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Although numerous quantitative trait loci (QTL) mapping studies involving milk protein percent (PP), milk yield (MY), and protein yield (PY) have been carried out, there has not been any systematic evaluation of the effects of individual QTL on these 3 interrelated traits. Consequently, the aim of the present study was to investigate the effects on MY and PY of QTL for PP previously mapped in various laboratories. The study, based on selective DNA pooling of milk samples, included 10 Israeli Holstein artificial insemination bulls, each the sire of 1,800 or more milk-recorded daughters. For each sire-trait combination across the 10 sires, milk samples of the highest and lowest daughters with respect to estimated breeding values for PP, PY, and MY were collected for pooling. A total of 134 dinucleotide microsatellites distributed over 25 bovine autosomes were used. An empirical standard error for marker-QTL linkage testing was calculated based on the variation among split samples within the same tail. Threshold comparison-wise error rate P-values were set to control proportion of false positives at P = 0.10 level for declaring significant effects at the marker-trait level. Estimates of the number of true null hypotheses for each trait were obtained from the histogram of marker comparison-wise error rate P-values. Based on these estimates, effective power of the experiment at the marker-trait level was estimated as 0.75, 0.41, and 0.73 for PP, PY, and MY. The proportion of heterozygosity at the QTL was estimated as 0.46, 0.39, and 0.40, respectively. After correcting for incomplete power and proportion of false positives, it was estimated that 38.7 and 37.5% of the markers affecting PP and MY, respectively, also affected PY. Of the markers affecting PY, 68.9 and 76.5%, respectively, also affected PP and MY. Apparently, none of the significant markers affected PY exclusively, and only 6.5 and 16.0%, respectively, affected PP or MY exclusively. Thus, almost all significant markers, and by inference almost all QTL, had effects on at least 2 of the 3 traits. [ABSTRACT FROM AUTHOR]

Mastitis is an important and common dairy cattle disease affecting milk yield, quality, and consumer safety as well as cheese yields and quality. Animal welfare and residues of the antibiotics used to treat mastitis cause public concern. Considerable genetic variation may allow selection for increased resistance to mastitis. Because of high genetic correlation to milk somatic cell score (SCS), SCS can serve as a surrogate trait for mastitis resistance. The present study intended to identify quantitative trait loci (QTL) affecting SCS in Israeli and Italian Holstein dairy cattle (IsH and ItH, respectively), using selective DNA pooling with single and multiple marker mapping. Milk samples of 4,788 daughters of 6 IsH and 7 ItH sires were used to construct sire-family high- and low-tail pools, which were genotyped at 123 (IsH) and 133 (ItH) microsatellite markers. Shadow correction was used to obtain pool allele frequency estimates. Frequency difference between the tails and empirical standard error of D, SE(D), were used to obtain P-values. All markers significant by single marker mapping were also significant by multiple marker mapping, but not vice versa. Combining both populations, 22 QTL on 21 chromosomes were identified; all corresponded to previous reports in the literature. Confidence intervals were set by chi-squared drop method. Heterozygosity of QTL was estimated at 44.2%. Allele substitution effects ranged from 1,782 to 4,930 cells/mL in estimated breeding value somatic cell count units. Most (80%) of the observed variation in estimated breeding value somatic cell score could be explained by the QTL identified under the stringent criteria. The results found here can be used as a basis for further genome-wide association studies for the same trait., (Copyright © 2010 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Fibroblast growth factor 2 (FGF2) is expressed in the bovine mammary gland and may play a role in the development and reorganization of the mammary gland. It is also expressed by the uterine endometrium throughout the estrous cycle and early pregnancy. The FGF2 was chosen for this study because it regulates the expression of interferon-tau, a key member of the signal transduction pathway involved in milk production. In previous studies, we reported the association of several genes in this pathway with milk production and health traits in dairy cattle. The objective of this study was to examine the association of FGF2 polymorphisms with milk composition, somatic cell score, and productive life in 3 Holstein cattle populations from the United States and Israel. The pooled DNA sequencing approach was used to identify single nucleotide polymorphisms (SNP) in FGF2. Sequencing of a total of 6.4 kb including 3 exons of the gene revealed only one SNP (A/G) in intron 1 at position 11646. This SNP was investigated for association with production traits in 2,773 individuals from 3 Holstein populations: the granddaughter-design Cooperative Dairy DNA Repository and the daughter-design University of Wisconsin populations from the United States and a daughter-design population from Israel. For both the Israeli and the UW populations, FGF2 variants were associated with fat yield and percentage, somatic cell score, and productive life with significant dominance and complete dominance effects. For the Cooperative Dairy DNA Repository population, no significant associations were observed for the examined traits. Given that FGF2 was chosen for this study because of its role in the interferon-tau signal transduction pathway and was found to be associated with production traits, results suggest that the candidate pathway could be an attractive strategy to search for candidate quantitative trait genes.

Selective DNA pooling was employed in a daughter design to screen all bovine autosomes for quantitative trait loci (QTL) affecting estimated breeding value for milk protein percentage (EBVP%). Milk pools prepared from high and low daughters of each of seven sires were genotyped for 138 dinucleotide microsatellites. Shadow-corrected estimates of sire allele frequencies were compared between high and low pools. An adjusted false discovery rate (FDR) method was employed to calculate experimentwise significance levels and empirical power. Significant associations with milk protein percentage were found for 61 of the markers (adjusted FDR = 0.10; estimated power, 0.68). The significant markers appear to be linked to 19--28 QTL. Mean allele substitution effects of the putative QTL averaged 0.016 (0.009--0.028) in units of the within-sire family standard deviation of EBVP% and summed to 0.460 EBVP%. Overall QTL heterozygosity was 0.40. The identified QTL appear to account for all of the variation in EBVP% in the population. Through use of selective DNA pooling, 4400 pool data points provided the statistical power of 600,000 individual data points.

"Selective DNA pooling" accomplishes quantitative trait locus (QTL) mapping through densitometric estimates of marker allele frequencies in pooled DNA samples of phenotypically extreme individuals. With poly(TG) microsatellites, such estimates are confounded by "shadow" ("stutter") bands. A correction procedure was developed on the basis of an observed linear regression between shadow band intensity and allele TG repeat number. Using this procedure, a selective DNA pooling study with respect to milk protein percentage was implemented in Israel-Holstein dairy cattle. Pools were prepared from milk samples of high and low daughters of each of seven sires and genotyped with respect to 11 markers. Highly significant associations with milk protein percentage were found for 5 of the markers; 4 of these markers confirmed previous reports. Selective DNA pooling accessed 80.6 and 48.3%, respectively, of the information that would have been available through individual selective genotyping or total population genotyping. In effect, the statistical power of 45,600 individual genotypings was obtained from 328 pool genotypings. This methodology can make genome-wide mapping of QTL accessible to moderately sized breeding organizations.