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New breeding tools for improving mastitis resistance in european dairy cattle


The result is a GUI application for Windows, written in Visual Fortran .NET for predicting the outcome of multiple generation introgression programmes in livestock. In such schemes a target gene from, say, an unimproved strain, is introgressed into an improved breed over a number of generations. Each generation carriers of the target gene are selected and crossed back to the improved breed, until after a pre-determined number of generations the new breed is mated inter-se. Such selection programmes introduce a 'drag' from the unimproved genome about the target gene, a component of which is obligatory and cannot be removed. Throughout the genome diversity is lost during the process leading to inbreeding. The software provides quantitative predictions of the extent of these consequences for populations undergoing this process. Results are obtained through both predictive formulae and simulation according to parameters input by the user determining the size of the scheme, the number of generations planned for the introgression, the size of the genome and the position of the target gene, and the type of selection undertaken. These results are presented both in summary tabular form and graphically as a function of genome position relative to the target gene. Results are also made available as text files.
A QTL affecting clinical mastitis and SCS on BTA9 has been finemapped to a two cM region, providing haplotypes that can predict genetic QTL effects across families in Finish Ayshire, SRB, and Danish Red. Haplotype tests can be used to increase the accuracy of predicting the genetic value of clinical and subclinical mastitis for young bulls and bull dams. As a consequence increased genetic gains in these traits can be obtained. We expect that the haplotype test can predict a haplotype effect in about 30% of a random sample, meaning that for a random animal the test predicts an effect of at least one of its alleles in about 50% of the cases. Given that the observed effect is caused by a single polymorphism, the test can be refined by identifying thatpolymorphism and have predictive ability in 100% of samples. The results are already usable in commercial populations. In February 2006 a patent application on exploiting the test for selective breeding was sent. Exploitation will be sought through the Nordic commercial breeding companies and NAV performing the Nordic breeding value estimation.
Multi trait analysis combining linkage and linkage disequilibrium information has been developed and implemented in a software package. The method can be used to refine position of QTL affecting more than one trait. Also it can help to distinguish between situations where two linked QTL each affect one trait versus a single pleiotropic QTL affecting two or more traits. The program is ready to be used for QTL detection, and the software is freely available for scientific use.
We have mapped a large number of microsatellite and EST/gene markers onto the RH map for BTA9. A total of 161 markers have successfully been mapped onto BTA9. Of these, 61 were from a previous study undertaken within the same laboratory (Williams et al 2002) resulting in approximately 100 new markers added to the RH map since the publication. The first step to building RH maps is to cluster the markers into linkage groups on chromosomes. Markers for the RH map of BTA9 fall into a single LOD4 and LOD 6 linkage groups spanning the whole chromosome of BTA9. The linkage groups were identified using Carthagene and were robust for LOD4 and LOD6 (data not shown). This maps allows for fine positioning of important markers. Generally linkage maps allow good positioning of markers over a large area within the chromosome, however, RH maps allow for reliable marker placement over shorter distances, particularly important for fine mapping of QTLs. A high-density linkage map for BTA9 has been created by integrating new information from the MASTITIS RESISTANCE project RH map, bovine genome sequence and project linkage data. Some genotyped markers were discarded from the final linkage maps because either there was not enough linkage information to determine their linkage position unambiguously and they have not been mapped by any other method or because they gave high number of recombination events at any of the proposed positions (which may indicate undetected genotyping errors or null alleles). The most reliable map consists of 59 markers with the total map length being 97.7cM.
Random regression models combining linkage and linkage disequilibrium information has been developed and implemented in a software package. The method can be used to identify QTL with non constant effects over time/stage of lactation or other gradients the QTL effects may interact with. If the interactions are strong the power of detection may increase substantially, and more information on the QTL effect can be revealed. The program is ready to be used for QTL detection. The software is freely available for scientific use.
Mapping resolution is determined by the number of meioses (number of recombinants) available. Rather than producing a large number of offspring, which is laborious and expensive, it is much more efficient to make use of historical recombinations. Utilising such linkage disequilibrium (LD) information has been successfully applied to the fine-scale mapping of human diseases. The idea behind LD mapping is that if a marker is sufficiently closely linked to the disease gene, there have been no recombinations between the original marker allele and the mutation that introduced the disease. Hence, an association between a marker allele and the disease, i.e. LD, indicates that the disease is close to this marker. Thus, LD mapping uses all historical recombination events that have occurred since the original mutation, while linkage analysis (such as interval mapping) only utilises recombinations within the data set under study. LD has also been suggested for high resolution mapping of QTL found in a genome wide scan. Recently, the combination of LD and linkage analysis information, has been shown to be even more powerful for fine scale mapping of QTL, narrowing down gene positions to approximately 1 cM. The current project has built on this expertise, extended and tested the statistical method for practical use. In order for the method to be used efficiently on real data in the current project, several functionalities have been improved. Methods were developed to calculate IBD probabilities taking into account the family structure and the mixture of breeds included in the study. Functionality was added to the IBD-DMU package, allowing for haplotype reconstruction, missing markers and null alleles. When possible a null-allele is considered a normal allele and given an identifier, so that even in the presence of null-alleles some more information with regard to haplotype IBD probabilities can be gleaned. Further the method used for the construction of the IBD matrix needed verification. The finemapping methods used are based on a matrix of IBD probabilities conditional on the haplotype similarities. These are based on pairwise comparisons of all founder haplotypes and the resulting matrix is therefore most often non-positive definite and cannot be inverted as required. Therefore the matrix must be manipulated somehow, for which several strategies can be used. Another challenge is the large number of haplotypes to be considered. The size of the matrix changes quadratically with the number of haplotypes per QTL locus. Especially in large experiments or in a commercial setting LDLA analysis will demand more computer resources then are readily available. A number of ways to cluster haplotypes and bend the resulting LD matrix or ignore off diagonals between clusters were programmed. An average-linkage hierarchical cluster analysis (Anderberg, 1973) was used to cluster haplotypes according to IBD probabilities in a similarity clustering.
We have mapped a large number of microsatellite and EST/gene markers onto the RH map for BTA11. There are now 138 markers on BTA11 with approximately 100 new markers, added since Williams in 2002, which at LOD 4 the linkage group spans the whole chromosome while at LOD 6 the linkage group is split. This map allows for fine positioning of important markers. Generally linkage maps allow good positioning of markers over a large area within the chromosome, however, RH maps allow for reliable marker placement over shorter distances, particularly important for fine mapping of QTLs. A total of 38 markers were included in the linkage map of BTA11 of 85.1 cM. Two alternative linkage maps were constructed, because there were discrepancies between map orders estimated from the project data, the MARC linkage map, project RH map and the bovine genome sequence (Btau 2.0; in the targeted region.
We have produced radiation hybrid (RH) maps for BTA9 and BTA11. The RH maps produced by this project are the most concise produced for BTA9 AND BTA11 to date. In addition to RH maps we also thought it important to create contig maps of BTA9 and BTA11. These maps underpin detailed construction of the bovine chromosome at a fine scale. To date the sequence has a 6X coverage (although unpublished to date) although the true coverage along with the reliability of the build means that although the genome has been sequenced there are a number of problems with the sequence. (i) As with the human chromosome the bovine genome contains a large number of gaps between areas of sequence. These gaps are of particular importance when it comes to the positioning of markers as a gap is usually unknown and may be given a fixed size i.e. 10,000bp when in fact in reality the gap could be a hundred fold greater or a hundred fold less than this.(ii) Not only are the gaps a problem but also the orientation of the scaffolds is often incorrect due to the lack of information concerning the sequence and the large gaps in the genome sequence mentioned previously. The contig maps for BTA9 and BTA11 were developed by comparing the contig information to the bovine genome sequence and producing an output that would allow identification of areas within the chromosomes that may be prone to sequence assembly error. This review process combined with the RH maps for yet finer scale mapping yields a more precise and more reliable assembly of the sequence. This is essential for fine scale mapping of QTL.

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