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beta-Carotene biochemistry is a fundamental process in mammalian biology. Aberrations either through malnutrition or potentially through genetic variation may lead to vitamin A deficiency, which is a substantial public health burden. In addition, understanding the genetic regulation of this process may enable bovine improvement. While many bovine QTL have been reported, few of the causative genes and mutations have been identified. We discovered a QTL for milk beta-carotene and subsequently identified a premature stop codon in bovine beta-carotene oxygenase 2 (BCO2), which also affects serum beta-carotene content. The BCO2 enzyme is thereby identified as a key regulator of beta-carotene metabolism.

When a genetic marker and a quantitative trait locus (QTL) are in linkage disequilibrium (LD) in one population, they may not be in LD in another population or their LD phase may be reversed. The objectives of this study were to compare the extent of LD and the persistence of LD phase across multiple cattle populations. LD measures r and r(2) were calculated for syntenic marker pairs using genomewide single-nucleotide polymorphisms (SNP) that were genotyped in Dutch and Australian Holstein-Friesian (HF) bulls, Australian Angus cattle, and New Zealand Friesian and Jersey cows. Average r(2) was approximately 0.35, 0.25, 0.22, 0.14, and 0.06 at marker distances 10, 20, 40, 100, and 1000 kb, respectively, which indicates that genomic selection within cattle breeds with r(2) >or= 0.20 between adjacent markers would require approximately 50,000 SNPs. The correlation of r values between populations for the same marker pairs was close to 1 for pairs of very close markers (<10 kb) and decreased with increasing marker distance and the extent of divergence between the populations. To find markers that are in LD with QTL across diverged breeds, such as HF, Jersey, and Angus, would require approximately 300,000 markers.

Twenty Dutch Holstein-Friesian families, with a total of 715 sires, were evaluated in a granddaughter experiment design for marker-QTL associations. Five traits-milk, fat and protein yield and fat and protein percent-were analyzed. Across-family analysis was undertaken using multimarker regression principles. One and two QTL models were fitted. Critical values for the test statistic were calculated empirically by permuting the data. Individual trait distributions of permuted test statistics differed and, thus distributions, had to be calculated for each trait. Experimentwise critical values, which account for evaluating marker-QTL associations on all 29 autosomal-bovine chromosomes and for five traits, were calculated. A QTL for protein percent was identified in one, and two QTL models and was significant at the 1 and 2% level, respectively. Extending the multimarker regression approach to an analysis including two QTL was limited by families not being informative at all markers, which resulted in singularity. Below average heterozygosity for the first and last marker lowered information content for the first and last marker bracket. Highly informative markers at the ends of the mapped chromosome would overcome the decrease in information content in the first and last marker bracket and singularity for the two QTL model.