Die chronologische Liste zeigt aktuelle Veröffentlichungen aus dem Forschungsbetrieb der Hochschule Weihenstephan-Triesdorf. Zuständig ist das Zentrum für Forschung und Wissenstransfer (ZFW).
8 Ergebnisse
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.
Mehr
Jan D Hüwel,
Prof. Dr. Florian Haselbeck,
Prof. Dr. Dominik Grimm,
Christian Beecks
One of the major challenges in time series analysis are changing data distributions, especially when processing data streams. To ensure an up-to-date model delivering useful predictions at all times, model reconfigurations are required to adapt to such evolving streams. For Gaussian processes, this might require the adaptation of the internal kernel expression. In this paper, we present dynamically self-adjusting Gaussian processes by introducing Event Triggered Kernel Adjustments in Gaussian process modelling (ETKA), a novel data stream modelling algorithm that can handle evolving and changing data distributions. To this end, we enhance the recently introduced Adjusting Kernel Search with a novel online change point detection method. Our experiments on simulated data with varying change point patterns suggest a broad applicability of ETKA. On real-world data, ETKA outperforms comparison partners that differ regarding the model adjustment and its refitting trigger in nine respective ten out of 14 cases. These results confirm ETKA's ability to enable a more accurate and, in some settings, also more efficient data stream processing via Gaussian processes.Code availability: https://github.com/JanHuewel/ETKA
Vorbeugen ist besser als Löschen. (2022) Interview in agrarheute 9/2022, S. 22-25 .
Teresa Zölch,
Sabrina Erlwein,
Prof. Dr. Simone Linke,
Alexander Putz,
W. Lang,
Prof. Dr. Stephan Pauleit
Klimaorientierung im städtebaulich-landschaftsplanerischen Wettbewerb: Kommune und Wissenschaft im gemeinsamen Lernprozess (2022) Reallabore für urbane Transformationen, Gröschel Branding GmbH, Berlin
In Synthese- und Vernetzungsprojekt Zukunftsstadt (SynVer*Z; Hrsg.) , S. S. 103.
Betreuung der Publikationsseiten
Gerhard Radlmayr
Referent für Wissenstransfer und Forschungskommunikation
Wir verwenden Cookies. Einige sind notwendig für die Funktion der Webseite, andere helfen uns, die Webseite zu verbessern. Um unseren eigenen Ansprüchen beim Datenschutz gerecht zu werden, erfassen wir lediglich anonymisierte Nutzerdaten mit „Matomo“. Um unser Internetangebot für Sie ansprechender zu gestalten, binden wir außerdem externe Inhalte unserer Social-Media-Kanäle ein.
