 show jumping horses that were 4 to 5 years old. Gait analysis provided 9 principal components describing trot, canter, and walk. Longevity estimated breeding values (EBVs) for stallions were calculated using a survival analysis of more than 900,000 years of performances by 179,448 show jumping horses born from 1981 onwards. Longevity was measured as the number of years spent in competition. Model included region and month of birth, age at first competition, year, and performance level. Longevity EBVs were deregressed to obtain weighted pseudo-performances for 1,968 stallions. Genomic data were available for 3,658 jumping horses. Seventy-eight percent of the horses measured for gaits and twenty-five percent of those measured for longevity were genotyped. A GWAS of longevity revealed no significant QTLs. Genetic parameters between each of the 9 principal components of the gait variables and longevity were evaluated with a bi-trait animal linear mixed model using single-step GBLUP analysis with the relationship matrix constructed from genomic data and genealogy (24,448 ancestors over four generations). The heritability of the gait traits varied from 0.11 to 0.44. The third principal component for trot (high lateral activity) and the first principal component for canter (high dorsoventral activity and low stride frequency) were moderately genetically correlated with higher longevity: rg = 0.38 (0.15) and 0.28 (0.13), respectively. Our study revealed that functional longevity is a polygenic trait with no major genes. We found new correlations between longevity and gait traits. Before using gait characteristics in a selection plan, these correlations need to be understood better at the biomechanical level.

Genomic analysis of gaits and racing performance of the French trotter.

The aim was to disentangle gait characteristics from other qualities needed for racing performances with a genomic analysis of French trotters (FT). A sample of 1,390 horses were recruited, from which 46% were genotyped with Illumina chip of 54,602 SNPs, 49% with Affymetrix chip of 670,806 SNPs and 586 had a completed questionnaire on trotting technique. Racing performances cover the period 1996 to 2018. There were 252,368 FT-born; 96,617 qualified and 83,962 which participated in a race. After quality control, 377,611 SNPs were retained and imputed. Questionnaire described trotting technique over 13 questions which were summarized, after principal component analysis in 3 traits: pacer, heavy trot/gallop and other defects. GWAS and genomic evaluation were performed using single-step approach. We found 25 QTL for racing performances and 9 for trotting technique. Only DMRT3 mutation was significant for both traits. To tend to pace avoid the defect at gallop and lead to a better early career for earnings, less percentage of disqualified races at all ages and more harness than under saddle career. This is the portrait of AA genotype at DMRT3. We found 5 other QTL, not linked to gait traits, which might improve selection of genetically independent performance traits of earnings per races and percentage of finished races. For only earnings at different ages and in under saddle or harness races, genomic evaluation remains the best way to predict performances.

Genetic consistency between gait analysis by accelerometry and evaluation scores at breeding shows for the selection of jumping competition horses.

The aim was to assess the efficiency of gaits characteristics in improving jumping performance of sport horses and confront accelerometers and judge scores for this purpose. A sample of 1,477 young jumping horses were measured using accelerometers for walk, trot, and canter. Of these, 702 were genotyped with 541,175 SNPs after quality control. Dataset of 26,914 horses scored by judges in breeding shows for gaits and dataset of 142,682 horses that performed in jumping competitions were used. Analysis of accelerometric data defined three principal components from 64% to 89% of variability explained for each gait. Animal mixed models were used to estimate genetic parameters with the inclusion to up 308,105 ancestors for the relationship matrix. Fixed effects for the accelerometric variables included velocity, gender, age, and event. A GWAS was performed on residuals with the fixed effect of each SNP. The GWAS did not reveal other QTLs for gait traits than the one related to the height at withers. The accelerometric principal components were highly heritable for the one linked to stride frequency and dorsoventral displacement at trot (0.53) and canter (0.41) and moderately for the one linked to longitudinal activities (0.33 for trot, 0.19 for canter). Low heritabilities were found for the walk traits. The genetic correlations of the accelerometric principal components with the jumping competition were essentially nil, except for a negative correlation with longitudinal activity at canter (-0.19). The genetic correlation between the judges' scores and the jumping competition reached 0.45 for canter (0.31 for trot and 0.17 for walk). But these correlations turned negative when the scores were corrected for the known parental breeding value for competition at the time of the judging. In conclusion, gait traits were not helpful to select for jumping performances. Different gaits may be suitable for a good jumping horse.

Inclusive inheritance for residual feed intake in pigs and rabbits.

Non-genetic information (epigenetic, microbiota, behaviour) that results in different phenotypes in animals can be transmitted from one generation to the next and thus is potentially involved in the inheritance of traits. However, in livestock species, animals are selected based on genetic inheritance only. The objective of the present study was to determine whether non-genetic inherited effects play a role in the inheritance of residual feed intake (RFI) in two species: pigs and rabbits. If so, the path coefficients of the information transmitted from sire and dam to offspring would differ from the expected transmission factor of 0.5 that occurs if inherited information is of genetic origin only. Two pigs (pig1, pig2) and two rabbits (rabbit1, rabbit2) datasets were used in this study (1,603, 3,901, 5,213 and 4,584 records, respectively). The test of the path coefficients to 0.5 was performed for each dataset using likelihood ratio tests (null model: transmissibility model with both path coefficients equal to 0.5, full model: unconstrained transmissibility model). The path coefficients differed significantly from 0.5 for one of the pig datasets (pig2). Although not significant, we observed, as a general trend, that sire path coefficients of transmission were lower than dam path coefficients in three of the datasets (0.46 vs 0.53 for pig1, 0.39 vs 0.44 for pig2 and 0.38 vs 0.50 for rabbit1). These results suggest that phenomena other than genetic sources of inheritance explain the phenotypic resemblance between relatives for RFI, with a higher transmission from the dam's side than from the sire's side.

Accelerometers Provide Early Genetic Selection Criteria for Jumping Horses.

The aim of this study was to evaluate the genetic component of the locomotor jumping ability, via a wearable accelerometer sensor, and to estimate the genetic correlation with performance in competition, to introduce such criteria in selection schema. A sample of 1,056 young 3-year-old horses were equipped with a 3-dimensional accelerometer during a free jumping test, in regular breeding shows from 2015 to 2017. Seven variables were extracted from the dorso-ventral acceleration curve for the last three jumps over a double bar obstacle of 1.15 m for the front pole and 1.20 m for the back pole with a 1.20 m spread. Variables were the peaks of forelimbs, hindlimbs, and landing acceleration, the duration between peaks at take-off, the peak of forelimb acceleration and start of jump, jump duration and duration between the beginning of the impact of forelimbs and the peak at landing. During breeding shows, judges scored balance, strength, style, and reactivity for free jumping and jumping tests under saddle. Jumping competition results were recorded by logarithm of the sum of points earned in each competition. All horses in official competitions were included, i.e., 160,257 horses born in 1997 with a total of 649,491 annual performances. An animal mixed model with complete pedigree over four generations (353,236 horses) were used with fixed effects of jumping test location and date, morning/afternoon, gender, month of birth, rank of jump for accelerometric data, effect of year of competition, combined with age and gender for competition results. As a result, jump duration was the most heritable and repeatable for jump variables: h 2 = 0.16 (0.06), r = 0.52 (0.02), while accelerations were moderately heritable (h 2 = 0.05-0.09, r = 0.39-0.51). Judgement scores were heritable: 0.21 (0.07)-0.33 (0.09) and were highly correlated. Scores during free jumping were genetically correlated to jump duration: 0.71 (0.15)-0.88 (0.16). Both jump duration and judgement scores were genetically correlated to competition performance: 0.59 (0.13) for jump duration, from 0.60 (0.11) to 0.77 (0.12) for scores. Jump duration and judgement scores can be used as early selection criteria. The advantage of the accelerometric measurement is its objectivity and the ease of recording.

Genome-Wide Homozygosity Patterns and Evidence for Selection in a Set of European and Near Eastern Horse Breeds.

Intensive artificial and natural selection have shaped substantial variation among European horse breeds. Whereas most equine selection signature studies employ divergent genetic population structures in order to derive specific inter-breed targets of selection, we screened a total of 1476 horses originating from 12 breeds for the loss of genetic diversity by runs of homozygosity (ROH) utilizing a 670,000 single nucleotide polymorphism (SNP) genotyping array. Overlapping homozygous regions (ROH islands) indicating signatures of selection were identified by breed and similarities/dissimilarities between populations were evaluated. In the entire dataset, 180 ROH islands were identified, whilst 100 islands were breed specific, all other overlapped in 36 genomic regions with at least one ROH island of another breed. Furthermore, two ROH hot spots were determined at horse chromosome 3 (ECA3) and ECA11. Besides the confirmation of previously documented target genes involved in selection for coat color (MC1R, STX17, ASIP), body size (LCORL/NCAPG, ZFAT, LASP1, HMGA2), racing ability (PPARGC1A), behavioral traits (GRIN2B, NTM/OPCML) and gait patterns (DMRT3), several putative target genes related to embryonic morphogenesis (HOXB), energy metabolism (IGFBP-1, IGFBP-3), hair follicle morphogenesis (KRT25, KRT27, INTU) and autophagy (RALB) were highlighted. Furthermore, genes were pinpointed which might be involved in environmental adaptation of specific habitats (UVSSA, STXBP4, COX11, HLF, MMD).

A Unified Model for Inclusive Inheritance in Livestock Species.

For years, animal selection in livestock species has been performed by selecting animals based on genetic inheritance. However, evolutionary studies have reported that nongenetic information that drives natural selection can also be inherited across generations (epigenetic, microbiota, environmental inheritance). In response to this finding, the concept of inclusive heritability, which combines all sources of information inherited across generations, was developed. To better predict the transmissible potential of each animal by taking into account these diverse sources of inheritance and improve selection in livestock species, we propose the "transmissibility model." Similarly to the animal model, this model uses pedigree and phenotypic information to estimate variance components and predict the transmissible potential of an individual, but differs by estimating the path coefficients of inherited information from parent to offspring instead of using a set value of 0.5 for both the sire and the dam (additive genetic relationship matrix). We demonstrated the structural identifiability of the transmissibility model, and performed a practical identifiability and power study of the model. We also performed simulations to compare the performances of the animal and transmissibility models for estimating the covariances between relatives and predicting the transmissible potential under different combinations of sources of inheritance. The transmissibility model provided similar results to the animal model when inheritance was of genetic origin only, but outperformed the animal model for estimating the covariances between relatives and predicting the transmissible potential when the proportion of inheritance of nongenetic origin was high or when the sire and dam path coefficients were very different.

Genotype imputation accuracy in multiple equine breeds from medium- to high-density genotypes.

Genotype imputation is now a key component of genomic analyses as it increases the density of available genotypes within a population. However, many factors can influence imputation accuracy. The aim of this study was to assess and compare the accuracy of imputation of high-density genotypes (Affymetrix Axiom Equine genotyping array, 670,806 SNPs) from two moderate-density genotypes (Illumina Equine SNP50 BeadChip, 54,602 SNPs and Illumina Equine SNP70 BeadChip, 65,157 SNPs), using single-breed or multiple-breed reference sets. Genotypes were available from five groups of horse breeds: Arab (AR, 1,207 horses), Trotteur Français (TF, 979 horses), Selle Français (SF, 1,979 horses), Anglo-Arab (AA, 229 horses) and various foreign sport horses (FH, 209 horses). The proportions of horses genotyped with the high-density (HD) chip in each breed group were 10% in AA, 15% in AR and FH, 30% in TF and 57% in SF. A validation set consisting of one-third of the horses genotyped with the HD chip was formed and their genotypes deleted. Two imputation strategies were compared, one in which the reference population consisted only of horses from the same breed group as in the validation set, and another with horses from all breed groups. For the first strategy, concordance rates (CRs) ranged from 97.8% (AR) to 99.0% (TF) and correlations (r²) from 0.94 (AR) to 0.99 (TF). For the second strategy, CR ranged from 97.4% (AR) to 98.9% (TF) and r² from 0.93 (AR) to 0.99 (TF). Overall, the results show a small advantage of within-breed imputation compared with multi-breed imputation. Adding horses from different breed groups to the reference population does not improve the accuracy of imputation. Imputation provides an accurate means of combining data sets from different genotyping platforms, now necessary with the increasing use of the recently developed Affymetrix Axiom Equine genotyping array.

GWAS by GBLUP: Single and Multimarker EMMAX and Bayes Factors, with an Example in Detection of a Major Gene for Horse Gait.

Bayesian models for genomic prediction and association mapping are being increasingly used in genetics analysis of quantitative traits. Given a point estimate of variance components, the popular methods SNP-BLUP and GBLUP result in joint estimates of the effect of all markers on the analyzed trait; single and multiple marker frequentist tests (EMMAX) can be constructed from these estimates. Indeed, BLUP methods can be seen simultaneously as Bayesian or frequentist methods. So far there is no formal method to produce Bayesian statistics from GBLUP. Here we show that the Bayes Factor, a commonly admitted statistical procedure, can be computed as the ratio of two normal densities: the first, of the estimate of the marker effect over its posterior standard deviation; the second of the null hypothesis (a value of 0 over the prior standard deviation). We extend the BF to pool evidence from several markers and of several traits. A real data set that we analyze, with ours and existing methods, analyzes 630 horses genotyped for 41711 polymorphic SNPs for the trait "outcome of the qualification test" (which addresses gait, or ambling, of horses) for which a known major gene exists. In the horse data, single marker EMMAX shows a significant effect at the right place at Bonferroni level. The BF points to the same location although with low numerical values. The strength of evidence combining information from several consecutive markers increases using the BF and decreases using EMMAX, which comes from a fundamental difference in the Bayesian and frequentist schools of hypothesis testing. We conclude that our BF method complements frequentist EMMAX analyses because it provides a better pooling of evidence across markers, although its use for primary detection is unclear due to the lack of defined rejection thresholds.

Population Networks Associated with Runs of Homozygosity Reveal New Insights into the Breeding History of the Haflinger Horse.

Within the scope of current genetic diversity analyses, population structure and homozygosity measures are independently analyzed and interpreted. To enhance analytical power, we combined the visualization of recently described high-resolution population networks with runs of homozygosity (ROH). In this study, we demonstrate that this approach enabled us to reveal important aspects of the breeding history of the Haflinger horse. We collected high-density genotype information of 531 horses originating from 7 populations which were involved in the formation of the Haflinger, namely 32 Italian Haflingers, 78 Austrian Haflingers, 190 Noriker, 23 Bosnian Mountain Horses, 20 Gidran, 33 Shagya Arabians, and 155 Purebred Arabians. Model-based cluster analysis identified substructures within Purebred Arabian, Haflinger, and Noriker that reflected distinct genealogy (Purebred Arabian), geographic origin (Haflinger), and coat color patterns (Noriker). Analysis of ROH revealed that the 2 Arabian populations (Purebred and Shagya Arabians), Gidran and the Bosnian Mountain Horse had the highest genome proportion covered by ROH segments (306-397 Mb). The Noriker and the Austrian Haflinger showed the lowest ROH coverage (228, 282 Mb). Our combined visualization approach made it feasible to clearly identify outbred (admixture) and inbred (ROH segments) horses. Genomic inbreeding coefficients (FROH) ranged from 10.1% (Noriker) to 17.7% (Purebred Arabian). Finally it could be demonstrated, that the Austrian Haflinger sample has a lack of longer ROH segments and a deviating ROH spectrum, which is associated with past bottleneck events and the recent mating strategy favoring out-crosses within the breed.

Correction: Genome Wide Association Study Identifies New Loci Associated with Undesired Coat Color Phenotypes in Saanen Goats.

[This corrects the article DOI: 10.1371/journal.pone.0152426.].

Endurance Exercise Ability in the Horse: A Trait with Complex Polygenic Determinism.

Endurance horses are able to run at more than 20 km/h for 160 km (in bouts of 30-40 km). This level of performance is based on intense aerobic metabolism, effective body heat dissipation and the ability to endure painful exercise. The known heritabilities of endurance performance and exercise-related physiological traits in Arabian horses suggest that adaptation to extreme endurance exercise is influenced by genetic factors. The objective of the present genome-wide association study (GWAS) was to identify single nucleotide polymorphisms (SNPs) related to endurance racing performance in 597 Arabian horses. The performance traits studied were the total race distance, average race speed and finishing status (qualified, eliminated or retired). We used three mixed models that included a fixed allele or genotype effect and a random, polygenic effect. Quantile-quantile plots were acceptable, and the regression coefficients for actual vs. expected log10p-values ranged from 0.865 to 1.055. The GWAS revealed five significant quantitative trait loci (QTL) corresponding to 6 SNPs on chromosomes 6, 1, 7, 16, and 29 (two SNPs) with corrected p-values from 1.7 × 10-6 to 1.8 × 10-5. Annotation of these 5 QTL revealed two genes: sortilin-related VPS10-domain-containing receptor 3 (SORCS3) on chromosome 1 is involved in protein trafficking, and solute carrier family 39 member 12 (SLC39A12) on chromosome 29 is active in zinc transport and cell homeostasis. These two coding genes could be involved in neuronal tissues (CNS). The other QTL on chromosomes 6, 7, and 16 may be involved in the regulation of the gene expression through non-coding RNAs, CpG islands and transcription factor binding sites. On chromosome 6, a new candidate equine long non-coding RNA (KCNQ1OT1 ortholog: opposite antisense transcript 1 of potassium voltage-gated channel subfamily Q member 1 gene) was predicted in silico and validated by RT-qPCR in primary cultures of equine myoblasts and fibroblasts. This lncRNA could be one element of the cardiac rhythm regulation. Our GWAS revealed that equine performance during endurance races is a complex polygenic trait, and is partially governed by at least 5 QTL: two coding genes involved in neuronal tissues and three other loci with many regulatory functions such as slowing down heart rate.

Genome Wide Association Study Identifies New Loci Associated with Undesired Coat Color Phenotypes in Saanen Goats.

This paper reports a quantitative genetics and genomic analysis of undesirable coat color patterns in goats. Two undesirable coat colors have routinely been recorded for the past 15 years in French Saanen goats. One fifth of Saanen females have been phenotyped "pink" (8.0%) or "pink neck" (11.5%) and consequently have not been included in the breeding program as elite animals. Heritability of the binary "pink" and "pink neck" phenotype, estimated from 103,443 females was 0.26 for "pink" and 0.21 for "pink neck". Genome wide association studies (using haplotypes or single SNPs) were implemented using a daughter design of 810 Saanen goats sired by 9 Artificial Insemination bucks genotyped with the goatSNP50 chip. A highly significant signal (-log10pvalue = 10.2) was associated with the "pink neck" phenotype on chromosome 11, suggesting the presence of a major gene. Highly significant signals for the "pink" phenotype were found on chromosomes 5 and 13 (-log10p values of 7.2 and, 7.7 respectively). The most significant SNP on chromosome 13 was in the ASIP gene region, well known for its association with coat color phenotypes. Nine significant signals were also found for both traits. The highest signal for each trait was detected by both single SNP and haplotype approaches, whereas the smaller signals were not consistently detected by the two methods. Altogether these results demonstrated a strong genetic control of the "pink" and "pink neck" phenotypes in French Saanen goats suggesting that SNP information could be used to identify and remove undesired colored animals from the breeding program.