Genetic parameter estimation for long endurance trials in the Uruguayan Criollo horse.

The aim of this study was to estimate the genetic parameters of performance in a 750-km, 15-day ride in Criollo horses. Heritability (h2 ) and maternal lineage effects (mt2 ) were obtained for rank, a relative placing measure of performance. Additive genetic and maternal lineage (rmt) correlations among five medium-to-high intensity phase ranks (pRK) and final rank (RK) were also estimated. Individual records from 1,236 Criollo horses from 1979 to 2012 were used. A multivariate threshold animal model was applied to the pRK and RK. Heritability was moderate to low (0.156-0.275). Estimates of mt2 were consistently low (0.04-0.06). Additive genetic correlations between individual pRK and RK were high (0.801-0.924), and the genetic correlations between individual pRKs ranged from 0.763 to 0.847. The pRK heritabilities revealed that some phases were explained by a greater additive component, whereas others showed stronger genetic relationships with RK. Thus, not all pRK may be considered as similar measures of performance in competition.

Modelling female fertility traits in beef cattle using linear and non-linear models.

Female fertility traits are key components of the profitability of beef cattle production. However, these traits are difficult and expensive to measure, particularly under extensive pastoral conditions, and consequently, fertility records are in general scarce and somehow incomplete. Moreover, fertility traits are usually dominated by the effects of herd-year environment, and it is generally assumed that relatively small margins are kept for genetic improvement. New ways of modelling genetic variation in these traits are needed. Inspired in the methodological developments made by Prof. Daniel Gianola and co-workers, we assayed linear (Gaussian), Poisson, probit (threshold), censored Poisson and censored Gaussian models to three different kinds of endpoints, namely calving success (CS), number of days from first calving (CD) and number of failed oestrus (FE). For models involving FE and CS, non-linear models overperformed their linear counterparts. For models derived from CD, linear versions displayed better adjustment than the non-linear counterparts. Non-linear models showed consistently higher estimates of heritability and repeatability in all cases (h2  < 0.08 and r < 0.13, for linear models; h2  > 0.23 and r > 0.24, for non-linear models). While additive and permanent environment effects showed highly favourable correlations between all models (>0.789), consistency in selecting the 10% best sires showed important differences, mainly amongst the considered endpoints (FE, CS and CD). In consequence, endpoints should be considered as modelling different underlying genetic effects, with linear models more appropriate to describe CD and non-linear models better for FE and CS.

Genetic parameters of objectionable fibers and of their associations with fleece traits in Corriedale sheep.

The aim of this research was to assess the variability and genetic relationships among binary traits denoting the presence or absence of objectionable fibers, namely pigmented (BINPPF), medullated (BINPMED), and kemp fibers (BINPK), and of fleece traits (fiber diameter [FD] and clean fleece weight [CFW]) in Corriedale sheep. Additionally, the total response to selection against objectionable fibers and indirect responses when selecting for fleece traits were evaluated. Fiber records from 679 animals and fleece records from 795 animals obtained from 2 experimental flocks (from 2005 to 2007) were used; the pedigree file included a total of 3,792 animals. Heritability and genetic correlations among the traits were estimated with a multivariate animal model under a Bayesian setting. Heritability estimates (posterior SD) for BINPPF, BINPMED, and BINPK were 0.35 (0.08), 0.37 (0.10), and 0.63 (0.09), respectively; for CFW and FD, estimates were 0.42 (0.09) and 0.43 (0.08), respectively. The genetic correlations between CFW and the 3 types of objectionable fibers were very low (i.e., <0.2). Thus selection for CFW is not expected to affect the number of such fibers in any direction. The same occurred for the genetic correlation between BINPK and FD. Genetic correlations between FD and BINPMED and FD and BINPPF were positive and favorable (0.50 and 0.56, respectively). Selecting for lower FD would decrease the numbers of objectionable fibers. The expected correlated responses in BINPPF, BINPMED, and BINPK when selecting for CFW were -0.03 (0.11), 0.03 (0.11), and -0.05 (0.18), respectively; when selecting for FD, the correlated responses were -0.26 (0.11), -0.26 (0.11), and -0.14 (0.16). Overall, this study reports novel information on genetic parameters for the presence of objectionable fibers and their associations with fleece traits in sheep. Our findings suggest that it could be possible to improve FD while at the same time reducing the content of BINPMED and BINPPF in wool; however, improvements in CFW are likely to have no effect on the numbers of objectionable fibers.

Genetic relationships among mastitis and alternative somatic cell count traits in the first 3 lactations of Swedish Holsteins.

The objectives of this study were to estimate heritabilities of, and genetic correlations among, clinical mastitis (CM), subclinical mastitis (SCM), and alternative somatic cell count (SCC) traits in the first 3 lactations of Swedish Holstein cows, and to estimate genetic correlations for the alternative traits across lactations. Data from cows having their first calving between 2002 and 2009 were used. The alternative SCC traits were based on information on CM and monthly test-day (TD) records of SCC traits of 178,613, 116,079, and 64,474 lactations in first, second, or third parity, respectively. Sires had an average of 230, 165, or 124 daughters in the data (parities 1, 2, or 3, respectively). Subclinical mastitis was defined as the number of periods with an SCC >150,000 cell/mL and without a treatment for CM. Average TD SCC between 5 and 150 d was used as a reference trait. The alternative SCC traits analyzed were 1) presence of at least 1 TD SCC between 41,000 and 80,000 cell/mL (TD41-80), 2) at least 1 TD SCC >500,000 cells/mL, 3) standard deviation of log SCC over the lactation, 4) number of infection peaks, and 5) average days diseased per peak. The same variables in different parities were treated as distinct traits. The statistical model considered the effects of herd-year, year, month, age at calving, animal, and residual. Heritability estimates were 0.07 to 0.08 for CM, 0.12 to 0.17 for SCM, and 0.14 for SCC150. For the alternative traits, heritability estimates were 0.12 to 0.17 for standard deviation of log SCC, TD SCC >500,000 cells/mL, and average days diseased per peak, and 0.06 to 0.10 for TD41-80 and number of infection peaks. Genetic correlations between CM with SCM were 0.62 to 0.74, and correlations for these traits with the alternative SCC traits were positive and very high (0.67 to 0.82 for CM, and 0.94 to 0.99 for SCM). Trait TD41-80 was the only alternative trait that showed negative, favorable, genetic correlations with CM (-0.22 to -0.50) and SCM (-0.48 to -0.85) because it is associated with healthy cows. Genetic correlations among the alternative traits in all 3 parities were high (0.93 to 0.99, 0.92 to 0.98, and 0.78 to 0.99, respectively). The only exception was TD41-80, which showed moderate to strong negative correlations with the rest of the traits. Genetic correlations of the same trait across parities were in general positive and very high (0.83 to 0.99). In conclusion, these alternative SCC traits could be used in practical breeding programs aiming to improve udder health in dairy cattle.

Assessment of Poisson, probit and linear models for genetic analysis of presence and number of black spots in Corriedale sheep.

Black skin spots are associated with pigmented fibres in wool, an important quality fault. Our objective was to assess alternative models for genetic analysis of presence (BINBS) and number (NUMBS) of black spots in Corriedale sheep. During 2002-08, 5624 records from 2839 animals in two flocks, aged 1 through 6 years, were taken at shearing. Four models were considered: linear and probit for BINBS and linear and Poisson for NUMBS. All models included flock-year and age as fixed effects and animal and permanent environmental as random effects. Models were fitted to the whole data set and were also compared based on their predictive ability in cross-validation. Estimates of heritability ranged from 0.154 to 0.230 for BINBS and 0.269 to 0.474 for NUMBS. For BINBS, the probit model fitted slightly better to the data than the linear model. Predictions of random effects from these models were highly correlated, and both models exhibited similar predictive ability. For NUMBS, the Poisson model, with a residual term to account for overdispersion, performed better than the linear model in goodness of fit and predictive ability. Predictions of random effects from the Poisson model were more strongly correlated with those from BINBS models than those from the linear model. Overall, the use of probit or linear models for BINBS and of a Poisson model with a residual for NUMBS seems a reasonable choice for genetic selection purposes in Corriedale sheep.

Phenotypic and genetic characterization of novel somatic cell count traits from weekly or monthly observations.

The objectives of this study were (1) to explore traits that better capture weekly or monthly changes in somatic cell counts (SCC) than does the commonly used lactation-average SCC, (2) to estimate their heritabilities and relationships to clinical mastitis (CM), and (3) to determine if these traits are feasible for use in monthly testing schemes. Clinical mastitis and weekly test-day (TD) records of SCC and milk production traits from 1,006 lactations of Swedish Red and Holstein cows collected from 1989 to 2004 were used (data set W). A data subset was also created to mimic monthly recording (data set M, 980 lactations). Twenty SCC traits were defined, taking into account SCC general levels and variation along the lactation curve, time and level of infection, and time of recovery. To reduce dimensionality, cluster and stepwise logistic regression procedures were applied. In data set W, 3 traits, "standard deviation of SCC over the lactation," a discrete (0/1) indicator of "at least one TD with SCC >500,000 cells/mL", and "number of days sick in the widest SCC peak" (DWidest) were the variables kept both with cluster procedures and a stepwise logistic regression with the logit of CM as dependent variable. In data set M, DWidest was replaced by "number of SCC peaks" and "average number of days sick per peak" (ADSick). Lactation-average SCC (in the first 150 d or between 150 and 305 d) did not enter into the logistic regression. Heritability estimates obtained for these new traits under a Bayesian setting and a Gibbs sampling approach were 10 to 16% (except for ADSick: 5%). Heritabilities were at least as high in the monthly data set as in the weekly data set. Thus, these SCC traits seem promising for use in breeding programs based on monthly milk recording.

Fertility traits in spring-calving Aberdeen Angus cattle. 2. Model comparison.

The aim of this study was to investigate the possible superiority of a threshold-linear (TL) approach for calving day (CD) and calving success (CS) analysis in beef cattle over 2 multiple-trait (MT), censored models, considering CD at the first 3 calving opportunities. The CD observations on animals that failed to calve in the latter models were defined as cows being assigned a penalty value of 21 d beyond the last observed CD record within contemporary group (PEN model) or censored CD values that were randomly obtained from a truncated normal distribution (CEN-model). In the TL model, CD records were treated as missing if a cow failed to calve, and parameters were estimated in a TL analysis including CS traits (TLMISS-model). The models included the effects of contemporary group (herd x year of calving x mating management), age at calving, physiological status at mating (lactating or nonlactating cow), animal additive genetic effects, and residual. Field data included 6,763 calving records obtained from first, second, and third parities of 3,442 spring-calving Uruguayan Aberdeen Angus cows. Models were contrasted using a data splitting technique, analyzing correlations between predicted breeding values (PBV) for each pair of subsamples, by rank correlations between PBV obtained with the different models, and by inspecting percentage of sires selected in common using the different approaches at 10 and 25% hypothetical percentages of animals selected. Breeding value correlations of CD between the subsamples for the TLMISS approach were greater (0.67 to 0.68) than correlations for the censored MT models (0.49 to 0.54). Average correlations between PBV of CD in 1 subsample obtained by CEN (PEN, TLMISS) and PBV of CS in the other subsample were -0.53 (-0.55, -0.60) in the first calving opportunity (CO), -0.54 (-0.58, -0.63) in the second CO, and -0.50 (-0.49, -0.58) in the third CO. Rank correlations between PBV for CD in PEN and CEN were high (0.93 to 0.97), but correlations of either method with PBV of CD in TLMISS ranged from 0.50 to 0.71. Common identification of bulls for the top 10% of sires (25% of sires), when selected with PEN/CEN models or the TLMISS model, varied between 50 (44%) and 60 (52%). The use of the TL animal model for genetic evaluation seems attractive for genetic evaluation of fertility traits in beef cattle.

Fertility traits in spring-calving Aberdeen Angus cattle. 1. Model development and genetic parameters.

Calving records (n = 6,763) obtained from first, second, and third parities of 3,442 spring-calving, Uruguayan Aberdeen Angus cows were used to estimate heritabilities and genetic correlations for the linear trait calving day (CD) and the binary trait calving success (CS), using models that considered CD and CS at 3 calving opportunities as separate traits. Three approaches were defined to handle the CD observations on animals that failed to calve: 1) the cows were assigned a penalty value of 21 d beyond the last observed CD record within contemporary group (PEN); 2) the censored CD values were randomly obtained from a truncated normal distribution (CEN); and 3) the CD records were treated as missing, and the parameters were estimated in a joint threshold-linear analysis including CS traits (TLMISS). The models included the effects of contemporary group (herd x year of calving x mating management), age at calving (3 levels), physiological status at mating (nonlactating or lactating), animal additive genetic effects, and residual. Estimates of heritability for CD traits in the PEN and CEN data sets ranged from 0.20 to 0.31, with greater values in the first calving opportunity. Genetic correlations were positive and medium to high in magnitude, 0.57 to 0.59 in the PEN data set and 0.38 to 0.91 in the CEN data set. In the TLMISS data set, heritabilities ranged from 0.19 to 0.23 for CD and 0.37 to 0.42 for CS. Genetic correlations between CD traits varied between 0.82 and 0.88; between CS traits, genetic correlations varied between 0.56 and 0.80. Negative (genetically favorable), medium to high genetic correlations (-0.54 to -0.91) were estimated between CD and CS traits, suggesting that CD could be used as an indicator trait for CS. Data recording must improve in quality for practical applications in genetic evaluation for fertility traits.

Genetic variability in calving success in Aberdeen Angus cows under extensive recording.

Data from 2032 Uruguayan Aberdeen Angus cows under extensive management and recording practices were analysed with Bayesian threshold-liability sire models, to assess genetic variability in calving success (CS), defined as a different binary trait for each of the second (CS2), third (CS3) and fourth (CS4) calving opportunities. Sire (herd) variances ranged from 0.08 to 0.11 (0.10 to 0.20) and heritability from 0.27 to 0.35, with large credibility intervals. Correlations between herd effects on CS at different calving opportunities were positive. Genetic correlation between CS2 and CS4 was positive (0.68), whereas those involving adjacent calving opportunities (CS2-CS3 and CS3-CS4) were negative, at -0.39 and -0.54, respectively. The residual correlation CS2-CS3 was negative (-0.32). The extent of uncertainty associated with the posterior estimates of the parameters was further evaluated through simulation, assuming different true values (-0.4, -0.2, +0.2 and +0.4) for the genetic correlations and changes in the degree of belief parameters of the inverse Wishart priors for the sire covariance matrix. Although inferences were not sharp enough, CS appears to be moderately heritable. The quality of data recording should be improved, in order to effect genetic improvement in female fertility.