PD Dr. rer. nat. habil. Dörte Wittenburg

+49 38208 68-902
Research 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
  • Considering population structure, different sources of genetic variation (additive, dominance, epistasis) and dependencies between genomic sites
  • Estimation of population-genetic parameters (linkage disequilibrium and recombination rate)

Curriculum Vitae

  • 2021: Habilitation and Venia Legendi in animal breeding and genetics
    Thesis: Statistical perspectives on dependencies between genomic markers
  • Since 2019: Head of Unit “Statistics in Genomics”, FBN Dummerstorf
  • 2013-2018: Head of Junior Scientist group "Improving the genome-based phenotype prediction", FBN Dummerstorf
  • 2008-2012: Postdoc in Junior Scientist Group "BovIBI Bovine Integrative Bioinformatics for Genomic Selection", FBN Dummerstorf
  • 2005-2008: Doctoral studies in statistical genetics (Dr. rer. nat. in Biomathematics), FBN Dummerstorf and University Greifswald
    PhD thesis: Statistical modelling of birth weight variability within litter in pigs
  • 2000-2005: Studies of Business Mathematics (Dipl.-Math. oec.), University Rostock
    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, AUF


de los Rios Pérez, L.; Druet, T.; Goldammer, T.; Wittenburg, D. (2022):
Analysis of autozygosity using whole-genome sequence data of full-sib families in pikeperch (Sander lucioperca). Front Genet 12: 786934, 1-9
Klosa, J.; Simon, N.; Liebscher, V.; Wittenburg, D. (2022):
A fitted sparse-group lasso for genome-based evaluations [epublished ahead of print]. IEEE ACM T COMPUT BI
Qanbari, S.; Schnabel, R. D.; Wittenburg, D. (2022):
Evidence of Rare Misassemblies in the Bovine Reference Genome Revealed by Population Genetic Metrics. Anim Genet 53 (4): 498-505
Wittenburg, D.; Doschoris, M.; Klosa, J. (2021):
Grouping of genomic markers in populations with family structure. BMC Bioinformatics 22: 79, 1-12
Jahnel, R.E.; Wittenburg, D.; Mayer, M.; Täubert, H.; Reinsch, N. (2021):
DGFZ Preis 2020 (Masterarbeiten) Estimation of genetic parameters of milk urea content. Zuchtungskunde 93 (2): 157-168
Goldammer, T.; Verleih, M.; Brunner, R. M.; Rebl, A.; Nguinkal, J. A.; de los Rios Pérez, L.; Schäfer, N.; Stüecken, M.; Swirplies, F.; Wittenburg, D. (2021):
Pikeperch genome data – basis for the smart farming in aquaculture. Mitteilungen der Landesforschungsanstalt für Landw (63): 125-133
Wittenburg, D. (2021):
Statistical perspectives on dependencies between genomic markers Rostock: 1-161
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