Dörte Wittenburg

Research Institute for Farm Animal Biology (FBN) | FBN · Institute of Genetics and Biometry

The arrangement of markers on the genome can be defined in either physical or linkage terms. While a physical map represents the inter-marker distances in base pairs, a genetic (or linkage) map pictures the recombination rate between pairs of markers. High-resolution genetic maps are key elements for genomic research, such as fine-mapping of quanti...

Breeding cattle with low nitrogen emissions has been proposed as a countermeasure against eutrophication due to dairy production. Milk urea content (MU) could potentially serve as a new readily measured indicator trait for nitrogen emissions by cows. Therefore, we estimated genetic parameters related to MU and its relationship with other milk trait...

Determination of sample size (the number of replications) is a key step in the design of an observational study or randomized experiment. Statistical procedures for this purpose are readily available. Their treatment in textbooks is often somewhat marginal, however, and frequently the focus is on just one particular method of inference (significanc...

Creation of the bovine reference assembly paved the way to develop the high‐throughput genotyping arrays of the single nucleotide polymorphisms (SNPs) based on the available map coordinates that facilitated major advances in gene mapping and selection programs. The assembly flaws, however, may cause false results in the downstream gene mapping stud...

In life sciences, high-throughput techniques typically lead to high-dimensional data and often the number of covariates is much larger than the number of observations. This inherently comes with multicollinearity challenging a statistical analysis in a linear regression framework. Penalization methods such as the lasso, ridge regression, the group...

Pikeperch (Sander lucioperca) has emerged as a high value species to the aquaculture industry. However, its farming techniques are at an early stage and its production is often performed without a selective breeding program, potentially leading to high levels of inbreeding. In this study, we identified and characterized autozygosity based on genome...

An amendment to this paper has been published and can be accessed via the original article.

To study the genetic impact on a quantitative trait, molecular markers are used as predictor variables in a statistical model. This habilitation thesis elucidated challenges accompanied with such investigations. First, the usefulness of including different kinds of genetic effects, which can be additive or non-additive, was verified. Second, depend...

The arrangement of markers on the genome can be defined either in physical or linkage terms. While a physical map represents the inter-marker distances in base pairs, a linkage map pictures the recombination frequency between pairs of markers. The rate by which two measures are correlated varies along the chromosomes and provides insights into the...

Creation of the bovine reference assembly paved the way to develop the high-throughput genotyping arrays of the single nucleotide polymorphisms (SNPs) based on the available map coordinates that facilitated major advances in gene mapping and selection programs. The assembly flaws, however, may cause false positive results in the downstream gene map...

The dairy cattle industry emits considerable amounts of nitrogen, contributing to eutrophication and greenhouse gas emissions. Therefore, breeding and selection of cattle with outstanding low nitrogen emission is investigated as a possible countermeasure. Since milk urea content (MUC) correlates with the amount of nitrogen emitted, this study aimed...

Background Linkage and linkage disequilibrium (LD) between genome regions cause dependencies among genomic markers. Due to family stratification in populations with non-random mating in livestock or crop, the standard measures of population LD such as $$r^2$$ r 2 may be biased. Grouping of markers according to their interdependence needs to account...

Pikeperch (Sander lucioperca) is a fish species with growing economic significance in the aquaculture industry. However, successful positioning of pikeperch in large-scale aquaculture requires advances in our understanding of its genome organization. In this study, an ultra-high density linkage map for pikeperch comprising 24 linkage groups and 1,0...

The dairy cattle industry emits enormous amounts of nitrogen, which pollutes the environment. Therefore, breeding and selection of cattle with outstanding nitrogen efficiency could minimize environmental pollution. Since milk urea content (MUC) correlates with the amount of nitrogen emitted, this study aimed at estimating genetic parameters of MUC...

Background: Single nucleotide polymorphisms (SNPs) which capture a significant impact on a trait can be identified with genome-wide association studies. High linkage disequilibrium (LD) among SNPs makes it difficult to identify causative variants correctly. Thus, often target regions instead of single SNPs are reported. Sample size has not only a...

Background Recombination is a process by which chromosomes are broken and recombine to generate new combinations of alleles, therefore playing a major role in shaping genome variation. Recombination frequencies ( $$\theta$$ θ ) between markers are used to construct genetic maps, which have important implications in genomic studies. Here, we report...

Background: Statistical analyses of biological problems in life sciences often lead to high-dimensional linear models. To solve the corresponding system of equations, penalization approaches are often the methods of choice. They are especially useful in case of multicollinearity, which appears if the number of explanatory variables exceeds the num...

Background : Linkage and linkage disequilibrium (LD) between genome regions cause dependencies among genomic markers. Due to family stratification in populations with non-random mating in livestock or crop, the standard measures of population LD such as $r^2$ may be biased. Grouping of markers according to their interdependence needs to account for...

Background: Linkage and linkage disequilibrium (LD) between genome regions cause dependencies among genomic markers. Due to family stratification in populations with non-random mating in livestock or crop, the standard measures of population LD such as r 2 may be biased. Grouping of markers according to their interdependence needs to account for th...

Background : Linkage and linkage disequilibrium (LD) between genome regions cause dependencies among genomic markers. Due to family stratification in populations with non-random mating in livestock or crop, the standard measures of population LD such as r 2 may be biased. Grouping of markers according to their interdependence needs to account for t...

Selective breeding can significantly improve the establishment of sustainable and profitable aquaculture fish farming. For rainbow trout (Oncorhynchus mykiss), one of the main aquaculture coldwater species in Europe, a variety of selected hatchery strains are commercially available. In this study, we investigated the genetic variation between the l...

Statistical analyses of biological problems in life sciences often lead to high-dimensional linear models. To solve the corresponding system of equations, penalisation approaches are often the methods of choice. They are especially useful in case of multicollinearity which appears if the number of explanatory variables exceeds the number of observa...

Single nucleotide polymorphisms (SNPs) with significant impact on a trait can be identified with genome-wide association studies. High linkage disequilibrium (LD) among SNPs makes it difficult to identify causative variants correctly. Thus, often target regions instead of single SNPs are reported. Sample size has not only a crucial impact on the pr...

Single nucleotide polymorphisms (SNPs) which capture a significant impact on a trait can be identified with genome-wide association studies. High linkage disequilibrium (LD) among SNPs makes it difficult to identify causative variants correctly. Thus, often target regions instead of single SNPs are reported. Sample size has not only a crucial impac...

The pikeperch (Sander lucioperca) is a fresh and brackish water Percid fish natively inhabiting the northern hemisphere. This species is emerging as a promising candidate for intensive aquaculture production in Europe. Specific traits like cannibalism, growth rate and meat quality require genomics based understanding, for an optimal husbandry and d...

Single nucleotide polymorphisms (SNPs) with significant impact on a trait can be identified with genome-wide association studies. The high linkage disequilibrium (LD) among SNPs makes it difficult to identify causative variants correctly. In contrast to a single-locus model, where single SNPs are investigated successively, a multi-locus model is th...

Blood values of calcium (Ca), inorganic phosphorus (IP), and alkaline phosphatase activity (ALP) are valuable indicators for mineral status and bone mineralization. The mineral homeostasis is maintained by absorption, retention, and excretion processes employing a number of known and unknown sensing and regulating factors with implications on immun...

Modern genome-wide association studies as well as methods for genomic selection involve genetic data, derived either from the analysis of biological samples or from simulations, where the number of genetic markers (e.g. SNPs) vastly exceeds the number of individuals. In this high-dimensional setting, exploring the precision of SNP-effect estimates...

Molecular markers can be used to assess the genetic variation in a livestock population. Not only are the physical but also the genetic position of markers important for characterising a livestock population and for planning mating decisions in livestock breeding. Though the physical position is available from the current genome assembly, the genet...

For the genomic evaluation of domestic animals, whole-genome regression methods are applied which use extensive information about genomic markers (e.g. single nucleotide polymorphisms; SNPs). As the number of model parameters increases with a still growing number of SNPs, multicollinearity between covariates can affect the precision of marker-effec...

Modern genome-wide association studies as well as methods for genomic selection frequently involve linear models where the number of genetic markers vastly exceeds the number of observations. In this high-dimensional setting, exploring the precision of SNP-effect estimates leading to a reliable identification of causative variants is complicated. W...

Genomic information can be used to study the genetic architecture of some trait. Not only the size of the genetic effect captured by molecular markers and their position on the genome but also the mode of inheritance, which might be additive or dominant, and the presence of interactions are interesting parameters. When searching for interacting loc...

Estimates of paternal recombination rate for all autosomes using empirical bovine data. Pairwise recombination rates were obtained using the stepwise procedure EMDP.

Validation of recombination-rate estimates using empirical bovine data on BTA4. Pairwise recombination rates were obtained using the stepwise procedure EMDP. BTA4 contained SNPs which were misplaced (A) within and (B) between chromosomes.

MSE of estimated paternal recombination rate and maternal linkage disequilibrium for simulated scenarios. Start values were fixed (EMT0 and EMT05) or adapted (EMDP), 1,000 half-sibs were simulated with 10,000 replicates.

Estimates of r2 for all autosomes using empirical bovine data. Pairwise r2's were obtained using the stepwise procedure EMDP.

Bias of estimated paternal recombination rate and maternal linkage disequilibrium for simulated scenarios. Start values were fixed (EMT0 and EMT05) or adapted (EMDP), 1,000 half-sibs were simulated with 10,000 replicates.

Investigations on the likelihood function and derivation of the Hessian matrix.

Estimated vs. simulated recombination rate depending on start-value strategy. Start values were fixed (EMT0 and EMT05) or adapted (EMDP). Simulated maternal allele frequency and LD: (A) p1 = 0.5, Ddam = 0.05, (B) p1 = 0.5, Ddam = 0.10, (C) p1 = 0.4, Ddam = 0.05, and (D) p1 = 0.4, Ddam = 0.10. In total, 1,000 half-sibs were simulated with 1,000 repl...

Estimates of maternal linkage disequilibrium for all autosomes using empirical bovine data. Pairwise linkage disequilibria were obtained using the stepwise procedure EMDP.

Genotype data consisting of 39,780 SNPs (columns), and 265 progeny (rows).

Assignment of genotypes to half-sib families.

Physical position of SNPs based on assembly Btau 4.2 and UMD 3.1.1.

A livestock population can be characterized by different population genetic parameters, such as linkage disequilibrium and recombination rate between pairs of genetic markers. The population structure, which may be caused by family stratification, has an influence on the estimates of these parameters. An expectation maximization algorithm has been...

Quantifying the population stratification in genotype samples has become a standard procedure for data manipulation before conducting genome wide association studies, as well as for tracing patterns of migration in humans and animals, and for inference about extinct founder populations. The most widely used approach capable of providing biologicall...

Population genetic parameters, such as linkage disequilibrium and recombination rate (theta), are parameters for characterising livestock populations. The population structure has an influence on these parameters. In half-sib families, which are a typical family structure in dairy cattle, the paternal theta and the linkage disequilibrium of materna...

Identifying positions along the genome which affect a performance trait is of vast interest in quantitative genetics. Bayesian methods are among the most popular and successful mathematical approaches to estimate genetic effects captured by markers and to select the relevant loci, but their results strongly rely on proper choices of prior distribut...

Half-sib family is a typical population structure in dairy cattle. The population structure has influence on population parameters such as linkage disequilibrium (LD) and recombination rate between pairs of genomic markers. Estimates of LD can be incorporated in extended models for genome-based phenotype prediction. The paternal contribution to LD...

In livestock, current statistical approaches utilize extensive molecular data, e.g., single nucleotide polymorphisms (SNPs), to improve the genetic evaluation of individuals. The number of model parameters increases with the number of SNPs, so the multicollinearity between covariates can affect the results obtained using whole genome regression met...

Modern genotyping techniques result in large amounts of molecular data, e.g. SNPs. Thus, multicollinearities between variables appear. These dependencies are not only a consequence of the high complexity, but are also due to linkage and linkage disequilibrium between SNPs and can mathematically be expressed as covariances, forming a high-dimensiona...

In livestock, current statistical approaches involve extensive molecular data (e.g. SNPs) to reach an improved genetic evaluation of phenotypes. As the number of model parameters increases with a still growing number of SNPs, multicollinearity between covariates can affect the results of whole genome regression methods. The objective of this study...

In livestock, current statistical approaches involve extensive molecular data (e.g. SNPs) to reach an improved genetic evaluation. As the number of model parameters increases with a still growing number of SNPs, multicollinearity between covariates can affect the results of whole genome regression methods. The objective of this study is to addition...

Abstract Text: As the number of model parameters increases with still growing number of SNPs, multicollinearity between covariates can affect the results of whole genome prediction. Selecting appropriate SNPs may counteract this phenomenon. Additionally, dependencies between single SNPs or chromosome regions can directly be incorporated in predicti...

Milk performance traits are likely influenced by both additive and non-additive (e.g. dominance) genetic effects. Genetic variation can be partitioned using genomic information. The objective of this study was to estimate genetic variance components of production and milk component traits (e.g. acetone, fatty acids), which are particularly importan...

Genomic information can be used to study the genetic architecture of some trait. In particular, when searching for eQTL, genome-wide available SNP data are employed to identify loci with impact on mRNA expression levels which are analysed successively gene by gene. For processing such multitudes of information, a rapid algorithm is desired for esti...

ADRB2 and flanking regions. Coding region is shown in blue, untranslated regions in yellow. Vertical arrows show position of polymorphisms. Horizontal double-headed arrows depict amplicons used for resequencing. STR – short tandem repeat, I – insertion/deletion, A – nonsynonymous variant

Porcine adrenergic receptor beta 2 (ADRB2) gene exhibits differential allelic expression in skeletal muscle, and its genetic variation has been associated with muscle pH. Exploring the molecular-genetic background of expression variation for porcine ADRB2 will provide insight into the mechanisms driving its regulatory divergence and may also contri...

In this study the benefit of metabolome level analysis for the prediction of genetic value of three traditional milk traits was investigated. Our proposed approach consists of three steps: First, milk metabolite profiles are used to predict three traditional milk traits of 1,305 Holstein cows. Two regression methods, both enabling variable selectio...

Important SNP markers, occurring in more than seven cross-validation (CV) runs, for each milk trait obtained via the metabolite approach. For this analysis, the 10 training sets from the outer cross-validation was used. (PDF)

Correlations between important milk metabolites for all investigated milk traits. The correlation values were adapted from [6]. (PDF)

Known QTL regions or QTL peaks, which were filtered from the cattleQTL database [25]. The following criteria were applied: trait name equal to milk fat percentage and milk protein percentage, analysis type equal to QTL, breed equal to Holstein, and chromosome number and both flanking markers or peak markers had to be available. Based on the marker...

Phenotypic variation can partly be explained by genetic variation, such as variation in single nucleotide polymorphism (SNP) genotypes. Genomic selection methods seek to predict genetic values (breeding values) based on SNP genotypes. To develop and to optimize these methods, simulated data are often used, which follow a rather simple genotype-phen...

In the field of dairy cattle research, it is of great interest to improve the detection and prevention of diseases (e.g., mastitis and ketosis) and monitor specific traits related to the state of health and management. During the standard milk performance test, traditional milk traits are monitored, and quality and quantity are screened. In additio...

The composition of milk is crucial to evaluate milk performance and quality measures. Milk components partly contribute to breeding scores, and they can be assessed to judge metabolic and energy status of the cow as well as to serve as predictive markers for diseases. In addition to the milk composition measures (e.g., fat, protein, lactose) tradit...

The composition of milk is clue to evaluate milk performance and quality measures. Milk components partly contribute to breeding scores, and they can be assessed to judge metabolic and energy status of the cow as well as to serve as predictive markers for diseases. In addition to the milk composition measures (e.g. fat, protein, lactose) traditiona...

Traditional milk phenotypes (e.g. fat, protein, lactose) are measured regularly during the standard milk performance test (MPT). To investigate the metabolic state of cow and to understand the interplay between different milk traits, it is necessary to study milk composition in more depth and to disassemble milk into its components. Using the gas c...

Quantitative traits are typically influenced by a myriad of genes with their additive, dominance and epistatic effects, whereat their number and kind of interplay are hardly known. Although additive genetic effects are of major interest in breeding applications, the knowledge about non-additive genetic effects is important for the understanding of...

The figure shows estimates of genetic effects and location if epistasis was present in the 23-QTL scenario: (a) additive, (b) dominance, (c) additive × additive and (d) additive × dominance effects for a single dataset with M2 using fBayesB. Filled circles were plotted for each estimated effect >10-4. Location of (e) additive × additive and (f) add...

The fBayesB approach was applied to public data on a heterogeneous stock of mice. Genetic effects were estimated based on the different models including only additive effects (M0), additive and dominance effects (M1), additive, dominance and pairwise epistatic effects (M2).

Molecular marker information is a common source to draw inferences about the relationship between genetic and phenotypic variation. Genetic effects are often modelled as additively acting marker allele effects. The true mode of biological action can, of course, be different from this plain assumption. One possibility to better understand the geneti...

Reduction in the variability of piglet birth weight within litter and increased piglet survival are key objective in schemes aiming to improve sow prolificacy. In previous studies, variation in birth weight was described by the sample standard deviation of birth weights within one litter, and the genetic impact has been proved. In this study, we ad...

Sex differences in birth weight contribute to within-litter variability, which itself is connected to piglet survival. Therefore, we studied whether the sex difference in piglet birth weight is a genetically variable sex dimorphism. For that purpose a linear mixed model including sex-specific additive genetic effects was set up. A hypothesis testin...

It is a challenging task to predict genetic values for traits in dairy cattle on the basis of genome-wide SNP markers. Methods including additive genetic effects have already been studied, but the importance of non-additive effects for the genetic variation is not fully understood. A better prediction of genetic values is intended, when additive, d...

We are interested in predicting the genetic values for traits in dairy cattle on the basis of genome-wide SNP markers. The impact of additive genetic effects has been widely studied in the past, but the importance of non-additive effects for the genetic variation is not fully understood. From the biological perspective it is especially of interest...