Methods for calculating the breeding values of missing traits and their comparison

The objective of this study was to calculate the breeding values (BVs) of traits missing in a selection index. Different traits can be evaluated within the breeding programs of given countries. The BV of a trait can be calculated based on genetic correlations with other traits. Similarly, the BV of a missing trait can be calculated for imported bulls. Two methods of calculation were used. Method A was based on a regression of BVs. Method B was based on performing a de-regression of BVs and their retroactive calculation. Both of these methods were tested using a Czech and a Canadian database of BVs for Holstein bulls. The Czech database of Holstein bulls contained 766 bulls and the Canadian database 851. Two calculations were performed for bulls with low reliability of estimated BVs, the first calculation with their genetic correlation matrix and the second with a genetic correlation matrix created from a set of bulls with high reliability of BVs. These newly calculated BVs (CBVs) were then compared with the national BVs (NBVs) using correlation coefficients. The highest correlations were achieved with high reliability bulls when all traits were included into the calculation (34 evaluated traits). The correlations of these bulls averaged 0.82, with an average standard deviation of 0.19. The lowest correlations were found when low reliability bulls were included and the genetic correlation matrix from the high reliability bulls was applied. That average correlation was 0.74 and standard deviation 0.25. When only 15 traits were evaluated in the model, the average correlation for all sets was 0.68 with standard deviation of 0.28. These results show that calculating the BV of a missing trait is possible using both methods. Method B was slightly more accurate in its prediction

Genetic Distances and Admixture between Sire Lines of the Old Kladruber Horse

The objective of the study was to determine the genetic distances and admixture in sire lines of Old Kladruber horse (populations in the context of a currently conducted conservation program) base on microsatellite analysis. Basic molecular parameters were estimated. The observed heterozygosity ranged from 0.48 to 0.85. The expected heterozygosity estimated for the sire lines was higher than observed heterozygosity. The minor genetic differences between sire lines of Old Kladruber horse were observed. Differences between the sire lines were identified using discriminant analysis. The first discriminant function separates the individuals of black and grey variants. For the discriminant function, however, the differentiation between sire lines was not so significant. These results showed that the breeding strategy revision is suggested in Old Kladruber horse

Genetic diversity in five Czech native horse breeds assessed using microsatellite markers

Received: 2018-05-07 | Accepted: 2018-05-14 | Available online: 2018-11-26https://doi.org/10.15414/afz.2018.21.04.190-193The aim of the present study was to analyse the genetic diversity of the endangered horse breeds kept in the Czech Republic. A set of 13 microsatellites was used for genotyping 349 Silesian Norikers, 397 Norikers, 552 Czech-Moravian Belgian horses, 271 Old Kladrubers (175 greys, 95 blacks) and 241 Hucul horses. The proportion of obtained heterozygosity indicates no major loss of genetic diversity within analyzed breeds. The Wright’s FST and genetic distances indicated genetic segregation of both colour varieties of the Old Kladruber breed and small genetic distances between draft horse breeds. Moreover, the membership probability outputs showed that the frequencies of alleles varied across the three main regions. First region is represented by draft horse breeds, second region is represented by Old Kladruber horse and the last is represented by Hucul breed. The study provides data and information utilizable in the management of conservation programs in order to reduce inbreeding and to minimize loss of genetic variability.Keywords: admixture, endangered breeds, horse, loss of genetic diversityReferencesDelgado J.F., De Andres N., Valera M., Gutierrez J.P., Cervantes I. (2014) Assessment of population structure depending on breeding objectives in Spanish Arabian horse by genealogical and molecular information. Livestock Science, 168, 9–16. DOI: https://dx.doi.org/10.1016/j.livsci.2014.07.012Jombart T., Ahmed I. (2011) adegenet 1.3-1: new tools for the analysis of genome-wide SNP data. Bioinformatics, 27, 3070–3071. DOI: https://dx.doi.org/10.1093/bioinformatics/btr521 Jombart T., Collins C. (2015): A tutorial for diskriminant analysis of principal components (DAPC) using adegenet 2.0.0. MRC Centre for Outbreak Analysis and Modelling. [Online] London: Imperial College London. Available at: http://adegenet.rforge. r-project.org/files/tutorial-dapc.pdf [accessed 20 November 2017].Kasarda R., Vostry L., Moravcikova N., Vostra-Vydrova H., Dovc P., Kadlecik O. (2016) Detailed insight into genetic diversity of the Old Kladruber horse substructure in comparison to the Lipizzan breed. Acta Agriculturae Scandinavica, Section A – Animal Science, 66, 67–74. DOI: https://dx.doi.org/10.1080/09064702.2016.1249400Peakall, R. and Smouse P.E. (2012) GenAlEx 6.5: genetic analysis in Excel. Population genetic software for taching and research-an update. Bioinformatics 28, 2537-2539. DOI: https://dx.doi.org/10.1093/bioinformatics/bts460Szwaczkowski T., Gregula-Kania M., Stachurska A., Borowska A., Jaworski Z., Gruszecki T.M. (2016) Interand intra-genetic diversity in the Polish Konik horse: implications for the conservation program. Canadian Journal of Animal Science, 96 (4), 570–580. DOI: https://dx.doi.org/10.1139/cjas-2015-017

Genetic Parameters for Linear Type Traits in Three Czech Draught Horse Breeds

Horse conformation is considered an indicator of performance, which plays an important role in breeding decisions. Genetic parameters were estimated for linear type traits in three draught horse breeds – Czech-Moravian Belgian horse, Silesian Noriker and Noriker. Traits were divided in six groups according to the region of the body. Observations on 946 Czech Moravian Belgian horses, 574 Silesian Norikers and 640 Norikers were analysed using a multi breed multitrait animal model. Fixed effects of sex, age at scoring, breed and contemporary group were considered. Genetic parameters were estimated using restricted maximum likelihood. Estimated heritability ranged from 0.05 to 0.59. Lowest values were estimated for stance of back pasterns and shape of back feet, while highest values were found for body measures. Estimations of genetic correlation between traits ranged from -0.53 to 0.98. The highest correlation was found between length of stride in walk and length of stride in trot. The estimated heritabilities and correlations suggest that a genetic improvement of analysed traits is feasible

Population studies of Czech Sport Pony

Received: 2016-11-07 | Accepted: 2016-11-18 | Available online: 2017-12-31http://dx.doi.org/10.15414/afz.2017.20.04.84-89Population study of Czech Sport Pony breed was carried out based on pedigree information of animals registered in the Studbook. Pedigree records collected from the year 1972 to 2016 comprised information on 12548 animals used in the analyses. The pedigree depth of the analysed individuals was relatively low (3.7 generations). The mean value of inbreeding coefficient was 0.3 % (with maximum value 26 %). The proportion of non-inbreed animals was high (80 %). The average rate of inbreeding in the reference population was lower than 1 %, and the estimates of effective population sizes were relatively high (789). The presented paper is indicating that genetic diversity in the Czech Sport Pony breeds is still relatively high. However the available genetic variability in the Czech Sport Pony breed as an open population with continuous migration and gene flow was lower than was expected. Active management of the future rate of inbreeding is necessary for this breed.Keywords: inbreeding, rate of inbreeding, effective populations, open populationReferencesÁLVAREZ, I. et al. (2008) Relationship between genealogical and microsatellite information characterizing losses of genetic variability: Empirical evidence from the rare Xalda sheep breed. Livest. Sci., vol. 115, pp. 80–88. doi:http://dx.doi.org/10.1016/j.livsci.2007.06.009BOICHARD, D. et al., (1997) The value of using probabilities of gene origin to measure genetic variability in a population. Genet. Sel. Evol., vol .29, pp. 5–23. doi:http://dx.doi.org/10.1051/gse:19970101CABALLERO, A. (1994) Developments in the prediction of effictive population size. Heredity, vol. 73, pp. 657-679. doi:http://dx.doi.org/10.1038/hdy.1994.174CABALLERO, A. and TORO, M. A. (2000) Interrelations between effective population size and other pedigree tools for the management of conserved populations. Genet. Res. vol., 75, pp. 331–343.CABALLERO, A. and TORO, M. A. (2002) Analysis of genetic diversity for the management of conserved subdivided populations. Conserv. Genet., vol. 3, pp. 289–299.CERVANTES, I. et al. (2011) Estimation of effective population size from the rate of coancestry in pedigreed populations: Effective population size from rate of coancestry. J. Anim. Breed. Genet., vol. 128, pp. 56–63. doi:http://dx.doi.org/10.1111/j.1439-0388.2010.00881.xCERVANTES, I. et al. (2008) Population history and genetic variability in the Spanish Arab Horse assessed via pedigree analysis. Livest. Sci., vol. 113. pp. 24–33. doi:http://dx.doi.org/10.1016/j.livsci.2007.02.011CURIK, I. (2003) Inbreeding, Microsatellite Heterozygosity, and Morphological Traits in Lipizzan Horses. J. Hered., vol. 94, pp. 125–132. doi:http://dx.doi.org/10.1093/jhered/esg029DRUML, T., BAUMUNG, R. and SÖLKNER J. ( 2009) Pedigree analysis in the Austrian Noriker draught horse: genetic diversity and the impact of breeding for coat colour on population structure. J. Anim. Breed. Genet. 126:348–356. doi:http://dx.doi.org/10.1111/j.1439-0388.2008.00790.xFALCONER, D. S., and MACKAY, T. F. C. (2009) Introduction to quantitative genetics. 4. ed., Pearson, Prentice Hall, Harlow.FERNANDEZ, J. et al. (2005) Efficiency of the Use of Pedigree and Molecular Marker Information in Conservation Programs. Genetics., vol. 170, pp.1313–1321. doi:http://dx.doi.org/10.1534/genetics.104.037325GÓMEZ, M. D. et al.(2009) Assessment of inbreeding depression for body measurements in Spanish Purebred (Andalusian) horses. Livest. Sci., vol. 122, pp. 149–155. doi:http://dx.doi.org/10.1016/j.livsci.2008.08.007GOYACHE, F. et al. (2003) Using pedigree information to monitor genetic variability of endangered populations: the Xalda sheep breed of Asturias as an example. J. Anim. Breed. Genet., vol. 120, pp. 95–105. doi:http://dx.doi.org/10.1046/j.1439-0388.2003.00378.xGUTIÉRREZ, J. P. (2008) Individual increase in inbreeding allows estimating effective sizes from pedigrees. Genet. Sel. Evol., vol. 40, pp. 359–378. doi:http://dx.doi.org/10.1051/gse:2008008JAMES, J. W. (1972) Computation of genetic contributions from pedigrees. Theor. Appl. Genet., vol. 42, pp. 272–273. doi:http://dx.doi.org/10.1007/BF00277555KADLEČÍK, O., and KASARDA, R. (2014) Genetic diversity of Slovak Sport Pony based on genealogical information. In Book of abstracts of the 65th annual meeting of the European federation of animal science. Wageningen: Wageningen Academic Publishers, 2014, p. 378.Lacy, R. C. (1989) Analysis of founder representation in pedigrees: Founder equivalents and founder genome equivalents. Zoo Biol.. vol. 8, pp. 111–123. doi:http://dx.doi.org/10.1002/zoo.1430080203LACY, R. C. (1995) Clarification of genetic terms and their use in the management of captive populations. Zoo Biol., vol. 14, pp. 565–577. doi:http://dx.doi.org/10.1002/zoo.1430140609LACY, R. C. and BALLOU J. D. (1998) Effectiveness of Selection in Reducing the Genetic Load in Populations of Peromyscus polionotus During Generations of Inbreeding. Evolution, vol. 52, pp. 900. doi:http://dx.doi.org/10.2307/2411285MacCLUER, J.  et al. (1983) Inbreeding and Pedigree Structure in Standardbred horses. Heredity, vol. 74, pp. 394–399.MAIGNEL, L., BOICHARD D. and VERRIER E. (1996) Genetic variability of French dairy breeds estimated from pedigree information. Interbull Bull., vol. 14, pp. 49–54.PJONTEK, J. et al. (2012) Pedigree analysis in four Slovak endangered horse breeds. Czech J Anim Sci., vol. 57, pp. 54–64.SIDERITS, M., BAUMUNG, R. and FUERST-WALTL, B. (2013) Pedigree analysis in the German Paint Horse: Genetic variability and the influence of pedigree quality. Livest. Sci. 151:152–157. doi:http://dx.doi.org/10.1016/j.livsci.2012.10.018SØRENSEN, A. C., SØRENSEN, M. K. and BERG, P. (2005) Inbreeding in Danish dairy cattle breeds. J. Dairy Sci., vol. 88, pp.1865–1872.Valera, M. et al. (2005) Pedigree analysis in the Andalusian horse: population structure, genetic variability and influence of the Carthusian strain. Livest. Prod. Sci., vol. 95, pp. 57–66. doi:http://dx.doi.org/10.1016/j.livprodsci.2004.12.004VanRADEN, P. M. (1992) Accounting for Inbreeding and Crossbreeding in Genetic Evaluation of Large Populations. J. Dairy Sci., vol. 75, pp. 3136–3144. doi:http://dx.doi.org/10.3168/jds.S0022-0302(92)78077-1VICENTE, A. A., CAROLINO, N.. and GAMA, L. T. (2012) Genetic diversity in the Lusitano horse breed assessed by pedigree analysis. Livest. 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Analysis of Inbreeding Effects on Survival at Birth of Pannon White Rabbits Using the Inbreeding-Purging Model

Mating between related animals is an inevitable consequence of a closed population structure especially when it coincides with a small population size. As a result, inbreeding depression may be encountered especially when considering fitness traits. However, under certain circumstances, the joint effects of inbreeding and selection may at least partly purge the detrimental genes from the population. In the course of this study, our objective was to determine the status of purging and to quantify the magnitude of the eliminated genetic load for the survival at birth of Pannon White rabbit kits maintained in a closed nucleus population. The evolution of the survival at birth was evaluated by applying the PurgeR R package based on the inbreeding-purging model. In the period from 1992 to 2017, 22.718 kindling records were analyzed. According to the heuristic approach, the purging coefficient reached the maximum possible value of 0.5 when estimating between 1992 and 1997. Based on the expected fitness over generations and on the expressed opportunity of purging, the beneficial effects of purging could be expected after 10 generations. The proportion of the purged genetic load could be between 20% and 60%. While the results obtained are not entirely conclusive, they do raise the possibility that some of the inbreeding load was caused, at least in part, by genes that could be successfully removed from the population by purging