Threshold-linear Animal Model Research Articles

Testicular hypoplasia in Nellore Cattle: Genetic analysis and functional analysis of genome-wide association study results.

Characterized by the incomplete development of the germinal epithelium of the seminiferous tubules, Testicular hypoplasia (TH) leads to decreased sperm concentration, increased morphological changes in sperm and azoospermia. Economic losses resulting from the disposal of affected bulls reduce the efficiency of meat production systems. A genome-wide association study and functional analysis were performed to identify genomic windows and the underlying positional candidate genes associated with TH in Nellore cattle. Phenotypic and pedigree data from 207,195 animals and genotypes (461,057 single nucleotide polymorphism, SNP) from 17,326 sires were used in this study. TH was evaluated as a binary trait measured at 18 months of age. A possible correlated response on TH resulting from the selection for scrotal circumference was evaluated by using a two-trait analysis. Thus, estimated breeding values were calculated by fitting a linear-threshold animal model in a Bayesian approach. The SNP effects were estimated using the weighted single-step genomic BLUP method. Twelve non-overlapping windows of 20 adjacent SNP that explained more than 1% of the additive genetic variance were selected for candidate gene annotation. Functional and gene prioritization analysis of the candidate genes identified genes (KHDRBS3, GPX5, STAR, ERLIN2), which might play an important role in the expression of TH due to their known roles in the spermatogenesis process, synthesis of steroids and lipid metabolism.

Bayesian estimation of the genetic relationship of survival traits from birth to yearling age with birth weight in Guilan sheep.

This study aimed to estimate genetic parameters for cumulative survival traits from birth to yearling age and to estimate their genetic relationship with birth weight in Guilan sheep. The dataset used in this study comprised 41,037 survival records of Guilan lambs born from 496 sires and 10,256 dams, collected by the Guilan Province Agricultural Jihad Organization (in Rasht, Iran) during 1990-2013. The data included complete pedigree information; gender; year, month, and day of death; dam age; year, month, and day of birth; birth type; and birth weight. Cumulative survival traits from birth to yearling age were analyzed using threshold animal models via the Bayesian method. Also, linear-threshold animal models were used to study the genetic relationship between survival at different ages and birth weight. Direct heritability estimates of cumulative survival from birth to 60, 90, 180, 270, and 365days of age were low and equal to 0.17, 0.16, 0.08, 0.04, and 0.04, respectively, and the corresponding maternal heritability estimates were 0.21, 0.18, 0.15, 0.08 and 0.08, respectively. Mean estimates of direct genetic correlations between birth weight and survival traits were medium (from 0.22 to 0.28). To improve the survival traits, more emphasis must be put on the amelioration of the non-genetic factors affecting it. Indirect selection based on traits high genetically correlated with survival could increase the survival rate in Guilan lambs.

Genetic parameters for worm resistance in Santa Inês sheep using the Bayesian animal model.

ObjectiveThe objective of this study was to estimate the genetic parameters for worm resistance (WR) and associated characteristics, using the linear-threshold animal model via Bayesian inference in single- and multiple-trait analyses.MethodsData were collected from a herd of Santa Inês breed sheep. All information was collected with animals submitted to natural contamination conditions. All data (number of eggs per gram of feces [FEC], Famacha score [FS], body condition score [BCS], and hematocrit [HCT]) were collected on the same day. The animals were weighed individually on the day after collection (after 12-h fasting). The WR trait was defined by the multivariate cluster analysis, using the FEC, HCT, BCS, and FS of material collected from naturally infected sheep of the Santa Inês breed. The variance components and genetic parameters for the WR, FEC, HCT, BCS, and FS traits were estimated using the Bayesian inference under the linear and threshold animal model.ResultsA low magnitude was obtained for repeatability of worm-related traits. The mean values estimated for heritability were of low-to-high (0.05 to 0.88) magnitude. The FEC, HCT, BCS, FS, and body weight traits showed higher heritability (although low magnitude) in the multiple-trait model due to increased information about traits. All WR characters showed a significant genetic correlation, and heritability estimates ranged from low (0.44; single-trait model) to high (0.88; multiple-trait model).ConclusionTherefore, we suggest that FS be included as a criterion of ovine genetic selection for endoparasite resistance using the trait defined by multivariate cluster analysis, as it will provide greater genetic gains when compared to any single trait. In addition, its measurement is easy and inexpensive, exhibiting greater heritability and repeatability and a high genetic correlation with the trait of resistance to worms.

Genetic relationships of fertility traits with test-day milk yield and fat-to-protein ratio in tropical smallholder dairy farms.

The test-day milk fat-to-protein ratio (TD-FPR) could serve as a measure of energy balance status and might be used as a criterion to improve metabolic stability and fertility through genetic selection. Therefore, genetic parameters for fertility traits, test-day milk yield (TD-MY) and TD-FPR, as well as, their relationships during different stages of lactation, were estimated on data collected from 25 968 primiparous Thai dairy crossbred cows. Gibbs sampling algorithms were implemented to obtain (co)variance components using both univariate linear and threshold animal models and bivariate linear-linear and linear-threshold animal models with random regression. Average TD-MY and TD-FPR were 12.60 and 1.15. Heritability estimates for TD-MY, TD-FPR and selected fertility traits ranged from 0.31 to 0.58, 0.17 to 0.19 and 0.02 to 0.05, respectively. Genetic correlations among TD-FPR and TD-MY, TD-FPR and fertility traits, and TD-MY and fertility traits ranged from 0.05 to -0.44, from -0.98 to 0.98 and -0.22 to 0.79, respectively. Selection for lower TD-FPR would decrease numbers of inseminations per conception and increase conception at first service and pregnancy within 90 days. In addition, cow selection based only on high milk production has strong effects to prolong days to first service, days open and calving interval.

Comparison of models for estimating genetic parameters and predicting breeding values for birth weight and calving ease in Czech Charolais cattle

The most appropriate model for genetic parameters estimation for calving ease and birth weight in beef cattle was selected. A total of 27 402 field records were available from the Czech Charolais breed. For estimation of genetic parameters for calving ease and body weight, three bivariate models were tested: a linear-linear animal model (L-LM) with calving ease classified into four categories (1 – easy; 2–4 – most difficult), a linear-linear animal model (SC-LM) in which calving ease scores were transformed into Snell scores (Snell 1964) and expressed as percentage of assisted calving (ranging 0–100%), and a bivariate threshold-linear animal model (T-LM) with calving ease classified into four categories (1 – easy, 2–4 – most difficult). All tested models included fixed effects for contemporary group (herd × year × season), age of dam, sex and breed of a calf. Random effects included direct and maternal genetic effects, maternal permanent environmental effect, and residual error. Direct heritability estimates for calving ease and birth weight were, with the use of L-LM, SC-LM, and T-LM, from 0.096 ± 0.013 to 0.226 ± 0.024 and from 0.210 ± 0.024 to 0.225 ± 0.026, respectively. Maternal heritability estimates for calving ease and birth weight were, with the use of L-LM, SC-LM, and T-LM, from 0.060 ± 0.031 to 0.104 ± 0.125 and from 0.074 ± 0.041 to 0.075 ± 0.040, respectively. Genetic correlations of direct calving ease with direct birth weight ranged from 0.46 ± 0.06 to 0.50 ± 0.06 for all tested models; whereas maternal genetic correlations between these two traits ranged from 0.24 ± 0.17 to 0.25 ± 0.53. Correlations between direct and maternal genetic effects within-trait were negative and substantial for all tested models (ranging from –0.574 ± 0.125 to –0.680 ± 0.141 for calving ease and from –0.553 ± 0.122 to –0.558 ± 0.118 for birth weight, respectively), illustrating the importance of including this parameter in calving ease evaluations. Results indicate that any of the tested models could be used to reliably estimate genetic parameters for calving ease for beef cattle in the Czech Republic. However, because of advantages in computation time and practical considerations, genetic analysis using SC-LM (transformed data) is recommended.

Genetic analysis of twinning rate and milk yield using a threshold‐linear model in Japanese Holsteins

The objective of this study was to estimate genetic parameters and breeding values for the twinning rate of the first three parities (T1, T2 and T3) and 305-day milk yield in first lactation (MY), using a four-trait threshold-linear animal model in Japanese Holsteins. Data contained 1 323 946 cows calving between 1990 and 2007. Twinning was treated as a binary character: 'single' or 'twin or more'. Reported T1, T2 and T3 were 0.70%, 2.87%, and 3.73%, respectively. Individual 305-day milk yield was computed using a multiple trait prediction for cows with at least eight test-day records. (Co)variance components were estimated via Gibbs sampling for randomly sampled subsets. Posterior means of heritabilities for T1, T2 and T3 were 0.11, 0.16 and 0.14, respectively. Genetic correlations between parities were 0.92 or greater. Genetic correlations of MY with twinning rate were not 'significant' (i.e. their 95% highest probability density intervals contained zeros). Multiple births at different parities were considered as the same genetic trait. The average evaluations of T1 (T2) for sires born before 1991 was 0.48% (2.25%) compared with a mean of 0.76% (3.37%) for sires born after 1992. A recent increase in the reported twinning rate reflects the positive genetic trend for sires in Japanese Holsteins.

Estimation of regional genetic parameters for mortality and 305-d milk yield of US Holsteins in the first 3 parities

Several research reports have indicated increasing dairy cow mortality in recent years. The objectives of this research were to characterize the phenotypic differences in mortality in the first 3 parities across 3 regions of the United States to estimate the heritability of mortality of Holstein cows across regions and parities, and to estimate genetic and environmental correlations between milk yield and mortality across parities and regions. Dairy Herd Information (DHI) milk yield and mortality data were obtained from 3 different US regions: the Southeast (SE), Southwest (SW), and Northeast (NE). A total of 3,522,824 records for the first 3 parities were used: 732,009 (SE), 656,768 (SW), and 2,134,047 (NE) from 1999 to 2008. Cows that received a termination code of 6—“Cow died on the dairy; downer cows that were euthanized should be included here”—were given a mortality score of 2 (dead), whereas all other codes were assigned a mortality score of 1 (alive). Average annual mortalities in the first 3 parities across regions ranged from 2.2 to 7.2%, with mortality frequency increasing with increasing parity across all regions and with the SE having the highest mortality frequency. For genetic analysis, a 2-trait (305-d milk yield and mortality) linear-threshold animal model that fitted fixed effects of herd-year (for 305-d milk yield), cow age, days in milk (in month classes), month-of-termination, and random effects of herd-year (for mortality), animal, and residual was implemented. The model was used to estimate variance components separately for each region and parity. Heritability estimates for mortality were similar for all regions and parities, ranging from 0.04 to 0.07. Genetic correlations between mortality and 305-d milk yield across the first 3 parities were 0.14, 0.20, and 0.29 in SE; −0.01, 0.01, and 0.31 in SW; and 0.28, 0.33, and 0.19 in NE. We detected an adverse genetic relationship between milk production and mortality; however, the moderate magnitudes of the genetic correlations suggest that indices that include both milk yield and mortality could be effective in identifying sires that would provide opportunities for minimizing death loss even when selecting for increased milk yield.

Genetic analyses of binary longitudinal health data in small low input dairy cattle herds using generalized linear mixed models

Genetic parameters were inferred for the health traits mastitis, metritis, retained placenta, ovarian cysts and acetonemia from 1247 Brown Swiss cows in first parity kept in 53 organic and low input farms in Switzerland. For genetic analyses, univariate animal and sire models, repeatability animal and sire models, and random regression sire models (RRM) in a “generalized linear mixed model (GLMM) context” were applied. The five health traits were defined as binary data, count data, and longitudinal binary data in the interval between −1 and 120d in milk (DIM). Firstly, binary data were analyzed by applying linear animal and sire models, and threshold animal and sire models with a probit link function. Secondly, data of total number of disease cases recorded within the defined time span were analyzed by using GLMM animal and sire models with a log link function for Poisson distributed count data. Thirdly, for longitudinal health data, linear repeatability animal and sire models, linear sire RRM, threshold animal and sire repeatability models, and threshold sire RRM with a probit link function were applied. Disease incidences of the five health disorders in organic farms were on a generally low level, with a highest incidence of 5.78% for mastitis within the time span of 120d. With regard to mastitis, moderate heritabilities with an average value of 0.15 were realized from univariate models and binary data, and from GLMM with the log link function and count data. Heritabilities for mastitis were smaller (<0.10) when using the longitudinal data structure in combination with repeatability models and RRM. Repeatabilities and heritabilities for longitudinal data as realized from repeatability models were on a quite similar level. Only for longitudinal ovarian cysts, heritabilities substantially differed from repeatabilities. Heritability was 0.02 from the animal model and 0.01 from the sire model, but repeatabilities were 0.14, which indicates a substantial permanent environmental effect. Daily heritabilities for all health traits from linear and threshold RRM at the beginning of lactation and at the end of the defined interval were three times higher than corresponding heritabilities in the middle of lactation. Bayesian information criterion (BIC) and heritabilities themselves favored threshold models over linear models. However, linear models converged more easily than threshold models, and genetic parameter estimates had smaller standard errors. Similar BIC values were found when comparing animal with sire models, although generally higher heritabilities were realized from sire models. For RRM applications, BIC was smaller and heritabilities were higher for linear sire compared to threshold sire models.

Ranking of Nellore animals in cattle championships: genetic parameters and correlations with production traits.

Records of 17,141 Nellore cattle participating in cattle championships, born from 1994-2009, were used to estimate genetic parameters between animal rank in cattle championships, evaluated from weaning to 36 months of age as repeated traits, and growth, fertility, and carcass traits, evaluated at 365 days of age as single traits. Two traits were defined for animal rank in cattle championships: value 1 was attributed to animals ranked from 1st to 3rd place within the age category, and value 0 was assigned to the remaining animals (TOP3). Value 1 was attributed to animals ranked from 1st to 5th place within the age category and value 0 was assigned to the remaining animals (TOP5). The (co)variance components were estimated based on Bayesian inference under a 2-trait threshold-linear animal model. The posterior means of heritability estimated for TOP3 and TOP5 were 0.182 ± 0.010 and 0.260 ± 0.012, respectively, and their repeatabilities were 0.341 ± 0.007 and 0.400 ± 0.007, respectively. High-ranking animals generally presented higher breeding values for body weight, height, body length, and heart girth. The phenotypic correlations indicate that judges of cattle championships primarily rank animals based on weight and heart girth.

Estimation of genetic parameters for birth weight, preweaning mortality, and hot carcass weight of crossbred pigs1

Genetic parameters for birth weight (BWT), preweaning mortality (PWM), and HCW were estimated for a crossbred pig population to determine if BWT could be used as an early predictor for later performances. Sire genetic effects for those traits were estimated to determine if early selection of purebred sires used in crossbreeding could be improved. Data were recorded from 1 commercial farm between 2008 and 2010. Data were from 24,376 crossbred pigs from Duroc sires and crossbred Large White × Landrace dams and included 24,376 BWT and PWM records and 13,029 HCW records. For the analysis, PWM was considered as a binary trait (0 for live or 1 for dead piglet at weaning). A multitrait threshold-linear animal model was used, with animal effect divided into sire genetic and dam effects; the dam effects included both genetic and environmental variation due to the absence of pedigree information for crossbred dams. Fixed effects were sex and parity for all traits, contemporary groups for BWT and HCW, and age at slaughter as a linear covariable for HCW. Random effects were sire additive genetic, dam, litter, and residual effects for all traits and contemporary group for PWM. Heritability estimates were 0.04 for BWT, 0.02 for PWM, and 0.12 for HCW. The ratio between sire genetic and total estimated variances was 0.01 for BWT and PWM and 0.03 for HCW. Dam and litter variances explained, respectively, 14% and 15% of total variance for BWT, 2% and 10% for PWM, and 3% and 8% for HCW. Genetic correlations were -0.52 between BWT and PWM, 0.55 between BWT and HCW, and -0.13 between PWM and HCW. Selection of purebred sires for higher BWT of crossbreds may slightly improve survival until weaning and final market weight at the commercial level.

Relationships between conception rate in Holstein heifers and cows and milk yield at various stages of lactation

We investigated the relationships between conception rates (CRs) at first service in Japanese Holstein heifers (i.e. animals that had not yet had their first calf) and cows and their test-day (TD) milk yields. Data included records of artificial insemination (AI) for heifers and cows that had calved for the first time between 2000 and 2008 and their TD milk yields at 6 through 305 days in milk (DIM) from first through third lactations. CR was defined as a binary trait for which first AI was a failure or success. A threshold-linear animal model was applied to estimate genetic correlations between CRs of heifers or cows and TD milk yield at various lactation stages. Two-trait genetic analyses were performed for every combination of CR and TD milk yield by using the Bayesian method with Gibbs sampling. The posterior means of the heritabilities of CR were 0.031 for heifers, 0.034 for first-lactation cows and 0.028 for second-lactation cows. Heritabilities for TD milk yield increased from 0.324 to 0.433 with increasing DIM but decreased slightly after 210 DIM during first lactation. These heritabilities from the second and third lactations were higher during late stages of lactation than during early stages. Posterior means of the genetic correlations between heifer CR and all TD yields were positive (range, 0.082 to 0.287), but those between CR of cows and milk yields during first or second lactation were negative (range, −0.121 to −0.250). Therefore, during every stage of lactation, selection in the direction of increasing milk yield may reduce CR in cows. The genetic relationships between CR and lactation curve shape were quite weak, because the genetic correlations between CR and TD milk yield were constant during the lactation period.

Genetic correlation between growth and female and male contributions to fertility in rabbit

A Bayesian bivariate Linear-Threshold Animal Model was implemented to determine the genetic correlation between fertility (F), defined as success or failure to conceive, and average daily gain (ADG) in a rabbit line selected for ADG. A total of 27 234 records of F from 7895 females and 1293 males, and 114 135 records of ADG were used for the analysis. The pedigree included 114 485 animals. The model used for ADG included the systematic effects of year-season, parity order and number of kids born alive, the animal additive effect, the maternal and paternal permanent environmental effects, the common litter permanent environmental effect and the residual. The model for the liability of F included the systematic effects of year-season and physiological status of the female, the female and male additive genetic effects, the female and male permanent environmental effects and the residual, which was divided into a permanent environmental effect related to the common litter effect for ADG, and an independent term. The estimated heritabilities were 0.15 for ADG and 0.07 and 0.04 for the female and male contributions to F, respectively. Male and female contributions to F had a positive genetic correlation (0.34). The genetic correlation between ADG and the female component of F was low to moderate and negative (-0.31), whereas it was null for the male contribution to F. Thus, it is expected that only the female contribution to reproductive performance may be impaired by selection for ADG in rabbit lines.

Validation of alternative models in genetic evaluation of racing performance in North Swedish and Norwegian cold-blooded trotters

There have been several approaches to the estimation of breeding values of performance in trotters, and the objective of this study was to validate different alternatives for genetic evaluation of racing performance in the North Swedish and Norwegian cold-blooded trotters. The current bivariate approach with the traits racing status (RACE) and earnings (EARN) was compared with a threshold-linear animal model and the univariate alternative with the performance trait only. The models were compared based on cross-validation of standardized earnings, using mean-squared errors of prediction (MSEP) and the correlation between the phenotype (Y) and the estimated breeding value (EBV). Despite possible effects of selection, a rather high estimate of heritability of EARN was found in our univariate analysis. The genetic trend estimate for EARN was clearly higher in the bivariate specification than in the univariate model, as a consequence of the considerable size of estimated heritability of RACE and its high correlation with EARN (approximately 0.8). RACE is highly influenced by ancestry rather than the on-farm performance of the horse itself. Consequently, the use of RACE in the genetic analysis may inflate the genetic trend of EARN because of a double counting of pedigree information. Although, because of the higher predictive ability of the bivariate specification, the improved ranking of animals within a year-class and the inability to discriminate between models for genetic trend, we propose to base prediction of breeding values on the current bivariate model.

Bayesian genetic parameters for body weight and survival of Nile tilapia farmed in Brazil

The objective of this study was to estimate genetic parameters for survival and weight of Nile tilapia (Oreochromis niloticus), farmed in cages and ponds in Brazil, and to predict genetic gain under different scenarios. Survival was recorded as a binary response (dead or alive), during harvest time in the 2008 grow-out period. Genetic parameters were estimated using a Bayesian mixed linear-threshold animal model via Gibbs sampling. The breeding population consisted of 2,912 individual fish, which were analyzed together with the pedigree of 5,394 fish. The heritabilities estimates, with 95% posterior credible intervals, for tagging weight, harvest weight and survival were 0.17 (0.09-0.27), 0.21 (0.12-0.32) and 0.32 (0.22-0.44), respectively. Credible intervals show a 95% probability that the true genetic correlations were in a favourable direction. The selection for weight has a positive impact on survival. Estimated genetic gain was high when selecting for harvest weight (5.07%), and indirect gain for tagging weight (2.17%) and survival (2.03%) were also considerable.

A Bayesian threshold-linear model evaluation of perinatal mortality, dystocia, birth weight, and gestation length in a Holstein herd

The objective of this research was to estimate genetic parameters for a multiple-trait evaluation of dystocia (DYS), perinatal mortality (PM), birth weight (BWT), and gestation length (GL) in Holsteins. The data included 5,712 calving records collected between 1968 and 2005 from the Iowa State University dairy breeding herd in Ankeny. The incidence of PM was 8.8% and that of DYS 28.8%; mean BWT was 40.5kg, and GL was 279 d. A threshold-linear animal model included the effects of year, season, sex of calf, parity, sire group, direct genetic, maternal genetic, and maternal permanent environment. Direct heritabilities for DYS, PM, BWT, and GL were 0.11 (0.04), 0.13 (0.05), 0.26 (0.04), and 0.51 (0.05), respectively. Maternal heritabilities were 0.14 (0.04), 0.15 (0.03), 0.08 (0.01), and 0.08 (0.02), for DYS, PM, BWT, and GL, respectively. The heritabilities are the posterior means of the Gibbs samples with their standard deviations in parentheses. The direct genetic correlation between PM and DYS was estimated at 0.67 (0.19), whereas the maternal genetic correlation was 0.45 (0.16). Direct and maternal PM and DYS are partially controlled by the same genes. Selection on only calving ease is not sufficient to control PM. With moderate genetic correlations between all 4 traits, BWT and GL should be included with DYS and PM in an evaluation of calving performance.

Análise bayesiana na estimação de correlações genéticas entre escores visuais e características reprodutivas de bovinos Nelore utilizando modelos linear-limiar

Estimaram-se as correlações genéticas entre os escores visuais e as características reprodutivas, utilizando a estatística bayesiana sob modelo animal linear-limiar, em bovinos da raça Nelore. Foram estudadas características categóricas morfológicas, avaliadas visualmente aos oito, 15 e 22 meses de idade; e características contínuas de perímetro escrotal padronizado aos 365 e 450 dias de idade, além da idade ao primeiro parto. As estimativas de correlações genéticas foram de sentido favorável à seleção, apresentando magnitudes moderadas, sugerindo que a seleção de animais para um biótipo desejável pode levar a animais com maior fertilidade e precocidade sexual. As estimativas de correlação genética para o perímetro escrotal padronizado aos 450 dias e a idade ao primeiro parto com as características morfológicas avaliadas aos 22 meses de idade foram maiores do que as obtidas entre as características de escores visuais avaliadas aos oito e 15 meses de idade. A utilização de escores visuais como critério de seleção trará progresso genético também para as características reprodutivas.

Linear–threshold animal model for birth weight, gestation length and calving ease in United Kingdom Limousin beef cattle data

Breeding value evaluation for UK Limousin beef cattle data was carried out by multiple-trait linear–threshold animal model with variance components assumed to be known. Polychotomous calving ease with five categories was analysed with two continuous traits: birth weight and gestation length. Field data consisted of 220,799 animals with observations with every possible combination of traits, and 270,035 animals in the pedigree. The threshold model was solved either with Newton Raphson or Expectation Maximisation algorithm, and solutions were compared to evaluation by a linear model with original and normalised scores. There were insignificant differences in solutions between the two algorithms for threshold model analyses. Furthermore, solutions of the continuous traits were similar by the threshold and linear models. For the categorical trait, correlations for random effects from the threshold and linear models were high. In case of normalised scores (original scores case in brackets) correlations with solutions from the threshold and linear model were 0.97 (0.94) and 0.97 (0.93) for direct and maternal genetic effects and 0.95 (0.89) for permanent maternal effects. Even so, at least one third of the top 1% ranking of bulls differed between the linear and the threshold models. Predictive abilities as correlations between estimated breeding values and pedigree indices were almost equal between the linear and threshold models for both continuous and categorical traits. In conclusion, despite the higher computational demand, the linear–threshold animal model can be seen worthwhile in the genetic evaluation of the national UK beef cattle data set.

ESTIMATIVAS DE CORRELAÇÕES GENÉTICAS ENTRE ESCORES VISUAIS E CARACTERÍSTICAS DE CRESCIMENTO EM BOVINOS DA RAÇA NELORE UTILIZANDO MODELOS BAYESIANOS LINEAR-LIMIAR

The objective of this paper was to study the genetic correlations of the visual scores traits with the growth continuous traits, by applying bayesian statistic methodology, using two-trait analyses under linear-threshold animal models. The morphological categorical traits of musculature, physical structure, conformation and sacrum were studied in animals of the Nelore breed at the age of 8, 15 and 22 months, and also in adult cows; and the growth continuous traits, weights at the age of 210, 365 and 450 days old, as well as the adult weight of the cow. Estimates of genetic correlations between these visual scores (musculature, physical structure and conformation) with the growth traits were favorably positive, indicating that the selection of one of them will bring genetic progress to another. The results achieved in this study also indicated that the physical structure and the conformation are determined, to a large extent, by the same sets of genes as the weight. In the same way, the evaluated visual scores in adult cows presented high genetic correlations with the adult weight of the cow. As concerning the sacrum, the estimates of genetic correlations were low and negative. KEY WORDS: Gibbs sampler, morphological traits, weights, zebu cattle.

Selection for a QTL trait in a realistic multiple-trait scenario in a simulated animal population

Responses to different modes of single-trait selection on a trait with identified quantitative trait locus (QTL trait) and multiple-trait selection on a QTL trait and genetically correlated binary traits were studied. The aim was to identify the selection mode which most efficiently lowered the prevalence of a QTL trait or of a QTL trait and correlated binary traits under conditions encountered in animal breeding. Simulated data resembling a multiple-trait scenario including one QTL trait in a realistic setting with respect to the number of individuals with available phenotype, genotype or phenotype and genotype information were used to study selection responses after one generation. Selection responses were defined as prevalence changes of the binary traits in the offspring of selected sires relative to the prevalence in the offspring of all sires. Simulations were performed for two different levels of heritability of the QTL trait (0.2, 0.4), two different proportions of genetic variance of this trait explained by the QTL (0.5, 0.1) and two different frequencies of the favorable QTL allele (0.5, 0.2). Genetic parameters for the simulated populations were estimated in mixed linear-threshold animal models using Gibbs sampling. Single-trait selection reduced the prevalence of the QTL trait relatively by up to 10% when based on phenotype, by up to 41% when based on genotype or genotype and phenotype, and by up to 81% when based on polygenic BV and genotype of the QTL trait. At the same time, the prevalences of the correlated binary traits were almost unchanged. Multiple-trait selection based on polygenic BV, polygenic BV and QTL genotype or overall BV simultaneously reduced the prevalences of all binary traits by 20–55%. Relative prevalence decrease of the QTL trait under multiple-trait selection was largest when selecting only sires with homozygous favorable QTL genotype and above-average total index derived from polygenic BV. Low proportions of individuals homozygous for the favorable QTL allele may limit practicability of most efficient single- and multiple-trait selection schemes, so selection of individuals with above-average BV which are homo- or heterozygous for the favorable QTL allele is recommended to quickly achieve relevant selection response, while keeping sufficient numbers of breeding animals. Advantages of combined use of phenotype and genotype information were obvious even under practical conditions of small numbers of individuals with trait information, low heritability of the QTL trait, small proportion of genetic variance explained by the QTL, and low frequency of the favorable QTL allele.

Bayesian prediction of breeding values for multivariate binary and continuous traits in simulated horse populations using threshold–linear models with Gibbs sampling

Simulated data were used to determine the properties of multivariate prediction of breeding values for categorical and continuous traits using phenotypic, molecular genetic and pedigree information by mixed linear–threshold animal models via Gibbs sampling. Simulation parameters were chosen such that the data resembled situations encountered in Warmblood horse populations. Genetic evaluation was performed in the context of the radiographic findings in the equine limbs. The simulated pedigree comprised seven generations and 40 000 animals per generation. The simulated data included additive genetic values, residuals and fixed effects for one continuous trait and liabilities of four binary traits. For one of the binary traits, quantitative trait locus (QTL) effects and genetic markers were simulated, with three different scenarios with respect to recombination rate (r) between genetic markers and QTL and polymorphism information content (PIC) of genetic markers being studied: r = 0.00 and PIC = 0.90 (r0p9), r = 0.01 and PIC = 0.90 (r1p9), and r = 0.00 and PIC = 0.70 (r0p7). For each scenario, 10 replicates were sampled from the simulated horse population, and six different data sets were generated per replicate. Data sets differed in number and distribution of animals with trait records and the availability of genetic marker information. Breeding values were predicted via Gibbs sampling using a Bayesian mixed linear–threshold animal model with residual covariances fixed to zero and a proper prior for the genetic covariance matrix. Relative breeding values were used to investigate expected response to multi- and single-trait selection. In the sires with 10 or more offspring with trait information, correlations between true and predicted breeding values ranged between 0.89 and 0.94 for the continuous traits and between 0.39 and 0.77 for the binary traits. Proportions of successful identification of sires of average, favourable and unfavourable genetic value were 81% to 86% for the continuous trait and 57% to 74% for the binary traits in these sires. Expected decrease of prevalence of the QTL trait was 3% to 12% after multi-trait selection for all binary traits and 9% to 17% after single-trait selection for the QTL trait. The combined use of phenotype and genotype data was superior to the use of phenotype data alone. It was concluded that information on phenotypes and highly informative genetic markers should be used for prediction of breeding values in mixed linear–threshold animal models via Gibbs sampling to achieve maximum reduction in prevalences of binary traits.