Dr. rer. nat. Dörte Wittenburg

+49 38208 68-902
Leibniz Institute for Farm Animal Biology (FBN)
Institute of Genetics and Biometry
Statistics in Genomics Unit
Wilhelm-Stahl-Allee 2
18196 Dummerstorf

Research interests

  • Statistical methods for the estimation of genetic effects on quantitative traits, significance tests and power analyses
  • Investigation of dependencies between genomic markers
  • Estimation of population genetic parameters

Curriculum Vitae

  • Since 2019: Head of Unit “Statistics in Genomics”, Leibniz Institute for Farm Animal Biology (FBN), Institute of Genetics and Biometry
    Main subject: Accounting for dependencies between genomic markers in the estimation of genetic effects
  • 2013-2018: Head of Junior Scientist group "Improving the genome-based phenotype prediction", Leibniz Institute for Farm Animal Biology (FBN), Institute of Genetics and Biometry
    Main subject: Considering population structure and different sources of genetic variation for phenotype prediction and study of dependencies between genomic sites
  • 2008-2012: PostDoc in Junior Scientist Group "BovIBI Bovine Integrative Bioinformatics for Genomic Selection", Leibniz Institute for Farm Animal Biology (FBN)
    Main subject: Development of statistical models for phenotype prediction based on genome-wide SNP data and their extension to include non-additive effects
  • 2005-2008: Doctoral studies in statistical genetics (Doctor of natural sciences [Dr. rer. nat.] in Biomathematics), Leibniz Institute for Farm Animal Biology (FBN) and University Greifswald
    PhD thesis: Statistical modelling of birth weight variability within litter in pigs
  • 2000-2005: Studies of Business Mathematics (Diploma in Business Mathematics [Dipl.-Math. oec.]), University Rostock
    Main subjects: Mathematical and asymptotical statistics, partial differential equations, financial management, data bases
    Diploma thesis: Linear and generalised linear models for the detection of QTL effects on the variability of repeated measurements


Contribution to lectures in the module "Linear and mixed models" which is part of the master programmes Animal Science and Plant Production at the University Rostock


Wittenburg, D.; Doschoris, M.; Klosa, J. (2021):
Grouping of genomic markers in populations with family structure. BMC Bioinformatics 22 (79): 1-12
Wittenburg, D.; Bonk, S. M.; Doschoris, M.; Reyer, H. (2020):
Design of experiments for fine-mapping quantitative trait loci in livestock populations . BMC Genet 21: 66,1-14
de los Rios Pérez, L.; Brunner, R. M.; Hadlich, F.; Rebl, A.; Kühn, C.; Wittenburg, D.; Goldammer, T.; Verleih, M. (2020):
Comparative analysis of the transcriptome and distribution of putative SNPs in two rainbow trout (Oncorhynchus mykiss) breeding strains by using next-generation sequencing. Genes-Basel 11: 841, 1-16
Klosa, J.; Simon, N.; Westermark, P. O.; Liebscher, V.; Wittenburg, D. (2020):
Seagull: lasso, group lasso and sparse-group lasso regularisation for linear regression models via proximal gradient descent . BMC Bioinformatics 21: 407, 1-8
Qanbari, S.; Wittenburg, D. (2020):
Male recombination map of the autosomal genome in German Holstein. Genet Sel Evol 52 (73): 1-11
de los Rios Pérez, L.; Nguinkal, J.A.; Verleih, M.; Rebl, A.; Brunner, R. M.; Klosa, J.; Schäfer, N.; Stüeken, M.; Goldammer, T.; Wittenburg, D. (2020):
An ultra-high density SNP-based linkage map for enhancing the pikeperch (Sander lucioperca) genome assembly to chromosome-scale. Sci Rep-UK 10 (22335): 1-13
Reyer, H.; Oster, M.; Wittenburg, D.; Murani, E.; Ponsuksili, S.; Wimmers, K. (2019):
Genetic contribution to variation in blood calcium, phosphorus, and alkaline phosphatase activity in pigs. Front Genet 10: 590, 1-12
Nguinkal, J.A.; Brunner, R. M.; Verleih, M.; Rebl, A.; de los Rios Pérez, L.; Schäfer, N.; Hadlich, F.; Stüeken, M.; Wittenburg, D.; Goldammer, T. (2019):
The first highly contiguous genome assembly of pikeperch (Sander lucioperca), an emerging aquaculture species in Europe. Genes-Basel 10: 708, 1-14
Hampel, A.; Teuscher, F.; Gomez-Raya, L.; Doschoris, M.; Wittenburg, D. (2018):
Estimation of recombination rate and maternal linkage disequilibrium in half-sibs. Front Genet 9: 186, 1-13
Boerner, V.; Wittenburg, D. (2018):
On estimation of genome composition in genetically admixed individuals using constrained genomic regression. Front Genet 9: 185, 1-14
Wittenburg, D.; Liebscher, V. (2018):
An approximate Bayesian significance test for genomic evaluations. Biometrical J 60: 1096-1109
Wittenburg, D.; Teuscher, F.; Klosa, J.; Reinsch, N. (2016):
Covariance between genotypic effects and its use for genomic inference in half-sib families. G3-Genes Genomes Genetics 6 (9): 2761-2772
Hampel, A.; Teuscher, F.; Wittenburg, D. (2016):
A likelihood approach for the estimation of recombination rate and linkage disequilibrium in half-sib families . Schriftenreihe / Leibniz-Institut für Nutztierbiol 25: 9-12
Wittenburg, D.; Melzer, N.; Reinsch, N. (2015):
Genomic additive and dominance variance of milk performance traits. J Anim Breed Genet 132 (1): 3-8
Zebunke, M.; Repsilber, D.; Nürnberg, G.; Wittenburg, D.; Puppe, B. (2015):
The backtest in pigs revisited - an analysis of intra-situational behaviour. Appl Anim Behav Sci 169: 17-25
Wittenburg, D.; Reinsch, N. (2014):
Selective shrinkage of genomic effects using synthetic dependencies in neighboring chromosome regions. In: Proceedings of the 10th World Congress on Genetics Applied to Livestock Production (American Society of Animal Science, Hrsg.): 216
Wittenburg, D.; Melzer, N.; Willmitzer, L.; Lisec, J.; Kesting, U.; Reinsch, N.; Repsilber, D. (2013):
Milk metabolites and their genetic variability. J Dairy Sci 96 (4): 2557-2569
Muràni, E.; Ponsuksili, S.; Reyer, H.; Wittenburg, D.; Wimmers, K. (2013):
Expression variation of the porcine ADRB2 has a complex genetic background. Mol Genet genomics 288 (11): 615-625
Melzer, N.; Wittenburg, D.; Hartwig, S.; Jakubowski, S.; Kesting, U.; Willmitzer, L.; Lisec, J.; Reinsch, N.; Repsilber, D. (2013):
Investigating associations between milk metabolite profiles and milk traits of Holstein cows. J Dairy Sci 96 (3): 1521-1534
Melzer, N.; Wittenburg, D.; Repsilber, D. (2013):
Integrating milk metabolite profile information for the prediction of traditional milk traits based on SNP information for Holstein cows. Plos One 8 (8): 1-10