Template-Type: ReDIF-Article 1.0 Author-Name: Anita Kranjčevičová Author-Workplace-Name: Department of Genetics and Breeding, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech Republic Author-Workplace-Name: Department of Genetics and Breeding of Farm Animals, Institute of Animal Science, Prague-Uhříněves, Czech Republic Author-Name: Eva Kašná Author-Workplace-Name: Department of Genetics and Breeding of Farm Animals, Institute of Animal Science, Prague-Uhříněves, Czech Republic Author-Name: Michaela Brzáková Author-Workplace-Name: Department of Genetics and Breeding, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech Republic Author-Name: Josef Přibyl Author-Workplace-Name: Department of Genetics and Breeding of Farm Animals, Institute of Animal Science, Prague-Uhříněves, Czech Republic Author-Name: Luboš Vostrý Author-Workplace-Name: Department of Genetics and Breeding, Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech Republic Title: Impact of reference population and marker density on accuracy of population imputation Abstract: The effect of the reference population size and the number of missing single nucleotide polymorphisms (SNPs) on imputation accuracy was determined. The population imputation method using the FImpute software was applied. The dataset used for the purpose of this study was taken from the database of the Holstein Cattle Breeders Association of the Czech Republic. It contains 1000 animals genotyped with the Illumina BovineSNP50 v.2 BeadChip. Two datasets were created, the first containing the original genotypes, including the missing SNPs, the second containing the same genotypes modified to avoid missing data. In these datasets, animals were randomly selected for a reference population (10, 25, 50 and 75%) and there were randomly selected SNPs for deletion (15, 30, 55, 70, and 95%) in animals that were not used as the reference population. Subsequently, the data accuracy was determined by two parameters: correlation between original and imputed SNPs and percentage of correctly imputed SNPs. Since animals and SNPs were randomly selected, the process including data imputation was repeated 100 times. Accuracy was determined as the average accuracy over all repetitions. It was found that the imputation accuracy is influenced by both parameters. If the size of the reference population is sufficient, the imputation accuracy is higher despite the large number of missing SNPs. Keywords: cattle, genomics, marker density, missing SNPs, simulation Journal: Czech Journal of Animal Science Pages: 405-410 Volume: 64 Issue: 10 Year: 2019 DOI: 10.17221/148/2019-CJAS File-URL: http://cjas.agriculturejournals.cz/doi/10.17221/148/2019-CJAS.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/cjs-201910-0001.txt Handle: RePEc:caa:jnlcjs:v:64:y:2019:i:10:id:148-2019-CJAS Template-Type: ReDIF-Article 1.0 Author-Name: Eymen Demir Author-Name: Murat Soner Balcioglu Author-Workplace-Name: Department of Animal Science, Faculty of Agriculture, Akdeniz University, Antalya, Turkey Title: Genetic diversity and population structure of four cattle breeds raised in Turkey using microsatellite markers Abstract: In the present study, genetic diversity and population structure of Holstein Friesian and three native cattle breeds of Turkey including Turkish Grey Steppe, Eastern Anatolian Red and Anatolian Black were assessed. Totally 120 individuals of 4 breeds were genotyped using 20 microsatellite markers and 204 different alleles, of which 31 were private alleles, were detected. The average observed and expected heterozygosity values were 0.63 and 0.74, respectively. Observed heterozygosity at the marker level ranged from 0.30 (DRBP1) to 0.88 (ILSTS011), while expected heterozygosity ranged from 0.51 (INRABERN172) to 0.88 (SPS113). Inbreeding coefficient values for Turkish Grey Steppe, Eastern Anatolian Red, Anatolian Black and Holstein Friesian were 0.216, 0.202, 0.128 and 0.069, respectively. The lowest pairwise FST value (0.030) was detected between Turkish Grey Steppe and Anatolian Black breeds, while the highest value (0.070) was detected between Turkish Grey Steppe and Holstein Friesian. Results of structure and factorial correspondence analysis revealed that Turkish native cattle breeds and Holstein Friesian were genetically different enough to separate the two breeds. Results of bottleneck analysis indicated heterozygosity deficiency in Turkish Grey Steppe (P < 0.05). Keywords: bovine, genetic characterization, indigenous population Journal: Czech Journal of Animal Science Pages: 411-419 Volume: 64 Issue: 10 Year: 2019 DOI: 10.17221/62/2019-CJAS File-URL: http://cjas.agriculturejournals.cz/doi/10.17221/62/2019-CJAS.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/cjs-201910-0002.txt Handle: RePEc:caa:jnlcjs:v:64:y:2019:i:10:id:62-2019-CJAS Template-Type: ReDIF-Article 1.0 Author-Name: Qing Quan Author-Workplace-Name: College of Animal Science and Technology, Anhui Agricultural University, Hefei, P.R. China Author-Workplace-Name: College of Economy and Technology, Anhui Agricultural University, Hefei, P.R. China Author-Name: Lu Zhu Author-Workplace-Name: College of Animal Science and Technology, Anhui Agricultural University, Hefei, P.R. China Author-Workplace-Name: Local Animal Genetic Resources Conservation and Biobreeding Laboratory of Anhui Province, Hefei, P.R. China Author-Name: Qi Zheng Author-Workplace-Name: College of Animal Science and Technology, Anhui Agricultural University, Hefei, P.R. China Author-Workplace-Name: Local Animal Genetic Resources Conservation and Biobreeding Laboratory of Anhui Province, Hefei, P.R. China Author-Name: Hao Wu Author-Workplace-Name: College of Animal Science and Technology, Anhui Agricultural University, Hefei, P.R. China Author-Workplace-Name: Local Animal Genetic Resources Conservation and Biobreeding Laboratory of Anhui Province, Hefei, P.R. China Author-Name: Jing Jing Author-Workplace-Name: College of Animal Science and Technology, Anhui Agricultural University, Hefei, P.R. China Author-Workplace-Name: Local Animal Genetic Resources Conservation and Biobreeding Laboratory of Anhui Province, Hefei, P.R. China Author-Name: Qing Chen Author-Workplace-Name: College of Animal Science and Technology, Anhui Agricultural University, Hefei, P.R. China Author-Workplace-Name: Local Animal Genetic Resources Conservation and Biobreeding Laboratory of Anhui Province, Hefei, P.R. China Author-Name: Ya Liu Author-Workplace-Name: College of Animal Science and Technology, Anhui Agricultural University, Hefei, P.R. China Author-Workplace-Name: Local Animal Genetic Resources Conservation and Biobreeding Laboratory of Anhui Province, Hefei, P.R. China Author-Name: Fugui Fang Author-Workplace-Name: College of Animal Science and Technology, Anhui Agricultural University, Hefei, P.R. China Author-Workplace-Name: Local Animal Genetic Resources Conservation and Biobreeding Laboratory of Anhui Province, Hefei, P.R. China Author-Name: Yunsheng Li Author-Workplace-Name: College of Animal Science and Technology, Anhui Agricultural University, Hefei, P.R. China Author-Workplace-Name: Local Animal Genetic Resources Conservation and Biobreeding Laboratory of Anhui Province, Hefei, P.R. China Author-Name: Yunhai Zhang Author-Workplace-Name: College of Animal Science and Technology, Anhui Agricultural University, Hefei, P.R. China Author-Workplace-Name: Local Animal Genetic Resources Conservation and Biobreeding Laboratory of Anhui Province, Hefei, P.R. China Author-Name: Yinghui Ling Author-Workplace-Name: College of Animal Science and Technology, Anhui Agricultural University, Hefei, P.R. China Author-Workplace-Name: School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne, UK Title: Comparison of the pituitary gland transcriptome in pregnant and non-pregnant goats (Capra hircus) Abstract: Pregnancy is strictly regulated by neuronal and hormonal factors with an essential role being played by the pituitary gland. We screened for differentially expressed genes (DEGs) in the pituitary that function in goat gestational development. Pregnant (AWGp) and non-pregnant Anhui white goats (AWGn) were analysed by deep-sequencing technology. A total of 12 774 092 and 13 872 327 clear reads were obtained in the AWGp and AWGn libraries, respectively. A total of 2593 genes were labelled as significantly differentially expressed in AWGp compared to AWGn, including 2158 upregulated genes and 435 downregulated genes. These genes included follicle stimulating hormone beta (FSHB) and luteinizing hormone beta (LHB), which showed an involvement in reproductive regulation and downregulation (AWGp vs AWGn). Quantitative real-time PCR (qPCR) results validated the DEG data. Subsequent gene ontology analysis indicated that a large number of these DEGs function in cellular processes, cell structures, and cell binding. The DEGs were also found by Kyoto Gene and Genomic Encyclopaedia analysis to be significantly enriched in 54 pathways, including the GnRH and TGF-beta signalling pathways that affect cell proliferation and hormone secretion. These data also identify genes that may play a role in pregnancy and reproduction in the goat and thus provide avenues for future research. Keywords: differentially expressed genes, hypophysis, Anhui white goats, RNA-Seq Journal: Czech Journal of Animal Science Pages: 420-430 Volume: 64 Issue: 10 Year: 2019 DOI: 10.17221/141/2019-CJAS File-URL: http://cjas.agriculturejournals.cz/doi/10.17221/141/2019-CJAS.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/cjs-201910-0003.txt Handle: RePEc:caa:jnlcjs:v:64:y:2019:i:10:id:141-2019-CJAS Template-Type: ReDIF-Article 1.0 Author-Name: Matúš Gašparík Author-Workplace-Name: Department of Animal Science; Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech Republic Author-Name: Luděk Stádník Author-Workplace-Name: Department of Animal Science; Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech Republic Author-Name: Jaromír Ducháček Author-Workplace-Name: Department of Animal Science; Faculty of Agrobiology, Food and Natural Resources, Czech University of Life Sciences Prague, Prague, Czech Republic Author-Name: Vladimír Tančin Author-Workplace-Name: National Agricultural and Food Centre, Research Institute for Animal Production, Lužianky, Slovak Republic Author-Workplace-Name: Department of Veterinary Sciences, Faculty of Agrobiology and Food Resources, Slovak University of Agriculture, Nitra, Slovak Republic Title: Differences between Jersey and Holstein cows in milking-induced teat prolongation during lactation Abstract: Factors consequential to milking-induced teat prolongation (MITP) were identified. Effects of breed, teat position, lactation number, lactation stage and their interactions were evaluated. The length of each teat before and after milking was measured seven times during lactation in 59 Holstein cows and 45 Jersey cows. Rear teats seemed to prolong more with the exception of rear left teats of Holstein cows. MITP of Holsteins was more balanced among quarters compared to Jerseys, where we observed significantly higher MITP of their rear teats. The pairs mostly had similar reactions even for different teat lengths, therefore for future studies evaluating one of each pair should be sufficient and more effective. Development of MITP during lactation showed more variability at the onset of lactation, followed by more uniform response at later stages. Lower MITP for higher parity cows was observed only in Holsteins. Overall, Jerseys achieved a significantly higher level of MITP, which suggests breed differences in reaction to milking. Effects identified in this study should be taken into consideration while designing future experiments in this area. In addition, our results suggest the future necessity to improve milking technology to allow group or even individual settings optimization based on breed, lactation stage, lactation number, and teat position. Keywords: dairy cow, milking, teat length, teat position Journal: Czech Journal of Animal Science Pages: 431-438 Volume: 64 Issue: 10 Year: 2019 DOI: 10.17221/145/2019-CJAS File-URL: http://cjas.agriculturejournals.cz/doi/10.17221/145/2019-CJAS.html File-Format: text/html X-File-Ref: http://agriculturejournals.cz/RePEc/caa/references/cjs-201910-0004.txt Handle: RePEc:caa:jnlcjs:v:64:y:2019:i:10:id:145-2019-CJAS