Now showing 1 - 2 of 2
  • Publication
    Genome Structure in Australian Holstein Friesian Cattle Revealed by Combined Analysis of Three High Density SNP Panels
    (Association for the Advancement of Animal Breeding and Genetics (AAABG), 2009)
    Khatkar, M S
    ;
    ;
    Hobbs, M
    ;
    Khatkar, D
    ;
    Cavanagh, J A L
    ;
    ;
    Moser, G
    ;
    Raadsma, H W
    We genotyped overlapping samples of Australian dairy bulls using three different SNP chips (15k, 25k and 54k). These chips have different but complementary coverage hence increasing the number of animals and the density and coverage of SNPs to 74k in a combined dataset. A combined analysis of the data from these three SNP chips showed a four fold increase in the coverage of the genome by haplotype blocks over bovine hapmap reported previously (Khatkar et al. 2007). An analysis of contiguous runs of homozygosity revealed long stretches (up to 49.39 Mb) of homozygosity on chromosome 1 in many bulls. Distribution of these segments of homozygosity in a sample of bulls is presented. The results for one chromosome are described in detail.
  • Publication
    Genome wide association studies in dairy cattle using high density SNP scans
    (Association for the Advancement of Animal Breeding and Genetics (AAABG), 2009)
    Raadsma, H W
    ;
    Khatkar, M S
    ;
    Moser, G
    ;
    Hobbs, M
    ;
    ;
    Cavanagh, J A L
    ;
    Use of high density Single Nucleotide Polymorphic (SNP) marker information allows for prediction of genetic merit via genome wide selection and for localization of markers in gene regions of biological interest through Genome Wide Association Studies (GWAS). We report on a replicated GWAS in dairy cattle using 1,945 progeny tested bulls genotyped with three high density SNP panels representing 63,678 informative SNP. Single SNP genotypes were analysed against deregressed EBV for protein percent and fat percent using a mixed linear model accounting for SNP and animal polygenic effects. The 127,356 analyses (63,678 informative SNP by two traits) across the two data sets identified 143 and 87 significant (P<0.05, corrected for False Discovery Rate) associations for protein % in data set 1 and 2 respectively, whilst for fat % 102 and 61 significant associations were identified in the two data sets respectively. Outputs from selected SNP analyses are discussed for significance and pleiotropic effects and compared against integrated QTL meta-assembly from public domain studies.