Biomedical subjects

Jörn Bennewitz

Publications and source records attributed to Jörn Bennewitz.

6 recordsLinked to original sources

PubMed2006

Estimation of breed contributions to present and future genetic diversity of 44 North Eurasian cattle breeds using core set diversity measures.

Extinction of breeds threatens genetic diversity of livestock species. The need to conserve genetic diversity is widely accepted but involves in general two questions: (i) is the expected loss of diversity in a set of breeds within a defined future time horizon large enough to establish a conservation plan, and if so (ii) which breeds should be prioritised for such a conservation plan? The present study uses a marker assisted methodology to address these questions. The methodology combines core set diversity measures with a stochastic method for the estimation of expected future diversity and breed marginal diversities. The latter is defined as the change in the total diversity of all breeds caused by a one unit decrease in extinction probability of a particular breed. The stochastic method was validated by means of simulations. A large field data set consisting of 44 North Eurasian cattle breeds was analysed using simplified determined extinction probabilities. The results show that the expected loss of diversity in this set within the next 20 to 50 years is between 1 and 3% of the actual diversity, provided that the extinction probabilities which were used are approximately valid. If this loss is to be reduced, it is sufficient to include those three to five breeds with the highest marginal diversity in a conservation scheme.

Animals↗

PubMed2004

Evidence for multiple alleles at the DGAT1 locus better explains a quantitative trait locus with major effect on milk fat content in cattle.

A quantitative trait locus (QTL) for milk fat percentage has been mapped consistently to the centromeric region of bovine chromosome 14 (BTA14). Two independent studies have identified the nonconservative mutation K232A in the acylCoA-diacylglycerol-acyltransferase 1 (DGAT1) gene as likely to be causal for the observed variation. Here we provide evidence for additional genetic variability at the same QTL that is associated with milk fat percentage variation within the German Holstein population. Namely, we show that alleles of the DGAT1 promoter derived from the variable number of tandem repeat (VNTR) polymorphism are associated with milk fat content in animals homozygous for the allele 232A at DGAT1. Our results present another example for more than two trait-associated alleles being involved in a major gene effect on a quantitative trait. The segregation of multiple alleles affecting milk production traits at the QTL on BTA14 has to be considered whenever marker-assisted selection programs are implemented in dairy cattle. Due to the presence of a potential transcription factor binding site in the 18mer element of the VNTR, the variation in the number of tandem repeats of the 18mer element might be causal for the variability in the transcription level of the DGAT1 gene.

Acyltransferases↗

PubMed2004

Multiple quantitative trait loci mapping with cofactors and application of alternative variants of the false discovery rate in an enlarged granddaughter design.

The experimental power of a granddaughter design to detect quantitative trait loci (QTL) in dairy cattle is often limited by the availability of progeny-tested sires, by the ignoring of already identified QTL in the statistical analysis, and by the application of stringent experimentwise significance levels. This study describes an experiment that addressed these points. A large granddaughter design was set up that included sires from two countries (Germany and France), resulting in almost 2000 sires. The animals were genotyped for markers on nine different chromosomes. The QTL analysis was done for six traits separately using a multimarker regression that included putative QTL on other chromosomes as cofactors in the model. Different variants of the false discovery rate (FDR) were applied. Two of them accounted for the proportion of truly null hypotheses, which were estimated to be 0.28 and 0.3, respectively, and were therefore tailored to the experiment. A total of 25 QTL could be mapped when cofactors were included in the model-7 more than without cofactors. Controlling the FDR at 0.05 revealed 31 QTL for the two FDR methods that accounted for the proportion of truly null hypotheses. The relatively high power of this study can be attributed to the size of the experiment, to the QTL analysis with cofactors, and to the application of an appropriate FDR.

Animals↗

PubMed2002

Improved confidence intervals in quantitative trait loci mapping by permutation bootstrapping.

The nonparametric bootstrap approach is known to be suitable for calculating central confidence intervals for the locations of quantitative trait loci (QTL). However, the distribution of the bootstrap QTL position estimates along the chromosome is peaked at the positions of the markers and is not tailed equally. This results in conservativeness and large width of the confidence intervals. In this study three modified methods are proposed to calculate nonparametric bootstrap confidence intervals for QTL locations, which compute noncentral confidence intervals (uncorrected method I), correct for the impact of the markers (weighted method I), or both (weighted method II). Noncentral confidence intervals were computed with an analog of the highest posterior density method. The correction for the markers is based on the distribution of QTL estimates along the chromosome when the QTL is not linked with any marker, and it can be obtained with a permutation approach. In a simulation study the three methods were compared with the original bootstrap method. The results showed that it is useful, first, to compute noncentral confidence intervals and, second, to correct the bootstrap distribution of the QTL estimates for the impact of the markers. The weighted method II, combining these two properties, produced the shortest and less biased confidence intervals in a large number of simulated configurations.

Chromosome Mapping↗

PubMedDate not supplied

Combined analysis of data from two granddaughter designs: A simple strategy for QTL confirmation and increasing experimental power in dairy cattle.

A joint analysis of five paternal half-sib Holstein families that were part of two different granddaughter designs (ADR- or Inra-design) was carried out for five milk production traits and somatic cell score in order to conduct a QTL confirmation study and to increase the experimental power. Data were exchanged in a coded and standardised form. The combined data set (JOINT-design) consisted of on average 231 sires per grandsire. Genetic maps were calculated for 133 markers distributed over nine chromosomes. QTL analyses were performed separately for each design and each trait. The results revealed QTL for milk production on chromosome 14, for milk yield on chromosome 5, and for fat content on chromosome 19 in both the ADR- and the Inra-design (confirmed within this study). Some QTL could only be mapped in either the ADR- or in the Inra-design (not confirmed within this study). Additional QTL previously undetected in the single designs were mapped in the JOINT-design for fat yield (chromosome 19 and 26), protein yield (chromosome 26), protein content (chromosome 5), and somatic cell score (chromosome 2 and 19) with genomewide significance. This study demonstrated the potential benefits of a combined analysis of data from different granddaughter designs.

Animals↗

PubMedDate not supplied

A novel method for the estimation of the relative importance of breeds in order to conserve the total genetic variance.

The need for conservation of farm animal genetic resources is widely accepted. A key question is the choice of breeds to be conserved. For this purpose, a core set of breeds was introduced in that the total genetic variance of a hypothetical quantitative trait was maximised (MVT core set). For each breed the relative contribution to the core set was estimated and the breeds were ranked for conservation priority according to their relative contribution. The method was based on average kinships between and within breeds and these can be estimated using genetic marker data. The method was compared to a recently published core set method that maximises the variance of a hypothetical population that could be obtained by interbreeding the conserved breeds (MVO core set). The results show that the MVT (MVO) core set favours breeds with a high (low) within breed kinship that are not related to other breeds. Following this, the MVT core set method suggests conserving breeds that show a large difference in the respective population mean of a hypothetical quantitative trait. This maximises the speed of achieving selection response for this hypothetical selection direction. Additionally, bootstrap based methods for the estimation of the breed's contribution to the core sets were introduced, substantially improving the accuracy of the contribution estimates.

Animals↗