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Title:   Author  item
                                            Wiggans, Georgeitem
                                            Sonstegard, Taditem
                                            Vanraden, Paulitem
                                            MATUKUMALLI, L - GEORGE MASON UNIVitem
                                            SCHNABEL, R - UNIV OF MISSOURIitem
                                            TAYLOR, J - UNIV OF MISSOURIitem
                                            SCHENKEL, F - UNIV OF GUELPHitem
                                            Van Tassell, Curtis

                                                         - *Curt*
  Submitted to: Journal of Dairy Science
                                    Publication Type: Abstract Only
                                    Publication Acceptance Date: 2/25/2008
                                    Publication  Date: 7/11/2008
                                    Citation: Wiggans, G.R., Sonstegard, T.S., Van Raden, P.M., Matukumalli, L.K., Schnabel, R.D., Taylor, J.F., Schenkel, F.S., Van Tassell, C.P. 2008. Selection of single nucleotide polymorphisms and genotype quality for genomic prediction of genetic merit in dairy cattle. Journal of Dairy Science. 91(E-Suppl. 1):507(abstr. 524).Interpretive Summary:
                                Technical Abstract: A process to prepare high-density genotypic data for use in genomic prediction of genetic merit was developed. Marker genotypes from over 51,000 single nucleotide polymorphisms (SNP) were generated for 3,139 Holstein bulls on the Illumina Bovine SNP50TM chip. The SNP were categorized by minor allele frequency (MAF); 10,249 SNP with MAF <5% were excluded. The number of SNP for each MAF (45 groups, =0.05 to =0.5) was uniform (800 to 1,009). Hardy-Weinberg equilibrium was assessed by comparing observed to expected heterozygosity for each locus. For 6 SNP assigned to chromosome 7, no bulls were heterozygous, which confirms the latest assembly that places these SNP on the X chromosome.  Observed heterozygosity was within 2% of the expected value for 96% of SNP. Next, we analyzed linkage between adjacent SNP to reduce the dataset for downstream analysis.  For 1,237 pairs of adjacent autosomal SNP, each bull was homozygous or heterozygous for both marker genotypes (<10 bulls differed), so the first SNP from each pair was excluded; mean physical distance between these SNP pairs was much smaller (37 kb) than mean distance between 39,386 autosomal SNP (64 kb). Sire and son data for 2,566 bulls with 204 genotyped sires were compared to validate sample identification and Mendelian inheritance. For those bulls with greater than 100 inheritance errors, the correct sire was determined through comparison to the other sires of sons. For sons with the correct sire, 99.99% of the SNP with genotypes did not conflict. Comparison of genomic and pedigree relationships detected three members of a clonal family, a set of identical twins, and some possible pedigree errors. Genotyping consistency was investigated for nine bulls genotyped twice and for the twins and clones. Most of the few differences were caused by absence of genotypic data in one of the paired genotypes; however, one clone had 24 SNP conflicts (99.94% concordance). Evaluation of this SNP set is ongoing; however, we expect that the final SNP list will contain only minor changes from the current list. In summary, we generated the largest set of high-quality SNP data in Holsteins, and this data set should provide the basis for successful prediction of genetic merit.


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