Genetic diversity among horse populations with a special focus on the Franches-Montagnes breed

Genetic characterization helps to assure breed integrity and to assign individuals to defined populations. The objective of this study was to characterize genetic diversity in six horse breeds and to analyse the population structure of the Franches-Montagnes breed, especially with regard to the degree of introgression with Warmblood. A total of 402 alleles from 50 microsatellite loci were used. The average number of alleles per locus was significantly lower in Thoroughbreds and Arabians. Average heterozygosities between breeds ranged from 0.61 to 0.72. The overall average of the coefficient of gene differentiation because of breed differences was 0.100, with a range of 0.036-0.263. No significant correlation was found between this parameter and the number of alleles per locus. An increase in the number of homozygous loci with increasing inbreeding could not be shown for the Franches-Montagnes horses. The proportion of shared alleles, combined with the neighbour-joining method, defined clusters for Icelandic Horse, Comtois, Arabians and Franches-Montagnes. A more disparate clustering could be seen for European Warmbloods and Thoroughbreds, presumably from frequent grading-up of Warmbloods with Thoroughbreds. Grading-up effects were also observed when Bayesian and Monte Carlo resampling approaches were used for individual assignment to a given population. Individual breed assignments to defined reference populations will be very difficult when introgression has occurred. The Bayesian approach within the Franches-Montagnes breed differentiated individuals with varied proportions of Warmblood.     

Mitochondrial D-loop sequence variation among the 16 maternal lines of the Lipizzan horse breed

Mitochondrial DNA from 49 Lipizzan horses representing 16 maternal lines from the original stud at Lipica was used for SSCP analysis and DNA sequencing. The SSCP analysis of the 444 bp long fragment of the D-loop region extending from the tRNA(Pro) gene to the central conserved sequence block revealed three distinct groups of SSCP patterns. Both ends of the D-loop region (378 bp and 310 bp), which are considered as the most variable regions within the mammalian mitochondrial DNA, were sequenced. According to 49 polymorphic sites identified within the both parts of the D-loop region, the 16 maternal lines were grouped into 13 distinct mitochondrial haplotypes. The minimal difference between two different haplotype DNA sequences was one nucleotide and the maximal 24 nucleotides. The inheritance of mitochondrial haplotypes was stable and no sequence variation potentially attributable to mutation within maternal line was observed. Considerable DNA sequence similarity of Lipizzan mitochondrial haplotypes with the haplotypes from other breeds was observed. Phylogenetic analysis of the sequence data revealed a dendrogram with three separated branches, supporting the historical data about the multiple origin of the Lipizzan breed.     

Genetic stability in the Icelandic horse breed

Despite the Icelandic horse enjoying great popularity worldwide, the breed's gene pool is small. This is because of a millennium of isolation on Iceland, population crashes caused by natural disasters and selective breeding. Populations with small effective population sizes are considered to be more at risk of selection pressures such as disease and environmental change. By analysing historic and modern mitochondrial DNA sequences and nuclear coat colour genes, we examined real-time population dynamics in the Icelandic horse over the last 150 years. Despite the small gene pool of this breed, we found that the effective population size and genetic profile of the Icelandic horse have remained stable over the studied time period.     

Imputation of high-density genotypes in the Fleckvieh cattle population

Background

Currently, genome-wide evaluation of cattle populations is based on SNP-genotyping using ~ 54 000 SNP. Increasing the number of markers might improve genomic predictions and power of genome-wide association studies. Imputation of genotypes makes it possible to extrapolate genotypes from lower to higher density arrays based on a representative reference sample for which genotypes are obtained at higher density.

Methods

Genotypes using 639 214 SNP were available for 797 bulls of the Fleckvieh cattle breed. The data set was divided into a reference and a validation population. Genotypes for all SNP except those included in the BovineSNP50 Bead chip were masked and subsequently imputed for animals of the validation population. Imputation of genotypes was performed with Beagle, findhap.f90, MaCH and Minimac. The accuracy of the imputed genotypes was assessed for four different scenarios including 50, 100, 200 and 400 animals as reference population. The reference animals were selected to account for 78.03%, 89.21%, 97.47% and > 99% of the gene pool of the genotyped population, respectively.

Results

Imputation accuracy increased as the number of animals and relatives in the reference population increased. Population-based algorithms provided highly reliable imputation of genotypes, even for scenarios with 50 and 100 reference animals only. Using MaCH and Minimac, the correlation between true and imputed genotypes was > 0.975 with 100 reference animals only. Pre-phasing the genotypes of both the reference and validation populations not only provided highly accurate imputed genotypes but was also computationally efficient. Genome-wide analysis of imputation accuracy led to the identification of many misplaced SNP.

Conclusions

Genotyping key animals at high density and subsequent population-based genotype imputation yield high imputation accuracy. Pre-phasing the genotypes of the reference and validation populations is computationally efficient and results in high imputation accuracy, even when the reference population is small.     

Imputation of ungenotyped parental genotypes in dairy and beef cattle from progeny genotypes

The objective of this study was to quantify the accuracy of imputing the genotype of parents using information on the genotype of their progeny and a family-based and population-based imputation algorithm. Two separate data sets were used, one containing both dairy and beef animals (n=3122) with high-density genotypes (735 151 single nucleotide polymorphisms (SNPs)) and the other containing just dairy animals (n=5489) with medium-density genotypes (51 602 SNPs). Imputation accuracy of three different genotype density panels were evaluated representing low (i.e. 6501 SNPs), medium and high density. The full genotypes of sires with genotyped half-sib progeny were masked and subsequently imputed. Genotyped half-sib progeny group sizes were altered from 4 up to 12 and the impact on imputation accuracy was quantified. Up to 157 and 258 sires were used to test the accuracy of imputation in the dairy plus beef data set and the dairy-only data set, respectively. The efficiency and accuracy of imputation was quantified as the proportion of genotypes that could not be imputed, and as both the genotype concordance rate and allele concordance rate. The median proportion of genotypes per animal that could not be imputed in the imputation process decreased as the number of genotyped half-sib progeny increased; values for the medium-density panel ranged from a median of 0.015 with a half-sib progeny group size of 4 to a median of 0.0014 to 0.0015 with a half-sib progeny group size of 8. The accuracy of imputation across different paternal half-sib progeny group sizes was similar in both data sets. Concordance rates increased considerably as the number of genotyped half-sib progeny increased from four (mean animal allele concordance rate of 0.94 in both data sets for the medium-density genotype panel) to five (mean animal allele concordance rate of 0.96 in both data sets for the medium-density genotype panel) after which it was relatively stable up to a half-sib progeny group size of eight. In the data set with dairy-only animals, sufficient sires with paternal half-sib progeny groups up to 12 were available and the within-animal mean genotype concordance rates continued to increase up to this group size. The accuracy of imputation was worst for the low-density genotypes, especially with smaller half-sib progeny group sizes but the difference in imputation accuracy between density panels diminished as progeny group size increased; the difference between high and medium-density genotype panels was relatively small across all half-sib progeny group sizes. Where biological material or genotypes are not available on individual animals, at least five progeny can be genotyped (on either a medium or high-density genotyping platform) and the parental alleles imputed with, on average, ⩾96% accuracy.     

Genetic diversity and bottleneck studies in the Marwari horse breed

Genetic diversity within the Marwari breed of horses was evaluated using 26 different microsatellite pairs with 48 DNA samples from unrelated horses. This molecular characterisation was undertaken to evaluate the problem of genetic bottlenecks also, if any, in this breed. The estimated mean (± s.e.) allelic diversity was 5.9 (± 2.24), with a total of 133 alleles. A high level of genetic variability within this breed was observed in terms of high values of mean (±s.e.) effective number of alleles (3.3 ± 1.27), observed heterozygosity (0.5306 ± 0.22), expected Levene’s heterozygosity (0.6612 ± 0.15), expected Nei’s heterozygosity (0.6535 ± 0.14), and polymorphism information content (0.6120 ± 0.03). Low values of Wright’s fixation index, F_IS (0.2433 ± 0.05) indicated low levels of inbreeding. This basic study indicated the existence of substantial genetic diversity in the Marwari horse population. No significant genotypic linkage disequilibrium was detected across the population, suggesting no evidence of linkage between loci. A normal ‘L’ shaped distribution of mode-shift test, non-significant heterozygote excess on the basis of different models, as revealed from Sign, Standardized differences and Wilcoxon sign rank tests as well as non-significantM ratio value suggested that there was no recent bottleneck in the existing Marwari breed population, which is important information for equine breeders. This study also revealed that the Marwari breed can be differentiated from some other exotic breeds of horses on the basis of three microsatellite primers.     

Imputation of missing genotypes: an empirical evaluation of IMPUTE

Background

Polymorphism in genes of regulating enzymes, transporters and receptors of the neurotransmitters of the central nervous system have been associated with altered behaviour, and single nucleotide polymorphisms (SNPs) represent the most frequent type of genetic variation. The serotonin and dopamine signalling systems have a central influence on different behavioural phenotypes, both of invertebrates and vertebrates, and this study was undertaken in order to explore genetic variation that may be associated with variation in behaviour.

Results

Single nucleotide polymorphisms in canine genes related to behaviour were identified by individually sequencing eight dogs (Canis familiaris) of different breeds. Eighteen genes from the dopamine and the serotonin systems were screened, revealing 34 SNPs distributed in 14 of the 18 selected genes. A total of 24,895 bp coding sequence was sequenced yielding an average frequency of one SNP per 732 bp (1/732). A total of 11 non-synonymous SNPs (nsSNPs), which may be involved in alteration of protein function, were detected. Of these 11 nsSNPs, six resulted in a substitution of amino acid residue with concomitant change in structural parameters.

Conclusion

We have identified a number of coding SNPs in behaviour-related genes, several of which change the amino acids of the proteins. Some of the canine SNPs exist in codons that are evolutionary conserved between five compared species, and predictions indicate that they may have a functional effect on the protein. The reported coding SNP frequency of the studied genes falls within the range of SNP frequencies reported earlier in the dog and other mammalian species. Novel SNPs are presented and the results show a significant genetic variation in expressed sequences in this group of genes. The results can contribute to an improved understanding of the genetics of behaviour.     

Effect of breed of horse on muscle carnosine concentration

1. Muscle samples from the M. gluteus medius were obtained from six Quarter Horses (QH), six Thoroughbreds (TB), and five Standardbreds (SB) to determine carnosine values and fiber type percentages. 2. Muscle biopsies were for fiber type percentages and carnosine concentration. 3. QH had a lower percentage of slow twitch oxidative fibers and a higher percentage of past twitch glycolytic fibers than SB or TB. 4. Fast twitch oxidative-glycolytic fibers were lowest in the QH. 5. The QH had mean carnosine values significantly greater (P less than 0.01) than the mean values for SB and TB. 6. Across breeds muscle carnosine concentration was positively correlated (P less than 0.05; r = 0.53) with fast twitch glycolytic fiber percentage and negatively correlated (P less than 0.05, r = -0.51) with fast twitch oxidative fiber percentage. 7. Free intramuscular carnosine is believed to function as an intracellular buffer. Since carnosine was highest in the muscle of horses with the greatest percentage of fast twitch glycolytic fibers, these data are consistent with the proposed function of this dipeptide.     

Genetic diversity in the Pantaneiro horse breed assessed using microsatellite DNA markers

The genetic variability for a sample of 227 animals from three populations of Pantaneiro horses was estimated using data from 10 microsatellite loci. The number of alleles and the proportion of heterozygosity indicated high variability. A total of 91 alleles were found, with a significantly high mean number of alleles. The mean polymorphic information content was 0.7 and the paternity exclusion probability was 99.3%. The inbreeding coefficient (F(IS)) was low for the three populations: Ipiranga (F(IS) = 0.147), Nova Esperan?a (F(IS) = 0.094) and Promiss?o (F(IS) = 0.108). Genetic differentiation among all three populations was low (F(ST) = 0.008 to 0.064). Three methods were used to test for a recent bottleneck effect. The graphical method and the Wilcoxon test using the stepwise mutation model showed no bottleneck pattern for any of the populations. The test by two-phase mutation model showed genetic signatures of bottleneck for Ipiranga and Promiss?o. When we consider standard deviation value for Nova Esperan?a, the M-statistic detected a bottleneck pattern, but this result could be explained by a sample size effect. Therefore, there is no immediate cause for concern regarding loss of variation within the breed.     

Imputation of non-genotyped sheep from the genotypes of their mates and resulting progeny

Accurate genomic analyses are predicated on access to a large quantity of accurately genotyped and phenotyped animals. Because the cost of genotyping is often less than the cost of phenotyping, interest is increasing in generating genotypes for phenotyped animals. In some instances this may imply the requirement to genotype older animals with greater phenotypic information content. Biological material for these older informative animals may, however, no longer exist. The objective of the present study was to quantify the ability to impute 11 129 single nucleotide polymorphism (SNP) genotypes of non-genotyped animals (in this instance sires) from the genotypes of their progeny with or without including the genotypes of the progenys’ dams (i.e. mates of the sire to be imputed). The impact on the accuracy of genotype imputation by including more progeny (and their dams’) genotypes in the imputation reference population was also quantified. When genotypes of the dams were not available, genotypes of 41 sires with at least 15 genotyped progeny were used for the imputation; when genotypes of the dams were available, genotypes of 21 sires with at least 10 genotyped progeny were used for the imputation. Imputation was undertaken exploiting family and population level information. The mean and variability in the proportion of genotypes per individual that could not be imputed reduced as the number of progeny genotypes used per individual increased. Little improvement in the proportion of genotypes that could not be imputed was achieved once genotypes of seven progeny and their dams were used or genotypes of 11 progeny without their respective dam’s genotypes were used. Mean imputation accuracy per individual (depicted by both concordance rates and correlation between true and imputed) increased with increasing progeny group size. Moreover, the range in mean imputation accuracy per individual reduced as more progeny genotypes were used in the imputation. If the genotype of the mate of the sire was also used, high accuracy of imputation (mean genotype concordance rate per individual of 0.988), with little additional benefit thereafter, was achieved with seven genotyped progeny. In the absence of genotypes on the dam, similar imputation accuracy could not be achieved even using genotypes on up to 15 progeny. Results therefore suggest, at least for the SNP density used in the present study, that it is possible to accurately impute the genotypes of a non-genotyped parent from the genotypes of its progeny and there is a benefit of also including the genotype of the sire’s mate (i.e. dam of the progeny).     

Imputation of genotypes in Danish purebred and two-way crossbred pigs using low-density panels

Background

Genotype imputation is commonly used as an initial step in genomic selection since the accuracy of genomic selection does not decline if accurately imputed genotypes are used instead of actual genotypes but for a lower cost. Performance of imputation has rarely been investigated in crossbred animals and, in particular, in pigs. The extent and pattern of linkage disequilibrium differ in crossbred versus purebred animals, which may impact the performance of imputation. In this study, first we compared different scenarios of imputation from 5 K to 8 K single nucleotide polymorphisms (SNPs) in genotyped Danish Landrace and Yorkshire and crossbred Landrace-Yorkshire datasets and, second, we compared imputation from 8 K to 60 K SNPs in genotyped purebred and simulated crossbred datasets. All imputations were done using software Beagle version 3.3.2. Then, we investigated the reasons that could explain the differences observed.

Results

Genotype imputation performs as well in crossbred animals as in purebred animals when both parental breeds are included in the reference population. When the size of the reference population is very large, it is not necessary to use a reference population that combines the two breeds to impute the genotypes of purebred animals because a within-breed reference population can provide a very high level of imputation accuracy (correct rate ≥ 0.99, correlation ≥ 0.95). However, to ensure that similar imputation accuracies are obtained for crossbred animals, a reference population that combines both parental purebred animals is required. Imputation accuracies are higher when a larger proportion of haplotypes are shared between the reference population and the validation (imputed) populations.

Conclusions

The results from both real data and pedigree-based simulated data demonstrate that genotype imputation from low-density panels to medium-density panels is highly accurate in both purebred and crossbred pigs. In crossbred pigs, combining the parental purebred animals in the reference population is necessary to obtain high imputation accuracy.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-015-0134-4) contains supplementary material, which is available to authorized users.     

Imputation of missing genotypes from sparse to high density using long-range phasing

Related individuals share potentially long chromosome segments that trace to a common ancestor. We describe a phasing algorithm (ChromoPhase) that utilizes this characteristic of finite populations to phase large sections of a chromosome. In addition to phasing, our method imputes missing genotypes in individuals genotyped at lower marker density when more densely genotyped relatives are available. ChromoPhase uses a pedigree to collect an individual's (the proband) surrogate parents and offspring and uses genotypic similarity to identify its genomic surrogates. The algorithm then cycles through the relatives and genomic surrogates one at a time to find shared chromosome segments. Once a segment has been identified, any missing information in the proband is filled in with information from the relative. We tested ChromoPhase in a simulated population consisting of 400 individuals at a marker density of 1500/M, which is approximately equivalent to a 50K bovine single nucleotide polymorphism chip. In simulated data, 99.9% loci were correctly phased and, when imputing from 100 to 1500 markers, more than 87% of missing genotypes were correctly imputed. Performance increased when the number of generations available in the pedigree increased, but was reduced when the sparse genotype contained fewer loci. However, in simulated data, ChromoPhase correctly imputed at least 12% more genotypes than fastPHASE, depending on sparse marker density. We also tested the algorithm in a real Holstein cattle data set to impute 50K genotypes in animals with a sparse 3K genotype. In these data 92% of genotypes were correctly imputed in animals with a genotyped sire. We evaluated the accuracy of genomic predictions with the dense, sparse, and imputed simulated data sets and show that the reduction in genomic evaluation accuracy is modest even with imperfectly imputed genotype data. Our results demonstrate that imputation of missing genotypes, and potentially full genome sequence, using long-range phasing is feasible.     

Goat casein genotypes are associated with milk production traits in the Sarda breed

The aim of the current work was to analyze, in the Sarda breed goat, genetic polymorphism within the casein genes and to assess their influence on milk traits. Genetic variants at the CSN1S1, CSN2, CSN1S2 and CSN3 gene loci were investigated using PCR‐based methods, cloning and sequencing. Strong alleles prevailed at the CSN1S1 gene locus and defective alleles also were revealed. Null alleles were evidenced at each calcium‐sensitive gene locus. At the CSN3 gene locus, we observed a prevalence of the CSN3 A and B alleles; the occurrence of rare alleles such as CSN3 B'', C, C', D, E and M; and the CSN3 S allele (GenBank KF644565 ) described here for the first time in Capra hircus. Statistical analysis showed that all genes, except CSN3, significantly influenced milk traits. The CSN1S1 BB and AB genotypes were associated with the highest percentages of protein (4.41 and 4.40 respectively) and fat (5.26 and 5.34 respectively) (P < 0.001). A relevant finding was that CSN2 and CSN1S2 genotypes affected milk protein content and yield. The polymorphism of the CSN2 gene affected milk protein percentage with the highest values recorded in the CSN2 AA goats (4.35, at P < 0.001). The CSN1S2 AC goats provided the highest fat (51.02 g/day) and protein (41.42 g/day) (P < 0.01) production. This information can be incorporated into selection schemes for the Sarda breed goat.     

Evidence for eumelanin and pheomelanin producing genotypes in the Arabian horse

The ultrastructural imaging of melanocytes coupled with analyses to detect sulfur-containing melanosomes by energy-dispersive X-ray spectroscopy were used to test the hypothesis that the yellowish-red and black pigments found in Arabian horses result from pheomelanogenesis and eumelanogenesis, respectively. These procedures detected pheomelanosomes in follicles at the base of hairs in chestnut horses and eumelanosomes in follicles at the base of hairs in black horses. By analyzing tissue obtained by skin biopsy, these procedures also demonstrated that skin melanocytes in a chestnut horse produce eumelanosomes, and follicular melanocytes in the same horse produce pheomelanosomes. It was also shown that the type of follicular melanosome present in light bay horses is correlated with the color of the hair. The results of this study give experimental evidence for the Odriozola-Adalsteinsson hypothesis that the e allele is responsible for the chestnut phenotype; they also give fine structure and chemical confirmation of the action of the A and E loci in the Arabian horse as currently proposed for the mouse and other mammals.     

Morphological evolution and heritability estimates for some biometric traits in the Murgese horse breed

A data set concerning 1,816 subjects entered in the Italian Horse Registry from 1925 to 2002 was analyzed to investigate the morphological evolution of the Murgese horse and to obtain useful elements to enhance breeding practices. Three basic body measurements (height at withers, chest girth, and cannon bone circumference) were considered for each subject. Heritabilities were calculated for each parameter to infer the growth and development traits of this breed. Over the past 20 years the Murgese horse has undergone considerable changes, passing from a typical mesomorphic structure (height at withers: 156.30 and 151.04 cm; chest girth: 185.80 and 176.11 cm; cannon bone: 21.10 and 19.82 cm for males and females, respectively) to a mesodolichomorphic structure (height at withers: 160.31 and 156.44 cm; chest girth: 187.89 and 182.48 cm; cannon bone: 21.07 and 20.37 cm, for males and females, respectively). Due to these changes and to its characteristic strength and power, the Murgese, which was once used in agriculture and for meat production (at the end of its life), is now involved in sports, mainly in trekking and equestrian tourism. The heritability estimates for the three body measurements were found to be 0.24, 0.39 and 0.44.     

Imputation of genotypes from low- to high-density genotyping platforms and implications for genomic selection

The objective of this study was to quantify the accuracy achievable from imputing genotypes from a commercially available low-density marker panel (2730 single nucleotide polymorphisms (SNPs) following edits) to a commercially available higher density marker panel (51 602 SNPs following edits) in Holstein-Friesian cattle using Beagle, a freely available software package. A population of 764 Holstein-Friesian animals born since 2006 were used as the test group to quantify the accuracy of imputation, all of which had genotypes for the high-density panel; only SNPs on the low-density panel were retained with the remaining SNPs to be imputed. The reference population for imputation consisted of 4732 animals born before 2006 also with genotypes on the higher density marker panel. The concordance between the actual and imputed genotypes in the test group of animals did not vary across chromosomes and was on average 95%; the concordance between actual and imputed alleles was, on average, 97% across all SNPs. Genomic predictions were undertaken across a range of production and functional traits for the 764 test group animals using either their real or imputed genotypes. Little or no mean difference in the genomic predictions was evident when comparing direct genomic values (DGVs) using real or imputed genotypes. The average correlation between the DGVs estimated using the real or imputed genotypes for the 15 traits included in the Irish total merit index was 0.97 (range of 0.92 to 0.99), indicating good concordance between proofs from real or imputed genotypes. Results show that a commercially available high-density marker panel can be imputed from a commercially available lower density marker panel, which will also have a lower cost, thereby facilitating a reduction in the cost of genomic selection. Increased available numbers of genotyped and phenotyped animals also has implications for increasing the accuracy of genomic prediction in the entire population and thus genetic gain using genomic selection.     

Genome‐wide association studies based on sequence‐derived genotypes reveal new QTL associated with conformation and performance traits in the Franches–Montagnes horse breed

To identify novel quantitative trait loci (QTL) within horses, we performed genome‐wide association studies (GWAS) based on sequence‐level genotypes for conformation and performance traits in the Franches–Montagnes (FM) horse breed. Sequence‐level genotypes of FM horses were derived by re‐sequencing 30 key founders and imputing 50K data of genotyped horses. In total, we included 1077 FM horses genotyped for ~4 million SNPs and their respective de‐regressed breeding values of the traits in the analysis. Based on this dataset, we identified a total of 14 QTL associated with 18 conformation traits and one performance trait. Therefore, our results suggest that the application of sequence‐derived genotypes increases the power to identify novel QTL which were not identified previously based on 50K SNP chip data.     

Exon 1 polymorphisms in the equine CSN3 gene: SNPs distribution analysis in Murgese horse breed

The aim of this study was to assess genetic polymorphism at two loci in the exon 1 of the CSN3 gene in Murgese horse breed by PCR-RFLP analysis. The overall frequencies of alleles A and G at c.-66A?>?G locus were 0.80 and 0.20, respectively, and no GG animals were found in the population. At the c.-36C?>?A locus allelic frequencies were 0.74 and 0.26 for allele C and A, respectively, and no AA animals were detected. Population genetic indexes, namely gene heterozygosity, gene homozygosity, effective allele numbers, fixation index, and polymorphism information index were calculated. Combined genotypic frequencies and possible haplotypes frequencies were also reported. Only three out of nine possible genotypic combinations were found in the studied population. The most frequent genotype was AACC (0.49) while the frequency of AGCA was 0.40. Only five animals were genotyped as AACA (11%). Consequently, the most frequent haplotype in the population was AC (0.744), followed by GA (0.200) and AA (0.056).