Evidence of genetic resistance of cattle to infection with Mycobacterium bovis.

Anecdotal evidence points to genetic variation in resistance of cattle to infection with Mycobacterium bovis, the causative agent of bovine tuberculosis (BTB), and published experimental evidence in deer and cattle suggests significant genetic variation in resistance and reactivity to diagnostic tests. However, such genetic variation has not been properly quantified in the United Kingdom dairy cattle population; it is possible that it exists and may be a factor influencing the occurrence of BTB. Using models based on the outcome of the process of diagnosis (ultimate fate models) and on the outcome of a single stage of diagnosis (continuation ratio models, herd test-date models), this study shows that there is heritable variation in individual cow susceptibility to BTB, and that selection for milk yield is unlikely to have contributed to the current epidemic. Results demonstrate that genetics could play an important role in controlling BTB by reducing both the incidence and the severity of herd breakdowns.

Scrapie-resistant sheep show certain coat colour characteristics.

Susceptibility to scrapie is known to be associated with polymorphisms at the prion protein (PrP) gene, and this association is the basis of current selective programmes implemented to control scrapie in many countries. However, these programmes might have unintended consequences for other traits that might be associated with PrP genotype. The objective of this study was to investigate the relationship between PrP genotype and coat colour characteristics in two UK native sheep breeds valued for their distinctive coat colour patterns. Coat colour pattern, darkness and spotting and PrP genotype records were available for 11 674 Badgerfaced Welsh Mountain and 2338 Shetland sheep. The data were analysed with a log-linear model using maximum likelihood. Results showed a strong significant association of PrP genotype with coat colour pattern in Badgerfaced Welsh Mountain and Shetland sheep and with the presence of white spotting in Shetland sheep. Animals with the ARR/ARR genotype (the most scrapie resistant) had higher odds of having a light dorsum and a dark abdomen than the reverse pattern. The implication of these associations is that selection to increase resistance to scrapie based only on PrP genotype could result in change in morphological diversity and affect other associated traits such as fitness.

Genotype by environment interaction for first-lactation female fertility traits in UK dairy cattle.

The objective of this study was to examine whether there was genotype by environment interaction (G x E) for female fertility traits for various environmental descriptors used in the United Kingdom. Records on days to first service (DFS), nonreturn rate at 56 d (NR56), calving interval (CI), and number of inseminations (NINS) on approximately 200,000 first-lactation Holstein cows in 3,192 herds and from 1,147 sires were analyzed using both random regression reaction norm models and multiple-trait models. The environmental descriptors were herd averages of DFS, CI, and NR56, and herd production and intensity indices, the latter based on 305-d milk, fat, and protein yields, age at first calving, temperature, and rainfall. No GxE was found for NR56 and NINS. There was an indication of G x E for DFS and CI with respect to the herd average of that trait, but only from the reaction norm model. Genotype by environment interaction existed for DFS and CI with respect to both production and intensity indexes-genetic correlations between top and bottom quartiles ranged from 0.73 to 0.84, with similar results from both models, indicating reranking of bulls. Part of this G x E might be explained by low production and intensity herds also having more concentrated spring calving.

Genetics of tuberculosis in Irish Holstein-Friesian dairy herds.

Information is lacking on genetic parameters for tuberculosis (TB) susceptibility in dairy cattle. Mycobacterium bovis is the principal agent of tuberculosis in cattle. The objective of this study was to quantify the genetic variation present among Irish Holstein-Friesian dairy herds in their susceptibility to M. bovis infection. A total of 15,182 cow and 8,104 heifer single intradermal comparative tuberculin test (SICTT, a test for M. bovis exposure and presumed infection) records from November 1, 2002, to October 31, 2005, were available for inclusion in the analysis. Data on observed carcass TB lesions from abattoirs were also available for inclusion in the analysis. The only animals retained were those present in a herd during episodes in which at least 2 animals showed evidence of infection; this ensured a high likelihood of exposure to M. bovis. Linear animal models, and sire and animal threshold models were used to estimate the variance components for susceptibility to M. bovis-purified protein derivative (PPD) responsiveness and confirmed M. bovis infection. The heritability estimates from the threshold sire models were biased upward because the relatedness between dam-daughter pairs was ignored. The threshold animal model produced heritability estimates of 0.14 in cows and 0.12 in heifers for susceptibility to M. bovis-PPD responsiveness, and 0.18 in cows for confirmed M. bovis infection susceptibility. Therefore, exploitable genetic variation exists among Irish dairy cows for susceptibility to M. bovis infection. Sire rankings from the linear and threshold animal models were similar, indicating that either model could be used for the analysis of susceptibility to M. bovis-PPD responsiveness. A favorable genetic correlation close to unity was observed between susceptibility to confirmed M. bovis infection and M. bovis-PPD responsiveness, indicating that direct selection for resistance to M. bovis-PPD responsiveness will indirectly reduce susceptibility to confirmed M. bovis infection. Data from the national TB eradication program could be used routinely to estimate breeding values for susceptibility to M. bovis infection.

Genetic analysis of locomotion and associated conformation traits of Holstein-Friesian dairy cows managed in different housing systems.

The objectives of this study were to determine the influence of housing on lameness-related linear and composite traits, and to estimate heritabilities of the traits and correlations among them. Data comprised 156,770 national type evaluation records of pedigreed first-lactation Holstein-Friesian cows that calved from 2000 through 2006 and were classified in different housing systems--cubicles, straw yards, slatted or loafing yards, and on pasture. Locomotion score (LOCO), rear leg, side view (RLS), foot angle (FA), bone quality (BO-NEQ), legs and feet (L&F), and mammary composite (MAMM) were the traits measured. Data were analyzed by REML, using an animal model. In general, cows in grazing systems had better locomotion, straighter RLS, steeper FA, flat and more refined bones, better L&F, and better mammary systems compared with cows housed in other systems. Estimates of heritability ranged from 0.11 for LOCO to 0.31 for MAMM. Bone quality had the highest heritability (0.23) of the traits associated with L&F. Genetic associations between BO-NEQ and LOCO, L&F, and MAMM were moderate to high (0.30 to 0.50), but estimates between BONEQ and RLS and FA were not significantly different from zero. Locomotion score had a very high genetic (0.98) and phenotypic (0.78) correlation with L&F, indicating that both traits are genetically the same. On the basis of the genetic parameters, including BONEQ in a selection index as a predictor of longevity is promising, but further information on its association with longevity is required.

Genetic parameters for digital dermatitis and correlations with locomotion, production, fertility traits, and longevity in Holstein-Friesian dairy cows.

Heritability of digital dermatitis (DD) and correlations between DD and type traits related to legs and feet were estimated from a linear animal model. Data comprised 93,391 national type evaluation records of pedigreed first-lactation Holstein-Friesian cows that calved from 2002 through 2006. At the time of classification, cows were housed in different housing systems (i.e., cubicles, straw yards, slatted or loafing yards) and on pasture. The type traits evaluated were locomotion score (LOCO), rear legs side view (RLS), foot angle (FA), bone quality and leg and feet composite (L&F). In addition, cows were examined for DD lesions at classification. The relationships among these type traits, lifespan (LS), production (milk and fat), fertility (calving interval and 56-d nonreturn) and DD were examined by estimating the approximate genetic correlations from sire estimated breeding values. The study also evaluated the association between DD and the housing systems as well as the general conditions of the farm flooring where classification took place. In general, cows on pasture were less susceptible to DD than cows in other housing systems, whereas the association between DD and the flooring conditions was counterintuitive. Heritability estimate for DD was 0.011 on the 0/1 scale, which is equivalent to 0.029 on the assumed underlying normally distributed scale. Bone quality, LOCO, and L&F had moderate to high negative genetic correlations with DD, indicating that flatter, more refined bones, higher LOCO, and better L&F were associated with less incidence of DD. The genetic correlations between DD, RLS, and FA were not significantly different from zero. Digital dermatitis had moderate but negative genetic correlations with LS and milk and fat, suggesting that breeding for resistance to DD will result in an increase in both longevity and production. Cows affected with DD had a slightly shorter calving interval than healthy cows, an association found to be mediated through the reduced milk yield of these cows. Generally, the type traits included in this study had low genetic correlations with production and fertility traits whereas the associations between these traits and LS ranged from moderate to high. This indicates that good locomotion, straighter RLS, steeper FA, better L&F, and flatter, more refined bones are associated with increased longevity.

Differences between primiparous and multiparous dairy cows in the inter-relationships between metabolic traits, milk yield and body condition score in the periparturient period.

During the early postpartum period dairy cows mobilize fat and muscle to support lactation. This is associated with alterations in blood metabolite and hormone profiles which in turn influence milk yield and fertility. This study developed models to determine how metabolic traits, milk yield and body condition score were inter-related at different times in the periparturient period and to compare these relationships in primiparous (PP, n=188) and multiparous (MP, n=312) cows. Data from four previous studies which included information on blood metabolic parameters, parity, milk yield, body condition score and diet were collated into a single dataset. Coefficients of polynomial equations were calculated for each trait between -1 week pre-calving and week +7 postpartum using residual maximum likelihood modelling. The completed dataset was used in a multiple correlation model to determine how the best fit curves were related to each other over time. PP cows had higher concentrations of insulin-like growth factor-I and lower beta-hydroxybutyrate concentrations throughout, higher leptin concentrations pre-partum and both the peak in non-esterified fatty acids and the nadir in urea concentration occurred earlier after calving. These differences were associated with significantly lower milk production. Leptin concentrations fell at calving and were related to body condition score. Insulin was negatively correlated with yield in MP cows only. In MP cows the relationship between insulin-like growth factor-I and yield switched from negative to positive between weeks +4 and +7. Both beta-hydroxybutyrate and urea were positively related to yield in PP cows. In contrast, in MP cows beta-hydroxybutyrate was negatively correlated with yield and urea was strongly related to body condition score but not yield. These results suggest that there are differences in the control of tissue mobilization between PP and MP cows which may promote nutrient partitioning into growth as well as milk during the first lactation.

Genetic parameters of growth in dairy cattle and associations between growth and health traits.

Body weight (BW) observations on dairy cattle taken on average 35 times between birth and 1,000 d of life were used to estimate daily heritabilities and predict daily breeding values for both pregnancy-adjusted BW (PABW) and growth rate. Daily heritabilities for PABW were moderate to high, ranging from 0.41 (+/-0.027) to 0.82 (+/-0.041). Daily heritabilities for growth rate were high (>0.68 +/- 0.034). The genetic association between various health events, including mastitis and lameness, and weight and growth was investigated by regressing the incidence of health events on breeding values for weight at birth, weaning, calving, and growth rate at 56 d after calving, growth rate at 110 d after calving, and maximum growth rate. Growth at weaning was the only BW measure to significantly affect mastitis (r(g) = 0.24), indicating that cows growing faster at weaning are more prone to mastitis. Increased weight (r(g) = 0.65) and growth rate at weaning (r(g) = 0.38) and increased maximum growth rate (r(g) = 0.71) all contributed to increased feet disorders. The only significant negative genetic association was obtained between reproduction and weight at calving (r(g) = -0.61).

Prenatal maternal effects on body condition score, female fertility, and milk yield of dairy cows.

In this study, maternal effects were described as age of dam at first and second calving, first-lactation body condition score (BCS) of the dam during gestation, and milk yield of the dam. The impact of these effects on first-lactation daughter BCS, fertility, and test-day milk yield was assessed. The effect of milk yield of dam on daughter 305-d yield in the latter's first 3 lactations was also investigated. The proportion of total phenotypic variance in daughter traits accounted for by maternal effects was calculated. Dams calving early for the first time (18 to 23 mo of age) had daughters that produced 4.5% more first-lactation daily milk, had 7% higher BCS, and had their first service 3 d earlier than cows whose dams calved late (30 to 36 mo). However, daughters of dams that calved early had difficulties conceiving as they needed 7% more inseminations and had a 7.5% higher return rate. Cows from second calvings of relatively young (36 to 41 mo) dams produced 6% more first-lactation daily milk, had 2% higher BCS, and showed a significantly better fertility profile than cows whose dams calved at a late age (47 to 55 mo). High maternal BCS during gestation had a favorable effect on daughter BCS, nonreturn rate, and number of inseminations per conception. However, it was also associated with a small decrease in daughter daily milk yield. Changes in dam BCS during gestation did not affect daughter performance significantly. Maternal effects of milk yield of the dam, expressed as her permanent environment during lactation, adversely affected daughter 305-d milk, fat, and protein yield. However, although the effect was significant, it was practically negligible (<0.3% of the mean). Finally, overall maternal effects accounted for a significant proportion of the total phenotypic variance of calving interval (1.4 +/- 0.6%) and nonreturn rate (1.1 +/- 0.5%).

The relationship between body energy traits and production and fitness traits in first-lactation dairy cows.

Daily breeding values for various body energy traits were estimated from nationally recorded linear type information using random regression techniques. These traits included predicted live weight, growth rate (GR), and several measures of body energy during first lactation. The relationship between the individual linear type traits, body energy traits, and other production and fitness traits was examined by estimating the approximate genetic correlations (and standard errors) from adjusted predicted transmitting ability correlations. The relationship between fitness and body traits was further examined by calculating the partial correlation between the pairs of traits at a constant milk yield. Daily sire solutions for type traits showed that there were differences in how cows changed body shape across lactation. On average, cows lost body energy in early lactation but regained it by the end of the lactation. However, there was large variation, with the daughters of some sires still in negative energy balance by the end of lactation. The estimates of genetic correlation of linear type traits with production and fitness traits agreed with previous linear point estimates. The fertility traits were correlated across lactation with all linear type traits studied and indicated that bigger animals tend to have poorer fertility. There was an unfavorable correlation between production and GR; therefore, higher producing cows were more likely to have lower GR early in first lactation. The results also showed that higher producing animals were likely to loose body energy during the peak of first lactation. This is mirrored in the relationship of early lactation energy balance with somatic cell count and longevity, indicating that peak lactation is a critical time in terms of metabolic pressures on the dairy cow.

Characterization of the dairy farm environment in Great Britain and the effect of the farm environment on cow life span.

Dairy farms vary a great deal in the feeding and management systems that are used. These differences affect the performance of the cows, and some genotypes may be affected more than others. If effects of such genotype-by-environment interactions (GxE) are large, then farmers must be made aware of them to make informed breeding decisions. To investigate GxE, a classification system for farm environments was developed based on national- and fine-level data from dairy herds across the United Kingdom. The national data included herd and yield characteristics and local weather information. The fine-level data included information on feeding and management systems on farms, and was obtained from survey results from 778 farms. A principal components analysis of the surveys identified 2 major dimensions characterizing the data. The first dimension explained 14.6% of the variation and was related to the level of production intensity. The second dimension explained 11.5% of the variation and was related to climate. Information on milk yield, herd characteristics, and climate was then extracted from national databases for the survey farms. A canonical correlation analysis was used to relate the survey data to the variables extracted from the national data set to determine the most relevant variables. The canonical correlation between the chosen sets of national data and survey variables was 0.62. This environmental classification was then used to determine how the farm environment affects the life span of dairy cows. The life span of the daughters of 1,000 sires was related to the type of farm environment. The daughters of a majority of sires showed a "plastic" response, with increased life span in less intensive farms. The daughters of a smaller number of sires showed a more generalized response, with life span being less affected by the environment. This GxE suggested that sires vary in the sensitivity of their daughters to different farm environments. This variation in response could allow breeding companies and farmers to match sires to particular farm environments.

Genetic relationship between first-lactation body energy and later-life udder health in dairy cattle.

Weekly body condition score (BCS) and live weight records were used to calculate energy content (EC) and cumulative effective energy balance (CEEB) for 508 Holstein-Friesian cows in their first lactation. Cows were raised on an experimental farm and had calved between 1991 and 2000. Energy content was an estimate of the actual energy level of a cow at any given stage of lactation, whereas CEEB was associated with the total body energy content as defined by accumulated weekly energy balance changes since the onset of lactation. Genetic evaluations were computed for the 3 body energy traits (BCS, EC, and CEEB) for each week of first lactation. Random regression models were used to assess the association between first-lactation weekly genetic evaluations for body energy and monthly test-day log-transformed SCC, clinical mastitis, and other udder problems in the first 3 lactations. There was a significant effect of at least one body energy trait at any stage of first lactation past wk 3 on SCC in the first 3 lactations. Maximum genetic correlation estimates were -0.18 (+/-0.04) between wk-16 BCS and SCC in the first 2 lactations, -0.18 (+/-0.04) between wk-11 EC and SCC in the first 2 lactations, and -0.17 (+/-0.07) between wk-6 CEEB and SCC in the first 2 lactations. The effect of body energy traits on clinical mastitis was, in general, nonsignificant; nevertheless, moderate genetic correlations were estimated, ranging from -0.05 (+/-0.07) to -0.25 (+/-0.15). The effect of body energy traits on udder problems other than mastitis was negligible in all cases. Results suggest that, amongst the traits studied here, BCS, EC, and CEEB in the first 3 to 4 mo of lactation 1 had the greatest genetic association with SCC and mastitis in first, second, and, to a lesser extent, third lactations.

Genetic aspects of growth of Holstein-Friesian dairy cows from birth to maturity.

In general, genetic selection is applied after first calving to traits that manifest themselves during the animal's productive life, mostly during the early part of productive life. This selection policy has had undesirable correlated responses in other economically important traits, such as health and fertility, and may also have had an effect on the growth of animals both during productive life and before first calving. In this study, we analyzed the growth trajectory of dairy heifers that had been selected for maximum production of combined fat and protein (measured in kg; select line) or for average production (control line) in the United Kingdom. Before first calving, these divergent lines were managed as a single group. Select line heifers grew faster than did control line heifers. They were also heavier at first calving, but by the end of 3 lactations, the lines were not significantly different in live weight. Selection primarily for yield and for other traits has led to heifers that grow faster and reach higher growth rates earlier in life. A genetic analysis of birth, weaning, and calving weights yielded heritability estimates of 0.53 (birth weight), 0.45 (weaning weight), and 0.75 (calving weight). Confidence intervals for the genetic correlations between the traits indicated that these BW traits are not under the same genetic control.

Modeling daily energy balance of dairy cows in the first three lactations.

Daily energy balance was calculated for 111 Holstein cows in their first 3 lactations, based on combinations of smoothed preadjusted phenotypic records for milk yield, feed intake, live weight, and body condition score. Two energy balance traits were defined: one based on milk yield and feed intake (EB1) and the other on live weight and body condition score change (EB2). Bessel functions (BF), Legendre polynomials (LP), sinusoidal functions (SF), and cubic splines (CS) were used to model energy balance within and across lactations. Models with BF or LP fitted fixed regressions of order 1 to 6 and random regressions of order 1 to 10. Cubic splines were fitted at 5 to 30 equally spaced knot points. In within-lactation analyses with BF and LP models, likelihood ratio tests revealed that the fit improved significantly up to random regression order of 5 for EB1 and 4 for EB2, independently of the fixed regression order. For EB1 analyses with LP, improvement was marginal albeit significant even for higher random regression order. For CS models, optimal number of knot points was 13 and 12 for EB1 and EB2, respectively. Residual variance and comparisons between actual and predicted energy balance showed that LP of minimum order 8 and 5 modeled, respectively, EB1 and EB2 better than the other 3 functions. In across-lactation analyses with BF and LP models, likelihood ratio tests were significant as the random regression order increased, for any order of the fixed regression. For CS models, optimal number of knot points was 14 and 16 for EB1 and EB2, respectively. Residual variance and comparisons between actual and predicted energy balance showed that models fitting CS and high (>8) random order BF or LP provided the best fit to both traits. However, in an across-lactation analysis, even higher order of LP or BF will be required to provide as good a fit as within-lactation analyses.

Genetic profile of total body energy content of Holstein cows in the first three lactations.

Weekly total body energy content (TBEC) was calculated for 444 Holstein cows in their first 3 lactations. These calculations were based on body lipid and protein changes predicted from weekly changes in body condition score and live weight of each cow. In first lactation, cows lost TBEC during the initial 8 wk, regained it by wk 22, and continued to build up their reserves until wk 37. Cows started lactations 2 and 3 with considerable reserves from the dry period that they used during the first 13 wk of lactation. Variance components for TBEC were estimated using random regression analysis allowing for heterogeneous residual variance. The genetic variance increased within each lactation, suggesting that the genetic component becomes more important as lactation progresses. The genetic correlations between very early (wk 1 to 4) and later stages of first lactation were near zero but they increased considerably between later lactation stages. Genetic correlations between TBEC on wk 5 of first lactation and the remainder of this lactation ranged from 0.64 for the more distant weeks to 0.99 for the immediately subsequent weeks. Genetic correlations with TBEC in second lactation were moderately high (0.68 to 0.70) for the early weeks (1 to 8) and decreased gradually to 0.56 for weeks at the end of lactation. For third lactation, these estimates ranged from 0.53 to 0.63. Genetic correlation estimates of TBEC in wk 12 of first lactation with subsequent first-lactation weeks varied from 0.79 to 0.99, whereas they ranged from 0.65 to 0.77 and from 0.57 to 0.68 in second and third lactations, respectively. The genetic correlation between TBEC in later weeks of first lactation and the rest of productive life increased as first lactation progressed, but the improvement diminished. Weekly genetic evaluations for first-lactation TBEC were used to predict second- and third-lactation energy content. The accuracy of these predictions increased with progressing weeks in first lactation, but about three-fourths of the improvement occurred by wk 5. Our results suggest that TBEC calculated after a month from the first calving may give useful information about the future energy content of a cow.

Body trait profiles in Holstein-Friesians modeled using random regression.

Legendre polynomial and cubic spline functions were used in random regression models to model the change in body traits over the course of the first lactation for daughters of 954 sires. Both functions estimated similar genetic variances for d 50 to 250 across lactation for the majority of traits. The heritability of the traits was similar to other studies using univariate models as well as random regression models. There was little difference between the 2 functions in their predictive power for each of the body type traits, as measured by the absolute difference between the predicted and actual type traits and the proportion of the total phenotypic variance explained by the model. Overall, the Legendre polynomial appeared to model these traits slightly better. Plots of the fixed curves and daily sire solutions obtained from the random regression models showed that there were differences in how the traits and sires changed across lactation. The daily sire solutions were then used to predict differences in liveweight of sires' daughters across first lactation and showed that the daughters of some sires grew faster during first lactation than others. The spatial differences in the body traits that are displayed by this study could be an important indicator of the physical and biological changes that cows are undergoing in their first lactation. Information from these sire profiles could be harnessed to indicate production and functional traits later in life.

The effects of different farm environments on the performance of Texel sheep.

In order to assess the extent of genotype by environment interactions (G×E) and environmental sensitivity in sheep farm systems, environmental factors must be identified and quantified, after which the relationship with the traits(s) of interest can be investigated. The objectives of this study were to develop a farm environment (FE) scale, using a canonical correlation analysis, which could then be used in linear reaction norm models. Fine-scale farm survey data, collected from a sample of 39 Texel flocks across the United Kingdom, was combined with information available at the national level. The farm survey data included information on flock size and concentrate feed use. National data included flock performance averages for 21-week-old weight (21WT), ultrasound back-fat (UFD) and muscle (UMD) depths, as well as regional climatic data. The FE scale developed was then combined with 181 555 (21WT), 175 399 (UMD) and 175 279 (UFD) records from lambs born between 1990 and 2011, on 494 different Texel flocks, to predict reaction norms for sires used within the population. A range of sire sensitivities estimated across the FE scale confirmed the presence of genetic variability as both 'plastic' and 'robust' genotypes were observed. Variations in heritability estimates were also observed indicating that the rate genetic progress was dependent on the environment. Overall, the techniques and approaches used in this study have proven to be useful in defining sheep FEs. The results observed for 21WT, UMD and UFD, using the reaction norm models, indicate that in order to improve genetic gain and flock efficiency, future genetic evaluations would benefit by accounting for the G×E observed.

Characterisation of terminal sire sheep farm systems, based on a range of environmental factors: a case study in the context of genotype by environment interactions using Charollais lambs.

The objective of this study was to define different terminal sire flock environments, based on a range of environmental factors, and then investigate the presence of genotype by environment interactions (G×E) between the environments identified. Data from 79 different terminal sire flocks (40 Texel, 21 Charollais and 18 Suffolk), were analysed using principal coordinate and non-hierarchical cluster analyses, the results of which identified three distinct environmental cluster groups. The type of grazing, climatic conditions and the use of vitamins and mineral supplements were found to be the most important factors in the clustering of flocks. The presence of G×E was then investigated using data from the Charollais flocks only. Performance data were collected for 12 181 lambs, between 1990 and 2010, sired by 515 different sires. Fifty six of the sires had offspring in at least two of the three different cluster groups and pedigree information was available for a total of 161 431 animals. Traits studied were the 21-week old weight (21WT), ultrasound muscle depth (UMD) and log transformed backfat depth (LogUFD). Heritabilities estimated for each cluster, for each trait, ranged from 0.32 to 0.45. Genetic correlations estimated between Cluster 1 and Cluster 2 were all found to be significantly lower than unity, indicating the presence of G×E. They were 0.31 (±0.17), 0.68 (±0.14) and 0.18 (±0.21) for 21WT, UMD and LogUFD, respectively. Evidence of sires re-ranking across clusters was also observed. Providing a suitable strategy can be identified, there is potential for the optimisation of future breeding programmes, by taking into account the G×E observed. This would enable farmers to identify and select animals with an increased knowledge as to how they will perform in their specific farm environment thus reducing any unexpected differences in performance.

Estimating variance components and predicting breeding values for eventing disciplines and grades in sport horses.

Eventing competitions in Great Britain (GB) comprise three disciplines, each split into four grades, yielding 12 discipline-grade traits. As there is a demand for tools to estimate (co)variance matrices with a large number of traits, the aim of this work was to investigate different methods to produce large (co)variance matrices using GB eventing data. Data from 1999 to 2008 were used and penalty points were converted to normal scores. A sire model was utilised to estimate fixed effects of gender, age and class, and random effects of sire, horse and rider. Three methods were used to estimate (co)variance matrices. Method 1 used a method based on Gibbs sampling and data augmentation and imputation. Methods 2a and 2b combined sub-matrices from bivariate analyses; one took samples from a multivariate Normal distribution defined by the covariance matrix from each bivariate analysis, then analysed these data in a 12-trait multivariate analysis; the other replaced negative eigenvalues in the matrix with positive values to obtain a positive definite (co)variance matrix. A formal comparison of models could not be conducted; however, estimates from all methods, particularly Methods 2a/2b, were in reasonable agreement. The computational requirements of Method 1 were much less compared with Methods 2a or 2b. Method 2a heritability estimates were as follows: for dressage 7.2% to 9.0%, for show jumping 8.9% to 16.2% and for cross-country 1.3% to 1.4%. Method 1 heritability estimates were higher for the advanced grades, particularly for dressage (17.1%) and show jumping (22.6%). Irrespective of the model, genetic correlations between grades, for dressage and show jumping, were positive, high and significant, ranging from 0.59 to 0.99 for Method 2a and 0.78 to 0.95 for Method 1. For cross-country, using Method 2a, genetic correlations were only significant between novice and pre-novice (0.75); however, using Method 1 estimates were all significant and low to moderate (0.36 to 0.70). Between-discipline correlations were all low and of mixed sign. All methods produced positive definite 12 × 12 (co)variance matrices, suitable for the prediction of breeding values. Method 1 benefits from much reduced computational requirements, and by performing a true multivariate analysis.

Evaluating the effects of a single copy of a mutation in the myostatin gene (c.*1232G>A) on carcass traits in crossbred lambs.

This study evaluated the effects of the ovine c.*1232G>A myostatin mutation (MM) on carcass traits in heterozygous crossbred lambs sired by Texel and Poll Dorset rams using ultrasound, CT scanning, carcass classification and VIA. In experiment 1, MM was associated with increased loin depth (+2.8%) and area (+3.2%). MM-carriers had significantly higher CT-estimated lean weight and proportion (2 to 4%) and muscle to bone ratio (by ~3%), in both experiments, and muscle to fat ratio (28%) in experiment 2. Muscle areas in three cross-sectional CT scans, were higher (2 to 5%) in MM-carriers. In experiment 2, fat-related measurements were significantly lower in MM-carrier lambs but this was not seen in experiment 1. A significant increase in muscle density, indicative of lower intramuscular fat, in MM-carriers shows that meat quality characteristics need attention. Carrying MM significantly decreased carcass fat scores. VIA did not detect any significant MM effects.