Comparison of models for genetic evaluation of survival traits in dairy cattle: a simulation study.

Three models for the analysis of functional survival data in dairy cattle were compared using stochastic simulation. The simulated phenotype for survival was defined as a month after the first calving (from 1 to 100) in which a cow was involuntarily removed from the herd. Parameters for simulation were based on survival data of the Canadian Jersey population. Three different levels of heritability of survival (0.100, 0.050 and 0.025) and two levels of numbers of females per generation (2000 or 4000) were considered in the simulation. Twenty generations of random mating and selection (on a second trait, uncorrelated with survival) with 20 replicates were simulated for each scenario. Sires were evaluated for survival of their daughters by three models: proportional hazard (PH), linear multiple-trait (MT), and random regression (RR) animal models. Different models gave different ranking of sires with respect to survival of their daughters. Correlations between true and estimated breeding values for survival to five different points in a cow's lifetime after the first calving (120 and 240 days in milk after first, second, third and fourth calving) favoured the PH model, followed by the RR model evaluations. Rankings of models were independent of the heritability level, female population size and sire progeny group size (20 or 100). The RR model, however, showed a slight superiority over MT and PH models in predicting the proportion of sire's daughters that survived to the five different end-points after the first calving.     

Bayesian inference for genetic parameter estimation on growth traits for Nelore cattle in Brazil,using the Gibbs sampler

This data set consisted of over 29 245 field records from 24 herds of registered Nelore cattle born between 1980 and 1993, with calves sires by 657 sires and 12 151 dams. The records were collected in south‐eastern and midwestern Brazil and animals were raised on pasture in a tropical climate. Three growth traits were included in these analyses: 205‐ (W205), 365‐ (W365) and 550‐day (W550) weight. The linear model included fixed effects for contemporary groups (herd‐year‐season‐sex) and age of dam at calving. The model also included random effects for direct genetic, maternal genetic and maternal permanent environmental (MPE) contributions to observations. The analyses were conducted using single‐trait and multiple‐trait animal models. Variance and covariance components were estimated by restricted maximum likelihood (REML) using a derivative‐free algorithm (DFREML) for multiple traits (MTDFREML). Bayesian inference was obtained by a multiple trait Gibbs sampling algorithm (GS) for (co)variance component inference in animal models (MTGSAM). Three different sets of prior distributions for the (co)variance components were used: flat, symmetric, and sharp. The shape parameters (ν) were 0, 5 and 9, respectively. The results suggested that the shape of the prior distributions did not affect the estimates of (co)variance components. From the REML analyses, for all traits, direct heritabilities obtained from single trait analyses were smaller than those obtained from bivariate analyses and by the GS method. Estimates of genetic correlations between direct and maternal effects obtained using REML were positive but very low, indicating that genetic selection programs should consider both components jointly. GS produced similar but slightly higher estimates of genetic parameters than REML, however, the greater robustness of GS makes it the method of choice for many applications.     

Direct and maternal genetic effects for carcass traits in beef cattle.

Carcass measurements were taken on 1,537 steers produced over four generations in a rotational crossbreeding study. Breed direct and maternal additive and heterotic genetic effects were estimated for hot carcass weight (HCWT), retail yield (RY), longissimus muscle area (LM), fat thickness (FT), marbling score (MS), and Warner-Bratzler shear force (WBS). Angus (A), Brahman (B), Charolais (C), and Hereford (H) breeds were involved in straightbred, first-cross, and two-, three-, and four-breed rotational crossbred matings with each crossbred combination including the B. Breed direct (Ig) and maternal (Mg) additive genetic effects and direct (Ih) and maternal (Mh) heterotic genetic effects were estimated using a multiple-regression model. The Ig and Mg effects were expressed as deviations from the overall mean. The IgC effects (Ig for C breed) were significant for HCWT, RY, and LM and resulted in leaner, heavier carcasses. The IgA and IgH effects were, in general, negative (P < .05) for HCWT, RY, LM, and WBS, and positive (P < .01) for FT and MS. The IgB effects were large and undesirable for HCWT, RY, LM, MS, and WBS (P < .01). The majority of Ih effects were beneficial (P < .05) for HCWT, RY, LM, and WBS. The Ih effects exhibited by B combinations were of greater (P < .05) magnitude with positive influences for HCWT, RY, and LM and desirable effects for WBS. The maternal additive and heterotic effects were of lesser importance than the direct additive and heterotic effects for the carcass traits studied.     

Estimation of genetic parameters for longevity traits in dairy cattle: A review with focus on the characteristics of analytical models

Longevity is an economically important trait of dairy cattle for increasing the profitability of dairy management. The reasons for culling can be either voluntary (primarily productivity) or involuntary (primarily health and fertility). Longevity characteristics include: (i) true longevity (all culling reasons, including productivity); and (ii) functional longevity (all culling reasons, except productivity). Improvements to longevity are made to decrease the rate of involuntary culling rather than extend the herd life (HL). The proportional hazard model is useful for evaluating genetic ability for HL. However, the differences between estimates made using the proportional hazard model and those made using linear single or multiple‐trait animal models are not clear. The model commonly used for evaluation differs among countries. Productive traits, udder traits, and feet and legs traits are genetically correlated with longevity, and consequently these traits are used to indirectly evaluate longevity. The reliability of estimates of genetic ability for longevity is increased by combining direct and indirect estimates. In Japan, HL is evaluated using the multiple‐traits model. The genetic correlations between HL and other traits vary with the birth year. Therefore, these genetic correlations need to be reviewed regularly.     

Structural equation models to disentangle the biological relationship between microbiota and complex traits: Methane production in dairy cattle as a case of study

The advent of metagenomics in animal breeding poses the challenge of statistically modelling the relationship between the microbiome, the host genetics and relevant complex traits. A set of structural equation models (SEMs) of a recursive type within a Markov chain Monte Carlo (MCMC) framework was proposed here to jointly analyse the host–metagenome–phenotype relationship. A non-recursive bivariate model was set as benchmark to compare the recursive model. The relative abundance of rumen microbes (RA), methane concentration (CH₄) and the host genetics was used as a case of study. Data were from 337 Holstein cows from 12 herds in the north and north-west of Spain. Microbial composition from each cow was obtained from whole metagenome sequencing of ruminal content samples using a MinION device from Oxford Nanopore Technologies. Methane concentration was measured with Guardian^® NG infrared gas monitor from Edinburgh Sensors during cow's visits to the milking automated system. A quarterly average from the methane eructation peaks for each cow was computed and used as phenotype for CH₄. Heritability of CH₄ was estimated at 0.12 ± 0.01 in both the recursive and bivariate models. Likewise, heritability estimates for the relative abundance of the taxa overlapped between models and ranged between 0.08 and 0.48. Genetic correlations between the microbial composition and CH₄ ranged from −0.76 to 0.65 in the non-recursive bivariate model and from −0.68 to 0.69 in the recursive model. Regardless of the statistical model used, positive genetic correlations with methane were estimated consistently for the seven genera pertaining to the Ciliophora phylum, as well as for those genera belonging to the Euryarchaeota (Methanobrevibacter sp.), Chytridiomycota (Neocallimastix sp.) and Fibrobacteres (Fibrobacter sp.) phyla. These results suggest that rumen's whole metagenome recursively regulates methane emissions in dairy cows and that both CH₄ and the microbiota compositions are partially controlled by the host genotype.     

Use of robust multivariate linear mixed models for estimation of genetic parameters for carcass traits in beef cattle

Assumptions of normality of residuals for carcass evaluation may make inferences vulnerable to the presence of outliers, but heavy‐tail densities are viable alternatives to normal distributions and provide robustness against unusual or outlying observations when used to model the densities of residual effects. We compare estimates of genetic parameters by fitting multivariate Normal (MN) or heavy‐tail distributions (multivariate Student's t and multivariate Slash, MSt and MS) for residuals in data of hot carcass weight (HCW), longissimus muscle area (REA) and 12th to 13th rib fat (FAT) traits in beef cattle using 2475 records from 2007 to 2008 from a large commercial operation in Nebraska. Model comparisons using deviance information criteria (DIC) favoured MSt over MS and MN models, respectively. The posterior means (and 95% posterior probability intervals, PPI) of v for the MSt and MS models were 5.89 ± 0.90 (4.35, 7.86) and 2.04 ± 0.18 (1.70, 2.41), respectively. Smaller values of posterior densities of v for MSt and MS models confirm that the assumption of normally distributed residuals is not adequate for the analysis of the data set. Posterior mean (PM) and posterior median (PD) estimates of direct genetic variances were variable with MSt having the highest mean value followed by MS and MN, respectively. Posterior inferences on genetic variance were, however, comparable among the models for FAT. Posterior inference on additive heritabilities for HCW, REA and FAT using MN, MSt and MS models indicated similar and moderate heritability comparable with the literature. Posterior means of genetic correlations for carcass traits were variable but positive except for between REA and FAT, which showed an antagonistic relationship. We have demonstrated that genetic evaluation and selection strategies will be sensitive to the assumed model for residuals.     

Stability of genetic parameter estimates for production traits in pigs

Changes in variance component estimates in growing sets of performance data in two pig breeds were investigated. Data was used from the field and station test of Czech Landrace (LA: 75 099 observations) and the Slovakian breed, White Meaty swine (WM: 32 203 observations). In LA the traits analysed were estimated lean meat content (LM) and average daily gain (ADGF) on field test and average daily gain (ADGS) and weight of valuable cuts (VCW) on station test. In WM the traits analysed were backfat thickness on field and station test (BFF, BFS, respectively), proportion of valuable cuts (VCP) on station test, ADGF and ADGS. Covariance components were estimated from four- and five-trait animal models using the VCE software. Omitting data from factor levels with a low number of records led to 4.2% of LA records and 21.7% of WM records being deleted. Changes in genetic and residual variance estimates were less than 5% for all traits in LA and less than 12% for all traits except ADGS in WM. The changes in estimated genetic variances caused by 18 months (LA) or 24 months (WM) of new data were 2–25% and the changes in estimated residual variances were less than 5% in LA and less than 20% in WM. In both breeds, changes in heritability estimates did not exceed 0.06 in absolute value. In LA, it is reasonable to use genetic parameter estimates for 3 years before re-estimation. In WM the time interval should be shorter because of changes in the estimates caused by their lower accuracy arising from the smaller size of the data-set and smaller frequency of station testing.     

Estimation of individual cross-breeding effects on milk-production traits of the German Black Pied dairy cattle using different genetic models*

SUMMARY: Milk performance data of cross-breds in the synthetic breed German Black Pied Dairy Cattle (SMR), that had calved for the first time between 1970 and 1984, were used to estimate individual cross-breeding effects on milk production traits. Three million pure-bred and cross-bred cows that were in their first lactation and had originated from conventional housing systems were involved. For 1111331 cows genetic groups according to their respective ancestry could be formed. The additive breed differences and heterosis effects estimated by the Dickerson model correspond to those effects determined by the majority of other authors. For milk yield, highly significant negative effects were obtained for the Holstein-Friesian × Black Pied Cattle and Jersey, respectively. The estimates ranged between 4.8 % and 5.0 % of the mean of all cross-breeding groups. In cross-breds with Jersey the recombination loss for fat percentage was between 5.3 % and 6.0 %. These results support the theory that recombination loss occurs predominantly when breeds, which have been selected for a long period for certain traits, are crossed. The recombination loss for fat yield attains values between 1.9 % and 6.8 %. Different genetic models for the estimation of cross-breeding effects were compared. In contrast to the Dickerson model, the modified genetic models of Jakubec et al. (1991) and Mather and Jinks (1971) (models A, B, C and D) and those of Kinghorn (1980, 1982, 1987) enabled estimation of the genetic components underlying heterosis. Model A accounts for additive, dominant and additive × additive effects and this model can be transformed by linear functions into the Dickerson model. As model A shows an exact separation of the heterosis and epistatic effects, this model is preferred to that of Dickerson (1969, 1973). The estimated additive × dominance effects, obtained using model B, are significant and half as large as the additive × additive effects. The extent of dominance × dominance effects (models C and D) could not be determined with the restrictions used. If these epistatic interactions are taken into consideration, the standard errors of the estimates increase and the accuracy of the estimates decreases. ZUSAMMENFASSUNG: Sch?tzung individueller Kreuzungseffekte für Milchleistungsmerkmale beim Schwarzbunten Milchrind unter Verwendung verschiedener genetischer Modelle Die Untersuchung individueller Kreuzungseffekte für Milchleistungsmerkmale basiert auf den Milch-leistungsdaten von Rein- und Kreuzungszuchttieren der synthetischen Rasse Schwarzbuntes Milchrind (SMR), die zwischen den Jahren 1970 und 1984 zum ersten Mal abgekalbt haben. Insgesamt standen 3 Millionen Erstlaktierende aus herk?mmlichen Haltungssystemen zur Verfügung. 1 111 311 Kühe konnten entsprechend ihrer Abstammung eindeutig definierten Kreuzungsgruppen zugeordnet werden. Die Sch?tzwerte für die additiven Rassenunterschiede und Heterosis im Dickerson-Modell (1969) korrespondieren weitgehend mit den von anderen Autoren publizierten Ergebnissen. Hoch signifikante, negative Effekte wurden für die Kreuzungen von Holstein-Friesian mit dem Schwarzbunten Rind und Jersey gesch?tzt. Die Sch?tzwerte lagen zwischen 4,8 und 5 % des Mittels aller Generationsmittelwerte. Kreuzungen mit Jersey wiesen für den Fettgehalt einen Rekombinationsverlust zwischen 5,3 und 6 % auf. Diese Ergebnisse unterstützen die Theorie, da? Rekombinationsverluste vornehmlich dann auftreten, wenn Rassen, die für lange Zeit auf bestimmte Merkmale selektiert wurden, gekreuzt werden. Der relative Rekombinationsverlust für den Fettgehalt erreichte Werte zwischen 1,9 und 6,8 %. Die Untersuchung hatte auch zum Ziel, die Sch?tzwerte verschiedener genetischer Modelle zu vergleichen. Im Gegensatz zum Dickerson-Modell (1969) erm?glichten das modifizierte Modell von Jakubec et al. (1991), die Modelle von Mather und Jinks (1971) (Modelle A, B, C, D) sowie von Kinghorn (1980, 1982, 1987) die Sch?tzung von der Heterosis zugrundliegenden genetischen Komponenten. Das Modell A beinhaltete von den Zweiwege-Interaktionen nur die additiv × additive Komponente, es kann aber anhand von linearen Funktionen in das Dickerson-Modell (1969) überführt werden. Da Model A die Trennung der Heterosis von epistatischen Effekten erm?glicht, ist dieses Modell dem Dickerson-Modell (1969, 1973) vorzuziehen. Die gesch?tzten additiv × dominanten Effekte in Modell B waren signifikant und in etwa halb so gro? wie die additiv × additiven Sch?tzwerte. Es war schwierig, die dominant × dominanten Effekte in den Modellen C und D zu bestimmen, da sich die Standardfehler für die Sch?tzwerte erh?hten und damit die Genauigkeit der Sch?tzer abnahm.     

Heritability estimates and genetic correlations of various production and reproductive traits of different grades of dairy cattle reared under subtropical condition

Inheritance of economic traits and their genetic correlation was studied in different breeds and their various grades (crossbred’s cattle) under the subtropical condition. Data on principal parameters comprising 10 years, that is 2004–2014, were utilized for the present study. Different grades of dairy cows comprising Holstein Friesian (HF), Sahiwal x Friesian (SxHF), Jersey (J), Jersey x Achai (JxAC) and Achai (AC) were included in the study. Heritability estimates and genetic correlations of some important productive and reproductive traits were worked out. Heritability estimates of certain economic traits were found to be: birthweight, 0.32 ± 0.181; age at maturity, 0.11 ± 0.136; age at first calving, 0.19 ± 0.162; days open, 0.09 ± 0.121; calving interval, 0.14 ± 0.211; dry period, 0.11 ± 0.124; lactation length, 0.04 ± 0.212 and lactation yield, 0.46 ± 0.206. Genetic correlation showed that body weight was significantly and positively correlated with lactation length (0.30) and lactation yield (0.81), while negatively correlated with age at maturity, age at first calving, days open, calving interval and dry period (?0.09, ?0.07, ?0.16, ?0.34 and ?0.002, respectively). Calving interval was positively and significantly correlated with the dry period (0.56), lactation length (0.72) and lactation yield (0.37). Moderate to higher heritability estimates with adequate genetic variance was found for body weight and lactation yield. The moderate to higher heritability estimates of birthweight in the present study revealed that this important trait might be considered in selection criteria.     

Genetic parameter estimates for preweaning traits of beef cattle in a stressful environment

Data collected from 1957 through 1985 from a Hereford herd located in the Southwest were analyzed separately for each sex to evaluate the heritabilities of and genetic correlations among preweaning growth traits within groups of environmentally similar years. Data were grouped into years with poor, moderate and good environments based on contemporary group means for male calves' weaning weight. A total of 7,690 records were analyzed for birth weight, weaning weight and preweaning daily gain with a model that included year of birth, sire within year of birth, age of dam and a covariate of day of birth for birth weight or age at weaning for the weaning traits. Year of birth was a significant source of variation in all environments for all traits, accounting for more of the variation in the good and poor years than in moderate years. Heritability estimates for all traits were greater in good and moderate years than in poor years for bull calves. For heifers, however, estimates for weaning weight and preweaning daily gain were greater in the poor environment. Genetic correlations among birth weight and preweaning gain increased from the good environment to the poor environment (-.49 +/- .26 to .82 +/- .56 for male calves and -.09 +/- 2.6 to .46 +/- .25 for female calves) but phenotypic correlations were near zero in all environments.(ABSTRACT TRUNCATED AT 250 WORDS)     

Resistance of cattle of various genetic groups to the tick Rhipicephalus microplus and the relationship with coat traits

This study evaluated the resistance of cattle of different genetic groups to the tick Rhipicephalus microplus and the relationship with traits of the animals' hair and coat. Cows of the Senepol×Nelore (SN), Angus×Nelore (AN) and Nelore (NX) genetic groups were submitted to four consecutive artificial infestations, at 14-day intervals, each one with approximately 20,000 tick larvae placed on the animals' lumbar region. From the 19th to 23rd day of each infestation five counts of the number of ticks were performed on each animal's left body side. The tick count data (TTC) were transformed into log(10) (n+1), and also into percentage of return (PR), where n is the total number of ticks counted at each infestation. Hair samples were collected 24h after the last infestation with flat-nosed pliers. Measures of the average hair length (HL), coat thickness (CT), number of hairs per cm(2) (NHCM2) and weight of the samples (SW) were obtained. Pearson's correlation coefficients were calculated within genetic group to measure association between PR and the hair and coat data. There was a significant difference among genetic groups for the number of ticks, with the AN group having higher counts than the SN and NX groups. For the hair and coat traits, the NX and SN groups had lower values of HL and SW than did the AN group. The SN genetic group had lower NHCM2 counts than the NX and AN groups. There were positive correlations between TTC and CT (P<0.05) and SW (P<0.05) in the SN group. No significant correlation was found for the AN genetic group (P>0.05).     

Genetic parameter estimates for postweaning traits of beef cattle in a stressful environment

Postweaning growth data, collected from a Hereford herd located in the Southwest, were used to estimate genetic parameters for weights and gains. The herd was maintained on unsupplemented range forage, and average weight losses from weaning to yearling age were 9% for bulls and 12% for heifers. Data were grouped into years with poor and good environments based on contemporary group means for gain from 8 to 12 mo. Postweaning growth data (12- and 20-mo weights, 8- to 12-mo gain and 12- to 20-mo gain) were analyzed by least squares methods with a model that included year of birth, sire within year of birth, age of dam and a covariate of age for 12- and 20-mo weights. Heritability estimates of 12- and 20-mo weights for bulls were .58 +/- .15 and .55 +/- .22 in good environments vs .32 +/- .11 and 1.09 +/- .15 in poor environments; for heifers these estimates were .19 +/- .08 and .35 +/- .12 in good environments vs .38 +/- .07 and .47 +/- .09 in poor environments. Heritability estimates of 8- to 12-mo and 12- to 20-mo gain for bulls were .32 +/- .14 and .51 +/- .24 in good environments vs .16 +/- .11 and .09 +/- .14 in poor environments; for heifers these estimates were .21 +/- .08 and .14 +/- .10 in good environments vs .10 +/- .06 and .44 +/- .10 in poor environments. Genetic correlations among the preweaning traits of birth and weaning weight and postweaning weight traits were positive and of a moderate to large magnitude, with the exception of birth and 12-mo weight in a poor environment (-.06 +/- .49). Genetic correlations between 8- to 12-mo gain and birth weight in poor environment and weaning weight in all environments were negative (range from -.06 +/- .33 to -.53 +/- .41). Genetic correlations among 12- and 20-mo weights were large and positive in all environments. Relationships among gains were more variable.     

Somatic cell score genetic parameter estimates of dairy cattle in Portugal using fractional polynomials

Milk somatic cell count is an indicator trait for mastitis resistance. Genetic parameters for somatic cell score in the Portuguese Holstein-Friesian population were estimated by modeling the pattern of genetic correlation over the first 3 lactations (days in milk) with a random regression model. Data records from the first 3 lactations were from the national database of the Portuguese Holstein Association herds. Heritability estimates ranged from 0.05 at the beginning of the lactation for the 3 lactations, to 0.07 at the end of the lactation period for the first and third lactations, to 0.09 for the second lactation. This increase in the heritability values was due to an increase in the genetic variance and a decrease in the residual variances. Genetic correlations evaluated for monthly time points were high (0.65 to 0.99) for all 3 lactations, whereas phenotypic correlations were much less than the genetic correlations (0.13 to 0.62).     

Estimation of dominance genetic variances for reproductive traits and growth traits of calves in Japanese Black cattle

The dominance genetic effects for reproductive and calf growth abilities in the practical Japanese Black populations were examined using average information (AI) algorithm restricted maximum likelihood (REML) under animal models. The reproductive traits were observed in Japanese Black cattle maintained at Tottori and Okinawa prefectures, and growth traits of calves were observed in cattle at Okinawa. The average of dominance relationships in Tottori ranged from 0.2 to 0.4%, while the level in Okinawa was lower and sparse compared with Tottori. The proportions of the dominance variances to sum of additive and dominance variances () were all 0.02 for reproductive traits in Tottori. In contrast, the proportion was 0.02–0.64 in Okinawa regardless of the level of dominance relationships. These proportions suggested that the dominance might affect the expression of calving interval, days open and gestation length in Okinawa, where breeding units were spread over many islands. Although the dominance variances could not estimate birthweight, w as 0.34 for calf market weight and 0.27 for average daily gain from birth to calf market in Okinawa. These values also suggested that the dominance might affect the early growth of calves. In the near future, genetic relationships will become more complicated with continuation of the current selection and mating systems. Therefore, genetic evaluation accounting for dominance effects would be necessary for particular traits and populations.     

Phenotypic and genetic parameter estimates for racing traits of Arabian horses in Turkey

The racing records for Arabian horses used in the study were obtained from the Turkish Jockey Club. The traits used in the study were racing time, best racing time, rank, annual earnings, earnings per start, log annual earnings and log earnings per start. Genetic parameters were estimated by the restricted maximum likelihood (REML) procedure using the DFREML program. The effects of age, sex and origin of horse were significant for each trait. The effect of year was significant on time and earning traits, but not rank. The effect of month on time traits was also significant. Heritability estimates of the entire data set were 0.280, 0.281, 0.069, 0.139, 0.174, 0.152 and 0.171 for racing time, best racing time, rank, annual earnings, earnings per start, log annual earnings and log earnings per start respectively. Estimates of repeatability varied from 0.349 to 0.500 for racing time, from 0.430 to 0.524 for best racing time and from 0.129 to 0.171 for rank depending on the data set used in the analyses. Best racing time was the most appropriate trait for selection in this study, as this might lead to genetic improvement than other traits.     

Autoregressive model for genetic evaluation of longitudinal reproductive traits in Brazilian Holstein cattle

Reproductive efficiency is major determinant of the dairy herd profitability. Thus, reproductive traits have been widely used as selection objectives in the current dairy cattle breeding programs. We aimed to evaluate strategies to model days open (DO), calving interval (CI) and daughter pregnancy rate (DPR) in Brazilian Holstein cattle. These reproductive traits were analysed by the autoregressive (AR) model and compared with classical repeatability (REP) model using 127,280, 173,092 and 127,280 phenotypic records, respectively. The first three calving orders of cows from 1,469 Holstein herds were used here. The AR model reported lower values for Akaike Information Criteria and Mean Square Errors, as well as larger model probabilities, for all evaluated traits. Similarly, larger additive genetic and lower residual variances were estimated from AR model. Heritability and repeatability estimates were similar for both models. Heritabilities for DO, CI and DPR were 0.04, 0.07 and 0.04; and 0.05, 0.06 and 0.04 for AR and REP models, respectively. Individual EBV reliabilities estimated from AR for DO, CI and DPR were, in average, 0.29, 0.30 and 0.29 units higher than those obtained from REP model. Rank correlation between EBVs obtained from AR and REP models considering the top 10 bulls ranged from 0.72 to 0.76; and increased from 0.98 to 0.99 for the top 100 bulls. The percentage of coincidence between selected bulls from both methods increased over the number of bulls included in the top groups. Overall, the results of model-fitting criteria, genetic parameters estimates and EBV predictions were favourable to the AR model, indicating that it may be applied for genetic evaluation of longitudinal reproductive traits in Brazilian Holstein cattle.     

Tag-SNP selection using Bayesian genomewide association study for growth traits in Hereford and Braford cattle

The aim of this study was to perform a Bayesian genomewide association study (GWAS) to identify genomic regions associated with growth traits in Hereford and Braford cattle, and to select Tag-SNPs to represent these regions in low-density panels useful for genomic predictions. In addition, we propose candidate genes through functional enrichment analysis associated with growth traits using Medical Subject Headings (MeSH). Phenotypic data from 126,290 animals and genotypes for 131 sires and 3,545 animals were used. The Tag-SNPs were selected with BayesB (π = 0.995) method to compose low-density panels. The number of Tag-single nucleotide polymorphism (SNP) ranged between 79 and 103 SNP for the growth traits at weaning and between 78 and 100 SNP for the yearling growth traits. The average proportion of variance explained by Tag-SNP with BayesA was 0.29, 0.23, 0.32 and 0.19 for birthweight (BW), weaning weight (WW205), yearling weight (YW550) and postweaning gain (PWG345), respectively. For Tag-SNP with BayesA method accuracy values ranged from 0.13 to 0.30 for k-means and from 0.30 to 0.65 for random clustering of animals to compose reference and validation groups. Although genomic prediction accuracies were higher with the full marker panel, predictions with low-density panels retained on average 76% of the accuracy obtained with BayesB with full markers for growth traits. The MeSH analysis was able to translate genomic information providing biological meanings of more specific gene products related to the growth traits. The proposed Tag-SNP panels may be useful for future fine mapping studies and for lower-cost commercial genomic prediction applications.     

Estimation of genetic parameters for ultrasound-predicted percentage of intramuscular fat in Angus cattle using random regression models

The present study included 3,358 observations of 675 bulls and heifers from the Iowa State University beef cattle breeding project. Data were collected over a 3-yr period between 1998 and 2000. Each year, cattle were scanned four to six times for ultrasound-predicted percentage of intramuscular fat (UPFAT) and other ultrasound traits, starting at a minimum age of 28 wk. The objective of the current study was to estimate variance components, heritability, and repeatability of UPFAT in young bulls and heifers. Data were subjected to random-regression animal models that included fixed effects of contemporary group, fixed Legendre polynomial of age at measurement, and random regression coefficients on Legendre polynomial of age at measurement for animals' direct genetic and direct permanent environmental effects. Phenotypic and genetic models involving different levels of polynomial fit for the animal component were considered. A model fitting a linear effect of Legendre polynomial of age at a measurement for animal direct genetic and direct permanent environmental effects and a homogeneous error variance described the present data adequately. Heritability of UPFAT ranged from 0.32 at 28 wk of age to a maximum of 0.53 at 63 wk. Repeatability of UPFAT increased from a minimum of 0.60 at ages of 28 to 39 wk to a maximum of 0.80 at ages 61 to 63 wk. Heritability and repeatability of yearling UPFAT were 0.50 and 0.71, respectively. With the exception of minor differences at earlier ages, fitting heterogeneous error variances did not have an effect on genetic parameter estimates for most ages of measurement. The present results showed an optimal heritability and repeatability of UPFAT measures around 52 wk and through at least 63 wk of age. This suggested that differences in UPFAT measures during this period also are good measures of differences in marbling genetic potential of Angus cattle.     

Test-day somatic cell score, fat-to-protein ratio and milk yield as indicator traits for sub-clinical mastitis in dairy cattle

Test-day (TD) records of milk, fat-to-protein ratio (F:P) and somatic cell score (SCS) of first-lactation Canadian Holstein cows were analysed by a three-trait finite mixture random regression model, with the purpose of revealing hidden structures in the data owing to putative, sub-clinical mastitis. Different distributions of the data were allowed in 30 intervals of days in milk (DIM), covering the lactation from 5 to 305 days. Bayesian analysis with Gibbs sampling was used for model inferences. Estimated proportion of TD records originated from cows infected with mastitis was 0.66 in DIM from 5 to 15 and averaged 0.2 in the remaining part of lactation. Data from healthy and mastitic cows exhibited markedly different distributions, with respect to both average value and the variance, across all parts of lactation. Heterogeneity of distributions for infected cows was also apparent in different DIM intervals. Cows with mastitis were characterized by smaller milk yield (down to -5 kg) and larger F:P (up to 0.13) and SCS (up to 1.3) compared with healthy contemporaries. Differences in averages between healthy and infected cows for F:P were the most profound at the beginning of lactation, when a dairy cow suffers the strongest energy deficit and is therefore more prone to mammary infection. Residual variances for data from infected cows were substantially larger than for the other mixture components. Fat-to-protein ratio had a significant genetic component, with estimates of heritability that were larger or comparable with milk yield, and was not strongly correlated with milk and SCS on both genetic and environmental scales. Daily milk, F:P and SCS are easily available from milk-recording data for most breeding schemes in dairy cattle. Fat-to-protein ratio can potentially be a valuable addition to SCS and milk yield as an indicator trait for selection against mastitis.     

A review of genetic parameter estimates for wool, growth, meat and reproduction traits in sheep

Genetic parameters for a range of sheep production traits have been reviewed from estimates published over the last decade. Weighted means and standard errors of estimates of direct and maternal heritability, common environmental effects and the correlation between direct and maternal effects are presented for various growth, carcass and meat, wool, reproduction, disease resistance and feed intake traits. Weighted means and confidence intervals for the genetic and phenotypic correlations between these traits are also presented. A random effects model that incorporated between and within study variance components was used to obtain the weighted means and variances. The weighted mean heritability estimates for the major wool traits (clean fleece weight, fibre diameter and staple length) and all the growth traits were based on more than 20 independent estimates, with the other wool traits based on more than 10 independent estimates. The mean heritability estimates for the carcass and meat traits were based on very few estimates except for fat (27) and muscle depth (11) in live animals. There were more than 10 independent estimates of heritability for most reproduction traits and for worm resistance, but few estimates for other sheep disease traits or feed intake. The mean genetic and phenotypic correlations were based on considerably smaller numbers of independent estimates. There were a reasonable number of estimates of genetic correlations among most of the wool and growth traits, although there were few estimates for the wool quality traits and among the reproduction traits. Estimates of genetic correlations between the groups of different production traits were very sparse. The mean genetic correlations generally had wide confidence intervals reflecting the large variation between estimates and relatively small data sets (number of sires) used. More accurate estimates of genetic parameters and in particular correlations between economically important traits are required for accurate genetic evaluation and development of breeding objectives.