GENOME TRACKING BY UTILIZING HIGH DENSITY SNP-ARRAY TECHNOLOGY FOR STUDIES RELATED TO GENOMIC SELECTION, GENOMIC DYNAMICS, POPULATION GENOMICS, AND, WHOLE GENOME ASSOCIATION

The genetic disposition of most relevant traits in cattle breeding is based on a multitude of genes with small effects. With the advent of molecular biological research in animal breeding the question arose, how genes with an impact on breeding performance could be identified and used for selection in the near future. In the FUGATO-plus GenoTrack project, which is primarily focused on basic research, the enormous progress in the development of Single Nucleotide Polymorphism (SNP) – markers and the availability of efficient high throughput technology for array based genotyping was used to investigate for the first time in detail all elementary aspects of a genome wide study in real animal populations.
The sub-project part of Humboldt-Universit?t zu Berlin covered as initial step the quality control of data from the high throughput genotyping of more than 3000 cattle with the Illumina BovineSNP50 Beadchip, which included the development of a fast remapping procedure for the chip SNPs as a means of updating the SNP positions in the reference genome. Further, haplotype blocks were reconstructed from the SNP for fine mapping of the genomic structure in the Holstein-Frisian cattle breed. They served as basis for association analyses between haplotypes and milk performance traits, which were available as breeding values of elite bulls. Special attention was turned on the identification of genes with influence on the energy balance in dairy cattle, whose regulation decisively determines the fat content of milk. More than one hundred known candidate genes for fat deposition in humans served as starting point for analyzing the corresponding homologous genes in cattle, with respect to potential effects on milk fat content. One third of the conserved genes was located in genomic regions where SNPs showed a significant effect on milk fat content. Among these genes was the gene encoding the Brain Derived Neurotrophic Factor (BDNF). The minor allele form of the most significant SNP showed an additive effect with a difference of more than ten kilogram milk fat between the homozygous genotype classes in average over the first three lactations. Detailed analyses of allele-, geno-, haplo- and diplotypes effects on the milk fat content demonstrated that the phenotypic variance of milk fat content in the population can genetically be better explained by diplotypes than by individual SNP alleles. This result underscores the importance of genomic structures for estimating genomic effects on phenotypes. Analyses of genomic effects on milk performance traits considered at different lactation time points also showed that marker effects on fat and protein content increase during the course of lactation. This suggests that differences in the allele effects of individuals, which are homozygous for the minor or major allele, become more pronounced towards the end of lactation.
Given the hypothesis that genomic regions with above-average extent of heterozygosity could make an important contribution to the fitness of a population, the haplotype diversity at each haplotype block in the cattle genome was quantified. To this end a diversity measure was applied, which originates from ecology. Approximately 1.5% of all haplotype blocks met the criteria required for genomic regions with above-average haplotype diversity. Association analysis showed for 95% of these haplotype blocks significant associations with fitness-related phenotypes. Such functional interrelationships of genes and their encoded proteins make it possible to identify networks, in which genes collectively determine a polygenic phenotype. Methods developed at Humboldt-Universit?t and analyses conducted provide an important contribution in identifying diverse molecular genetic variants with impact on breeding relevant traits.