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Collaborative project: FUGATO-plus - GenoTrack - high-throughput SNP typing for genomic selection in cattle, association studies and population genetic analysis of the bovine genome; Subproject University of Göttingen

Project

Production processes

This project contributes to the research aim 'Production processes'. Which funding institutions are active for this aim? What are the sub-aims? Take a look:
Production processes


Project code: 0315134C
Contract period: 01.03.2008 - 28.02.2011
Budget: 273,746 Euro
Purpose of research: Basic research

The enormous progress in the development and chip-based representation of SNP markers in conjunction with the establishment of efficient high throughput genotyping platforms allowing complete on large animal figures. The wealth of genomic information opens up new and hitherto unimagined possibilities for the exploration of the bovine genome and in particular allows direct access to the genetic variation of quantitative traits. The joint project GenoTrack provides carefully selected groups of animals of different breeds of cattle to 54,000 SNPs typisieren and using this information to pursue different issues. In the center of this new structural approaches is the description of the genetic architecture in the form of Haplotypinventaren of individual populations. The estimate of the effects of these haplotypes on the performance characteristics and health leads on to the individual animal related summary look at genomic breeding values. This genomic breeding values can already at the time of the birth of an animal be calculated very early and enable accurate selection decisions, the breeding progress substantially increase. In addition chromosome segments can be identified who are in their population genetic characteristics (eg Homozygotiegrad) significantly from the total genome differ. It can be new dimensions for inbreeding and genetic diversity derived. Comparisons of the high resolution of species across genomes give any hints on evolutionary effective mechanisms, particularly for fitness characteristics could be significant. Moreover, with the help of the dense genome-wide marker coverage association studies between the SNP and putative causal variants are carried out. These are appropriate test statistics developed from the large number of expected significant results to estimate the determination and the exclusion of false positive signals guarantee.

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