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Inflammation of the mammary gland following bacterial infection, commonly known as mastitis, affects all mammalian species. Although the aetiology and epidemiology of mastitis in the dairy cow are well described, the genetic factors mediating resistance to mammary gland infection are not well known, due in part to the difficulty in obtaining robust phenotypic information from sufficiently large numbers of individuals. To address this problem, an experimental mammary gland infection experiment was undertaken, using a Friesian-Jersey cross breed F2 herd. A total of 604 animals received an intramammary infusion of Streptococcus uberis in one gland, and the clinical response over 13 milkings was used for linkage mapping and genome-wide association analysis. A quantitative trait locus (QTL) was detected on bovine chromosome 11 for clinical mastitis status using micro-satellite and Affymetrix 10 K SNP markers, and then exome and genome sequence data used from the six F1 sires of the experimental animals to examine this region in more detail. A total of 485 sequence variants were typed in the QTL interval, and association mapping using these and an additional 37 986 genome-wide markers from the Illumina SNP50 bovine SNP panel revealed association with markers encompassing the interleukin-1 gene cluster locus. This study highlights a region on bovine chromosome 11, consistent with earlier studies, as conferring resistance to experimentally induced mammary gland infection, and newly prioritises the IL1 gene cluster for further analysis in genetic resistance to mastitis.

The objective of this study was to estimate heritability and crossbreeding parameters (breed and heterosis effects) of various fatty acid (FA) concentrations in milk fat of New Zealand dairy cattle. For this purpose, calibration equations to predict concentration of each of the most common FAs were derived with partial least squares (PLS) using mid-infrared (MIR) spectral data from milk samples (n=850) collected in the 2003-04 season from 348 second-parity crossbred cows during peak, mid and late lactation. The milk samples produced both, MIR spectral data and concentration of the most common FAs determined using gas chromatography (GC). The concordance correlation coefficients (CCC) between the concentration of a FA determined by GC and the PLS equation ranged from 0.63 to 0.94, suggesting that some prediction equations can be considered to have substantial predictive ability. The PLS calibration equations were then used to predict the concentration of each of the fatty acids in 26,769 milk samples from 7385 cows that were herd-tested during the 2007-08 season. Data were analysed using a single-trait repeatability animal model. Shorter chain FA (16:0 and below) were significantly higher (P<0.05) in Jersey cows, while longer chain, including unsaturated longer chain FA were higher in Holstein-Friesian cows. The estimates of heritabilities ranged from 0.17 to 0.41 suggesting that selective breeding could be used to ensure milk fat composition stays aligned to consumer, market and manufacturing needs.