Die chronologische Liste zeigt aktuelle Veröffentlichungen aus dem Forschungsbetrieb der Hochschule Weihenstephan-Triesdorf. Zuständig ist das Zentrum für Forschung und Wissenstransfer (ZFW).
Vortragstagung der DGfZ und GfT am 21./22. September 2022 in Kiel Analyse der bei Deutschen Holstein Kühen mit Schwanzläsionen assoziierten Kandidatengene L. Volkert, S. Meier, K. Schubert, P.V. Kremer-Rücker1 1Fakultät Landwirtschaft, Lebensmittel und Ernährung, Hochschule Weihenstephan-Triesdorf, 91746 Weidenbach 1 Einleitung Verschiedene Aspekte des Tierwohls rücken seit einiger Zeit mehr und mehr in den Fokus. Zahlreiche neue und alte Label sollen die Transparenz im Markt für den Verbraucher in Bezug auf das Wohlergehen der Tiere erhöhen. Hierzu zählt inzwischen auch die Kennzeichnung der Haltungsform. Gerade die Laufstallhaltung beim Milchvieh mit allen Vor- und Nachteilen wird in Zukunft eine wichtige Rolle spielen. Ein bereits lange beschriebenes Problem auf perforierten Böden mit frei laufenden Tieren sind. Schwanzspitzennekrosen. Diese treten z.B. bei Masttieren häufiger auf Vollspaltenböden als in der Anbindehaltung auf (Kordowitzki, 2015). Bei eigenen Untersuchungen an Milchrindern zeigte sich jedoch, dass Veränderungen der Schwänze auch bei diesen Tieren ein häufiges Problem darstellen. Neben den bekannten, entzündlichen Läsionen der Schwanzspitze, konnte eine Vielzahl von unterschiedlichen Veränderungen beobachtet werden (Meier et al., 2021). Laut Literatur spielen als Ursache von Schwanzläsionen Haltungsbedingungen, Haltungsform, Besatzdichte, Management und der Umgang mit dem Tier eine Rolle (Kordowitzki, 2015). Häufig als ursächlich beschrieben werden außerdem Mykotoxine. Dabei wird zwischen dem von Mutterkorn-Alkaloiden ausgelöstem Ergotismus und durch nicht weiter definiertes pilzbelastetes Futter ausgelöste Erkrankungen wie fescue foot oder Deg Nala Disease unterschieden (Cowan, 2020; Rahimabadi et al., 2022). Als dritte potenzielle Ursache kommt die Fütterung in Frage (Freitag et al., 2017). Dabei wird ein ähnlicher Pathomechanismus wie bei SINS (Swine Inflammation and Necrosis Syndrome) vermutet: Acidosen im Pansen oder Dickdarm führen zu einer massenhaften Vermehrung gram (-) Bakterien, die wiederum Lipopolysaccharide (LPS) freisetzen. Diese gelangen durch ein geschwächtes Epithelgewebe in die Blutbahn und sorgen in feinen Blutgefäßen für Durchblutungsstörungen (Plaizier et al., 2012). Ziel der Arbeit war es herauszufinden, ob bei zuvor in Bezug auf Veränderungen des Schwanzes phänotypisierten Deutsch Holstein Kühen genetische Unterschiede bestehen und diese eventuell Hinweise auf eine der potenziellen Ursachen liefern können. 2 Material und Methoden Für die Studie wurden 167 Deutsche Holstein Kühe in Bezug auf die Merkmalskomplexe 1) Schwanzspitzenentzündungen und -nekrosen, 2) Ringartige Veränderungen, 3) Hyperkeratosen, 4) Schwellungen, 5) Verdünnungen, 6) Achsabweichungen, 7) Warzenähnliche Zubildungen untersucht und binär bewertet. Der Genotyp wurde bei 118 Tieren über den Illumina EuroG10k (V5, V7, V8), ein SNP-Chip mit 7k bzw. 10k SNP-Analysepunkten, erfasst und bei 51 Kühen mit dem lllumina EuroG_MD (V1, V1.1, V2). Dieser SNP-Chip erlaubt die Analyse von 45k SNPs, während die Daten der 118 Kühe auf 45.613 SNPs mittels FImpute (Gene Set Enrichment Analysis) imputiert wurden. Für jedes der oben genannten Merkmale wurde separat eine genomweite Assoziationsstudie (GWAS) mittels der Software GEMMA (Zhou & Stephens, 2014) durchgeführt. Innerhalb des univariaten linearen gemischten Modells wurde eine standardisierte Verwandtschaftsmatrix verwendet, die anhand der SNP-Marker berechnet wurde und somit die Populationsstratifikation berücksichtigte. Die Laktation (1., 2., ≥3.) wurde als Kovariate betrachtet. Die Genotyp-Matrix wurde zudem im Modell verwendet und die daraus resultierenden SNP-Effekte wurden mittels Likelyhood-ratio-Test auf Signifikanz geprüft. Die genomweite Signifikanzschwelle von α = 0,05 wurde bei einem -log10(p)-Wert von 5,91 erreicht. Da es sich um eine kleine Stichprobe handelt wurden die Top-Marker bereits ab -log10(p) ≥ 3,5 weiterer Betrachtung unterzogen. Dabei wurde jeweils der höchste Wert unter den einzelnen GWAS für einen SNP herangezogen. In der Linkage Disequilibrium decay Analyse (Laido et al., 2014) wurde ein r² > 0,6 im Abstand von 325 kbp festgestellt. Dieser Abstand wurde zur Kandidatengenanalyse (Positionelle Kandidatengene) verwendet. Die Analyse der Kandidatengene erfolgte auf ENSEMBL (http://oct2018.archive.ensembl.org/Bos_taurus/) mit dem hinterlegten Referenzgenom Bos taurus UMD3.1. Die Kandidatengene wurden auf gemeinsame Funktion in der Zelle und im Organismus mittels Genontologie-Analyse (GO-Analyse) über g:Profiler (https://biit.cs.ut.ee/gprofiler/gost) und String (https://string-db.org) durchgeführt. Einzelne GOen wurden ausgewählt und alle dazu zugeordneten Gene wurden auf deren Funktion in der Zelle und im Organismus überprüft. Hier wurde auch auf Studien anderer Tierarten und des Menschen zurückgegriffen. Zuletzt wurden die oben genannten SNPs mit ihrem Untersuchungsfenster in der AnimalQTLdb (https://www.animalgenome.org/cgi-bin/QTLdb/BT/index) auf bekannte QTL untersucht. Beachtet wurden dabei nur Merkmale, die nicht das Exterieur, die Milchleistung/-inhaltsstoffe oder Fruchtbarkeitskennzahlen beschreiben. 3 Ergebnisse und Diskussion Über alle sieben Merkmale fanden sich 92 zu analysierende Marker damit 682 zugeordnete Gene bzw. 562 Kandidatengene. Beim Merkmal „Verdünnung“ konnten mit 24 SNPs mit -log10(p) ≥ 3,50 die meisten SNPs für die Kandidatengenanalyse festgestellt werden. Zwei Marker für dieses Merkmal überschreiten die genomweite Signifikanzschwelle. Auf BTA5 liegt rs41618168, mit einem Wert von 6,40 für -log10(p). Mit ihm konnte Kandidatengen ADAMTS20 und die Merkmale Zellzahl, Zwillingsgeburten, Trockenmasseaufnahme und Reaktion auf Parasitenbefall über den QTL-Abgleich in Verbindung gebracht werden. Das Gen ist für Fruchtbarkeitsprobleme beim Menschen bekannt. May et al. (2022) untersuchten die Erstlaktationsdaten von ca. 14800 HF Kühen in Ostdeutschland auf Fruchtbarkeitsstörungen. ADAMTS20 ist in dieser Untersuchung ein Kandidatengen für Endometritis des dritten Schweregrads. Auf BTA1 liegt rs42577957 mit -log10(p) = 9,43, es konnte das Kandidatengen TBL1XR1 und die Merkmale Hitzestress und Länge des produktiven Lebens über den QTL-Abgleich mit ihm in Verbindung gebracht werden. TBL1XR1 konnte als einzelnes Gen ebenfalls mit Hitzestress bei HF Kühen und anderen Wiederkäuern assoziiert werden (Carabaño et al., 2016). Durch die GO-Analyse über g:Profiler wurden 23 GO und über String 20 GO in den gleichen Kategorien ermittelt. Über beide Plattformen konnte die GO „lipopolysaccharid binding“ (LPS Bindungsvermögen) identifiziert werden. Die hier gehäuft auftretenden Gene gehören zur Familie der Cathelicidine und werden in der vorliegenden Studie mit dem Marker rs109960160, auf Chromosom 22 und mit dem Merkmal Schwellung assoziiert. Cathelicidine zeigten bei Rindern Wirkung gegen Bakterien, Viren und Parasiten und sind in der Lage Lipopolysaccharide (LPS) zu binden und damit deren Wirkungen zu unterbinden (Flores, 2011). Diese Gruppe ist somit ein Teil der Immunantwort und wird auch in vielen Studien mit Mastitiden in Verbindung gebracht. LPS sind Membranbestandteile von gram (-) Bakterien, die sich z.B. bei einer Pansenacidose stark vermehren können. Dies stellt einen potenziellen Zusammenhang zwischen Fütterung und Veränderungen am Rinderschwanz dar. Tomasinsig et al. (2010) konnten die antimikrobielle Wirkung von Cathelicidinen in vitro bestätigen. Überprüft wurden Vergleichsstämme und Isolate aus Mastitisfällen und damit die Erreger: E. coli, K. pneumoniae, S. aureus, S. epidermidis, Sc. uberis und Sc. agalactiae. Zanetti (2005) gibt einen Überblick über die große Bandbreite von Mikroorganismen, die laut verschiedener Studien durch Cathelicidine bekämpft und abgetötet werden. Dabei wird betont, dass Ergebnisse in vitro aufgrund des komplexen Zusammenspiels verschiedenster Proteine im Organismus oftmals anders ausfallen als die Ergebnisse in vivo. Welche Funktionsweisen der antimikrobiellen Wirkung, besonders gegen gram (-) Bakterien, verwendet werden, zeigen Young-Speirs et al. (2018) in einem Review auf. Dabei ist die amphiphile Natur der Cathilicidine besonders wichtig, da Membranen gram (-) Bakterien selbst auch aus amphiphilen Molekülen aufgebaut sind und so gute Reaktionspartner sind. Insgesamt bieten die analysierten Gene einen Anhaltspunkt dafür, dass genetische Unterschiede einen Einfluss auf Veränderungen der Schwanzspitze haben. Das Krankheitsbild ist zwar nicht geklärt, aber durch die Ergebnisse dieser Arbeit sollten bei weiteren Untersuchungen LPS, Cathelicidine, ADAMTS20 und TBL1XR1 mit betrachtet werden. 4 Literatur Carabaño, M.J., Ramón, M., Díaz, C., et al. 2016: Breeding for resilience to heat stress effects: A comparison across dairy ruminant species. Journal of Animal Science 94 (Suppl_5), 195, DOI: 10.2527/jam2016-0402, Abstract. Cowan, V.E. 2020: Investigation of the subclinical toxicological effects of ergot alkaloid mycotoxin (Claviceps purpurea) exposure in beef cows and bulls. University of Saskatchewan, Dissertation. Flores, E.G. 2011: Characterization of the bovine cathelicidin gene family. Texas A&M University ProQuest Dissertations Publishing, UMI 3486189, Dissertation. Freitag, M., Heers, P.A., Beune, H. 2017: Schädigt falsche Fütterung die Schwanzspitzen?. top agrar 9/2017, R26–R28. Kordowitzki, P. 2015: Untersuchungen zum Auftreten der Schwanzspitzennekrose bei Mastbullen. Freie Universität Berlin, Dissertation, DOI: 10.17169/refubium-15478 . Laido, G., Marone, D., Russo, M.A., et al. 2014: Linkage Disequilibrium and Genome-Wide Association Mapping in Tetraploid Wheat (Triticum turgidum L.). PLoS ONE 9(4), 1–18, DOI: 10.1371/journal.pone.0095211 . May, K., Sames, L., Scheper, C., König, S. 2022: Genomic loci and genetic parameters for uterine diseases in first-parity Holstein cows and associations with milk production and fertility. Journal of Dairy Science 105 (1), 509–524, DOI: 10.3168/jds.2021-20685 . Meier, S., Abel, K., Kremer-Rücker, P.V. 2021: Development of a Tail Scoring as Health Indicator for Dairy Cows. Proceedings of the 44th ICAR Annual Conference virtually held from Leeuwarden, NL 2021 (25), 1-16. Plaizier J.C., Khafipour E., Li S., et al. 2012: Subacute ruminal acidosis (SARA), endotoxins and health consequences. Animal Feed Science and Technology 172 (1-2), 9–21, DOI: 10.1016/j.anifeedsci.2011.12.004 . Rahimabadi, P.D., Yourdkhani, S., Golchin, D., Rad, H.A. 2022: Ergotism in feedlot cattle: clinical, hematological, and pathological findings. Comparative Clinical Pathology 31 (2), 281–291, DOI: 10.1007/s00580-022-03331-7 . Tomasinsig, L., De Conti, G., Skerlavaj, B., et al. 2010: Broad-Spectrum Activity against Bacterial Mastitis Pathogens and Activation of Mammary Epithelial Cells Support a Protective Role of Neutrophil Cathelicidins in Bovine Mastitis. Infection and Immunity 78 (4), 1781–1788, DOI: 10.1128/IAI.01090-09 . Young-Speirs, M., Drouin, D., Cavalcante, P.A., et al. 2018: Host defense cathelicidins in cattle: types, production, bioactive functions and potential therapeutic and diagnostic applications. Review. International Journal of Antimicrobial Agents 51 (6), 813–821, DOI: 10.1016/j.ijantimicag.2018.02.006 . Zanetti, M. 2005: The Role of Cathelicidins in the Innate Host Defenses of Mammals. Current Issues in Molecular Biology 7 (2), 179–196, DOI: 10.21775/cimb.007.179 . Zhou, X., Stephens, M. 2014: Efficient multivariate linear mixed model algorithms for genome-wide association studies. Nature Methods 11 (4), 407–409, DOI: 10.1038/nmeth.2848 .
Mehr
Fedir PERTSEVYI,
Volodymyr Ladyka,
Prof. Dr. Iryna Smetanska
Technology of thermostable and frozen fillings from dairy raw materials and sesame seeds concentrate. (2022) Dissa+ 2022 , S. 1-192.
ObjectivesSomatic cell count (SCC) is a reliable and approved parameter for the estimation of udder health. The maincell types regarding somatic cells in the udder are lymphocytes, macrophages, and polymorph nuclearleucocytes (PMN). The differential somatic cell count (DSCC) represents the proportion of lymphocytes andPMN to total SCC, the remaining percentages to SCC are macrophages. So far, the effects of milk yield,season, parity, milking frequency, days in milk, and major pathogens on the DSCC are already described. Afurther known effect on udder health and SCC is the milking interval (MI). On farms with automatic milkingsystems (AMS) the MI can vary for each cow compared to conventional milking systems. Regarding DSCCand SCC, cows milked by AMS systems showed higher values compared to cows milked by conventionalmilking systems. Therefore, the aim of this study was to evaluate the effect of MI on DSCC.Materials and methodsData from 27 dairy herds from Germany including 6,500 dairy cows and 43,229 recordings were evaluated.The data resulting from milk yield performance testing were collected between January to December 2020. Allherds used automatic milking systems combined with free cow traffic. Milk yield performance testing data wasrecorded 11-times per year on each farm and included the DSCC measured using the FOSS methoddescribed by Damm et al. (2017). Date and time from each milking at the farms were available and used tocalculate each individual MI between milkings. MI ranged from 1 h minimum to 24 h maximum. Data of milkinginterval >24 h were excluded. Means were compared using Wilcoxon test. P-values were Bonferroni adjusted;the threshold for significance was set after adjusting to α < 0.05. A linear mixed model was used to estimatethe effect on DSCC including MI, milk yield, lactation, days in milk, and season as fixed effects and herd,individual cow, and residuals as random effects.ResultsMean MI was 10.6 h (±0.04 h SE). MI of ≤4 h resulted in the highest DSCC (52.3 ±1.0%). The DSCCdecreased significantly for cows showing a MI >4 and ≤6 h (39.0 ±0.6%) and had its minimum between MI >6and ≤8 h (37.9 ±0.4%). MI between >8 - ≤10 h resulted in a DSCC of 40.5% (±0.4%). The DSCC increased forMI >10 - ≤12 h and for >12 h MI (42.8 ±0.4%; 46.6 ±0.3%, respectively; all P-values < 0.001). Therefore, themost frequently milked cows showed higher DSCC compared to cows between 4 and 8 hours MI. Consideringnatural behavior, the suckling interval of calves from their mothers ranges between 4 to 6 times per day, whichresults in a MI of 6 to 4 hours, representing the MI of the second lowest DSCC found in this dataset.The standard deviation of the MI (MISD) expresses the irregularity of milkings. Data evaluation showed the lower the MISD, the lower the DSCC. For MISD ≤2 h the DSCC was lowest (38.8 ±0.7%), compared to MISD >2- ≤4 h (41.0 ±0.5%), MISD >4 - ≤6 h (43.2 ±0.7%), and MISD >6 h (48.1 ±1.1%). Irregular milking is also knownto impair udder health and increase the SCC of cows.ConclusionsMilking interval between 4 to 8 hours minimizes DSCC, which aims the natural MI of suckling calves. A moreregular milking interval in AMS farms could reduce DSCC and therefore improve udder health. AMS farmsshould strive their management and settings of the AMS to encourage cows to visit the AMS more regularly.AcknowledgementWe kindly acknowledge the QNETICS GmbH, Erfurt, Germany, for providing the dataset of DSCC values andmilk yield recording data for this study.
Mehr
Gustavo Chaves,
Artem G. Ayuyan,
Vladimir V. Cherny,
Deri Morgan,
Arne Franzen,
Lynne Fieber,
Prof. Dr. Lydia Nausch,
Christian Derst,
Iryna Mahorivska,
Christophe Jardin,
Thomas E. DeCoursey,
Boris Musset
ObjectivesTail injuries and pathological alterations have been reported in many species. In cattle, they were investigatedmainly in fattening bulls and feedlot cattle. In dairy cows high prevalences for different tail alterations werefound. However, aetiology and pathogenesis of this health trait are still unclear and need further investigation.Out of 4443 phenotypes of different tail alterations we assorted seven groups common in dairy cows: 1. verytip of the tail , 2. ring-like, 3. scurf, 4. swelling, 5. thinning, 6. axis anomaly, and 7. verruca-like mass. Theobjective of this study was to identify genomic regions that may influence the occurrence of different tailalterations in dairy cows, which could be useful for a potential implementation of a genomic selection tool formore robust and healthy cows in the future.Material and methodsOccurrence data of each tail alteration group were collected monthly from 167 German Holstein cows. Thecows originated from a German 1300 cows dairy herd. Data collection was performed from May to December2021, since calving of all included cows was from April to May. The cows were in their first to seventh lactation.The phenotype was encoded binary, where 0 means the absence and 1 the presence of a tail alteration groupwithin the whole timespan.For 118 cows, Illumina EuroG10k genotypes were available and imputed up to 45k (FImpute). The remainingcows were genotyped with the Illumina EuroG MD (V1, V1.1, V2) with 45613 SNPs. After quality check (onlysegregating SNPs, at least two groups with a minimum of 10 observations, no duplicated markers, a minorallele frequency of 1%, and within Hardy-Weinberg-Equilibrium P>0.01), 41062 SNPs remained.A genome-wide association study was performed using the software GEMMA and the univariate linear mixedmodel. Each tail alteration group was treated as a separate phenotype. A standardized relatedness matrix wasincluded in the model and calculated on SNP chip data to consider the population stratification, since manyhalf-sib groups were present. The lactation (1st, 2nd, ≥3rd) was included as covariate. The genotype matrix wasincluded in the model and the effect size per marker was estimated and tested for significance using a Waldtest.For positional candidate gene analysis, genomic regions around top markers (P < 0.0001) of 325kbp wereconsidered,since the linkage disequilibrium decay analysis gave a mean r² of >0.61 within this distance. Themarker positions are given on the ARS-UCD 1.2 Bos taurus genome assembly.ResultsIn total 51 top markers resulted for all seven tail alteration groups, whereof one marker reached Bonferronicorrectedgenome-wide significance threshold for tail alteration group “thinning” (BTA1: rs42577957, −log10(P)= 9.22). The markers were found on 18 different chromosomes. Close to these markers, 65 positionalcandidate genes reside. Among them CCDC122 (rs42421906, −log10(P) = 5.46), which was associated withthe phenotype “scurf” in our analysis. CCDC122 is one of the top differentially expressed genes in livermetabolism in pigs showing swine inflammation and necrosis syndrome (Ringseis et al., 2021). This syndromeresults in severe tail alterations in pigs as well.ConclusionsThis first genetic investigation of tail alterations in dairy cows showed the potential of finding genetic markersfor this novel health trait. Nonetheless, it is recommended to increase the sample size of cows and to furtherinvestigate the cause of tail alterations, to substantiate the reported phenotypes.LiteratureRingseis, R., Gessner, D. K., Loewenstein, F., Kuehling, J., Becker, S., Willems, H., et al. (2021). Swine inflammation and necrosis syndrome is associated with plasma metabolites and liver transcriptome in affected piglets. Animals 11, 1–14. doi:10.3390/ani11030772 Sargolzaei, M., Chesnais, J. P., and Schenkel, F. S. (2014). A new approach for efficient genotype imputation using information from relatives. BMC Genomics 15. doi:10.1186/1471-2164-15-478 Zhou, X., and Stephens, M. (2014). Efficient Algorithms for Multivariate Linear Mixed Models in Genome-wide Association Studies. Nat Methods 11, 407–409. doi:10.1038/nmeth.2848 AcknowledgementWe thank the MASTERRIND GmbH, Verden, Germany, for providing the genotypes from the investigatedcows.FundingPart of the data results from the project TINCa Dairy, which is funded by the Tönnies Forschung, Rheda,Germany.
ObjectivesSomatic cell count (SCC) is a reliable and approved parameter for the estimation of udder health. The maincell types regarding somatic cells in the udder are lymphocytes, macrophages, and polymorph nuclearleucocytes (PMN). The differential somatic cell count (DSCC) represents the proportion of lymphocytes andPMN to total SCC, the remaining percentages to SCC are macrophages. So far, the effects of milk yield,season, parity, milking frequency, days in milk, and major pathogens on the DSCC are already described. Afurther known effect on udder health and SCC is the milking interval (MI). On farms with automatic milkingsystems (AMS) the MI can vary for each cow compared to conventional milking systems. Regarding DSCCand SCC, cows milked by AMS systems showed higher values compared to cows milked by conventionalmilking systems. Therefore, the aim of this study was to evaluate the effect of MI on DSCC.Materials and methodsData from 27 dairy herds from Germany including 6,500 dairy cows and 43,229 recordings were evaluated.The data resulting from milk yield performance testing were collected between January to December 2020. Allherds used automatic milking systems combined with free cow traffic. Milk yield performance testing data wasrecorded 11-times per year on each farm and included the DSCC measured using the FOSS methoddescribed by Damm et al. (2017). Date and time from each milking at the farms were available and used tocalculate each individual MI between milkings. MI ranged from 1 h minimum to 24 h maximum. Data of milkinginterval >24 h were excluded. Means were compared using Wilcoxon test. P-values were Bonferroni adjusted;the threshold for significance was set after adjusting to α < 0.05. A linear mixed model was used to estimatethe effect on DSCC including MI, milk yield, lactation, days in milk, and season as fixed effects and herd,individual cow, and residuals as random effects.ResultsMean MI was 10.6 h (±0.04 h SE). MI of ≤4 h resulted in the highest DSCC (52.3 ±1.0%). The DSCCdecreased significantly for cows showing a MI >4 and ≤6 h (39.0 ±0.6%) and had its minimum between MI >6and ≤8 h (37.9 ±0.4%). MI between >8 - ≤10 h resulted in a DSCC of 40.5% (±0.4%). The DSCC increased forMI >10 - ≤12 h and for >12 h MI (42.8 ±0.4%; 46.6 ±0.3%, respectively; all P-values < 0.001). Therefore, themost frequently milked cows showed higher DSCC compared to cows between 4 and 8 hours MI. Consideringnatural behavior, the suckling interval of calves from their mothers ranges between 4 to 6 times per day, whichresults in a MI of 6 to 4 hours, representing the MI of the second lowest DSCC found in this dataset.The standard deviation of the MI (MISD) expresses the irregularity of milkings. Data evaluation showed the lower the MISD, the lower the DSCC. For MISD ≤2 h the DSCC was lowest (38.8 ±0.7%), compared to MISD >2- ≤4 h (41.0 ±0.5%), MISD >4 - ≤6 h (43.2 ±0.7%), and MISD >6 h (48.1 ±1.1%). Irregular milking is also knownto impair udder health and increase the SCC of cows.ConclusionsMilking interval between 4 to 8 hours minimizes DSCC, which aims the natural MI of suckling calves. A moreregular milking interval in AMS farms could reduce DSCC and therefore improve udder health. AMS farmsshould strive their management and settings of the AMS to encourage cows to visit the AMS more regularly.AcknowledgementWe kindly acknowledge the QNETICS GmbH, Erfurt, Germany, for providing the dataset of DSCC values andmilk yield recording data for this study.
ObjectivesTail injuries and pathological alterations have been reported in many species. In cattle, they were investigatedmainly in fattening bulls and feedlot cattle. In dairy cows high prevalences for different tail alterations werefound. However, aetiology and pathogenesis of this health trait are still unclear and need further investigation.Out of 4443 phenotypes of different tail alterations we assorted seven groups common in dairy cows: 1. verytip of the tail , 2. ring-like, 3. scurf, 4. swelling, 5. thinning, 6. axis anomaly, and 7. verruca-like mass. Theobjective of this study was to identify genomic regions that may influence the occurrence of different tailalterations in dairy cows, which could be useful for a potential implementation of a genomic selection tool formore robust and healthy cows in the future.Material and methodsData collection started in December 2019 from a German 75 German Holstein (HOL) cows dairy herd. All cows wereexamined every two weeks during six months regarding any kind of tail alterations. The findings were described andphotographed. Data analysis resulted in seven different kinds of tail alterations: 1. very tip of the tail, 2. ring-like, 3. scurf,4. swelling, 5. thinning, 6. axis anomalies, and 7. verruca-like mass.Hereinafter, prevalences for the observed tail alterations were calculated based on monthly data collection from fivedifferent dairy herds: 3 HOL herds, counting average herd sizes of 75, 300, and 1300, respectively; 2 German Fleckvieh(FV) herds, counting 60 cows, each. All cows were housed in free stall barns with conventional (HOL, FV) or automaticmilking systems (FV).In total, 4443 Dairy Cows' Tail Scores were recorded. Data preparation and analysis were performed using R version4.1.2. Prevalences for tail alterations were calculated by dividing the number of observations within by the total number ofobservations of each kind of tail alteration and was given in percent. For calculating the total prevalence per breed andfarm, the occurrence of at least one tail alteration counted as an observation, was divided by the total number of cowsunder investigation and given in percent.ResultsThe overall prevalence for any kind of tail alteration was 88% in German Holstein and 99% in Fleckvieh cows; it variedbetween farms from 74% to 99%. Prevalences for HOL and FV regarding alterations of the very tip of the tail were 26%and 71%, ring-like alterations 24% and 30%, swelling 26% and 42%, scurf 55% and 60%, thinning combined with axisanomalies 16% and 21%, and verruca-like mass 10% and 21%, respectively. Number per tail ranged for ring-likealterations and thinning/axis anomalies from 1 to 5 and for verruca-like mass from 1 to 3.ConclusionsDuring this study, high prevalences for different tail alterations in HOL and FV dairy cows were found out. The grouping ofdifferent alterations as described above can be useful to phenotype tail alterations in dairy cows. However, furtherinvestigations regarding pathogenesis, aetiology, and genetics of the observed alterations in dairy cows' tails are neededto understand their origin and impact on animal health and welfare.FundingThis research was funded by the Tönnies Forschung, Rheda, Germany.
Mehr
Prof. Dr. Prisca Kremer-Rücker,
Lukas Volkert,
Kim F. Schubert,
Dr. Saskia Meier
ObjectivesTail injuries and pathological alterations have been reported in many species. In cattle, they were investigatedmainly in fattening bulls and feedlot cattle. In dairy cows high prevalences for different tail alterations werefound. However, aetiology and pathogenesis of this health trait are still unclear and need further investigation.Out of 4443 phenotypes of different tail alterations we assorted seven groups common in dairy cows: 1. verytip of the tail , 2. ring-like, 3. scurf, 4. swelling, 5. thinning, 6. axis anomaly, and 7. verruca-like mass. Theobjective of this study was to identify genomic regions that may influence the occurrence of different tailalterations in dairy cows, which could be useful for a potential implementation of a genomic selection tool formore robust and healthy cows in the future.Material and methodsOccurrence data of each tail alteration group were collected monthly from 167 German Holstein cows. Thecows originated from a German 1300 cows dairy herd. Data collection was performed from May to December2021, since calving of all included cows was from April to May. The cows were in their first to seventh lactation.The phenotype was encoded binary, where 0 means the absence and 1 the presence of a tail alteration groupwithin the whole timespan.For 118 cows, Illumina EuroG10k genotypes were available and imputed up to 45k (FImpute). The remainingcows were genotyped with the Illumina EuroG MD (V1, V1.1, V2) with 45613 SNPs. After quality check (onlysegregating SNPs, at least two groups with a minimum of 10 observations, no duplicated markers, a minorallele frequency of 1%, and within Hardy-Weinberg-Equilibrium P>0.01), 41062 SNPs remained.A genome-wide association study was performed using the software GEMMA and the univariate linear mixedmodel. Each tail alteration group was treated as a separate phenotype. A standardized relatedness matrix wasincluded in the model and calculated on SNP chip data to consider the population stratification, since manyhalf-sib groups were present. The lactation (1st, 2nd, ≥3rd) was included as covariate. The genotype matrix wasincluded in the model and the effect size per marker was estimated and tested for significance using a Waldtest.For positional candidate gene analysis, genomic regions around top markers (P < 0.0001) of 325kbp wereconsidered,since the linkage disequilibrium decay analysis gave a mean r² of >0.61 within this distance. Themarker positions are given on the ARS-UCD 1.2 Bos taurus genome assembly.ResultsIn total 51 top markers resulted for all seven tail alteration groups, whereof one marker reached Bonferronicorrectedgenome-wide significance threshold for tail alteration group “thinning” (BTA1: rs42577957, −log10(P)= 9.22). The markers were found on 18 different chromosomes. Close to these markers, 65 positionalcandidate genes reside. Among them CCDC122 (rs42421906, −log10(P) = 5.46), which was associated withthe phenotype “scurf” in our analysis. CCDC122 is one of the top differentially expressed genes in livermetabolism in pigs showing swine inflammation and necrosis syndrome (Ringseis et al., 2021). This syndromeresults in severe tail alterations in pigs as well.ConclusionsThis first genetic investigation of tail alterations in dairy cows showed the potential of finding genetic markersfor this novel health trait. Nonetheless, it is recommended to increase the sample size of cows and to furtherinvestigate the cause of tail alterations, to substantiate the reported phenotypes.LiteratureRingseis, R., Gessner, D. K., Loewenstein, F., Kuehling, J., Becker, S., Willems, H., et al. (2021). Swine inflammation and necrosis syndrome is associated with plasma metabolites and liver transcriptome in affected piglets. Animals 11, 1–14. doi:10.3390/ani11030772 Sargolzaei, M., Chesnais, J. P., and Schenkel, F. S. (2014). A new approach for efficient genotype imputation using information from relatives. BMC Genomics 15. doi:10.1186/1471-2164-15-478 Zhou, X., and Stephens, M. (2014). Efficient Algorithms for Multivariate Linear Mixed Models in Genome-wide Association Studies. Nat Methods 11, 407–409. doi:10.1038/nmeth.2848 AcknowledgementWe thank the MASTERRIND GmbH, Verden, Germany, for providing the genotypes from the investigatedcows.FundingPart of the data results from the project TINCa Dairy, which is funded by the Tönnies Forschung, Rheda,Germany.
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