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Improvement of milk production traits in dairy sheep is required to increase the competitiveness of the industry and to maintain the production of high quality cheese in regions of Mediterranean countries with less favourable conditions. Additional improvement over classical selection could be reached if genes with significant effects on the relevant traits were specifically targeted by selection. However, so far, few studies have been undertaken to detect quantitative trait loci (QTL) in dairy sheep. In this study, we present a complete genome scan performed in a commercial population of Spanish Churra sheep to identify chromosomal regions associated with phenotypic variation observed in milk production traits. Eleven half-sib families, including a total of 1213 ewes, were analysed following a daughter design. Genome-wise multi-marker regression analysis revealed a genome-wise significant QTL for milk protein percentage on chromosome 3. Eight other regions, localized on chromosomes 1, 2, 20, 23 and 25, showed suggestive significant linkage associations with some of the analysed traits. To our knowledge, this study represents the first complete genome scan for milk production traits reported in dairy sheep. The experiment described here shows that analysis of commercial dairy sheep populations has the potential to increase our understanding of the genetic determinants of complex production-related traits. [ABSTRACT FROM AUTHOR]

Fourteen microsatellite markers with a coverage of 63.5 cM on bovine chromosome 6 were selected, and 26 sire families with 2,260 daughters were analyzed for mapping quantitative trait loci (QTL) affecting 5 milk production traits in a Chinese Holstein population. In the analyses across 26 families and within the largest significant families with a one-QTL model fitted, a QTL near BMS470 was detected that affected fat yield at the 5% experiment-wide significance level. When a 2-QTL model was fitted in the across-family analysis, it was found that there might exist 2 QTL affecting the 3 yield traits, although the exact or empirical thresholds for the significance testing were unknown. In all analyses, the results for milk yield and protein yield were generally consistent, which might have resulted from the same genetic background for milk and protein yield. [ABSTRACT FROM AUTHOR]

A Chinese Holstein population with daughter design was analyzed using 14 microsatellites covering a map distance of 557 cM on chromosome 6 to fine map QTL for five milk production traits. 26 paternal half-sib families with 2356 daughters were involved. Two different approaches, linear regression approach and variance component approach, were employed, with a one-QTL model and two-QTL model fitted. With a one-QTL model, the linear regression approach revealed a QTL near BMS470 with effects on milk yield, fat yield, protein yield, and fat percentage, and another QTL near BMS2460 for protein percentage. The variance component approach confirmed the results of linear regression approach for the three yield traits, with the exception that the QTL for fat yield was mapped to a different position near BMS1242. The 95% confidence intervals resulted from linear regression, obtained by bootstrapping, were generally large, ranging from 31 to 53 cM, whereas the variance component approach revealed very small confidence intervals, calculated by LOD drop-off method, for the three yield traits, only 4-5 cM. With a two-QTL model, both approaches provided strong evidence for the existence of two QTLs for the three yield traits. Along with the QTLs identified in one-QTL model analyses, the linear regression approach revealed a second QTL near BP7 with effects on all the three yield traits, whereas the variance component approach located the second QTL near ILSS035, BMS470, and BP7 for the three traits, respectively. [ABSTRACT FROM AUTHOR]

Eleven Israeli Holstein families including 5221 cows were analyzed by a daughter design for eight economic traits: milk, fat and protein production, fat and protein percentage, somatic cell score (SCS), herd-life, and female fertility. The cows were genotyped for 73 microsatellites with maximum spacing between markers of 53 cM. There were 86,304 informative genotypes. Preliminary analysis was by ANOVA of each trait, with the marker effect nested within sire. Significance was determined by controlling the false discovery rate at 0.4, after excluding markers with genome-wide significance for at least a single trait, and traits without any significant effects at this level. Thus, four markers on chromosomes 6 and 14 and female fertility were excluded. There remained 40 significant marker-trait combinations, and it is expected that 24 of these are true effects. To perform interval mapping for the families with significant contrasts, 21 additional markers were genotyped on chromosomes 2, 7, and 27. The bootstrap confidence intervals for gene effect did not include zero for protein percent on chromosome 2 and fat yield, protein yield, and SCS on chromosome 7. Quantitative trait locus heterozygosity was 33%, which is consistent with the hypothesis that only two alleles are segregating with unequal allele frequency. [ABSTRACT FROM AUTHOR]