Tetens, Jens

[["dc.bibliographiccitation.journal","Frontiers in Genetics"],["dc.bibliographiccitation.volume","13"],["dc.contributor.affiliation","Mott, Alexander Charles; \r\n1\r\nDepartment of Animal Sciences, Georg-August-University, Göttingen, Germany"],["dc.contributor.affiliation","Mott, Andrea; \r\n1\r\nDepartment of Animal Sciences, Georg-August-University, Göttingen, Germany"],["dc.contributor.affiliation","Preuß, Siegfried; \r\n2\r\nInstitute of Animal Science, University of Hohenheim, Stuttgart, Germany"],["dc.contributor.affiliation","Bennewitz, Jörn; \r\n2\r\nInstitute of Animal Science, University of Hohenheim, Stuttgart, Germany"],["dc.contributor.affiliation","Tetens, Jens; \r\n1\r\nDepartment of Animal Sciences, Georg-August-University, Göttingen, Germany"],["dc.contributor.affiliation","Falker-Gieske, Clemens; \r\n1\r\nDepartment of Animal Sciences, Georg-August-University, Göttingen, Germany"],["dc.contributor.author","Mott, Alexander Charles"],["dc.contributor.author","Mott, Andrea"],["dc.contributor.author","Preuß, Siegfried"],["dc.contributor.author","Bennewitz, Jörn"],["dc.contributor.author","Tetens, Jens"],["dc.contributor.author","Falker-Gieske, Clemens"],["dc.date.accessioned","2022-08-31T11:11:52Z"],["dc.date.available","2022-08-31T11:11:52Z"],["dc.date.issued","2022-08-17"],["dc.date.updated","2022-08-31T09:11:03Z"],["dc.description.abstract","Feather pecking in chickens is a damaging behavior, seriously impacting animal welfare and leading to economic losses. Feather pecking is a complex trait, which is partly under genetic control. Different hypotheses have been proposed to explain the etiology of feather pecking and notably, several studies have identified similarities between feather pecking and human mental disorders such as obsessive-compulsive disorder and schizophrenia. This study uses transcriptomic and phenotypic data from 167 chickens to map expression quantitative trait loci and to identify regulatory genes with a significant effect on this behavioral disorder using an association weight matrix approach. From 70 of the analyzed differentially expressed genes, 11,790 genome wide significantly associated variants were detected, of which 23 showed multiple associations (≥15). These were located in proximity to a number of genes, which are transcription regulators involved in chromatin binding, nucleic acid metabolism, protein translation and putative regulatory RNAs. The association weight matrix identified 36 genes and the two transcription factors: SP6 (synonym: KLF14) and ENSGALG00000042129 (synonym: CHTOP) as the most significant, with an enrichment of KLF14 binding sites being detectable in 40 differentially expressed genes. This indicates that differential expression between animals showing high and low levels of feather pecking was significantly associated with a genetic variant in proximity to KLF14. This multiallelic variant was located 652 bp downstream of KLF14 and is a deletion of 1-3 bp. We propose that a deletion downstream of the transcription factor KLF14 has a negative impact on the level of T cells in the developing brain of high feather pecking chickens, which leads to developmental and behavioral abnormalities. The lack of CD4 T cells and gamma-Aminobutyric acid (GABA) receptors are important factors for the increased propensity of laying hens to perform feather pecking. As such, KLF14 is a clear candidate regulator for the expression of genes involved in the pathogenic development. By further elucidating the regulatory pathways involved in feather pecking we hope to take significant steps forward in explaining and understanding other mental disorders, not just in chickens."],["dc.description.sponsorship","Open-Access-Publikationsfonds 2022"],["dc.identifier.doi","10.3389/fgene.2022.969752"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/113333"],["dc.language.iso","en"],["dc.relation.eissn","1664-8021"],["dc.rights","CC BY 4.0"],["dc.rights.uri","http://creativecommons.org/licenses/by/4.0/"],["dc.title","eQTL analysis of laying hens divergently selected for feather pecking identifies KLF14 as a potential key regulator for this behavioral disorder"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","235"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","Life"],["dc.bibliographiccitation.volume","11"],["dc.contributor.author","Borda-Molina, Daniel"],["dc.contributor.author","Iffland, Hanna"],["dc.contributor.author","Schmid, Markus"],["dc.contributor.author","Müller, Regina"],["dc.contributor.author","Schad, Svenja"],["dc.contributor.author","Seifert, Jana"],["dc.contributor.author","Tetens, Jens"],["dc.contributor.author","Bessei, Werner"],["dc.contributor.author","Bennewitz, Jörn"],["dc.contributor.author","Camarinha-Silva, Amélia"],["dc.date.accessioned","2021-06-01T09:42:38Z"],["dc.date.available","2021-06-01T09:42:38Z"],["dc.date.issued","2021"],["dc.description.abstract","Background: Feather pecking is a well-known problem in layer flocks that causes animal welfare restrictions and contributes to economic losses. Birds’ gut microbiota has been linked to feather pecking. This study aims to characterize the microbial communities of two laying hen lines divergently selected for high (HFP) and low (LFP) feather pecking and investigates if the microbiota is associated with feather pecking or agonistic behavior. Methods: Besides phenotyping for the behavioral traits, microbial communities from the digesta and mucosa of the ileum and caeca were investigated using target amplicon sequencing and functional predictions. Microbiability was estimated with a microbial mixed linear model. Results: Ileum digesta showed an increase in the abundance of the genus Lactobacillus in LFP, while Escherichia was abundant in HFP hens. In the caeca digesta and mucosa of the LFP line were more abundant Faecalibacterium and Blautia. Tryptophan metabolism and lysine degradation were higher in both digesta and mucosa of the HFP hens. Linear models revealed that the two lines differ significantly in all behavior traits. Microbiabilities were close to zero and not significant in both lines and for all traits. Conclusions: Trait variation was not affected by the gut microbial composition in both selection lines."],["dc.description.sponsorship","Deutsche Forschungsgemeinschaft"],["dc.identifier.doi","10.3390/life11030235"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/85309"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-425"],["dc.publisher","MDPI"],["dc.relation.eissn","2075-1729"],["dc.rights","https://creativecommons.org/licenses/by/4.0/"],["dc.title","Gut Microbial Composition and Predicted Functions Are Not Associated with Feather Pecking and Antagonistic Behavior in Laying Hens"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","18"],["dc.bibliographiccitation.journal","Genetics Selection Evolution"],["dc.bibliographiccitation.volume","49"],["dc.contributor.author","Lutz, Vanessa"],["dc.contributor.author","Stratz, Patrick"],["dc.contributor.author","Preuss, Siegfried"],["dc.contributor.author","Tetens, Jens"],["dc.contributor.author","Grashorn, Michael A."],["dc.contributor.author","Bessei, Werner"],["dc.contributor.author","Bennewitz, Joern"],["dc.date.accessioned","2018-11-07T10:27:35Z"],["dc.date.available","2018-11-07T10:27:35Z"],["dc.date.issued","2017"],["dc.description.abstract","Background: Feather pecking and aggressive pecking in laying hens are serious economic and welfare issues. In spite of extensive research on feather pecking during the last decades, the motivation for this behavior is still not clear. A small to moderate heritability has frequently been reported for these traits. Recently, we identified several single-nucleotide polymorphisms (SNPs) associated with feather pecking by mapping selection signatures in two divergent feather pecking lines. Here, we performed a genome-wide association analysis (GWAS) for feather pecking and aggressive pecking behavior, then combined the results with those from the recent selection signature experiment, and linked them to those obtained from a differential gene expression study. Methods: A large F2 cross of 960 F2 hens was generated using the divergent lines as founders. Hens were phenotyped for feather pecks delivered (FPD), aggressive pecks delivered (APD), and aggressive pecks received (APR). Individuals were genotyped with the Illumina 60K chicken Infinium iSelect chip. After data filtering, 29,376 SNPs remained for analyses. Single-marker GWAS was performed using a Poisson model. The results were combined with those from the selection signature experiment using Fisher's combined probability test. Results: Numerous significant SNPs were identified for all traits but with low false discovery rates. Nearly all significant SNPs were located in clusters that spanned a maximum of 3 Mb and included at least two significant SNPs. For FPD, four clusters were identified, which increased to 13 based on the meta-analysis (FPDmeta). Seven clusters were identified for APD and three for APR. Eight genes (of the 750 investigated genes located in the FPDmeta clusters) were significantly differentially-expressed in the brain of hens from both lines. One gene, SLC12A9, and the positional candidate gene for APD, GNG2, may be linked to the monomanine signaling pathway, which is involved in feather pecking and aggressive behavior. Conclusions: Combining the results from the GWAS with those of the selection signature experiment substantially increased the statistical power. The behavioral traits were controlled by many genes with small effects and no single SNP had effects large enough to justify its use in marker-assisted selection."],["dc.description.sponsorship","German Research Foundation (Deutsche Forschungsgemeinschaft, DFG)"],["dc.identifier.doi","10.1186/s12711-017-0287-4"],["dc.identifier.isi","000394715600001"],["dc.identifier.pmid","28158968"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/14218"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/43262"],["dc.notes.status","zu prüfen"],["dc.notes.submitter","PUB_WoS_Import"],["dc.publisher","Biomed Central Ltd"],["dc.relation.issn","1297-9686"],["dc.relation.issn","0999-193X"],["dc.rights.access","openAccess"],["dc.rights.holder","The Author(s)"],["dc.title","A genome-wide association study in a large F2-cross of laying hens reveals novel genomic regions associated with feather pecking and aggressive pecking behavior"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.peerReviewed","yes"],["dc.type.status","published"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","e0271057"],["dc.bibliographiccitation.issue","9"],["dc.bibliographiccitation.journal","PLoS One"],["dc.bibliographiccitation.volume","17"],["dc.contributor.author","Krebs, Tony"],["dc.contributor.author","Kilic, Isabel"],["dc.contributor.author","Neuenroth, Lisa"],["dc.contributor.author","Wasselin, Thierry"],["dc.contributor.author","Ninov, Momchil"],["dc.contributor.author","Tetens, Jens"],["dc.contributor.author","Lenz, Christof"],["dc.contributor.editor","Reid, Christopher W."],["dc.date.accessioned","2022-10-04T10:21:47Z"],["dc.date.available","2022-10-04T10:21:47Z"],["dc.date.issued","2022"],["dc.description.abstract","Bovine pregnancy-associated glycoproteins (boPAGs) are extensively glycosylated secretory proteins of trophoblast cells. Roughly 20 different boPAG members are known but their distribution patterns and degree of glycosylation during pregnancy are not well characterized. The objective of the present study was the development of a parallel reaction monitoring-based assay for the profiling of different boPAGs during pregnancy and after gestation. Furthermore, we investigated the effects of N-glycosylation on our analytical results. BoPAGs were purified from cotyledons of four different pregnancy stages. The assay detects 25 proteotypic peptides from 18 boPAGs in a single run. The highest abundances were found for boPAG 1 in both, glycosylated and deglycosylated samples. Strongest effects of glycosylation were detected during mid and late pregnancy as well as in afterbirth samples. Furthermore, we identified different boPAG-clusters based on the observed relative protein abundances between glycosylated and deglycosylated samples. A linkage between the impact of glycosylation and potential N-glycosylation sites or phylogenetic relation was not detected. In conclusion, the newly developed parallel reaction monitoring-based assay enables for the first time a comprehensive semi-quantitative profiling of 18 different boPAGs during pregnancy and post-partum on protein level, thereby investigating the influence of glycosylation. The results of this study provide new and important starting points to address further research on boPAGs to better understand their physiological role during pregnancy and for the development of new pregnancy detection tests."],["dc.description.sponsorship"," Landwirtschaftliche Rentenbank 501100018686"],["dc.description.sponsorship"," H. Wilhelm Schaumann Stiftung 501100019415"],["dc.description.sponsorship","Open Access Publication Funds of the University of Goettingen"],["dc.identifier.doi","10.1371/journal.pone.0271057"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/114502"],["dc.language.iso","en"],["dc.notes.intern","DOI-Import GROB-600"],["dc.relation.eissn","1932-6203"],["dc.rights","CC BY 4.0"],["dc.rights.uri","http://creativecommons.org/licenses/by/4.0/"],["dc.title","A multiplexed parallel reaction monitoring assay to monitor bovine pregnancy-associated glycoproteins throughout pregnancy and after gestation"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","unpublished"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Scientific Reports"],["dc.bibliographiccitation.volume","9"],["dc.contributor.author","Falker-Gieske, Clemens"],["dc.contributor.author","Knorr, Christoph"],["dc.contributor.author","Tetens, Jens"],["dc.date.accessioned","2020-12-10T18:11:09Z"],["dc.date.available","2020-12-10T18:11:09Z"],["dc.date.issued","2019"],["dc.identifier.doi","10.1038/s41598-019-53901-z"],["dc.identifier.eissn","2045-2322"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/16737"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/73908"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.notes.intern","Merged from goescholar"],["dc.rights","CC BY 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by/4.0"],["dc.title","Blood transcriptome analysis in a buck-ewe hybrid and its parents"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","873"],["dc.bibliographiccitation.issue","6"],["dc.bibliographiccitation.journal","Genes"],["dc.bibliographiccitation.volume","12"],["dc.contributor.author","Hosseini, Shahrbanou"],["dc.contributor.author","Schmitt, Armin Otto"],["dc.contributor.author","Tetens, Jens"],["dc.contributor.author","Brenig, Bertram"],["dc.contributor.author","Simianer, Henner"],["dc.contributor.author","Sharifi, Ahmad Reza"],["dc.contributor.author","Gültas, Mehmet"],["dc.date.accessioned","2021-08-12T07:45:56Z"],["dc.date.available","2021-08-12T07:45:56Z"],["dc.date.issued","2021"],["dc.description.abstract","The transcriptional regulation of gene expression in higher organisms is essential for different cellular and biological processes. These processes are controlled by transcription factors and their combinatorial interplay, which are crucial for complex genetic programs and transcriptional machinery. The regulation of sex-biased gene expression plays a major role in phenotypic sexual dimorphism in many species, causing dimorphic gene expression patterns between two different sexes. The role of transcription factor (TF) in gene regulatory mechanisms so far has not been studied for sex determination and sex-associated colour patterning in zebrafish with respect to phenotypic sexual dimorphism. To address this open biological issue, we applied bioinformatics approaches for identifying the predicted TF pairs based on their binding sites for sex and colour genes in zebrafish. In this study, we identified 25 (e.g., STAT6-GATA4; JUN-GATA4; SOX9-JUN) and 14 (e.g., IRF-STAT6; SOX9-JUN; STAT6-GATA4) potentially cooperating TFs based on their binding patterns in promoter regions for sex determination and colour pattern genes in zebrafish, respectively. The comparison between identified TFs for sex and colour genes revealed several predicted TF pairs (e.g., STAT6-GATA4; JUN-SOX9) are common for both phenotypes, which may play a pivotal role in phenotypic sexual dimorphism in zebrafish."],["dc.description.abstract","The transcriptional regulation of gene expression in higher organisms is essential for different cellular and biological processes. These processes are controlled by transcription factors and their combinatorial interplay, which are crucial for complex genetic programs and transcriptional machinery. The regulation of sex-biased gene expression plays a major role in phenotypic sexual dimorphism in many species, causing dimorphic gene expression patterns between two different sexes. The role of transcription factor (TF) in gene regulatory mechanisms so far has not been studied for sex determination and sex-associated colour patterning in zebrafish with respect to phenotypic sexual dimorphism. To address this open biological issue, we applied bioinformatics approaches for identifying the predicted TF pairs based on their binding sites for sex and colour genes in zebrafish. In this study, we identified 25 (e.g., STAT6-GATA4; JUN-GATA4; SOX9-JUN) and 14 (e.g., IRF-STAT6; SOX9-JUN; STAT6-GATA4) potentially cooperating TFs based on their binding patterns in promoter regions for sex determination and colour pattern genes in zebrafish, respectively. The comparison between identified TFs for sex and colour genes revealed several predicted TF pairs (e.g., STAT6-GATA4; JUN-SOX9) are common for both phenotypes, which may play a pivotal role in phenotypic sexual dimorphism in zebrafish."],["dc.description.sponsorship","Open-Access-Publikationsfonds 2021"],["dc.identifier.doi","10.3390/genes12060873"],["dc.identifier.pii","genes12060873"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/88580"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-448"],["dc.relation.eissn","2073-4425"],["dc.relation.orgunit","Abteilung Tierzucht und Haustiergenetik"],["dc.rights","CC BY 4.0"],["dc.title","In Silico Prediction of Transcription Factor Collaborations Underlying Phenotypic Sexual Dimorphism in Zebrafish (Danio rerio)"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.artnumber","49"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Genetics Selection Evolution"],["dc.bibliographiccitation.volume","54"],["dc.contributor.author","Reich, Paula"],["dc.contributor.author","Falker-Gieske, Clemens"],["dc.contributor.author","Pook, Torsten"],["dc.contributor.author","Tetens, Jens"],["dc.date.accessioned","2022-08-04T12:06:22Z"],["dc.date.available","2022-08-04T12:06:22Z"],["dc.date.issued","2022-07-04"],["dc.date.updated","2022-07-25T11:18:58Z"],["dc.description.abstract","Background Genotype imputation is a cost-effective method to generate sequence-level genotypes for a large number of animals. Its application can improve the power of genomic studies, provided that the accuracy of imputation is sufficiently high. The purpose of this study was to develop an optimal strategy for genotype imputation from genotyping array data to sequence level in German warmblood horses, and to investigate the effect of different factors on the accuracy of imputation. Publicly available whole-genome sequence data from 317 horses of 46 breeds was used to conduct the analyses. Results Depending on the size and composition of the reference panel, the accuracy of imputation from medium marker density (60K) to sequence level using the software Beagle 5.1 ranged from 0.64 to 0.70 for horse chromosome 3. Generally, imputation accuracy increased as the size of the reference panel increased, but if genetically distant individuals were included in the panel, the accuracy dropped. Imputation was most precise when using a reference panel of multiple but related breeds and the software Beagle 5.1, which outperformed the other two tested computer programs, Impute 5 and Minimac 4. Genome-wide imputation for this scenario resulted in a mean accuracy of 0.66. Stepwise imputation from 60K to 670K markers and subsequently to sequence level did not improve the accuracy of imputation. However, imputation from higher density (670K) was considerably more accurate (about 0.90) than from medium density. Likewise, imputation in genomic regions with a low marker coverage resulted in a reduced accuracy of imputation. Conclusions The accuracy of imputation in horses was influenced by the size and composition of the reference panel, the marker density of the genotyping array, and the imputation software. Genotype imputation can be used to extend the limited amount of available sequence-level data from horses in order to boost the power of downstream analyses, such as genome-wide association studies, or the detection of embryonic lethal variants."],["dc.identifier.citation","Genetics Selection Evolution. 2022 Jul 04;54(1):49"],["dc.identifier.doi","10.1186/s12711-022-00740-8"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/112649"],["dc.language.iso","en"],["dc.rights","CC BY 4.0"],["dc.rights.holder","The Author(s)"],["dc.title","Development and validation of a horse reference panel for genotype imputation"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","112"],["dc.bibliographiccitation.issue","1"],["dc.bibliographiccitation.journal","Ruminants"],["dc.bibliographiccitation.lastpage","132"],["dc.bibliographiccitation.volume","2"],["dc.contributor.affiliation","Mott, Alexander C.; 1Department of Animal Science, Georg-August-University of Göttingen, 37077 Goettingen, Germany; martin.huenerberg@uni-goettingen.de (M.H.); jhummel@gwdg.de (J.H.); jens.tetens@uni-goettingen.de (J.T.)"],["dc.contributor.affiliation","Schneider, Dominik; 2Department of Genomic and Applied Microbiology, Georg-August-University of Göttingen, 37077 Goettingen, Germany; dschnei1@gwdg.de"],["dc.contributor.affiliation","Hünerberg, Martin; 1Department of Animal Science, Georg-August-University of Göttingen, 37077 Goettingen, Germany; martin.huenerberg@uni-goettingen.de (M.H.); jhummel@gwdg.de (J.H.); jens.tetens@uni-goettingen.de (J.T.)"],["dc.contributor.affiliation","Hummel, Jürgen; 1Department of Animal Science, Georg-August-University of Göttingen, 37077 Goettingen, Germany; martin.huenerberg@uni-goettingen.de (M.H.); jhummel@gwdg.de (J.H.); jens.tetens@uni-goettingen.de (J.T.)"],["dc.contributor.affiliation","Tetens, Jens; 1Department of Animal Science, Georg-August-University of Göttingen, 37077 Goettingen, Germany; martin.huenerberg@uni-goettingen.de (M.H.); jhummel@gwdg.de (J.H.); jens.tetens@uni-goettingen.de (J.T.)"],["dc.contributor.author","Mott, Alexander C."],["dc.contributor.author","Schneider, Dominik"],["dc.contributor.author","Hünerberg, Martin"],["dc.contributor.author","Hummel, Jürgen"],["dc.contributor.author","Tetens, Jens"],["dc.date.accessioned","2022-09-05T08:24:08Z"],["dc.date.available","2022-09-05T08:24:08Z"],["dc.date.issued","2022-01-30"],["dc.date.updated","2022-09-03T14:50:12Z"],["dc.description.abstract","With increasing global demand for animal protein, it is very important to investigate the impact of the bovine rumen microbiome on its functional traits. In order to acquire accurate and reproducible data for this type of study, it is important to understand what factors can affect the results of microbial community analysis, and where biases can occur. This study shows the impact of different DNA extraction methods on microbial community composition. Five DNA extraction methods were used on a ruminal sample. These experiments expose a high level of variability between extraction methods in relation to the microbial communities observed. As direct access to the rumen is required, we also investigated possible alternative sampling sites that could be utilised as non-invasive indicators of the bovine rumen microbiome. Therefore, oral swabs and faecal samples were taken in addition to ruminal samples, and DNA was extracted using a single method, reducing bias, and analysed. This is a small pilot study intending to reinforce the need for a universally used methodology for rumen microbiome analysis. Although alternative sampling points can indicate some of the communities present in the rumen, this must be approached cautiously, as there are limits to the depth of community analysis possible without direct rumen sampling."],["dc.identifier.doi","10.3390/ruminants2010007"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/114026"],["dc.language.iso","en"],["dc.relation.eissn","2673-933X"],["dc.rights","CC BY 4.0"],["dc.title","Bovine Rumen Microbiome: Impact of DNA Extraction Methods and Comparison of Non-Invasive Sampling Sites"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.subtype","original_ja"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.firstpage","108"],["dc.bibliographiccitation.issue","3"],["dc.bibliographiccitation.journal","Animals"],["dc.bibliographiccitation.volume","9"],["dc.contributor.author","van der Sluis, Malou"],["dc.contributor.author","Siegford, Janice"],["dc.contributor.author","Guzhva, Oleksiy"],["dc.contributor.author","Bennewitz, Jörn"],["dc.contributor.author","Norton, Tomas"],["dc.contributor.author","Piette, Deborah"],["dc.contributor.author","Tetens, Jens"],["dc.contributor.author","de Klerk, Britt"],["dc.contributor.author","Visser, Bram"],["dc.contributor.author","Ellen, Esther D."],["dc.contributor.author","Toscano, Michael J."],["dc.contributor.author","van der Zande, Lisette E."],["dc.contributor.author","van der Eijk, Jerine A. J."],["dc.contributor.author","de Haas, Elske N."],["dc.contributor.author","Rodenburg, T. Bas"],["dc.date.accessioned","2020-12-10T18:46:55Z"],["dc.date.available","2020-12-10T18:46:55Z"],["dc.date.issued","2019"],["dc.description.sponsorship","European Cooperation in Science and Technology"],["dc.description.sponsorship","Ministerie van Economische Zaken"],["dc.description.sponsorship","National Institute of Food and Agriculture"],["dc.identifier.doi","10.3390/ani9030108"],["dc.identifier.eissn","2076-2615"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/78589"],["dc.language.iso","en"],["dc.notes.intern","DOI Import GROB-354"],["dc.publisher","MDPI"],["dc.relation.eissn","2076-2615"],["dc.relation.isreplacedby","hdl:2/78589"],["dc.rights","https://creativecommons.org/licenses/by/4.0/"],["dc.title","Review of Sensor Technologies in Animal Breeding: Phenotyping Behaviors of Laying Hens to Select Against Feather Pecking"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dspace.entity.type","Publication"]]

[["dc.bibliographiccitation.journal","Veterinary Medicine and Science"],["dc.contributor.author","Wiedemann, Isabel"],["dc.contributor.author","Krebs, Tony"],["dc.contributor.author","Momberg, Niklas"],["dc.contributor.author","Knorr, Christoph"],["dc.contributor.author","Tetens, Jens"],["dc.date.accessioned","2019-07-09T11:46:00Z"],["dc.date.available","2019-07-09T11:46:00Z"],["dc.date.issued","2018"],["dc.description.abstract","The multigene family of pregnancy-associated glycoproteins (PAGs) belongs to a group of aspartic proteases that are exclusively expressed by trophoblast cells in the placenta of even-toed ungulates. In Bovidae, 22 different PAG genes (boPAGs) with a wide range of temporal and spatial expression- and glycosylation patterns have been reported to date. In this study we describe the mRNA expression patterns using real-time quantitative PCR (qPCR) for selected modern (boPAG-1, -9, -21) and ancient bovine PAGs (boPAG-2, -8, -10, -11, - 12) in cotyledonary tissue. The highest mean expression was detected in boPAG-8 and lowest in boPAG-10 (P < 0.05). Furthermore, boPAG-8 and -11 were significantly greater expressed in early gestation compared with later pregnancy stages. The characterization of boPAG mRNA-expression levels gives important insights for further protein analyses which will be valuable information for the development of new pregnancy detection systems."],["dc.identifier.doi","10.1002/vms3.123"],["dc.identifier.pmid","30265452"],["dc.identifier.purl","https://resolver.sub.uni-goettingen.de/purl?gs-1/15375"],["dc.identifier.uri","https://resolver.sub.uni-goettingen.de/purl?gro-2/59360"],["dc.language.iso","en"],["dc.notes.intern","Merged from goescholar"],["dc.relation.issn","2053-1095"],["dc.rights","CC BY-NC-ND 4.0"],["dc.rights.uri","https://creativecommons.org/licenses/by-nc-nd/4.0"],["dc.subject.ddc","630"],["dc.title","mRNA expression profiling in cotyledons reveals significant up-regulation of the two bovine pregnancy-associated glycoprotein genes boPAG-8 and boPAG-11 in early gestation"],["dc.type","journal_article"],["dc.type.internalPublication","yes"],["dc.type.version","published_version"],["dspace.entity.type","Publication"]]