Genetic analysis of mastitis data with different models.

The aim of this study was to analyze different mastitis data sets with different statistical models and compare results. Data recording took place on 3 commercial milk farms with an average herd size of 3,200 German Holstein cows. Recording started in February 1998 and was completed in December 2005. During this period, 63,540 treatments for clinical mastitis were recorded. Five different data sets were analyzed and the number of cows varied between 12,972 and 13,618, depending on the data set. Data collection periods contained either the first 50 or the first 300 d of lactation. When the data-recording period ended after 50 d of lactation, data sets were analyzed with a lactation threshold model (LTM), a multiple threshold lactation model (MTLM), and a test-day threshold model (TDTM). In the LTM analysis, mastitis was treated as a binary trait coded as 0 (no mastitis) or 1 (mastitis), whereas in MTLM mastitis, codes were between 0 and 4, depending on the number of estimated days with mastitis. The TDTM treated each day as a single observation coded similarly to that of the LTM. When the data collection period included the first 300 d of lactation, data sets were analyzed with the LTM or MTLM only, because the TDTM was computationally infeasible. Mastitis frequencies in LTM data sets were 25.8 and 39.2%, and 26.9 and 39.2% in MTLM data sets, when data recording ended after 50 and 300 d of lactation, respectively. The mastitis frequency in the TDTM data set was 5.2%. Respective heritability estimates of liability to clinical mastitis were 0.08 and 0.09 using the LTM, and 0.08 and 0.11 using the MTLM. When the TDTM was used, the estimated heritability was 0.15. Rank correlation between breeding values of the different data sets ranged between 0.40 and 0.97. Rank correlation between the LTM and MTLM were higher (0.78 to 0.97) than those between these 2 models and the TDTM (0.40 to 0.59).The MTLM combined the positive effects of both the LTM, with respect to the size of the data sets, and the TDTM, with respect to the lack of information.

Epistatic analysis of carcass characteristics in pigs reveals genomic interactions between quantitative trait loci attributable to additive and dominance genetic effects.

The present study focused on the identification of epistatic QTL pairs for body composition traits (carcass cut, lean tissue, and fat tissue weights) measured at slaughter weight (140 kg of BW) in a 3-generation full-sib population developed by crossing Pietrain sires with a crossbred dam line. Depending on the trait, phenotypic observations were available for 306 to 315 F(2) animals. For the QTL analysis, 386 animals were genotyped for 88 molecular markers covering chromosomes SSC1, SSC2, SSC4, SSC6, SSC7, SSC8, SSC9, SSC10, SSC13, and SSC14. In total, 23 significant epistatic QTL pairs were identified, with the additive x additive genetic interaction being the most prevalent. Epistatic QTL were identified across all chromosomes except for SSC13, and epistatic QTL pairs accounted for between 5.8 and 10.2% of the phenotypic variance. Seven epistatic QTL pairs were between QTL that resided on the same chromosome, and 16 were between QTL that resided on different chromosomes. Sus scrofa chromosome 1, SSC2, SSC4, SSC6, SSC8, and SSC9 harbored the greatest number of epistatic QTL. The epistatic QTL pair with the greatest effect was for the entire loin weight between 2 locations on SSC7, explaining 10.2% of the phenotypic variance. Epistatic associations were identified between regions of the genome that contain the IGF-2 or melanocortin-4 receptor genes, with QTL residing in other genomic locations. Quantitative trait loci in the region of the melanocortin-4 receptor gene and on SSC7 showed significant positive dominance effects for entire belly weight, which were offset by negative dominance x dominance interactions between these QTL. In contrast, the QTL in the region of the IGF-2 gene showed significant negative dominance effects for entire ham weight, which were largely overcompensated for by positive additive x dominance genetic effects with a QTL on SSC9. The study shows that epistasis is of great importance for the genomic regulation of body composition in pigs and contributes substantially to the variation in complex traits.

The spatial expression pattern of antimicrobial peptides across the healthy bovine udder.

Antimicrobial peptides are key molecules in local host defense. With the aim to better understand the possible involvement of these peptides in the prevention of bovine mastitis, we determined, for the first time to our knowledge, the spatial pattern of constitutive expression of 5 bovine beta-defensins and bovine psoriasin (S100A7) across 5 localizations of the bovine mammary gland applying a quantitative real-time PCR approach. We observed 3 different expression patterns in the healthy udder: 1) constitutive expression of the lingual and tracheal antimicrobial peptides (LAP and TAP), as well that of bovine neutrophil beta-defensins 4 and 10 (BNBD4 and BNBD10), is essentially restricted to the mammary lymph node; 2) bovine beta-defensin 1 (DEFB1) is mainly expressed in the cisternal epithelium and the Rosette of Fürstenberg; 3) strong constitutive mRNA expression of the calcium-binding protein S100A7, which is also known as psoriasin and which has been reported to be highly active against Escherichia coli, was detected in the streak canal. These results indicate a crucial role of S100A7 in the early-stage prevention of coliform mastitis, and the analyzed beta-defensins might be regarded as inducible weapons against already invading pathogens.

Analysis of feed intake and energy balance of high-yielding first lactating Holstein cows with fixed and random regression models.

At the dairy research farm Karkendamm, the individual roughage intake was measured since 1 September 2005 using a computerised scale system to estimate daily energy balances as the difference between energy intake and calculated energy requirements for lactation and maintenance. Data of 289 heifers with observations between the 11th and 180th day of lactation over a period of 487 days were analysed. Average energy-corrected milk yield, feed intake, live weight and energy balance were 31.8kg, 20.6kg, 584 kg and 13.6 MJ NEL (net energy lactation), respectively, per day. Fixed and random regression models were used to estimate repeatabilities, correlations between cow effects and genetic parameters. The resulting genetic correlations in different lactation stages demonstrate that feed intake and energy balance at the beginning and the middle of lactation are genetically different traits. Heritability of feed intake is low with h2=0.06 during the first days after parturition and increases in the middle of lactation, whereas the energy balance shows the highest heritability with h2=0.34 in the first 30 days of lactation. Genetic correlations between energy balance and feed intake and milk yield, respectively, illustrate that energy balance depends more on feed intake than on milk yield. Genetic correlation between body condition score and energy balance decreases rapidly within the first 100 days of lactation. Hence, to avoid negative effects on health and reproduction as consequences of strong energy deficits at the beginning of lactation, the energy balance itself should be measured and used as a selection criterion in this lactation stage. Since the number of animals is rather small for a genetic analysis, the genetic parameters have to be evaluated on a more comprehensive dataset.

Quantitative trait loci for chemical body composition traits in pigs and their positional associations with body tissues, growth and feed intake.

In this study, quantitative trait loci (QTL) for chemical and physical body composition, growth and feed intake in pigs were identified in a three-generation full-sib population, developed by crossing Pietrain sires with a commercial dam line. Phenotypic data from 315 F(2) animals were available for protein and lipid deposition measured in live animals by the deuterium dilution technique at 30-, 60-, 90-, 120- and 140-kg body weight. At 140-kg body weight, carcass characteristics were measured by the AutoFOM grading system and after dissection. Three hundred and eighty-six animals from 49 families were genotyped for 51 molecular markers covering chromosomes SSC2, SSC4, SSC8, SSC9, SSC10 and SSC14. Novel QTL for protein (lipid) content at 60-kg body weight and protein (lipid) accretion from 120 to 140 kg were detected on SSC9 near several previously detected QTL for lean and fat tissue in neck, shoulder and ham cuts. Another QTL for lipid accretion was found on SSC8, closely associated with a QTL for intramuscular fat content. QTL for daily feed intake were detected on SSC2 and SSC10. The favourable allele of a QTL for food conversion ratio (FCR) on SSC2 was associated with alleles for increased lean tissue and decreased fat tissue. Because no QTL for growth rate were found in the region, the QTL for FCR is most likely due to a change in body composition. These QTL provide insights into the genomic regulation of chemical or physical body composition and its association with feed intake, feed efficiency and growth.

Variance component and breeding value estimation for reproductive traits in laying hens using a Bayesian threshold model.

Variance components and breeding values were estimated for 3 reproductive traits in a pure line of White Leghorn laying hens. The traits were proportion of fertile eggs of eggs set, proportion of first quality chicks of eggs set, and proportion of first-quality chicks of fertile eggs. A total of 3,020 hens were tested up to 3 times over a period of 7 d. For the definition of the traits, each egg was scored for each trait either as 0 or 1. To account for the binomial distribution of the data, a Bayesian animal threshold model implemented in a Gibbs sampler was applied that considered the record of each egg set as a repeated observation of the hen. The estimated heritability was 0.067, 0.126, and 0.136 for the traits proportion of fertile eggs of eggs set, proportion of first quality chicks of eggs set, and proportion of first-quality chicks of fertile eggs, respectively, and the SE were small. It was shown that the heritability estimates were substantially higher from their expected values based on linear models. This results in a higher genetic progress and consequently favors the applied Bayesian threshold model for a genetic evaluation of binomial distributed reproductive traits.

Associations of DNA markers with meat quality traits in pigs with emphasis on drip loss.

Phenotypic information on 1155 market pigs for several pig meat quality traits, was collected. Genotypes on 12 DNA markers, including RYR1 and PRKAG3 I199V, were also obtained on all pigs to investigate the relationship between genetic markers and meat quality. The RYR1 gene had the highest impact on meat quality, however, several other markers showed significant effects on one or more traits. Animals heterozygous at the RYR1 locus were significantly inferior in almost all meat quality traits, except ultimate pH value, initial conductivity and redness of the meat. Drip loss from case-ready meat (measured from 1 to 7 days post-mortem) was 43% higher for heterozygotes than animals of the stress resistant genotype. The homozygous genotype II at position I199V of the PRKAG3 locus also resulted in less drip loss than genotypes IV and VV, regardless of the method and time of measurement. Furthermore, the favourable genotype related to higher ultimate pH and darker meat. Both loci significantly affected the intercept, linear and quadratic terms of fitted drip loss development curves. The favourable genotypes showed a lower drip loss after one day of measurement and a slower increase and a more linear development over time. Whilst the RYR1 and PRKAG3 markers influenced numerous meat quality traits, some of the other markers were also found to have significant effects on one or two meat quality traits. Markers at MC4R and HMGA1 loci significantly affected drip loss, whereas LDHA, CAST (Hpy188I) and ATP2A1 influenced pH value. In addition, the marker ATP2A1 was associated with variation in intramuscular fat content in M. longissimus dorsi. GLUT4 affected temperature 45min post-mortem and several markers (MC4R, LDHA, GLUT4, HMGA1, CAST (Hpy188I and PvuII)) influenced one or two of the different colour measurements. The markers at MC4R, CKM, AGRP, PRKAG3, and HMGA1 loci were tested for their interactions with RYR1 regarding drip loss. Only AGRP showed a significant interaction, but this was based on only a few animals with the homozygous genotype for one allele. Our results suggest that genetic markers provide a useful tool to improve meat quality in pigs independently from RYR1, especially the mutation I199V in the PRKAG3 gene.

Genetic parameters for serial, automatically recorded milkability and its relationship to udder health in dairy cattle.

Serial measurements of three milkability traits from two commercial dairy farms in Germany were used to estimate heritabilities and breeding values (BVs). Overall, 6352 cows in first, second and third lactations supplied 2 188 810 records based on daily values recorded from 1998 to 2003. Only the records between day 8 and day 305 after calving were considered. The estimated genetic correlations between different parities within the three milkability traits ranged from rg = 0.88 to 0.98, i.e. they were sufficiently high to warrant a repeatability model. The resulting estimated heritability coefficients were h2 = 0.42 for average milk flow, h2 = 0.56 for maximum milk flow and h2 = 0.38 for milking time. We analysed the genetic correlation between milkability and somatic cell score (SCS) and between milkability and the liability to mastitis, respectively, as the optimum milk flow for udder health is not well defined. There were 66 146 records with information on somatic cell count. Furthermore, 23 488 days of medical treatment for udder diseases were available, resulting in 2 600 302 days of observation in total. Heritabilities for the liability to mastitis, estimated with a test-day threshold model, were h2 = 0.19 and h2 = 0.13, depending on the data-recording period (first 50 days of lactation and first 305 days of lactation, respectively). With respect to the relationship between milkability and udder health, the results indicated a slight and linear correlation insofar as one can assume: the higher the milk flow, the worse the udder health. For this reason, bulls and cows with high BVs for milk flow should be excluded from breeding to avoid a deterioration of udder health. The establishment of a special data-recording scheme for functional traits such as milkability and mastitis on commercial dairy farms may be possible according to these results.

Quantitative trait loci associated with AutoFOM grading characteristics, carcass cuts and chemical body composition during growth of Sus scrofa.

A three-generation full-sib resource family was constructed by crossing two commercial pig lines. Genotypes for 37 molecular markers covering chromosomes SSC1, SSC6, SSC7 and SSC13 were obtained for 315 F2 animals of 49 families and their parents and grandparents. Phenotypic records of traits including carcass characteristics measured by the AutoFOM grading system, dissected carcass cuts and meat quality characteristics were recorded at 140 kg slaughter weight. Furthermore, phenotypic records on live animals were obtained for chemical composition of the empty body, protein and lipid accretion (determined by the deuterium dilution technique), daily gain and feed intake during the course of growth from 30 to 140 kg body weight. Quantitative trait loci (QTL) detection was conducted using least-squares regression interval mapping. Highest significance at the 0.1% chromosome-wise level was obtained for five QTL: AutoFOM belly weight on SSC1; ham lean-meat weight, percentage of fat of primal cuts and daily feed intake between 60 and 90 kg live weight on SSC6; and loin lean-meat weight on SSC13. QTL affecting daily gain and protein accretion were found on SSC1 in the same region. QTL for protein and lipid content of empty body at 60 kg liveweight were located close to the ryanodine receptor 1 (RYR1) locus on SSC6. On SSC13, significant QTL for protein accretion and feed conversion ratio were detected during growth from 60 to 90 kg. In general, additive genetic effects of alleles originating from the Piétrain line were associated with lower fatness and larger muscularity as well as lower daily gain and lower protein accretion rates. Most of the QTL for carcass characteristics were found on SSC6 and were estimated after adjustment for the RYR1 gene. QTL for carcass traits, fatness and growth on SSC7 reported in the literature, mainly detected in crosses of commercial lines x obese breeds, were not obtained in the present study using crosses of only commercial lines, suggesting that these QTL are not segregating in the analysed commercial lines.

The use of a random regression model to account for change in racing speed of German trotters with increasing age.

In a genetic analysis of German trotters, the performance trait racing time per km was analysed by using a random regression model on six different age classes (2-, 3-, 4-, 5- and 6-year-old and older trotters; the age class of 3-year-old trotters was additionally divided by birth months of horses into two seasons). The best-fitting random regression model for the trait racing time per km on six age classes included as fixed effects sex, race track, condition of race track (fitted as second-order polynomial on age), distance of race and each driver (fitted as first-order polynomial on age) as well as the year-season (fitted independent of age). The random additive genetic and permanent environmental effects were fitted as second-order polynomials on age. Data consisted of 138,620 performance observations from 2,373 trotters and the pedigree data contained 9,952 horses from a four-generation pedigree. Heritabilities for racing time per km increased from 0.01 to 0.18 at age classes from 2- to 4-year-old trotters, then slightly decreased for 5 year and substantially decreased for 6-year-old horses. Genetic correlations of racing time per km among the six age classes were very high (rg = 0.82-0.99). Heritability was h2 = 0.13 when using a repeatability animal model for racing time per km considering the six age classes as fixed effect. Breeding values using repeatability analysis over all and within age classes resulted in slightly different ranking of trotters than those using random regression analysis. When using random regression analysis almost no reranking of trotters over time took place. Generally, the analyses showed that using a random regression model improved the accuracy of selection of trotters over age classes.

Characterization of the DGAT1 mutations and the CSN1S1 promoter in the German Angeln dairy cattle population.

The identification of quantitative trait loci (QTL) and genes with influence on milk production traits has been the objective of various mapping studies in the last decade. In the centromeric region of Bos taurus autosome (BTA) 14, the acyl-CoA:diacylglycerol acyltransferase1 gene (DGAT1) has been identified as the most likely causative gene underlying a QTL for milk fat yield and content. Recently, a second polymorphism in the promoter of DGAT1 emerged as an additional source of variation. In this study, the frequencies and the effects of alleles at the DGAT1 K232A and at the DGAT1 promoter variable number of tandem repeat (VNTR) locus on BTA14, and of alleles at the CSN1S1 (alpha(S1)-casein-encoding gene) promoter on BTA6 in the German Angeln dairy cattle population were investigated. Analyzed traits were milk, fat, protein, lactose, and milk energy yield, fat, protein, lactose, and milk energy content and somatic cell score. The lysine variant of the DGAT1 K232A mutation showed significant effects for most of the milk production traits. A specific allele of the DGAT1 promoter VNTR showed significant effects on the traits lactose yield and content, milk energy content, and SCS compared with the other alleles. Additionally, a regulation mechanism between the DGAT1 K232A mutation and the DGAT1 promoter VNTR was found for fat yield and content, which could be caused by an upper physiological bound for the effects of the DGAT1 gene. At the CSN1S1 promoter, 2 of 4 alleles showed significant allele substitution effects on the milk yield traits.

Genetic parameters for health traits and their relationship to different persistency traits in German Holstein dairy cattle.

Data from 3,200 Holstein cows from 3 commercial dairy farms in Germany were used to estimate heritabilities and breeding values for liability to udder diseases (UD), fertility diseases (FD), metabolic diseases (MD), and claw and leg diseases (CLD) using single-trait threshold sire models. A total of 92,722 medical treatments recorded from 1998 to 2003 were included in the analysis. Approximate genetic correlations between persistency of milk yield, fat yield, protein yield, and persistency of milk energy yield and liability to the health traits were calculated based on correlations between EBV. Posterior means of heritability of liability ranged from 0.05 to 0.08 for UD, from 0.04 to 0.07 for FD, from 0.08 to 0.12 for MD, and from 0.04 to 0.07 for CLD. Approximate genetic correlations of the disease traits with the persistency traits were favorable, except for MD in all lactations, which were unfavorable, and UD, which were around zero. Highest correlations in the range of 0.13 to 0.46 were found between the different persistency traits and CLD.

Mapping of quantitative trait loci for lactation persistency traits in German Holstein dairy cattle.

A whole genome scan to map quantitative trait loci (QTL) for persistency of milk yield (PMY), persistency of fat yield (PFY), persistency of protein yield (PPY) and persistency of milk energy yield (PEY) was performed in a granddaughter design in the German Holstein dairy cattle population. The analysis included 16 paternal half-sib families with a total of 872 bulls. The analysis was carried out for the first lactation and for the first three lactations combined using univariate weighted multimarker regression. Controlling the false discovery rate across traits and data sets at a level of 0.15 and treating the four persistency traits as different traits revealed 27 significant QTL. A total of 12 chromosomes showed significant QTL effects on a chromosomewise basis. The DGAT1 effect was highly significant for PPY and protein yield. A haplotype analysis using results of previous studies of the same design revealed a co-segregation of various persistency QTL and QTL affecting health traits like dystocia and stillbirth and functional traits like non-return rate 90 and somatic cell score.

Wrong and missing sire information affects genetic gain in the Angeln dairy cattle population.

In the present study, molecular genetic markers were used to help estimate the degree of wrong sire information in the German Angeln dairy cattle population. Sixteen polymorphic microsatellite markers were genotyped on 5 different paternal half-sib families with a total of 805 daughters. For the genotyping process, blood samples of the daughters and semen samples of the sires were used. Allelic frequencies and exclusion probabilities were estimated. The simultaneous effect of wrong (WSI) and missing sire information (MSI) on the reliability of estimated breeding values and on the genetic gain was investigated using deterministic simulations. For these simulations, different values for the number of daughters per sire, heritability, WSI, and MSI were chosen. The estimated proportion of the WSI was 7% in the German Angeln dairy cattle population. The combined impact of WSI and MSI on the genetic gain was relatively large, especially in the case of small progeny size per sire and low heritability. The impact of WSI was more harmful than MSI on response to selection.

Association between body composition of growing pigs determined by magnetic resonance imaging, deuterium dilution technique, and chemical analysis.

Development of body composition of 440 growing pigs from a three generation full-sib design to identify quantitative trait loci (QTL) was determined by three different methods. Firstly, the non-invasive method deuterium dilution technique (DT), was applied to all pigs in the experiment at six weights 20, 30, 60, 90, 120 and 140kg. Secondly, at each weight class, eight pigs were slaughtered and their entire body chemically analysed (CA). Thirdly, magnetic resonance imaging (MRI) was applied on 16 live pigs at different weights. For the entire empty body (without content of the gastrointestinal tract and bladder), allometric prediction equations to predict body composition from empty body water content measured by DT were derived from chemically analysed serial slaughtered pigs. These equations showed high correlations of 0.92, 0.90 and 0.85 for the contents of body water, fat-free substance as well as protein in fat-free substance, respectively. For the soft tissue (empty body without bones and viscera), allometric prediction equation of body composition based on DT and CA showed correlations of 0.91, 0.88 and 0.82 for water content, fat-free substance, and protein content of fat free substance, respectively. Fat tissue content, fat tissue mass, and lean tissue mass measured by MRI showed allometric relationships to lipid content, lipid mass, and protein mass determined by DT with correlations of 0.98, 0.87, and 0.98, respectively. Lean (measured by MRI) and protein (determined by DT) content of soft tissue was best fitted by a linear-quadratic polynomial and resulted in a correlation of 0.86. Allometric coefficients for change of percentages of chemical components, water (b=-0.036) and protein (b=0.106) in fat-free substance of empty body during growth were similar to those in the literature indicating the consistency of accretion rates of chemical components of the fat-free substance in different studies. Means for protein- and lipid-deposition rates (determined by DT) as well as lean tissue- and fat tissue-deposition rates (measured by MRI) ranged from 95 to 154, 147 to 328, 373 to 420 and 129 to 254g in the different weight ranges. Variation between animals in protein (lean tissue) and lipid (fat tissue) deposition rate was large which can be exploited in order to identify QTL of these traits.

Drip loss of case-ready meat and of premium cuts and their associations with earlier measured sample drip loss, meat quality and carcass traits in pigs.

Drip loss of 374 samples taken from porcine M. longissimus dorsi and M. semimembranosus was measured by using the "bag method" (BM), EZ-DripLoss (EZ-DL) from premium cuts (PC) and in retail tray (case-ready meat; CRM). This provided a comparison between these methods and their relationships to other meat quality and carcass traits. Samples were prepared at 24h post-mortem (pm) and were measured 24 and 48h after preparation (at 48 and 72h pm) using the BM and after 48h (at 72h pm) with the EZ-DL and PC. Drip loss of meat kept in retail trays was measured after 7 days (CRM(7)) and daily within a week (CRM(1-7)). Average drip loss was 1.80% and 3.10% using the BM after 24 and 48h, respectively. EZ-DL and CRM(7) showed higher drip losses of 4.71% and 4.00%. Daily loss of CRM(1-7) showed a concavely shaped curve and increased from 1.57% to 5.64% after 7 days. High correlations were obtained between drip loss of CRM(7) and BM (r=0.88) or the EZ-DL (r=0.91). The development of drip loss in case-ready meat fitted by linear-quadratic regression (y=0.439+1.245x-0.072x(2)) showed that high drip loss measured earlier by bag and EZ-DripLoss methods was highly associated with a high intercept (r=0.63-0.72), a high linear increase (r=0.77-0.81), but larger decrease in increments (r=-0.82 to -0.86) during weekly stored meat in retail trays as supplied at consumer level. Because the positive linear regression coefficient was substantially higher than the negative quadratic regression coefficient, the development of drip loss is mainly dependent on the initial drip loss. Therefore, animals with high drip loss within 72h post-mortem also showed undesirable high drip loss curves over the entire retail period. Relationships between drip loss and other meat quality traits were similar for BM, EZ-DL and CRM(7). Of these the correlation between pH(24) and drip loss was highest with r=-0.54, -0.49 and -0.47 for BM, EZ-DL and CRMH(7), respectively. Interestingly, a correlation of r=-0.35 between blood pH value and CRML(7) was obtained. Carcass traits such as loin, ham, shoulder, belly weight or loin eye area showed only marginal correlations to drip loss. In conclusion, EZ-DL was the most appropriate method to predict drip loss of case-ready meat in retail trays and its development during a 7 day storage period.

Genetic analyses of mastitis data using animal threshold models and genetic correlation with production traits.

In the present study, 6 different mastitis data sets of 3 dairy herds with an overall herd size of 3200 German Holstein cows were analyzed. Data collection periods included the first 50, 100, or 300 d of lactation. The 3 data collection periods were analyzed with a lactation model and a test-day model. All models were animal threshold models. Mastitis frequencies in the lactation model data sets varied between 29 and 45%, and varied between 3 and 6% in the test-day model data sets. Depending on the period of data collection, heritabilities of liability to mastitis in the lactation models were 0.05 (50 d), 0.06 (100 d), and 0.07 (300 d). In the test-day models, heritabilities were slightly higher with values of 0.09 (50 and 100 d), and 0.06 (300 d). Between lactation models, the rank correlations between the relative breeding values were high and varied between 0.86 and 0.94. Rank correlations between the relative breeding values of the test-day models ranged from 0.68 to 0.87. The rank correlations between the relative breeding values of lactation models and test-day models varied from 0.51 and 0.80. Genetic correlations between mastitis and milk production traits were estimated with a linear animal test-day model. The correlations with mastitis were 0.29 (milk yield), 0.30 (fat yield), 0.20 (fat content), 0.34 (protein yield), and 0.20 (protein content). The estimated genetic correlation between mastitis and somatic cell score was 0.84.

Mapping and exclusion mapping of genomic imprinting effects in mouse F2 families.

Parent-of-origin effects were mapped by multimarker regression analysis in a cross between a high body weight selected line (DU6) and a control line (DUKs). The difference between F(2) progeny being heterozygous Qq and qQ (first allele is paternally derived) for grandpaternal Q and grandmaternal q alleles was genome-wide significant for the traits liver weight and spleen weight with a paternal imprinting effect at 1 cM on proximal chromosome 11. Suggestive imprinting effects (chromosome-wide error probability less than 0.05) were found for the traits body weight, liver weight, and kidney weight, and were located on chromosome 14 at 25 cM, 23 cM, and 32 cM, respectively. A genome-wide significant quantitative trait locus (QTL) for spleen weight at 26 cM slightly failed the suggestive significance level for imprinting. The effect was consistently maternal for all these traits on chromosome 14. Further suggestive imprinting effects were found for abdominal fat percentage on chromosome 3, for spleen weight on chromosome 5, and for liver weight on chromosome X. Our results are supported by a likely imprinting in a human genome region with homology to mouse chromosome 14 and agree well with the known imprinting of proximal chromosome 11 in the mouse.