Sire-maternal Grandsire Model Research Articles

An approach to functional longevity in Latxa dairy sheep

Productivity and profitability of sheep farming are strongly influenced by the productive performance of ewe during it lifetime. For that, it is relevant to quantify the genetic and non-genetic factors affecting functional longevity in order to consider its inclusion as a trait in a breeding scheme. In this investigation, a Weibull proportional hazard model was applied to study the length of productive live as functional longevity indicator in Latxa dairy sheep breeds. The time from the first calving to the date of culling was individually calculated using records from 28,466 Latxa Cara Rubia (LCR), 26,045 Latxa Cara Negra from Euskadi (LCNEAE) and 10,385 Latxa Cara Negra from Navarre (LCNNAF) from commercial flocks, born between 2000 and 2018. The culling risk associated to the age at first lambing, number of lambs born per lambing and total milk yield produced per lactation was estimated using a likelihood ratio test, and the genetic component of longevity was estimated using a sire-maternal grandsire model. The results concerning the relative culling risk showed that ewes having their first lambing at 2 years of age had around 1.30 times more risk of disposal compared with those of 1 year, regardless of the Latxa population. Similarly, it was found that LCR and LCNEAE having 2 o 3 lambs born per lambing had 1.20 and 1.34 higher risk to be culled in comparison to having 1 lamb, whereas the risk was 1.04 in LCNNAF. In contrast, the probability to be culled was drastically reduced by around 1.50 in all the Latxa populations as the milk yield moved from low to intermediate levels and by around 3.0 times when it moved from low to high. Regarding the genetic parameters of longevity, heritability values ranged from 0.042 to 0.061, which indicates that it is under low additive genetic control. Furthermore, a decreasing genetic was observed, although the decrease rate was smaller during recent years possibly due to the parallel improvement on udder traits. In the light of the results of this first longevity study in Latxa, it is possible to infer that ewes’ on-herd durability is negatively affected by a reproductive delay and a high prolificacy, whereas the higher the milk production, the lower the risk. Moreover, given the genetic findings, it can also be deduced that although selection on longevity is viable, the genetic progress may be a long process.

Genetic parameters and genomic regions associated with calving ease in primiparous Nellore heifers

The aim of this study was to estimate genetic parameters and to identify genomic regions associated with the calving ease (CE) in precocious Nellore heifers. A total of 1,277 CE phenotypes were collected and scored into two categories: i- non assisted calving, categorized as success (1) and ii- assisted calving where heifers required any form of assistance or intervention to give birth, categorized as failure (2). A pedigree structure containing the identification of the animal's sire and dam was used, with the relationship matrix comprising a total of 6,511 animals. Genotypic data from 1,201 animals were obtained using low-density panel (Clarifide Nelore 3.1) encompassing over 29,001 single nucleotide polymorphisms (SNP) markers. A threshold sire-maternal grandsire model (S-MGS) was used to estimate the genetic parameters, which included sire, maternal grandsire and residual effects as random effects and the fixed effects of contemporary groups (farm and year of calving, sex) and birth weight of the calf as covariable (linear effect). Genomic breeding values were estimated using an animal model with the direct and maternal genetic variances which were previously obtained by means of a S-MGS threshold model. The direct and maternal heritability estimates for CE were obtained considering the covariance of direct and maternal effects fixed as zero. Regions that accounted for more than 0.5% of the additive genetic variance were used. The direct and maternal heritability estimates for CE were low (0.18) and moderate (0.39) respectively, indicating that genetic progress for this trait is feasible, and so, it would respond favorably to direct selection. Genes identified within the significant windows, such as CA8, FAM110B, TOX, ARID1A, RBM15, HSF1 and PLAG1 were found to be related with maternal and direct effects on CE. Gene enrichment analysis revealed processes that might directly influence fetal processes involved in female pregnancy and stress response. These results should help to better understand the genetic and physiological mechanisms regulating placenta development and fetal development, and this information might be useful for future genomic studies in Nellore cattle.

Differential response from selection for high calving ease vs. low birth weight in American Simmental beef cattle.

Data on calving ease (CE) and birth, weaning weight (WW), and yearling weight (YW) were obtained from the American Simmental Association (ASA) and included pedigree and performance information on 11,640,735 animals. Our objective was to quantify differential response from selection for high CE vs. low birth weight (LBW) in first-calf Simmental heifers. We hypothesized that direct selection for CE should be used as the primary approach to reduce dystocia and mitigate losses in growth-related traits. WW and YW were adjusted to 205 and 365 d of age, respectively. Sire and maternal grandsire (co)variance components for CE, birth weight (BW), and 205-d weaning weight (205-d WW), and sire covariance components for 160-d postweaning gain (160-d gain) were estimated using a sire-maternal grandsire model. Direct and maternal expected progeny differences (EPD) for CE, BW, and 205-d WW and direct EPD for 160-d gain and 365-d yearling weight (365-d YW) for first-calf Simmental heifers population (465,710 animals) were estimated using a threshold-linear multivariate maternal animal model. This population was used to estimate genetic trends and as a selection pool (control) for various selection scenarios. Selection scenarios were high CE (HCE), LBW, the all-purpose selection index (API = -1.8 BW + 1.3 CE + 0.10 WW + 0.20 YW) of the ASA and its two derived subindices: (API1 = 1.3 CE + 0.20 YW) and (API2 = -1.8 BW + 0.20 YW), and lastly Dickerson's selection index (DSI = -3.2 BW + YW). Data for each selection scenario were created by selecting sires with EPD greater than or equal to the average along with the top 75% of dams. Comparison between selection scenarios involved evaluating the direct and maternal genetic trends from these scenarios. Direct heritabilities for CE, BW, 205-d WW, 160-d gain, and 365-d YW of Simmental cattle were 0.23, 0.52, 0.28, 0.21, and 0.33, respectively. The single trait, HCE, selection scenario, as opposed to LBW, increased the intercept for CE by 57.7% and the slopes (P < 0.001) for BW, 205-d WW, 160-d gain, and 365-d YW by 27.9%, 37.5%, 16%, and 28%, respectively. Comparisons of various selection scenarios revealed that the CE-based selection scenarios (HCE, API, and API1) had a greater response for CE and growth traits.

Threshold models for the determination of genetic variability among reproductive traits in Nellore cattle

Abstract: The objective of this work was to evaluate the potential of different threshold models to determine the genetic variability in Nellore cattle, with basis on the heritability estimates for the traits stayability (STA) and first calving probability at 36 months of age (CP36). Data came from the Nellore herds participating in the animal breeding program of the Embrapa-Geneplus partnership. Binomial and multi-threshold models were defined for the STA and CP36 traits. Heritability estimates were obtained following Bayesian procedures in the Multiple-trait Gibbs Sampler for Animal Models (MTGSAM) software, using a sire-maternal grandsire model. The heritability estimates, provided by the binary and alternative models, were, respectively, 0.08 and 0.12 for STA and 0.17 and 0.12 for CP36. The multi-threshold model can efficiently detect the genetic variability for stayability, but not for probability of calving for 36-month-old cows.

Parent-of-origin effects on carcass traits in Japanese Black cattle.

Variances caused by the differential expression of paternally and maternally imprinted genes controlling carcass traits in Japanese Black cattle were estimated in this study. Data on marbling score (BMS), carcass weight, rib thickness, rib-eye area (REA) and subcutaneous fat thickness (SFT) were collected from a total of 13,115 feedlot steers and heifers in a commercial population. A sire-maternal grandsire model was used to analyse the data, and then, imprinting parameters were derived by replacing the genetic effect of the dam with the effect of the maternal grandsire in the imprinting model to calculate the genetic parameter estimates. The proportions of the total genetic variance attributable to imprinted genes ranged from 8.7% (SFT) to 35.2% (BMS). The remarkably large imprinting variance of BMS was mainly contributed by maternally expressed inheritance because the maternal contribution of the trait was much larger than that of the paternal trait. The parent-of-origin effect originating from maternal gene expression was also observed for REA. The results suggested the existence of genomic imprinting effects on the traits of the Japanese Black cattle. Hence, the parent-of-origin effect should be considered for the genetic evaluation of Japanese Black cattle in breeding programmes.

Genetic evaluation of gestation length and its use in managing calving patterns

Data collected from Australian Holstein cows that calved between 1995 and 2016 were used for estimating genetic parameters and genetic evaluation of gestation length (GL). Genetic parameters were estimated using a sire maternal grandsire model considering GL in heifers as correlated, but a different trait to adult cows and animal repeatability model. The key objective of this study was to assess if selective mating of bulls with short GL estimated breeding values (EBV) can help to modify calving patterns in predominantly pasture-based production systems and thereby contribute to the reduction of calving induction. The mean GL in heifers and adult cows was 280 and 281 d, respectively. The heritability of direct GL was 0.28 in heifers, which is slightly lower than in adult cows (0.36). The maternal heritability of GL was close to 0.04 in both heifer and adult cows. The genetic correlation between direct effects in heifers and adult cows was lower (0.88) than between maternal effects (0.94). A genetic evaluation model that considered heifer and adult cow data as the same trait in a repeatability animal model showed adequate variability in EBV for both direct and maternal GL. The genetic trend in direct GL EBV declined from 2005 in bulls and from 2006 in cows. Selective mating of bulls with short direct GL EBV showed that the GL and calving interval of their mates can be modified by up to 3.5 d for GL and 2.0 d for calving interval. Relative to parent average, the use of genotype data to calculate genomic EBV increased the reliability of EBV by up to 11% in validation bulls when daughter trait deviation of bulls with trait deviation of cows (11%) and deregressed breeding values (8%) were used as response variables. On average, for animals with only genotype data, the GL EBV can be predicted with about 50 to 60% reliability (expected) depending on the response variable (deregressed breeding values or daughter trait deviation and trait deviation) and the size of reference set. Overall, the results of this study show that calving patterns can be made tighter by selectively mating short GL EBV bulls to cows that do not become pregnant early in the mating season. Additionally, better reproductive management and the use of bulls with high female fertility EBV are still crucial for the success of a pasture-based dairy production system.

Genetic parameters of calving ease using sire-maternal grandsire model in Korean Holsteins.

ObjectiveCalving ease (CE) is a complex reproductive trait of economic importance in dairy cattle. This study was aimed to investigate the genetic merits of CE for Holsteins in Korea.MethodsA total of 297,614 field records of CE, from 2000 to 2015, from first parity Holstein heifers were recorded initially. After necessary data pruning such as age at first calving (18 to 42 mo), gestation length, and presence of sire information, final datasets for CE consisted of 147,526 and 132,080 records for service sire calving ease (SCE) and daughter calving ease (DCE) evaluations, respectively. The CE categories were ordered and scores ranged from CE1 to CE5 (CE1, easy; CE2, slight assistance; CE3, moderate assistance; CE4, difficult calving; CE5, extreme difficulty calving). A linear transformation of CE score was obtained on each category using Snell procedure, and a scaling factor was applied to attain the spread between 0 (CE5) and 100% (CE1). A sire-maternal grandsire model analysis was performed using ASREML 3.0 software package.ResultsThe estimated direct heritability (h2) from SCE and DCE evaluations were 0.11±0.01 and 0.08±0.01, respectively. Maternal h2 estimates were 0.05±0.02 and 0.04±0.01 from SCE and DCE approaches, respectively. Estimates of genetic correlations between direct and maternal genetic components were −0.68±0.09 (SCE) and −0.71±0.09 (DCE). The average direct genetic effect increased over time, whereas average maternal effect was low and consistent. The estimated direct predicted transmitting ability (PTA) was desirable and increasing over time, but the maternal PTA was undesirable and decreasing.ConclusionThe evidence on sufficient genetic variances in this study could reflect a possible selection improvement over time regarding ease of calving. It is expected that the estimated genetic parameters could be a valuable resource to formulate sire selection and breeding plans which would be directed towards the reduction of calving difficulty in Korean Holsteins.

English

Length of productive life is an important economic trait in dairy cattle that has shown to have a genetic component and thus, it is subject to improvement through selection. Lifetime records of 13,659 Holstein cows from 72 herds, calving for the first time between January 2000 and December 2014 and their conformation, milk yield (ME 305 d milk) and pedigree information were used to evaluate the relationship of conformation and length of productive life. Length of productive life was adjusted to a maximum of 305 days for each lactation and of these 34% were right censored records. The objective of this study was to investigate the effect of conformation traits on the genetic evaluation of functional length of productive life of Mexican Holstein cattle using survival analysis with a sire-maternal grandsire model. The hazard function was modeled with a baseline function assumed to follow a Weibull distribution, including the fixed covariates of age at first calving and conformation traits (one at a time), time dependent covariates (random effect of herd-year of calving, milk yield level, and lactation phase with changes at 29, 249 and 305 days in each of the first four lactations), and random effects of sire and maternal grandsire. All effects incorporated in the model, before including conformation traits had significant contributions to the likelihood function (P <0.05), and when conformation traits were included, five of them (chest width, teat length, median suspensory ligament, udder texture and udder depth) were statistically significant in order to predict breeding values for length of productive life; therefore the genetic evaluation for length of productive life should include these traits as indirect predictors of longevity. This study strongly recommends the inclusion of conformation traits in the model for genetic improvement of length of productive life of Mexican Holstein cattle. Key words: Holstein cattle, genetic improvement, conformation traits.

Relationship between calving difficulty and fertility traits in first-parity Iranian Holsteins under standard and recursive models.

The main objective of this study was to estimate the genetic and phenotypic relationships between calving difficulty (CD) and fertility traits, including success at first service (SF), number of inseminations to conception (INS), interval from calving to first service (CTFS), interval between first and last service (IFL) and days open (DO), in first-parity Iranian Holsteins under standard (SMMs) and recursive (RMMs) mixed models. The data analysed in this paper included 29950 records on CD and fertility traits, collected in the time period from 1995 to 2014 by the Animal Breeding and Improvement Center of Iran. Under all observed SMMs and RMMs, five bivariate sire-maternal grandsire models (ten bivariate analyses in total) were used for the analyses. Recursive models were applied with a view to consider that CD influences the fertility traits in the subsequent reproductive cycle and the genetic determination of CD and fertility traits by fitting CD as covariate for any of the fertility traits studied. The existence of such cause-and-effect is considered in RMMs but not in SMMs. Our results implied a statistically non-zero magnitude of the causal relationships between CD and all the fertility traits studied, with the former influencing the latter. The causal effects of CD on SF (on the observed scale, %), INS, CTFS, IFL and DO were -2.23%, 0.10 services, 1.93days, 3.76days and 5.61days, respectively. Direct genetic correlations between CD and the fertility traits under both models were not statistically different from zero (95% HPD interval included zero), except for the correlation between CD and CTFS, which were 0.197 and 0.134 under SMM and RMM, respectively, indicating that genes associated with difficult births also increase intervals between calving and the first insemination afterwards. Comparison of both models by the deviance information criterion (DIC) demonstrated the plausibility of RMMs over SMMs.

Estimation of breeding values for functional productive life in the Slovak Holstein population

Genetic evaluation of length of functional productive life was carried out using a Weibull proportional hazard sire-maternal grandsire model. The database included 405 624 Holstein cows with 19.24% censoring. The analyzed effects were parity &amp;times; stage of lactation, within-herd standard deviations of milk production, herd &amp;times; year &amp;times; season interaction, change of herd size with respect to the previous year, age at first calving, and sire and maternal-grandsire effects. Parity &amp;times; stage of lactation had the most important influence on functional productive life. The results of the analysis confirmed more intensive selection at the beginning of each lactation, whereby the risk ratio increased with each other lactation. Heritability of functional productive life was 0.13 on the original scale. Breeding values of sires were expressed as relative breeding values with a mean of 100 and genetic standard deviation of 12. &amp;nbsp;

Association of total mixed ration particle fractions retained on the Penn State Particle Separator with milk, fat, and protein yield lactation curves at the cow level

As part of a larger project aiming to develop management evaluation tools based on results from test-day (TD) models, the objective of this study was to examine the effect of physical composition of total mixed rations (TMR) tested quarterly from March 2006 through December 2008 on milk, fat, and protein yield curves for 25 herds in Ragusa, Sicily. A random regression sire-maternal grandsire model was used to estimate variance components for milk, fat, and protein yields fitted on a full data set, including 241,153 TD records from 9,809 animals in 42 herds recorded from 1995 through 2008. The model included parity, age at calving, year at calving, and stage of pregnancy as fixed effects. Random effects were herd × test date, sire and maternal grandsire additive genetic effect, and permanent environmental effect modeled using third-order Legendre polynomials. Model fitting was carried out using ASREML. Afterward, for the 25 herds involved in the study, 9 particle size classes were defined based on the proportions of TMR particles on the top (19-mm) and middle (8-mm) screen of the Penn State Particle Separator. Subsequently, the model with estimated variance components was used to examine the influence of TMR particle size class on milk, fat, and protein yield curves. An interaction was included with the particle size class and days in milk. The effect of the TMR particle size class was modeled using a ninth-order Legendre polynomial. Lactation curves were predicted from the model while controlling for TMR chemical composition (crude protein content of 15.5%, neutral detergent fiber of 40.7%, and starch of 19.7% for all classes), to have pure estimates of particle distribution not confounded by nutrient content of TMR. We found little effect of class of particle proportions on milk yield and fat yield curves. Protein yield was greater for sieve classes with 10.4 to 17.4% of TMR particles retained on the top (19-mm) sieve. Optimal distributions different from those recommended may reflect regional differences based on climate and types and quality of forages fed.

Genetic evaluation of the functional productive life in Slovak Simmental cattle

Abstract. Genetic evaluation of sires based on length of functional productive life of their daughters was carried out using a Weibull proportional hazard sire-maternal grandsire model. The data consisted of 214634 registered Slovak Simmental cows with censoring of 21.34%. Besides the random sire and maternal grandsire effects, the model included time dependent effects parity × stage of lactation interaction, within-herd standard deviations of milk production, herd × year × season interaction, change of herd size with respect to the previous year, and time independent effect age at first calving. Within-herd, the standard deviations of milk production had the most important influence on functional productive life. The highest risk of culling was found in cows with the lowest milk production class (uncompleted lactation). Risk of culling decreased with an increasing milk production class. Estimated heritability of functional productive life was 0.05 on the original scale. Breeding values of sires expressed as a risk ratio of their daughters were between −0.57 and 0.53.

Heritable and non-heritable genetic effects on retained placenta in Meuse-Rhine-Yssel cattle

Failure of the timely expulsion of the fetal membranes, called retained placenta, leads to reduced fertility, increased veterinary costs and reduced milk yields. The objectives of this study were to concurrently look at the heritable and non-heritable genetic effects on retained placenta and test the hypothesis that a greater coefficient of relationship between dam and calf increases the risk of retained placenta in the dam.The average incidence of retained placenta in 43,661 calvings of Meuse-Rhine-Yssel cattle was 4.5%, ranging from 0% to 29.6% among half-sib groups. The average pedigree based relationship between the sire and the maternal grandsire was 0.05 and ranged from 0 to 1.04. Using a sire-maternal grandsire model the heritability was estimated at 0.22 (SEM=0.07) which is comparable with estimates for other dual purpose breeds. The coefficient of relationship between the sire and the maternal grandsire had an effect on retained placenta. The coefficient of relationship between the sire and the maternal grandsire was used as a proxy for the coefficient of relationship between dam and calf, which is correlated with the probability of major histocompatibility complex (MHC) class I compatibility between dam and calf. MHC class I compatibility is an important risk factor for retained placenta. Although the MHC class I haplotype is genetically determined, MHC class I compatibility is not heritable. This study shows that selection against retained placenta is possible and indicates that preventing the mating of related parents may play a role in the prevention of retained placenta.

Association of total-mixed-ration chemical composition with milk, fat, and protein yield lactation curves at the individual level

The objective of this study was to examine the effect of the chemical composition of a total mixed ration (TMR) tested quarterly from March 2006 through December 2008 for milk, fat, and protein yield curves for 27 herds in Ragusa, Sicily. Before this study, standard yield curves were generated on data from 241,153 test-day records of 9,809 animals from 42 herds in Ragusa province collected from 1995 to 2008. A random regression sire-maternal grandsire model was used to develop variance components for yields. The model included parity, age at calving, year at calving, and stage of pregnancy as fixed effects. Random effects were herd × test date, sire and maternal grandsire additive genetic effect, and permanent environmental effect modeled using third-order Legendre polynomials. Model fitting was carried out using ASReml. Subsequently, the model with estimated variance components was used to examine the influence of TMR crude protein, soluble N, acid detergent lignin, neutral detergent fiber, acid detergent fiber, starch, and ash on milk, fat, and protein yield curves. The data set contained 46,531 test-day milk yield records from 3,554 cows in the 27 herds recorded during the study period. Initially, an analysis was performed using one dietary component (one-component analysis) within each model as a fixed effect associated with the test-day record closest to the months the TMR was sampled within each herd. An interaction was included with the nutrient component and days in milk. The effect of the TMR chemical component(s) was modeled using a ninth-order Legendre polynomial. The conditional Wald F-statistic for the fixed effects revealed significant effects for acid detergent fiber, neutral detergent fiber, crude protein, starch, and their interactions with days in milk on milk, fat, and protein yield. On the basis of these results, a multicomponent analysis was performed in which crude protein, neutral detergent fiber, and starch were simultaneously included in the model with days in milk interactions. Although both analyses revealed that diet composition influenced production responses depending on lactation stage, the multiple-component analysis showed more pronounced effects of starch and neutral detergent fiber relative to crude protein for all traits throughout lactation.

Genome-wide association study to identify chromosomal regions associated with antibody response to Mycobacterium avium subspecies paratuberculosis in milk of Dutch Holstein-Friesians

Heritability of susceptibility to Johne's disease in cattle has been shown to vary from 0.041 to 0.159. Although the presence of genetic variation involved in susceptibility to Johne's disease has been demonstrated, the understanding of genes contributing to the genetic variance is far from complete. The objective of this study was to contribute to further understanding of genetic variation involved in susceptibility to Johne's disease by identifying associated chromosomal regions using a genome-wide association approach. Log-transformed ELISA test results of 265,290 individual Holstein-Friesian cows from 3,927 herds from the Netherlands were analyzed to obtain sire estimated breeding values for Mycobacterium avium subspecies paratuberculosis (MAP)-specific antibody response in milk using a sire-maternal grandsire model with fixed effects for parity, year of birth, lactation stage, and herd; a covariate for milk yield on test day; and random effects for sire, maternal grandsire, and error. For 192 sires with estimated breeding values with a minimum reliability of 70%, single nucleotide polymorphism (SNP) typing was conducted by a multiple SNP analysis with a random polygenic effect fitting 37,869 SNP simultaneously. Five SNP associated with MAP-specific antibody response in milk were identified distributed over 4 chromosomal regions (chromosome 4, 15, 18, and 28). Thirteen putative SNP associated with MAP-specific antibody response in milk were identified distributed over 10 chromosomes (chromosome 4, 14, 16, 18, 19, 20, 21, 26, 27, and 29). This knowledge contributes to the current understanding of genetic variation involved in Johne's disease susceptibility and facilitates control of Johne's disease and improvement of health status by breeding.

Genetic evaluation for calving ease trait using linear and threshold models in first parity dairy cows

Calving ease (CE) is a categorical trait which can be analyzed by both linear and threshold models. Though it has been assumed that threshold models qualify to be the best procedure for analyzing categorical traits, its efficiency with field data has not been clearly confirmed. This study was aimed at comparing linear and threshold models for estimation of CE genetic parameters. Data consisted of 10,575 first parturition CE records collected from 1985 to 2006 in Isfahan, Iran. CE scores were classified into 5 categories depending upon parturition situation. A sire-maternal grand sire model, consisting of birth herd-year-season and sex-age as fixed effects and parturition herd-season, sire and maternal grand sire additive genetic values as random effects, was applied in MATVEC software. Mean, standard deviation, coefficient of variation, skewness, and kurtosis for first parity CE records were 0.233, 0.644, 276.640, 2.950, and 8.097, respectively. CE scores varied from 0 (86%) to 4 (0.1%). CE means for males (0.285) and female calves (0.190) were significantly different. Parturitions during winter and summer were associated with the highest and lowest calving difficulties, respectively. Estimations for direct and maternal heritability were 0.1082, 0.0486 using linear model and 0.0689, 0.0100 using threshold model, respectively. Even though departure from normal distribution was expected to favour the threshold model, implementation of this model in field data analysis did not eventuate to better genetic estimations. Key words: Calving ease, Holstein, Sire-MGS, threshold, genetic parameters.

Effect of herd prevalence on heritability estimates of antibody response to Mycobacterium avium subspecies paratuberculosis

Worldwide, classical control strategies based on hygiene and culling of infected animals have been implemented to eradicate Johne's disease. Breeding for disease resistance may be a useful additional tool to control the disease. The aim of this study was to estimate genetic parameters for the presence of a Mycobacterium avium ssp. paratuberculosis specific antibody response in milk of Dutch Holstein-Friesian cows using subsets of data based on within-herd test prevalence. The analyzed data set consisted of milk samples of 684,364 animals from 12,077 herds collected during the routine milk production scheme. Milk samples were tested for antibodies specific for Johne's disease by an ELISA test. Heritability estimates were calculated for 4 different subsets of data to determine the sensitivity of heritability for within-herd test prevalence. Results expressed as percentage of the sample to positive ratio were analyzed with a sire-maternal grandsire model with fixed effects for parity, year of birth, lactation stage, and herd; a covariate for milk yield at test day; and random effects for sire, maternal grandsire, and error. The estimated heritability ranged from 0.031 for the complete data set to 0.097 for herds with a test prevalence of at least 10%. Cross-validation was applied to determine which of the subsets of data produced the most accurate estimated breeding values. Results showed that for genetic selection to contribute to disease control, breeding values were estimated most accurately from herds with at least 2 animals that tested positive. In this subset the heritability was 0.041.

Comparison of different models in genetic analysis of dystocia

Summary The aim of this study was to compare threshold sire model (TS), threshold sire-maternal grandsire model (TS-MGS) and linear sirematernal grandsire model (L) for genetic analysis of dystocia. Threshold models were based on Bayesian approach. In the study, a total of 19439 dystocia records from Holsteins in USA were used. The eff ects of calving year-season, sex of calf, parity of dam, sire of calf and herd eff ects were included in all models and also maternal grandsire eff ect of calf was included in only sire-maternal grandsire models. Variance-covariance estimates were greater in threshold models than in linear model. Estimates of heritability (±SE) of dystocia based on direct genetic eff ects (h 2 D) and maternal genetic eff ects (h 2 M) were 0.18±0.004 and 0.14±0.004 from TS-MGS and 0.12±0.003 and 0.09±0.003 from L, respectively. Heritability estimates based on direct genetic eff ects from TS was 0.20±0.009. Genetic correlation between direct and maternal genetic eff ect were -0.087±0.006 from the TS-MGS and -0.253±0.010 from L. It was concluded that the threshold models were better than the linear model in the analysis of dystocia. The higher heritability estimates on the underlying scale from threshold models should allow greater genetic improvement than those using linear model estimations.

Use of linear mixed models for genetic evaluation of gestation length and birth weight allowing for heavy-tailed residual effects

BackgroundThe distribution of residual effects in linear mixed models in animal breeding applications is typically assumed normal, which makes inferences vulnerable to outlier observations. In order to mute the impact of outliers, one option is to fit models with residuals having a heavy-tailed distribution. Here, a Student's-t model was considered for the distribution of the residuals with the degrees of freedom treated as unknown. Bayesian inference was used to investigate a bivariate Student's-t (BSt) model using Markov chain Monte Carlo methods in a simulation study and analysing field data for gestation length and birth weight permitted to study the practical implications of fitting heavy-tailed distributions for residuals in linear mixed models.MethodsIn the simulation study, bivariate residuals were generated using Student's-t distribution with 4 or 12 degrees of freedom, or a normal distribution. Sire models with bivariate Student's-t or normal residuals were fitted to each simulated dataset using a hierarchical Bayesian approach. For the field data, consisting of gestation length and birth weight records on 7,883 Italian Piemontese cattle, a sire-maternal grandsire model including fixed effects of sex-age of dam and uncorrelated random herd-year-season effects were fitted using a hierarchical Bayesian approach. Residuals were defined to follow bivariate normal or Student's-t distributions with unknown degrees of freedom.ResultsPosterior mean estimates of degrees of freedom parameters seemed to be accurate and unbiased in the simulation study. Estimates of sire and herd variances were similar, if not identical, across fitted models. In the field data, there was strong support based on predictive log-likelihood values for the Student's-t error model. Most of the posterior density for degrees of freedom was below 4. Posterior means of direct and maternal heritabilities for birth weight were smaller in the Student's-t model than those in the normal model. Re-rankings of sires were observed between heavy-tailed and normal models.ConclusionsReliable estimates of degrees of freedom were obtained in all simulated heavy-tailed and normal datasets. The predictive log-likelihood was able to distinguish the correct model among the models fitted to heavy-tailed datasets. There was no disadvantage of fitting a heavy-tailed model when the true model was normal. Predictive log-likelihood values indicated that heavy-tailed models with low degrees of freedom values fitted gestation length and birth weight data better than a model with normally distributed residuals.Heavy-tailed and normal models resulted in different estimates of direct and maternal heritabilities, and different sire rankings. Heavy-tailed models may be more appropriate for reliable estimation of genetic parameters from field data.

Genetic parameters for anovulation and pregnancy loss in dairy cattle

The objectives were to estimate heritabilities and genetic variances for anovulation at ∼50 d in milk and pregnancy loss occurring between first and second pregnancy diagnoses after artificial insemination. Data were originally collected for trials on reproductive management. Anovulation data consisted of 5,818 records from 13 studies in 8 herds with an overall prevalence of 23.3%. A Bayesian approach using Markov Chain Monte Carlo methods was used in mixed threshold models for both traits. The statistical model for anovulation included fixed effects [parity, herd-study-treatment, and body condition score (BCS)], covariates (inbreeding and milk yield), and random effects (sire and residual). A second statistical model included all terms in the first model except BCS. In addition, 2 bivariate, mixed sire models were used to analyze anovulation with BCS and anovulation with milk yield. The posterior mean heritability estimate for anovulation was 0.171 [posterior standard deviation (PSD)=0.052]. Correlations of anovulation with milk yield were as follows: genetic=0.168, PSD=0.187; residual=−0.046, PSD=0.022; and phenotypic=−0.036. Bivariate analysis of BCS with anovulation showed a genetic correlation (−0.301, PSD=0.177) and phenotypic correlation (−0.192, PSD=0.019). Pregnancy-loss data consisted of 3,775 records from 14 studies in 8 herds with an overall prevalence of 14.4%. Analysis of pregnancy loss used a sire–maternal grandsire threshold model with embryo survival as the subject of analysis. Independent variables consisted of fixed effects (parity and herd-study), covariates (embryo and maternal inbreeding), and random effects (sire of embryo, maternal grandsire of embryo, and residual). In addition, separate sire models were analyzed using embryo as the subject and cow as the subject of analysis. The sire–maternal grandsire model yielded a heritability for direct effect of 0.489 (PSD=0.221) and for maternal effects of 0.166 (PSD=0.113). In this study, the breeding value variance for embryo effects was 3 times the breeding value variance for maternal effects, indicating that, at the level of breeding values, the embryo's ability to survive has a greater effect on pregnancy loss than does the cow's ability to maintain the pregnancy. These results suggest that genetic improvement of reproductive performance could be enhanced by selection for fundamental measures such as abnormally long periods of postpartum anovulation and pregnancy loss. Larger studies of these traits are needed to obtain parameter estimates with greater precision.