Genome-wide association scan suggests basis for microtia in Awassi sheep.

Hereditary underdevelopment of the ear, a condition also known as microtia, has been observed in several sheep breeds as well as in humans and other species. Its genetic basis in sheep is unknown. The Awassi sheep, a breed native to southwest Asia, carries this phenotype and was targeted for molecular characterization via a genome-wide association study. DNA samples were collected from sheep in Jordan. Eight affected and 12 normal individuals were genotyped with the Illumina OvineSNP50(®) chip. Multilocus analyses failed to identify any genotypic association. In contrast, a single-locus analysis revealed a statistically significant association (P = 0.012, genome-wide) with a SNP at basepair 34 647 499 on OAR23. This marker is adjacent to the gene encoding transcription factor GATA-6, which has been shown to play a role in many developmental processes, including chondrogenesis. The lack of extended homozygosity in this region suggests a fairly ancient mutation, and the time of occurrence was estimated to be approximately 3000 years ago. Many of the earless sheep breeds may thus share the causative mutation, especially within the subgroup of fat-tailed, wool sheep.

Identification of quantitative trait loci affecting resistance to gastrointestinal parasites in a double backcross population of Red Maasai and Dorper sheep.

A genome-wide scan for quantitative trait loci (QTL) affecting gastrointestinal nematode resistance in sheep was completed using a double backcross population derived from Red Maasai and Dorper ewes bred to F(1) rams. This design provided an opportunity to map potentially unique genetic variation associated with a parasite-tolerant breed like Red Maasai, a breed developed to survive East African grazing conditions. Parasite indicator phenotypes (blood packed cell volume - PCV and faecal egg count - FEC) were collected on a weekly basis from 1064 lambs during a single 3-month post-weaning grazing challenge on infected pastures. The averages of last measurements for FEC (AVFEC) and PCV (AVPCV), along with decline in PCV from challenge start to end (PCVD), were used to select lambs (N = 371) for genotyping that represented the tails (10% threshold) of the phenotypic distributions. Marker genotypes for 172 microsatellite loci covering 25 of 26 autosomes (1560.7 cm) were scored and corrected by Genoprob prior to qxpak analysis that included Box-Cox transformed AVFEC and arcsine transformed PCV statistics. Significant QTL for AVFEC and AVPCV were detected on four chromosomes, and this included a novel AVFEC QTL on chromosome 6 that would have remained undetected without Box-Cox transformation methods. The most significant P-values for AVFEC, AVPCV and PCVD overlapped the same marker interval on chromosome 22, suggesting the potential for a single causative mutation, which remains unknown. In all cases, the favourable QTL allele was always contributed from Red Maasai, providing support for the idea that future marker-assisted selection for genetic improvement of production in East Africa will rely on markers in linkage disequilibrium with these QTL.

Integrating geo-referenced multiscale and multidisciplinary data for the management of biodiversity in livestock genetic resources.

In livestock genetic resource conservation, decision making about conservation priorities is based on the simultaneous analysis of several different criteria that may contribute to long-term sustainable breeding conditions, such as genetic and demographic characteristics, environmental conditions, and role of the breed in the local or regional economy. Here we address methods to integrate different data sets and highlight problems related to interdisciplinary comparisons. Data integration is based on the use of geographic coordinates and Geographic Information Systems (GIS). In addition to technical problems related to projection systems, GIS have to face the challenging issue of the non homogeneous scale of their data sets. We give examples of the successful use of GIS for data integration and examine the risk of obtaining biased results when integrating datasets that have been captured at different scales.

Objectives, criteria and methods for using molecular genetic data in priority setting for conservation of animal genetic resources.

The genetic diversity of the world's livestock populations is decreasing, both within and across breeds. A wide variety of factors has contributed to the loss, replacement or genetic dilution of many local breeds. Genetic variability within the more common commercial breeds has been greatly decreased by selectively intense breeding programmes. Conservation of livestock genetic variability is thus important, especially when considering possible future changes in production environments. The world has more than 7500 livestock breeds and conservation of all of them is not feasible. Therefore, prioritization is needed. The objective of this article is to review the state of the art in approaches for prioritization of breeds for conservation, particularly those approaches that consider molecular genetic information, and to identify any shortcomings that may restrict their application. The Weitzman method was among the first and most well-known approaches for utilization of molecular genetic information in conservation prioritization. This approach balances diversity and extinction probability to yield an objective measure of conservation potential. However, this approach was designed for decision making across species and measures diversity as distinctiveness. For livestock, prioritization will most commonly be performed among breeds within species, so alternatives that measure diversity as co-ancestry (i.e. also within-breed variability) have been proposed. Although these methods are technically sound, their application has generally been limited to research studies; most existing conservation programmes have effectively primarily based decisions on extinction risk. The development of user-friendly software incorporating these approaches may increase their rate of utilization.

Use of linked loci as individuals or haplotypes for marker-assisted breed assignment.

The objective of this study was to use simulation to evaluate the benefits of considering haplotypes of loci when linked single nucleotide polymorphisms are used for breed assignment. Three breeds of 10,000 females each were simulated under eight scenarios that differed according to the number of generations separating the breeds, size of breed founder populations and recombination rate between linked loci. Molecular genotypes consisted of 20 groups of three linked loci each. Breed assignment was performed in the final generation and was based on the frequency method. Haplotypes were reconstructed using the expectation-maximization algorithm. Accuracy of breed assignment was based on the frequency of correct breed assignment. Assignment accuracy increased as more genotypes (loci or haplotypes) were considered and more animals were used to estimate genotypic frequencies within breed. For most scenarios, use of haplotypes yielded equal or greater accuracies than when loci were considered independent. The advantage of haplotypes tended to increase as linkage disequilibrium between adjacent loci increased. The greatest advantage for using haplotypes was observed when recombination rate was low (0.001), breeds were separated by few generations (100), and a relatively large number of founder animals (110) was used to form new breeds. In this situation, 90% accuracy of breed assignment was achieved using nine to 14 haplotypes (i.e. 27-42 loci) depending on breed, vs. 39-57 individual loci.

Parentage testing in alpacas (Vicugna pacos) using semi-automated fluorescent multiplex PCRs with 10 microsatellite markers.

The aim of this study was to assess and apply a microsatellite multiplex system for parentage determination in alpacas. An approach for parentage testing based on 10 microsatellites was evaluated in a population of 329 unrelated alpacas from different geographical zones in Perú. All microsatellite markers, which amplified in two multiplex reactions, were highly polymorphic with a mean of 14.5 alleles per locus (six to 28 alleles per locus) and an average expected heterozygosity (H(E)) of 0.8185 (range of 0.698-0.946). The total parentage exclusion probability was 0.999456 for excluding a candidate parent from parentage of an arbitrary offspring, given only the genotype of the offspring, and 0.999991 for excluding a candidate parent from parentage of an arbitrary offspring, given the genotype of the offspring and the other parent. In a case test of parentage assignment, the microsatellite panel assigned 38 (from 45 cases) offspring parentage to 10 sires with LOD scores ranging from 2.19 x 10(+13) to 1.34 x 10(+15) and Delta values ranging from 2.80 x 10(+12) to 1.34 x 10(+15) with an estimated pedigree error rate of 15.5%. The performance of this multiplex panel of markers suggests that it will be useful in parentage testing of alpacas.

Genetic correlation patterns between somatic cell score and protein yield in the Italian Holstein-Friesian population.

Genetic parameters for somatic cell score (SCS) in the Italian Holstein-Friesian population were estimated addressing the pattern of genetic correlation with protein yield in different parities (first, second, and third) and on different days in milk within each parity. Three approaches for parameter estimation were applied using random samples of herds from the national database of the Italian Holstein Association. Genetic correlations for lactation measures (305-d protein yield and lactation SCS) were positive in the first parity (0.31) and close to zero in the second (0.01) and third (0.09) parities. These results indicated that larger values of SCS were genetically associated with increased production. The second and third sets of estimates were based on random regression test-day models, modeling the shape of lactation curve with the Wilmink function and fourth-order Legendre polynomials, respectively. Genetic correlations from both random regression models showed a specific pattern associated with days in milk within and across parities. Estimates varied from positive to negative in the first and second parity, and from null to negative in the third parity. Patterns were similar for both random regression models. The average overall correlation between SCS and protein yield was zero or slightly positive in the first lactation and ranged from zero to negative in later lactations. Correlation estimates differed by parity and stage of lactation. They also demonstrated the dubiousness of applying a single genetic correlation measure between SCS and protein in setting selection strategies. Differences in magnitude and the sign of genetic correlations between SCS and yields across and within parities should be accounted for in selection schemes.

Genetic analysis of somatic cell scores in US Holsteins with a Bayesian mixture model.

The objective of this study was to apply finite mixture models to field data for somatic cell scores (SCS) for estimation of genetic parameters. Data were approximately 170,000 test-day records for SCS from first-parity Holstein cows in Wisconsin. Five different models of increasing level of complexity were fitted. Model 1 was the standard single-component model, and the others were 2-component Gaussian mixtures consisting of similar but distinct linear models. All mixture models (i.e., 2 to 5) included separate means for the 2 components. Model 2 assumed entirely homogeneous variances for both components. Models 3 and 4 assumed heterogeneous variances for either residual (model 3) or genetic and permanent environmental variances (model 4). Model 5 was the most complex, in which variances of all random effects were allowed to vary across components. A Bayesian approach was applied and Gibbs sampling was used to obtain posterior estimates. Five chains of 205,000 cycles were generated for each model. Estimates of variance components were based on posterior means. Models were compared by use of the deviance information criterion. Based on the deviance information criterion, all mixture models were superior to the linear model for analysis of SCS. The best model was one in which genetic and PE variances were heterogeneous, but residual variances were homogeneous. The genetic analysis suggested that SCS in healthy and infected cattle are different traits, because the genetic correlation between SCS in the 2 components of 0.13 was significantly different from unity.

Relationships between somatic cell count and intramammary infection in buffaloes.

The objectives of this study were to evaluate the presence of intramammary infections (IMI) in dairy buffaloes and to examine the relationships among IMI, somatic cell counts (SCC), and milk production traits. Two farms in northern Italy were visited monthly for a complete milking season. Quarter-based milk samples were collected at each visit from 46 buffaloes. A total of 1,912 samples were assessed in this experiment. Samples were cultured for bacterial presence and were tested for SCC and percentages of milk protein and fat. In addition, daily milk yield was recorded from each buffalo. Prevalence of IMI was large; 63% of quarters were infected. No buffalo remained free from IMI throughout the course of the study. Coagulase-negative staphylococci were the most common pathogen (66% of positive samples). The SCC was distinctly greater in infected quarters; 100% of quarters with SCC >200,000 cell/mL had IMI, whereas 98% of quarters with SCC below this threshold were uninfected. The somatic cell scores (SCS) in these buffaloes were much lower than those commonly observed in dairy cattle. The mean SCS from quarters with IMI was only 2.93. The highest SCS was observed in quarters infected by streptococci. No drastic decrease in milk yield was observed among infected buffaloes relative to healthy contemporaries. The relatively low SCS and lack of a strong effect on milk yield provide evidence to discourage antibiotic treatment of buffaloes for subclinical IMI during lactation.

Risk factors for intramammary infections and relationship with somatic-cell counts in Italian dairy goats.

Routine examination of milk was performed on five herds of lactating goats in northern Italy as part of a milk quality-monitoring program in the year 2000. As part of the study, aseptic samples of foremilk were collected monthly from both half udders during the entire lactation for 305 goats, resulting in a total of 4571 samples. The samples were tested with cytological and bacteriological analyses to evaluate the relationship between mammary infections and somatic-cell count (SCC; Fossomatic (TM) method). Prevalence of intramammary infection (IMI) was 40.2% (n = 1837) of all udder-half samples examined. The most-prevalent mastitis agents were coagulase-negative Staphylococci (CNS), 80% (n = 1474 udder-half samples); within this group, Staphylococcus epidermidis was the most-prevalent species (38%). Other prevalence were Staphylococcus aureus 6% (n = 112 udder-half samples) and environmental pathogens 14% of infected udder-half samples (n = 251) with a diverse mixture of species, none of which had a frequency of > 4%. Enterococcus faecalis was the most-frequently isolated among this group. Neither Salmonella spp. nor Listeria monocytogenes were detected. The risk (sample level) of infection differed across herds, parities, and stage of lactation according to results from logistic multiple regression. Infection was more common among goats in third and fourth parities and during the later stages of lactation. Of the 2734 samples from uninfected udder halves, the mean log2 SCC was 3.9 cell/ml; of the 1837 bacteriological positive samples, the mean log2 SCC was 5.6 cell/ml. According to results from a linear mixed model, concentrations of somatic cells tended to increase with increasing age and days in milk and with the presence of bacteria. Infection with S. aureus was associated with the highest SCS.

Application of a finite mixture model to somatic cell scores of Italian goats.

The objectives of this study were to apply a finite mixture model (FMM) to data for somatic cell count in goats and to compare the fit of the FMM with that of a standard linear mixed effects model. Bacteriological information was used to assess the ability of the model to classify records from healthy or infected goats. Data were 4518 observations of somatic cell score (SCS) and bacterial infection from both udder halves of 310 goats from 5 herds in Northern Italy. The records were from a complete production season, and were taken monthly from February to November 2000. Explanatory factors in both models included a 3-parameter regression on days in milk (DIM); fixed class effects of herd-test-day, parity group, and udder side (left or right); and random effects of goat and udder half within goat. In addition, the 2-component FMM included a fixed mean for the second component of the model (theoretically corresponding to infected udder halves), as well as an unknown probability of membership to a given putative infection status. A Bayesian statistical approach was used for the analysis with Gibbs sampling used to obtain draws from posterior distributions of parameters of interest. Two sampling chains of 200,000 cycles each were generated for each model. The FMM yielded a much lower estimate of residual variance than the standard model (1.28 vs. 3.02 SCS2), and a slightly higher estimate for the between-goat variance (1.79 vs. 1.48). The deviance information criterion (DIC) was used to compare the fit of the 2 models. The DIC was much lower for the FMM, indicating a better fit to the data. The FMM was able to classify correctly 60 and 48% of the healthy and infected observations, respectively. This was slightly higher than what would be expected from random classification, but not high enough for useful mastitis diagnosis. Nevertheless, increased precision of genetic evaluation is the goal of applying the FMM, rather than timely and accurate mastitis diagnosis. The results suggest that more research on FMM for SCS is merited and necessary for proper application.

Estimation of variances for gametic effects on litter size in Yorkshire and Landrace swine.

The objective of this study was to test for effects of gametic imprinting on litter size in swine by estimating variances for parent-specific gametic effects. Data were 64,047 and 137,009 multiparous records of number born alive for the U.S. Landrace and Yorkshire breeds, respectively. The statistical model included fixed effects of parity number and herd, and random effects of herd-year-season, mate, permanent environment, animal (additive genetic), and either maternal or paternal gametes. A Bayesian approach that used Gibbs sampling to obtain posterior distributions was employed. To aid in the interpretation of results, the Landrace data structure was used to simulate data with and without effects of imprinting. Analyses of the simulated records indicated that the model applied was capable of detecting effects of imprinting when such effects were present. Small, but non-zero, estimates of gametic variances were obtained when no imprinting was simulated. Estimates of the proportion of total variance accounted for by paternally transmitted gametes were 0.8 and 0.9% for Landrace and Yorkshires, respectively. These estimates were different from zero, but were similar to the results observed for data simulated without an imprinting effect. Corresponding results for maternally transmitted gametes were 1.6% for Landrace and 0.8% for Yorkshires. The estimate for Landrace was significantly greater than that observed for Yorkshires and for the simulations without a true effect and suggested the presence of a non-Mendelian genetic influence on litter size. Paternally imprinted genes are a plausible reason for the observed results. Assuming that the effect observed was due to paternal imprinting at a single biallelic locus, the substitution effect of the superior allele could be greater than 0.7 piglets per litter. Identification of a genetic marker for such an allele would be useful in marker-assisted selection of females. Other possible explanations exist for the increased gametic variance in the Landrace breed, but these explanations (such as maternal or cytoplasmic effects) may be less likely than paternal imprinting.

Differentially expressed genes associated with Staphylococcus aureus mastitis in dairy goats.

To study gene expression within the mammary glands of dairy goats with mastitis, mRNA was collected from milk somatic cells (MSCs) of left udder halves challenged with Staphylococcus aureus and right udder halves infused with PBS, as control, at different time points (0, 12, 24 and 48h post-infection). Transcriptional profiles were investigated using bovine cDNA microarrays; of the total 288 differentially expressed genes identified with ANOVA analysis (False Discovery Rate=0.05, 1.5-fold change), 26, 36 and 16 genes were down-regulated at 12, 24 and 48h post-infection, respectively, while 60, 141 and 9 genes were up-regulated at the same corresponding time points. The expression profiles clearly changed at 24h post-infection with 177 genes significantly altered, corresponding to a 10-fold increase of S. aureus bacterial count in milk from infected udders. Differential expression of selected genes (CD2BP2, BCAP31, MHCII, FOSL2, MAPK13, ILT5 and JUNB) was also confirmed by real-time PCR at the different time points considered, showing high correlation with the microarray measurements and high reliability of the microarray analyses. The most readily inducible classes of genes in caprine MSCs infected with S. aureus were pro-inflammatory cytokines, chemokines and their receptors; IL-1alpha, lymphotoxin alpha, granulocyte chemotactic protein (CXCL6), and IL-2 receptor gamma were all up-regulated in infected udders versus healthy controls. This study identified a number of differentially expressed genes induced by S. aureus intramammary infection and demonstrates the intricacy of the patterns of gene expression that influence host response to a complex pathogen of significant relevance to both human and veterinary medicine.

Milk hygiene and udder health in the periurban area of Hamdallaye, Niger.

The prevalence of intra-mammary infections in dairy herds was studied in Hamdallaye, Niger. A total of 956 milk samples were collected in 2007 from 239 lactating cows of four local breeds in eight traditional herds; the first sampling was undertaken in the dry season at morning milking, and the second in the rainy season at evening milking. Staphylococcus aureus, Coagulase-Negative Staphylococci (CNS) and environmental microorganisms were detected in significantly (p < 0.05) more samples in the rainy season, 55.2%, than in the dry season, 27.1%. Statistically significant (P < 0.05) differences in prevalence were observed among herds and according to lactation number. Infections were assigned to four classes, according to the major pathogen, and the respective mean somatic cell counts during the dry season were: S. aureus, 775 x 10(3) cells/ml; CNS, 447 x 10(3) cells/ml; environmental microorganisms, 407 x 10(3) cells/ml; and non-infected, 262 x 10(3) cells/ml. Most of the tested strains were sensitive to antibiotics, and selected strains of S. aureus (n = 15) were negative to the multiplex PCR tests for production of enterotoxins.

Molecular typing of Staphylococcus aureus isolated from cows, goats and sheep with intramammary infections on the basis of gene polymorphisms and toxins genes.

We investigated 116 Staphylococcus aureus isolates from cows, goats and sheep with intramammary infections (IMI) in Italy to provide information about the spread of enterotoxigenic strains and to compare strains isolated from different ruminant species. The isolates were typed by restriction fragment length polymorphism (RFLP) analysis of the coagulase (coa) gene, by analysis of polymorphisms of the X region of protein A (spa) gene and by detection of genes encoding enterotoxins (sea, seb, sec, sed, see, seg, seh, sei, sej and sel). Seven different coa types and 12 different spa types were distinguished. On the basis of polymerase chain reaction-RFLP, 29 different coa subtypes were identified. Two different coa subtypes accounted for 49% and 67% of bovine and ovine isolates respectively. Only seven coa subtypes were observed in isolates from more than one host species and no coa subtype was present in isolates from all three ruminant species. Furthermore, 85 of the isolates (73%) harboured at least one enterotoxin gene (se) with a predominance of sea, sed and sej among isolates from bovine IMI, and sec and sel among isolates from caprine and ovine IMI. Comparing the S. aureus isolates on the basis of gene polymorphisms and presence of se genes, significant differences were found in distributions of genotypes among isolates from cows, goats and sheep.

Estimation of variance of maternal lineage effects among Canadian Holsteins.

Bayesian posterior estimates of variances of maternal lineage effects were obtained with a procedure that used Gibbs sampling. Data were records of yield during first parity from 245,510 Holstein cows that calved in Canada between 1990 and 1994. Maternal lineages were defined by tracing the maternal ancestry of cows to common female ancestors. Traits were standardized yields of milk, fat, and protein and percentages of fat and protein. Estimates of maternal lineage variance were < 0.5% of the total variance for all traits. Effects of this size hardly affected the cow rankings for estimated breeding value. Another analysis defined maternal lineages by establishing groups of dams and their daughters in an attempt to maximize the variance of environmental effects associated with maternal lineages, but only 1.1% of the variance in milk yield was associated with effects of the dam and daughter groups. Analyses of simulated data indicated that positive estimates of maternal lineage effects were not a result of restriction of estimates to positive values and that estimates of maternal lineage variance were biased slightly downward because of incomplete pedigree information. The partitioning of maternal lineage and additive genetic variance was correct when pedigree information was complete, according to results from simulation.

Genotype x environment interaction for grazing vs. confinement. II. Health and reproduction traits.

Continual selection for increased milk yield for more than 40 yr, combined with the antagonistic relationship between increasing yield, somatic cell count, and fertility, have resulted in sires that may not be optimal for producing daughters for grazing systems where seasonal calving is very important. The objective of this study was to investigate the possible existence of a genotype x environment interaction (G x E) in grazing vs. confinement herds within the United States for lactation average somatic cell score (LSCS), days open (DO), days to first service (DFS), and number of services per conception (SPC). Grazing herds were defined as those that utilized grazing for at least 6 mo each year and were enrolled in Dairy Herd Improvement (DHI). Control herds were confinement DHI herds of similar size in the same states. For LSCS, the performance of daughters in grazing and control herds was examined using linear regression of LSCS on the November 2000 USDA-DHIA sire predicted transmitting abilities (PTA) for SCS. Genetic parameters for all traits were estimated using REML in a bivariate animal model that treated the same trait in different environments as different traits. Rank correlations were calculated between sires' estimated breeding values for LSCS, calculated separately for sires in both environments. The coefficient of regression of daughter LSCS on sire PTA was less in grazing herds than in control herds. The coefficient of regression for control herds was closer to expectation. Estimates of heritability were approximately 0.12 for LSCS, and less than 0.05 for the reproduction traits. Heritabilities for DO, DFS, and SPC were slightly higher for control herds. Estimates of genetic correlation for each reproductive trait between the 2 environments were high and not significantly different from unity. Generally, these traits appear to be under similar genetic control, but a lower coefficient of regression of LSCS on sire PTA for SCS in grazing herds suggests differences in daughter performance in grazing herds may be overstated based on current PTA for SCS.

A Monte Carlo approach for estimation of haplotype probabilities in half-sib families.

The objective of this work was to propose an algorithm (HAPROB) to estimate haplotype probabilities for genotyped members of half-sib families for which parents lacked genotypic information. The algorithm had 2 basic steps. First, a Monte Carlo-based approach was used to estimate haplotype probabilities for sires conditional upon offspring genotypes and population allelic frequencies, and then offspring-haplotype probabilities were estimated conditional upon sire probabilities and population frequencies. The 2 steps were alternated iteratively until estimates of population frequencies were essentially unchanged. Simulation was used to evaluate effects of the number of Monte Carlo cycles on the accuracy of the reconstructed haplotypes. Fifty thousand cycles was found to be sufficient for the haplotype configurations considered. Accuracy of the algorithm was compared with that obtained by the public domain SIMWALK2 software. Predictions of the most likely haplotype configurations are produced by SIM-WALK2, but no estimates of probability are given. The accuracy of the current approach was comparable to that obtained from SIMWALK2. The proportions of times that haplotypes were reconstructed correctly were 87.0 and 92.4% (sires and offspring) for HAPROB vs. 87.5 and 91.5% for SIMWALK2. Effects of family size on accuracy of reconstruction were examined. Accuracy of reconstruction was only about 4% for sires with 2 offspring, but accuracy among the offspring themselves was 65%. Accuracy increased quickly as family size increased and reached 100% for sires with 30 offspring. Maximum accuracy for offspring was about 96%. Estimates of haplotype probabilities produced can be used in regression analyses to estimate effects of haplotypes on quantitative phenotypes.

Evaluation of sire predicted transmitting abilities for evidence of X-chromosomal inheritance in north american sire families.

This study tested for differences between genetic merits of sons and daughters of sires and for evidence of segregating quantitative trait loci on the X chromosomes of North American Holsteins. Son PTA adjusted for sire PTA was used as the dependent variable to test for biases and for genes that were passed from sire to daughter but not to son. The test of variability across sires of sons merely indicated an unaccounted source of variation, for which genes on X chromosomes might be responsible. Critical values for this test and power were determined by simulation for a variety of populations and traits differing in heritability, size of the X chromosome effect, and allelic frequency. Simulated genes on the X chromosome were detected with high power at intermediate frequencies of the favorable allele. The power of the test increased as the size of the effect increased and as genetic variance attributed to autosomes decreased. The test was then applied to recently evaluated data from US and Canadian Holstein populations. Genetic evaluations for >17,000 bulls from the US and >9000 from Canada were included. Results suggested that little extra variation was present for some traits formally evaluated in North America, but that genes on the X chromosome were unlikely to be the cause.

Bayesian segregation analysis of somatic cell scores of Ontario Holstein cattle.

Bayesian segregation analysis using a Gibbs sampling approach was applied to four sets of simulated data and one set of field data to detect evidence of major genes affecting the evaluated trait. The substitution effect of a major gene and its allelic frequency were estimated for each set of data. For two datasets simulated with a model with no major gene effect, the resulting estimates of polygenic variance and heritability agreed with the simulated values and tests for the presence of a major gene were not significant. Analyses of two sets of data simulated with a major gene produced posterior distributions that gave significant evidence of major gene effects but underestimated the substitution values of the major gene. The segregation analysis of field data suggested that a major gene significantly affected somatic cell score (SCS) in the population of Ontario Holstein cattle. The estimated heritability of SCS was approximately 0.16. The major gene variance accounted for about 17% of the total genetic variance and the point estimate of the frequency of the allele having a positive effect on SCS was 0.30. However, the precision of these estimates is questionable based on the simulation results. The effect of the major gene may be underestimated.