Preliminary analysis of utilization of genomic relationship in mating plan of Old Kladruber horse

The study analyzed 48 Old Kladruber horses genotyped by Illumina Equine SNP70 BeadChip for usefulness of genomic data in determining of mating plan. Totally 12 variants of data filtering and their impact on calculations in dependence of different parameters of GenCall Score, Minor Allele Frequency and assumed average values of loci of ancestors (l) was investigated. For possibility of comparison between genomic and commonly evaluated relationships, pedigree based relationship matrix was constructed and subsequently subtraction of pedigree from genomic matrix was performed. All matrices were thoroughly inspected and most suitable setting of parameters was chosen. Evaluation of genomic relationships can be successfully implemented in more precise method of mating plan design of Old Kladruber horses. Further genotyping and development of method for rescaling of differences between genomic and pedigree relationship matrices´ elements is advised for a purpose of better interpretation of results by breeders

GENETIC DIVERSITY IN CZECH HAFLINGER HORSES

The Haflinger as a small moutain horse breed originated from the South Tyrol district as a cross of Alpen Mountain breeds with Araber. This breed was expanding to Czech Republic during the last 25 years. The aim of this study was to analyse genetic diversity within the population using microsatellite markers. A total of 95 alleles have been detected. The highest frequency 88.18% showed allele 101 (HTG 6). The heterosigosity varied from 0.25 (HTG 6) to 0.84 (VHL 20), genetic diversity reached 0.6–0.8. The heterozygosity of the whole population studied is FIS= -0.013. The average effective number of allele per locus was 2.93 with standard deviation 1.54, with minimal and maximal level 1.30 and 7.83, respectively. Average polymorphism information content per locus was 0.608 with standard derivation 0.146, with minimal and maximal level 0.208 and 0.824, respectively. The results showed that breeding program of Czech Haflinger is optimal, including optimized mating strategies. The diversity of the population Czech Haflinger, based on a small number of microsatellites, seems to be sufficient

Genetic variability analysis of 26 sheep breeds in the Czech Republic.

In this study, the intra- and inter-population level of genetic diversity of 26 transboundary and local sheep breeds reared in the Czech Republic was analysed. A total of 14,999 animals genotyped for 11 microsatellite markers were included to describe the gene pool of the breeds. The level of genetic diversity was derived from the proportion of heterozygous animals among and within breeds. The average polymorphic information content (0.745) and Shannon’s index (1.361) showed a high genetic variability of the applied set of genetic markers. The average observed heterozygosity (0.683 ± 0.009), as well as FIS index (-0.025 ± 0.004), pointed to a sufficient proportion of heterozygotes concerning the loss of genetic diversity. The deficit of heterozygotes was most evident in Cameroon sheep (FIS = 0.036). The Nei's genetic distances and Wright's FST indexes showed that the analysed breeds are genetically differentiated to separate clusters with Cameroon sheep as the most genetically distant breed. Individual variation accounted for 83.2 % of total diversity conserved across breeds, whereas 16.8 % of genetic similarity resulted from the inter-population reduction in heterozygosity.Keywords: microsatellite analysis, genetic diversity, sheep, transboundary and local breedReferencesBravo, S. et al. (2019). Genetic diversity and phylogenetic relationship among araucana creole sheep and Spanish sheep breeds. Small Ruminant Research, 172, 23–30. https://doi.org/10.1016/j.smallrumres.2019.01.007Chessa, B. et al. (2009). Revealing the history of sheep domestication using retrovirus integrations. Science, 324(5926), 532–536. https://doi.org/10.1126/science.1170587Faigl, V. et al. (2012). Artificial insemination of small ruminants - A review. Acta Veterinaria Hungarica, 60(1), 115–129. https://doi.org/10.1556/AVet.2012.010FAO. (2007). The State of the World’s Animal Genetic Resources for Food and Agriculture. Edited by D. P. Barbara Rischkowsky. Rome, Italy.FAO. (2020). Domestic Animal Diversity Information System. Retrieved from http://www.fao.org/dad-is/transboundary-breed/en/Gaouar, S. B. S., Kdidi, S. and Ouragh, L. (2016). Estimating population structure and genetic diversity of five Moroccan sheep breeds by microsatellite markers. Small Ruminant Research, 144, 23–27. https://doi.org/10.1016/j.smallrumres.2016.07.021Hennink, S. and Zeven, A. C. (1990). The interpretation of Nei and Shannon-Weaver within population variation indices. Euphytica, 51(3), 235–240. https://doi.org/10.1007/BF00039724Hoda, A. and Bytyqi, H. (2017). Genetic diversity of sheep breeds from Albania and Kosova by microsatellite markers and mtDNA. Albanian Journal of Agricultural Science, 13-17.Jawasreh, K. et al. (2018). Genetic diversity and population structure of local and exotic sheep breeds in Jordan using microsatellites markers. Veterinary World, 11(6), 778–781. https://doi.org/10.14202/vetworld.2018.778-781Jyotsana, B. et al. (2010). Genetic features of Patanwadi, Marwari and Dumba ssheep breeds (India) inferred bymicrosatellite markers. Small Ruminant Research, 93(1), 57–60. https://doi.org/10.1016/j.smallrumres.2010.03.008Kalinowski, S. T., Taper, M. L. and Marshall, T. C. (2007). Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Molecular Ecology, 16(5), 1099–1106. https://doi.org/10.1111/j.1365-294x.2007.03089.xLoukovitis, D. et al. (2016). Genetic diversity of Greek sheep breeds and transhumant populations utilizing microsatellite markers. Small Ruminant Research, 136, 238–242. https://doi.org/10.1016/j.smallrumres.2016.02.008Mahmoud, A. H. et al. (2020). Genetic variability of sheep populations of Saudi Arabia using microsatellite markers. Indian Journal of Animal Research, 54(4), 409-412. http://dx.doi.org/10.18805/ijar.B-775Moravčíková, N. et al. (2016). Genetic diversity of Old Kladruber and Nonius horse populations through microsatellite variation analysis. Acta Agriculturae Slovenica, Supplement 5, 45–49.Naqvi, A. N. et al. (2017). Assessment of genetic diversity and structure of major sheep breeds from Pakistan. Small Ruminant Research, 148, 72–79. https://doi.org/10.1016/j.smallrumres.2016.12.032Nei, M. (1978). Estimation of average heterozygosity and genetic distance from a small number of individuals. Genetics, 89(3), 583-590.Neubauer, V. et al. (2015). Genetic diversity and population structure of Zackel sheep and other Hungarian sheep breeds. Archives Animal Breeding, 58(2), 343–50. https://doi.org/10.5194/aab-58-343-2015Niu, L. L. et al. (2012). Genetic variability and individual assignment of Chinese indigenous sheep populations (Ovis aries) using microsatellites. Animal Genetics, 43(1), 108–111. https://doi.org/10.1111/j.1365-2052.2011.02212.xOcampo, R. J. et al. (2017). Genetic characterization of Colombian indigenous ssheep. Revista Colombiana de Ciencias Pecuarias, 30(2), 116–25. http://dx.doi.org/10.17533/udea.rccp.v30n2a03Othman, O. E. M. et al. (2016). Sheep diversity of five Egyptian breeds: Genetic proximity revealed between desert breeds: Local sheep breeds diversity in Egypt. Small Ruminant Research, 144, 346–352. https://doi.org/10.1016/j.smallrumres.2016.10.020Peakall, R. and Smouse, P. E. (2012). GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research-an update. Bioinformatics, 28(19), 2537–2539. https://dx.doi.org/10.1093/bioinformatics/bts460Peakall, R. and Smouse, P. E. (2006). Genalex 6: genetic analysis in Excel. Population genetic software for teaching and research. Molecular Ecology Notes, 6(1), 288–295. https://doi.org/10.1111/j.1471-8286.2005.01155.xPeter, C. et al. (2007). Genetic diversity and subdivision of 57 European and Middle-Eastern ssheep breeds. Animal Genetics, 38(1), 37–44. https://doi.org/10.1111/j.1365-2052.2007.01561.xPichler, R. et al. (2017). Short tandem repeat (STR) based genetic diversity and relationship of domestic sheep breeds with primitive wild Punjab Urial sheep (Ovis vignei punjabiensis). Small Ruminant Research, 148, 11–21. https://doi.org/10.1016/j.smallrumres.2016.12.024Qwabe, S. O., van Marle-Köster, E. and Visser, C. (2013). Genetic diversity and population structure of the endangered Namaqua Afrikaner ssheep. Tropical Animal Health and Production, 45(2), 511–516. https://doi.org/10.1007/s11250-012-0250-xRaoul, J. and Elsen, J.-M. (2020). Effect of the rate of artificial insemination and paternity knowledge on the genetic gain for French meat sheep breeding programs. 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Multilocus genotypic data reveal high genetic diversity and low population genetic structure of Iranian indigenous sheep. Animal Genetics, 47(4), 463–470. https://doi.org/10.1111/age.12429Weir, B. S. and Cockerham, C. C. (1984). Estimating F-statistics for the analysis of population structure. Evolution, 38(6), 1358–1370. https://doi.org/10.2307/2408641

GENETIC CONTRIBUTION OF RAM ON LITTER SIZE IN ŠUMAVA SHEEP

The objective of the present study was to quantify the service sire effect in terms of (co) variance components of born and weaned lambs number and to propose models for the potential inclusion of this effect in the linear equations for breeding value estimation. The database with 21,324 lambings in Šumava sheep from 1992- 2013 was used. The basic model equation for the analysis of variance of litter size contained effects of ewe´s age at lambing, contemporary group, permanent environmental effect of ewe and direct additive genetic effect of ewe. Two modifications of the basic model were used for estimation of service sire effect. The proportions of variance for the service sire effect for number of born and weaned lambs were 2.1% and 2.0%, when service sire was not included into relationship matrix; while included into the relationship matrix and dividing effect into genetic contribution and permanent environment effect refer that nongenetic effect seems to be bigger than genetic (0.013 vs. 0.009 for number of born and 0.017 vs. 0.004 for number of weaned). Changes in other variance components were relatively low, except of contemporary group. Model including service sire effect as a simple random effect without genetic relationship matrix inclusion is recommended for genetic evaluation of litter size traits

QUANTITATIVE ASPECTS OF COAT COLOR IN OLD KLADRUBER BLACK HORSES

Base economic characteristics (total revenues, total costs, profit and profitability ratio) of the Slovak Pinzgau breed were calculated in this study. Under the actual production and economic conditions of the breed, production system is operated with loss (-457 € per cow and per year) and with negative profitability ratio (-20%). Optimisation of the production parameters on the level defined in the breed standard (5,200 kg milk per cow and year, 92% for conception rate of cows, 404 days of calving interval and 550 g in daily gain of reared heifers) and improved udder health traits (clinical mastitis incidence and somatic cells score) was of positive impact on the total revenues (+34%), on the effective utilisation of costs (+105%) and balanced profit of dairy systems. Next to the positive profitability of the system, higher quality and security of dairy milk products should be mentioned there. Moreover, direct subsidies as an important factor of positive economic result of dairy cattle systems has to be pointed as well. Subsidies should be provided to compensate the real biological limitation of the local breed farmed in marginal areas. However, improvement of the production parameters of the Slovak Pinzgau breed is recommended with the same attention to reach the economic sustainability of dairy production system. To reach economic sustainability of the breed from practical point of view, the farmer activity should be aimed especially to the enhanced herd management

Effect of a novel polymorphism of the LF and TLR4 genes on milk yield and milk compositions in dairy goats

In total 593 goats were genotyped on 5 single nucleotide polymorphisms (SNP): one SNP at Lactoferrin in exon 4 and four SNPs at Toll-like receptor 4 in exon 3 by using SNaPshot minisequencing. The most prevalent genotype was TT (546) in LF and genotype combination TTCCCCGC (216) and TTCCCCCC (204) in TLR4. There is possible influence of LF and TLR4 on milk yield and milk components, therefore, further studies are needed to evaluate this possible association in more number of goat farms

GWAS in practical cattle breeding in Czech Republic, single step method, genetic progress

Development of genetic evaluation of animals is permanent process. It was going from estimated breeding value (EBV) calculated by CC-test, across a BLUP – animal model and RR-TDM, to the genomic enhanced breeding value (GEBV) using genetic markers. Methods of genetic evaluation become a part of marketing strategies of insemination companies. Therefore all countries and association of breeders seek to be compatible with others. Now we are in a period of massive global implementation of genomic evaluation, which combines traditional BLUP with huge quantity of genetic SNP markers. Multi-step procedures are now usual in practice, which work with deregressed proofs. Development of methods attained to the single-step procedure (ssGBLUP) which overcomes some difficulties of previous methods, improves reliabilities of evaluation and compares all animals, genotyped and ungenotyped, in entire nation-wide population. Genomic evaluation influence above all young genotyped animals. In Czech Republic single-step procedure is routinely used for national evaluation of milk, linear type traits, reproduction and longevity. GEBVs are accompanied by genomic reliabilities. Genetic trends over last 20 years are in some traits different for genomic evaluation compared to traditional BLUP evaluation, although input data and genetic parameters (heritability) are the same and genotyped animals were only small proportion from entire evaluated population. Differences in genetic trends increase mainly in new batches of animals. Reason of it could be in the changed variability of breeding values and “genomic correction” of relationship between animals, which is expanded from genotyped animals to others individuals in a population. Keywords: genomic breeding value, single-step, genomic relationship, genetic trend, SNP ReferencesBauer, J. et al. (2014) Approximation of the reliability of single-step genomic breeding values for dairy cattle in the Czech Republic. Anim. Sci. Papers and Reports, 32, pp. 301-306.Bauer, J., Přibyl, J. and Vostrý, L. (2015) Contribution of domestic production records and Interbull EBV on approximate reliabilities of single-step genomic breeding values in dairy cattle. Czech J. Anim. Sci., 60, 263-267.Candrák, J., Kadlečík O. and Schaeffer L.R. (1997) The use of test-day model for Slovak cattle populations. In: Proc. 48th Annual Meeting of the European Association for Animal Production, Vienna, Austria, August 25–28.Christensen,  O.F. and Lund, M.S. (2010) Genomic prediction when some animals are not genotyped. Genet.Sel.Evol. 42, pp. 2.Fisher, R.A. (1918) The correlation between relatives in the supposition of Mendelianinheritance. Trans. Roy. Soc. Edinb. 52, pp. 399-433.            Fragomeni, B.O. et al. (2015) Hot topic: Use of genomic recursions in single-step genomic best linear unbiased predictor (BLUP) with a large number of genotypes. J. Dairy Sci., 98, pp. 4090-4094.Gao, H. et al. (2012) Comparison on genomic predictions using three GBLUP methods and two single step blending methods in the Nordic Holstein population. Genet. Sel.Evol. 44, pp. 8.Legarra A., Aguilar I. and Misztal, I. (2009) A relationship matrix including full pedigree and genomic information. J. Dairy Sci., 92, pp. 4656-4663.Masuda, Y. et al. (2016) Implementation of genomic recursions in single-step genomic best linear unbiased predictor for US Holsteins with a large number of genotyped animals. J. Dairy Sci., 99, pp. 1968-1974.Mendel, G.J. (1866) Versuche über Pflanzen-Hybriden. Verh. Naturforsch. Ver. Brünn 4, pp. 3–47 (1901, J. R. Hortic. Soc. 26, pp. 1–32).Meuwissen, T.H.E., Hayes, B.J. and Goddard, M.E. (2001) Prediction of total genetic value using genome-wide dense marker maps. Genetics, 157, pp. 1819–1829.Misztal, I., Legarra A. and Aguilar, I. (2009) Computing procedures for genetic evaluation including phenotypic, full pedigree, and genomic information. J. Dairy Sci., 92, pp. 4648–4655.Misztal, I. et al. (2013) Methods to approximate reliabilities in single-step genomic evaluation. J. Dairy Sci., 96, pp. 647-654.Pešek, P., Přibyl, J. and Vostrý, L. (2015) Genetic variances of SNP loci for milk yield in dairy cattle. J. Appl. Genet., 56, pp. 339-347.Přibyl, J. et al. (2014) Domestic and Interbull information in the single step genomic evaluation of Holstein milk production.  Czech J. Anim. Sci., 59, pp. 409-415.Přibyl, J. et al. (2015) Domestic estimated breeding values and genomic enhanced breeding values of bulls in comparison with their foreign genomic enhanced breeding values. Animal, 9, pp. 1635-1642.VanRaden, P.M. (2008) Efficient methods to compute genomic predictions. J. Dairy Sci., 91, pp. 4414–4423.VanRaden, P.M. et al. (2011) Genomic evaluations with many more genotypes. Genet. Sel.Evol. 43, pp. 10.Wright, S. (1921) Systems of mating. Genetics. 6, pp. 111-178.Zavadilová, L. et al. (2014) Single-step genomic evaluation for linear type traits of Holstein cows in Czech Republic. Anim. Sci. Papers and Reports vol. 32, pp. 201-208.

Sheep Post-Domestication Expansion in the Context of Mitochondrial and Y Chromosome Haplogroups and Haplotypes

Mitochondrial DNA and nonrecombinant parts of Y-chromosome DNA are a great tool for looking at a species’ past. They are inherited for generations almost unaffected because they do not participate in recombination; thus, the time of occurrence of each mutation can be estimated based on the average mutation rate. Thanks to this, male and female haplogroups guide confirming events in the distant past (potential centers of domestication, settlement of areas, trade connections) as well as in modern breeding (crossbreeding, confirmation of paternity). This research focuses mainly on the development of domestic sheep and its post-domestication expansion, which has occurred through human trade from one continent to another. So far, five mitochondrial and five Y-chromosome haplogroups and dozens of their haplotypes have been detected in domestic sheep through studies worldwide. Mitochondrial DNA variability is more or less correlated with distance from the domestication center, but variability on the recombinant region of the Y chromosome is not. According to available data, central China shows the highest variability of male haplogroups and haplotypes

Genetic Parameters for Limousine Interbeef Genetic Evaluation of Calving Traits

The aim of this study was to estimate across-country genetic correlations for calving traits (birth weight, calving ease) in the Limousine breed. Correlations were estimated for eight populations (Czech Republic, joint population of Denmark, Finland, and Sweden, France, Great Britain, Ireland, Slovenia, Switzerland, and Estonia). An animal model on raw performance accounting for across-country interactions (AMACI) was used. (Co)variance components were estimated for pairwise combinations of countries. Fixed and random effects were defined by each country according to its national genetic evaluation system. The average across-country genetic correlation for the direct genetic effect was 0.85 for birth weight (0.69–0.96) and 0.75 for calving ease (0.62–0.94). The average correlation for the maternal genetic effect was 0.57 for birth weight and 0.61 for calving ease. After the estimation of genetic parameters, the weighted bending procedure was used to compute the full Interbeef genetic correlation matrix. After bending, direct genetic correlations ranged from 0.62 to 0.84 (with an average of 0.73) for birth weight and from 0.58 to 0.82 (with an average of 0.68) for calving ease

Food Resources Biodiversity: The Case of Local Cattle in Slovakia

This study aimed to assess the level of biodiversity in selected local cattle populations as important food resources in Slovakia. The biodiversity level was derived from the genome-wide data collected for dairy (Jersey), dual-purpose (Slovak Pinzgau, Slovak Spotted), and beef breeds (Charolais, Limousine). The commonly used indices, genomic inbreeding (FROH, FGRM, FHOM, FUNI) and effective population size (NeLD), were used to quantify the impact of relatives mating on the genome of analysed populations. Even if the low NeLD estimates signalise significant loss of genetic variability within populations, the genomic inbreeding under 1% (except Jersey) showed that the intensity of diversity loss is not so rapid and can be managed by the re-arrangement of long-term breeding strategies. The analysis of genetic differentiation degree across populations assumed that the specialisation of breeds during their grading-up led to the specific nucleotide changes, especially in genes responsible for preferred phenotypic traits. The breed-specific differences observed mainly in the genome of Charolais (carcass traits) and Jersey (milk production traits) populations resulted from the polymorphisms in CAPN1 (μ-calpain) and CSN1S2 (casein alpha s2) genes, respectively. Obtained results confirmed that the specific haplotypes are strongly associated with the genetic nature of breed depending on production type