Genetic (co)variance components for slaughter traits in a multi-breed sheep population.

Carcass value is one of the main contributors to revenue in meat sheep enterprises, while age at slaughter is also a major component to the cost of production. Despite the contribution of such traits to overall profit, little is actually known on the extent of exploitable genetic variability in the traits that govern carcass value (i.e. carcass weight, carcass conformation, carcass fat) and age at slaughter, especially independent of each other. The objective of the present study was to estimate genetic (co)variances for and among carcass weight, carcass conformation, carcass fat, kill-out percentage and age at slaughter as well as their genetic (co)variances with traits measured earlier in life. Data consisted of slaughter records from 15 714 lambs, with 12 630 of these lambs having at least one live weight measure. The heritability (SE) of carcass weight, carcass conformation, carcass fat, kill-out percentage, and age at slaughter was 0.14 (0.02), 0.19 (0.02), 0.08 (0.01), 0.22 (0.03), and 0.16 (0.02), respectively. The maternal heritability for age at slaughter was 0.07 (0.02); no maternal genetic influence was found on any of the other slaughter traits. The coefficient of genetic variation for carcass weight and age at slaughter was 3 and 8%, respectively. The correlations between the direct genetic effects for live weight throughout life, and carcass weight were weak up to weaning but were strong (0.83) thereafter. The correlation between the direct genetic effects of birth weight and age at slaughter was zero, but varied from -0.91 to -0.56 between live weight measured later in life and age at slaughter. Results demonstrate significant exploitable genetic variability in a range of slaughter traits with the prediction of genetic merit for carcass traits and age at slaughter being possible using live weight measures taken on live animals. For example, the accuracy of selection for slaughter traits (comprising of age at slaughter, carcass conformation and carcass fat) from weaning weight records available on 100 progeny was 0.37; when slaughter data were also available for 10 progeny, the accuracy of selection increased to 0.56.

Evaluating the use of statistical and machine learning methods for estimating breed composition of purebred and crossbred animals in thirteen cattle breeds using genomic information.

Introduction: The ability to accurately predict breed composition using genomic information has many potential uses including increasing the accuracy of genetic evaluations, optimising mating plans and as a parameter for genotype quality control. The objective of the present study was to use a database of genotyped purebred and crossbred cattle to compare breed composition predictions using a freely available software, Admixture, with those from a single nucleotide polymorphism Best Linear Unbiased Prediction (SNP-BLUP) approach; a supplementary objective was to determine the accuracy and general robustness of low-density genotype panels for predicting breed composition. Methods: All animals had genotype information on 49,213 autosomal single nucleotide polymorphism (SNPs). Thirteen breeds were included in the analysis and 500 purebred animals per breed were used to establish the breed training populations. Accuracy of breed composition prediction was determined using a separate validation population of 3,146 verified purebred and 4,330 two and three-way crossbred cattle. Results: When all 49,213 autosomal SNPs were used for breed prediction, a minimal absolute mean difference of 0.04 between Admixture vs. SNP-BLUP breed predictions was evident. For crossbreds, the average absolute difference in breed prediction estimates generated using SNP-BLUP and Admixture was 0.068 with a root mean square error of 0.08. Breed predictions from low-density SNP panels were generated using both SNP-BLUP and Admixture and compared to breed prediction estimates using all 49,213 SNPs (representing the gold standard). Breed composition estimates of crossbreds required more SNPs than predicting the breed composition of purebreds. SNP-BLUP required ≥3,000 SNPs to predict crossbred breed composition, but only 2,000 SNPs were required to predict purebred breed status. The absolute mean (standard deviation) difference across all panels <2,000 SNPs was 0.091 (0.054) and 0.315 (0.316) when predicting the breed composition of all animals using Admixture and SNP-BLUP, respectively compared to the gold standard prediction. Discussion: Nevertheless, a negligible absolute mean (standard deviation) difference of 0.009 (0.123) in breed prediction existed between SNP-BLUP and Admixture once ≥3,000 SNPs were considered, indicating that the prediction of breed composition could be readily integrated into SNP-BLUP pipelines used for genomic evaluations thereby avoiding the necessity for a stand-alone software.

Inbreeding trends and genetic diversity in purebred sheep populations.

Monitoring the rate of change in inbreeding and genetic diversity within a population is important to guide breeding programmes. Such interest stems from the impact of loss in genetic diversity on sustainable genetic gain but also the impact on performance (i.e. inbreeding depression). The objective of the present study was to evaluate trends in inbreeding and genetic diversity in 43 066 Belclare, 120 753 Charollais, 22 652 Galway, 78 925 Suffolk, 187 395 Texel, and 19 821 Vendeen purebred sheep. The effective population size for each of the six breeds was between 116.0 (Belclare population) and 314.8 (Charollais population). The Charollais population was the most genetically diverse with the greatest number of effective founders, effective ancestors, and effective founder genomes; conversely, the Belclare was the least genetically diverse population with the fewest number of effective founders, effective ancestors, and effective founder genomes for each of the six breeds investigated. Overall, the effective population sizes and the total genetic diversity within each of the six breeds were above the minimum thresholds generally considered to be required for the long-term viability of a population.

Association between the prion protein genotype and animal performance traits in a large multibreed sheep population.

Genetic susceptibility to scrapie, a fatal disease of sheep and goats, is modulated by polymorphisms in the prion protein (PrP). Neither the frequency of the PrP genotypes nor their association with animal performance has been investigated in a large multibreed Irish sheep population. Scrapie genotypes were available on 16 416 animals; the breeds represented included purebred Belclare (733), Charollais (333), Suffolk (739), Texel (1 857), Vendeen (191), and crossbreds (12 563). Performance data on lambing, lamb and ewe performance as well as health traits were available. The association between alternative approaches of describing the PrP genotype (i.e. 15 individually called PrP genotypes, five genotype classes representing susceptibility to scrapie, or number of ARR haplotypes) and animal performance were quantified using animal linear mixed models. All 15 of the possible scrapie genotypes were detected, although the frequency differed by breed. The frequency of the five PrP haplotypes in the entire population were 0.70 (ARR), 0.15 (ARQ), 0.11 (ARH), 0.02 (AHQ) and 0.01 (VRQ); the most susceptible haplotype (VRQ) was only detected in purebred Texels and crossbreds. No association was detected between the PrP genotype of either the animal or dam and any of the lambing traits (i.e. lambing difficulty score, perinatal mortality and birth weight). With the exception of ultrasound muscle depth, no association between the PrP genotype and any of the lamb performance traits (i.e. lamb BW and carcass) was observed. Lambs carrying the category four PrP genotype (i.e. ARR/VRQ) had 1.20 (SE = 0.45) mm, 1.38 (SE = 0.12) mm, 1.47 (S = 0.25) mm shallower ultrasound muscle depth relative to lambs of the less susceptible scrapie categories of 1, 2, 3, respectively (P < 0.05). Nonetheless, no association between PrP genotype and lamb carcass conformation, the ultimate end goal of producers, was detected. Ewe litter size, body condition score or lameness did not differ by PrP genotype of the ewe (P > 0.05). For ewe mature BW, ARH/VRQ ewes differed from most other ewe PrP genotypes and were, on average, 3.79 (SE = 1.66) kg heavier than ARR/ARR genotype ewes. Lamb dag score differed by dam PrP genotype (P < 0.05), although the differences were small. Results from this study show that scrapie is segregating within the Irish sheep population, but the PrP genotype was not associated with most traits investigated and, where associations were detected, the biological significance was minimal. This suggests minimal impact of selection on PrP genotype on performance, at least for the traits investigated in the present study.

Inter-animal genetic variability exist in organoleptic properties of prime beef meat.

The objective of the present study was to estimate genetic parameters for four organoleptic traits in beef meat, namely tenderness, juiciness, flavour and chewiness using data from 5380 young crossbred progeny of 748 different sires. As well as using the mean animal sensory score across all panellists for a given trait, other aggregate functions such as the median and modal values were also investigated. The heritability (SE) of mean tenderness, juiciness, flavour and chewiness was 0.16 (0.04), 0.14 (0.04), 0.11 (0.03) and 0.21 (0.06), respectively; heritability estimates for the other aggregate values of these traits were generally lower. All genetic correlations between tenderness, juiciness and flavour were positive (0.52 to 0.68) while the genetic correlations between these three traits with chewiness were all negative varying from -0.95 to -0.48. Weak genetic correlations (≤|0.16|) were evident between the sensory traits and all of carcass weight, conformation and subcutaneous fat cover.

Genetic analyses of live weight and carcass composition traits in purebred Texel, Suffolk and Charollais lambs.

Lamb live weight is one of the key drivers of profitability on sheep farms. Previous studies in Ireland have estimated genetic parameters for live weight and carcass composition traits using a multi-breed population rather than on an individual breed basis. The objective of the present study was to undertake genetic analyses of three lamb live weight and two carcass composition traits pertaining to purebred Texel, Suffolk and Charollais lambs born in the Republic of Ireland between 2010 and 2017, inclusive. Traits (with lamb age range in parenthesis) considered in the analyses were: pre-weaning weight (20 to 65 days), weaning weight (66 to 120 days), post-weaning weight (121 to 180 days), muscle depth (121 to 180 days) and fat depth (121 to 180 days). After data edits, 137 402 records from 50 372 lambs across 416 flocks were analysed. Variance components were derived using animal linear mixed models separately for each breed. Fixed effects included for all traits were contemporary group, age at first lambing of the dam, parity of the dam, a gender by age of the lamb interaction and a birth type by rearing type of the lamb interaction. Random effects investigated in the pre-weaning and weaning weight analyses included animal direct additive genetic, dam maternal genetic, litter common environment, dam permanent environment and residual variances. The model of analysis for post-weaning, muscle and fat depth included an animal direct additive genetic and litter common environment effect only. Significant direct additive genetic variation existed in all cases. Direct heritability for pre-weaning weight ranged from 0.14 to 0.30 across the three breeds. Weaning weight had a direct heritability ranging from 0.17 to 0.27 and post-weaning weight had a direct heritability ranging from 0.15 to 0.27. Muscle and fat depth heritability estimates ranged from 0.21 to 0.31 and 0.15 to 0.20, respectively. Positive direct correlations were evident for all traits. Results revealed ample genetic variation among animals for the studied traits and significant differences between breeds to suggest that genetic evaluations could be conducted on a per-breed basis.

Mean difference in live-weight per incremental difference in body condition score estimated in multiple sheep breeds and crossbreds.

Body condition score (BCS) is a subjective assessment of the proportion of body fat an animal possesses and is independent of frame size. There is a growing awareness of the importance of mature animal live-weight given its contribution to the overall costs of production of a sector. Because of the known relationship between BCS and live-weight, strategies to reduce live-weight could contribute to the favouring of animals with lesser body condition. The objective of the present study was to estimate the average difference in live-weight per incremental change in BCS, measured subjectively on a scale of 1 to 5. The data used consisted of 19 033 BCS and live-weight observations recorded on the same day from 7556 ewes on commercial and research flocks; the breeds represented included purebred Belclare (540 ewes), Charollais (1484 ewes), Suffolk (885 ewes), Texel (1695 ewes), Vendeen (140 ewes), as well as, crossbreds (2812 ewes). All associations were quantified using linear mixed models with the dependent variable of live-weight; ewe parity was included as a random effect. The independent variables were BCS, breed (n=6), stage of the inter-lambing interval (n=6; pregnancy, lambing, pre-weaning, at weaning, post-weaning and mating) and parity (1, 2, 3, 4 and 5+). In addition, two-way interactions were used to investigate whether the association between BCS and live-weight differed by parity, a period of the inter-lambing interval or breed. The association between BCS and live-weight differed by parity, by a period of the inter-lambing interval and by breed. Across all data, a one-unit difference in BCS was associated with 4.82 (SE=0.08) kg live-weight, but this differed by parity from 4.23 kg in parity 1 ewes to 5.82 kg in parity 5+ ewes. The correlation between BCS and live-weight across all data was 0.48 (0.47 when adjusted for nuisance factors in the statistical model), but this varied from 0.48 to 0.53 by parity, from 0.36 to 0.63 by stage of the inter-lambing interval and from 0.41 to 0.62 by breed. Results demonstrate that consideration should be taken of differences in BCS when comparing ewes on live-weight as differences in BCS contribute quite substantially to differences in live-weight; moreover, adjustments for differences in BCS should consider the population stratum, especially breed.

Genetic selection for hoof health traits and cow mobility scores can accelerate the rate of genetic gain in producer-scored lameness in dairy cows.

Cattle breeding programs that strive to reduce the animal-level incidence of lameness are often hindered by the availability of informative phenotypes. As a result, indicator traits of lameness (i.e., hoof health and morphological conformation scores) can be used to improve the accuracy of selection and subsequent genetic gain. Therefore, the objectives of the present study were to estimate the variance components for hoof health traits using various phenotypes collected from a representative sample of Irish dairy cows. Also of interest to the present study was the genetic relationship between both hoof health traits and conformation traits with producer-scored lameness. Producer-recorded lameness events and linear conformation scores from 307,657 and 117,859 Irish dairy cows, respectively, were used. Data on hoof health (i.e., overgrown sole, white line disease, and sole hemorrhage), mobility scores, and body condition scores were also available from a research study on up to 11,282 Irish commercial dairy cows. Linear mixed models were used to quantify variance components for each trait and to estimate genetic correlations among traits. The estimated genetic parameters for hoof health traits in the present study were greater (i.e., heritability range: 0.005 to 0.27) than previously reported in dairy cows. With the exception of analyses that considered hoof health traits in repeatability models, little difference in estimated variance components existed among the various hoof-health phenotypes. Results also suggest that producer-recorded lameness is correlated with both hoof health (i.e., genetic correlation up to 0.48) and cow mobility (i.e., genetic correlation = 0.64). Moreover, cows that genetically tend to have rear feet that appear more parallel when viewed from the rear are also genetically more predisposed to lameness (genetic correlation = 0.39); genetic correlations between lameness and other feet and leg type traits, as well as between lameness and frame type traits, were not different from zero. Results suggest that if the population breeding goal was to reduce lameness incidence, improve hoof health, or improve cow mobility, genetic selection for either of these traits should indirectly benefit the other traits. Results were used to quantify the genetic gains achievable for lameness when alternative phenotypes are available.

Heritability estimates of meat sensory characteristics are a function of the number of panellists and their inter-correlations.

The objective of the present study was to quantify, using simulated data, the impact on estimated heritability of varying the number of panellists and their inter-correlations using meat sensory tenderness in cattle as an example. Estimated parameters from actual sensory-based tenderness scores from 9 individual panellists on 1252 beef cattle were used to parameterise the simulation. A single "tenderness score" for each of 10 panellists was simulated for 15,000 cattle. Heritability estimates were calculated for each of the 10 panellists individually as well as the mean score per animal for all n combinations of panellists. Heritability estimates improved with increasing number of panellists in line with expectations from a deterministic equation. The increase in heritability was due to a reduction in the residual variance, albeit the rate of reduction in residual variance declined with each additional panellist included in the calculated mean tenderness score. Results highlight the importance of reporting the number of panellist scores per animal as well as their inter-correlations in sensory-based studies.

Impact of alternative definitions of contemporary groups on genetic evaluations of traits recorded at lambing.

The objective of this study was to quantify the impact of alternative contemporary group definitions for lambing traits on genetic evaluations in the Irish multibreed sheep population. Three lambing traits were considered for analysis: lambing difficulty, birth weight, and survival. Eight alternative contemporary group definitions were investigated for each lambing trait; all contemporary groups were formed within flock of lambing and included (flock by) week of lambing, week of lambing by litter size (i.e., singles vs. multiples), 2-wk interval (i.e., fortnight) of lambing, fortnight of lambing by litter size, month of lambing, and month of lambing by litter size or were based on an optimized algorithm that creates contemporary groups based on animals from the same flock that are born in close proximity of date. Three alternative scenarios were modeled for each of the lambing traits using the contemporary group definitions: the first scenario (termed Current Scenario) represented the editing criteria currently employed in the Irish national genetic evaluations; the second scenario (No Restriction Scenario) removed any restriction on number of records per contemporary group, and the final scenario (Variation Scenario) included only data from contemporary groups with some variability in the dependent variable. Variance components and EBV for each of the 3 lambing traits were estimated using linear mixed models. The direct heritability estimates ranged from 0.09 ± 0.02 to 0.29 ± 0.02 for lambing difficulty, 0.11 ± 0.01 to 0.24 ± 0.01 for birth weight, and 0.05 ± 0.02 to 0.10 ± 0.02 for lamb survival. Irrespective of lambing trait, greater estimated accuracy of the sire EBV was achieved with the No Restriction Scenario. Results for the ability to predict future lambing characteristics, based on only the direct and maternal EBV, revealed that the area under the receiver operator characteristic curve for the dichotomized lambing assistance phenotype varied from 0.56 to 0.66; a lambing event predicted to be in the worst 10% risk category of a difficult lambing on the basis of genetic merit alone was 5.48 times (95% CI: 3.94 to 7.61; < 0.001) more likely to require assistance at lambing compared to a lambing event in the best 10%. Results show that the use of contemporary groups formed over short time periods, coupled with moderate editing of the data, yielded superior predictions for all lambing traits.

Animal breeding strategies can improve meat quality attributes within entire populations.

The contribution of animal breeding to changes in animal performance is well documented across a range of species. Once genetic variation in a trait exists, then breeding to improve the characteristics of that trait is possible, if so desired. Considerable genetic variation exists in a range of meat quality attributes across a range of species. The genetic variation that exists for meat quality is as large as observed for most performance traits; thus, within a well-structured breeding program, rapid genetic gain for meat quality could be possible. The rate of genetic gain can be augmented through the integration of DNA-based technologies into the breeding program; such DNA-based technologies should, however, be based on thousands of DNA markers dispersed across the entire genome. Genetic and genomic technologies can also have beneficial impact outside the farm gate as a tool to segregate carcasses or meat cuts based on expected meat quality features.

Impact of birth and rearing type, as well as inaccuracy of recording, on pre-weaning lamb phenotypic and genetic merit for live weight.

The objective of the present study was to quantify the impact of the systematic environmental effects of both birth and rearing type on pre-weaning lamb live weight, and to evaluate the repercussions of inaccurate recording of birth and rearing type on subsequent genetic evaluations. A total of 32,548 birth weight records, 35,770 forty-day weight records and 32,548 records for average daily gain (ADG) between birth and 40-day weight from the Irish national sheep database were used. For each lamb, a new variable, birth-rearing type, reflecting both the birth and rearing type of a lamb was generated by concatenating both parameters. The association between birth-rearing type and birth weight, 40-day weight, and ADG was estimated using linear mixed models. The repercussions of inaccurate recording of birth type were determined by quantifying the impact on sire estimated breeding value (EBV; with an accuracy of ≥ 35%), where one of the lambs born in a selection of twin litter births was assumed to have died at birth but the farmer recorded the birth and rearing type as a singleton. The heaviest mean birth weight was associated with lambs born and subsequently reared as singles (5.47 kg); the lightest mean birth weight was associated with lambs born and reared as triplets (4.10 kg). The association between birth-rearing type and 40-day weight differed by dam parity (P < 0.001). Lambs reared by first parity dams as singles, irrespective of birth type were, on average, heavier at 40-day weighing than lambs reared as multiples, but as parity number increased, single-born lambs reared as twins outperformed triplet-born lambs reared as singles. Irrespective of the trait evaluated, the correlation between sire EBV estimated from the accurately recorded data and sire EBV estimated from the data with recording errors was strong ranging from 0.93 (birth weight) to 0.97 (ADG). The EBV for sires with progeny data manipulated were 0.14 kg, 0.34 kg and 5.56 g/d less for birth weight, 40-day weight and ADG, respectively, compared to their equivalent EBV calculated using accurately recorded data. Results from this study highlight the importance of precise recording of birth-rearing type by producers for the generation of accurate genetic evaluations.

Genetic parameters for lameness, mastitis and dagginess in a multi-breed sheep population.

The objective of the present study was to quantify the extent of genetic variation in three health-related traits namely dagginess, lameness and mastitis, in an Irish sheep population. Each of the health traits investigated pose substantial welfare implications as well as considerable economic costs to producers. Data were also available on four body-related traits, namely body condition score (BCS), live weight, muscle depth and fat depth. Animals were categorised as lambs (<365 days old) or ewes (⩾365 days old) and were analysed both separately and combined. After edits, 39 315 records from 264 flocks between the years 2009 and 2015 inclusive were analysed. Variance components were estimated using animal linear mixed models. Fixed effects included contemporary group, represented as a three-way interaction between flock, date of inspection and animal type (i.e. lamb, yearling ewe (i.e. females ⩾365 days but <730 days old that have not yet had a recorded lambing) or ewe), animal breed proportion, coefficients of heterosis and recombination, animal gender (lambs only), animal parity (ewes only; lambs were assigned a separate 'parity') and the difference in age of the animal from the median of the respective parity/age group. An additive genetic effect and residual effect were both fitted as random terms with maternal genetic and non-genetic components also considered for traits of the lambs. The direct heritability of dagginess was similar across age groups (0.14 to 0.15), whereas the direct heritability of lameness ranged from 0.06 (ewes) to 0.12 (lambs). The direct heritability of mastitis was 0.04. For dagginess, 13% of the phenotypic variation was explained by dam litter, whereas the maternal heritability of dagginess was 0.05. The genetic correlation between ewe and lamb dagginess was 0.38; the correlation between ewe and lamb lameness was close to zero but was associated with a large standard error. Direct genetic correlations were evident between dagginess and BCS in ewes and between lameness and BCS in lambs. The present study has demonstrated that ample genetic variation exists for all three health traits investigated indicating that genetic improvement is indeed possible.

Risk factors associated with lambing traits.

The objective of this study was to establish the risk factors associated with both lambing difficulty and lamb mortality in the Irish sheep multibreed population. A total of 135 470 lambing events from 42 675 ewes in 839 Irish crossbred and purebred flocks were available. Risk factors associated with producer-scored ewe lambing difficulty score (scale of one (no difficulty) to four (severe difficulty)) were determined using linear mixed models. Risk factors associated with the logit of the probability of lamb mortality at birth (i.e. binary trait) were determined using generalised estimating equations. For each dependent variable, a series of simple regression models were developed as well as a multiple regression model. In the simple regression models, greater lambing difficulty was associated with quadruplet bearing, younger ewes, of terminal breed origin, lambing in February; for example, first parity ewes experienced greater (P7.0 kg) birth weights, quadruplet born lambs and lambs that experienced a more difficult lambing (predicted probability of death for lambs that required severe and veterinary assistance of 0.15 and 0.32, respectively); lambs from dual-purpose breeds and born to younger ewes were also at greater risk of mortality. In the multiple regression model, the association between ewe parity, age at first lambing, year of lambing and lamb mortality no longer persisted. The trend in solutions of the levels of each fixed effect that remained associated with lamb mortality in the multiple regression model, did not differ from the trends observed in the simple regression models although the differential in relative risk between the different lambing difficulty scores was greater in the multiple regression model. Results from this study show that many common flock- and animal-level factors are associated with both lambing difficulty and lamb mortality and management of different risk category groups (e.g. scanned litter sizes, ewe age groups) can be used to appropriately manage the flock at lambing to reduce their incidence.

Genetic selection for increased mean and reduced variance of twinning rate in Belclare ewes.

It is sometimes possible to breed for more uniform individuals by selecting animals with a greater tendency to be less variable, that is, those with a smaller environmental variance. This approach has been applied to reproduction traits in various animal species. We have evaluated fecundity in the Irish Belclare sheep breed by analyses of flocks with differing average litter size (number of lambs per ewe per year, NLB) and have estimated the genetic variance in environmental variance of lambing traits using double hierarchical generalized linear models (DHGLM). The data set comprised of 9470 litter size records from 4407 ewes collected in 56 flocks. The percentage of pedigreed lambing ewes with singles, twins and triplets was 30, 54 and 14%, respectively, in 2013 and has been relatively constant for the last 15 years. The variance of NLB increases with the mean in this data; the correlation of mean and standard deviation across sires is 0.50. The breeding goal is to increase the mean NLB without unduly increasing the incidence of triplets and higher litter sizes. The heritability estimates for lambing traits were NLB, 0.09; triplet occurrence (TRI) 0.07; and twin occurrence (TWN), 0.02. The highest and lowest twinning flocks differed by 23% (75% versus 52%) in the proportion of ewes lambing twins. Fitting bivariate sire models to NLB and the residual from the NLB model using a double hierarchical generalized linear model (DHGLM) model found a strong genetic correlation (0.88 ± 0.07) between the sire effect for the magnitude of the residual (VE ) and sire effects for NLB, confirming the general observation that increased average litter size is associated with increased variability in litter size. We propose a threshold model that may help breeders with low litter size increase the percentage of twin bearers without unduly increasing the percentage of ewes bearing triplets in Belclare sheep.

Genetic relationships between carcass cut weights predicted from video image analysis and other performance traits in cattle.

The objective of this study was to quantify the genetic associations between a range of carcass-related traits including wholesale cut weights predicted from video image analysis (VIA) technology, and a range of pre-slaughter performance traits in commercial Irish cattle. Predicted carcass cut weights comprised of cut weights based on retail value: lower value cuts (LVC), medium value cuts (MVC), high value cuts (HVC) and very high value cuts (VHVC), as well as total meat, fat and bone weights. Four main sources of data were used in the genetic analyses: price data of live animals collected from livestock auctions, live-weight data and linear type collected from both commercial and pedigree farms as well as from livestock auctions and weanling quality recorded on-farm. Heritability of carcass cut weights ranged from 0.21 to 0.39. Genetic correlations between the cut traits and the other performance traits were estimated using a series of bivariate sire linear mixed models where carcass cut weights were phenotypically adjusted to a constant carcass weight. Strongest positive genetic correlations were obtained between predicted carcass cut weights and carcass value (min r g(MVC) = 0.35; max r(g(VHVC)) = 0.69), and animal price at both weaning (min r(g(MVC)) = 0.37; max r(g(VHVC)) = 0.66) and post weaning (min r(g(MVC)) = 0.50; max r(g(VHVC)) = 0.67). Moderate genetic correlations were obtained between carcass cut weights and calf price (min r g(HVC) = 0.34; max r g(LVC) = 0.45), weanling quality (min r(g(MVC)) = 0.12; max r (g(VHVC)) = 0.49), linear scores for muscularity at both weaning (hindquarter development: min r(g(MVC)) = -0.06; max r(g(VHVC)) = 0.46), post weaning (hindquarter development: min r(g(MVC)) = 0.23; max r(g(VHVC)) = 0.44). The genetic correlations between total meat weight were consistent with those observed with the predicted wholesale cut weights. Total fat and total bone weights were generally negatively correlated with carcass value, auction prices and weanling quality. Total bone weight was, however, positively correlated with skeletal scores at weaning and post weaning. These results indicate that some traits collected early in life are moderate-to-strongly correlated with carcass cut weights predicted from VIA technology. This information can be used to improve the accuracy of selection for carcass cut weights in national genetic evaluations.

Genetic associations between feed efficiency measured in a performance test station and performance of growing cattle in commercial beef herds.

Interest in selection for improved feed efficiency is increasing, but before any steps are taken toward selecting for feed efficiency, correlations with other economically important traits must first be quantified. The objective of this study was to quantify the genetic associations between feed efficiency measured during performance testing and linear type traits, BW, live animal value, and carcass traits recorded in commercial herds. Feed efficiency data were available on 2,605 bulls from 1 performance test station. There were between 10,384 and 93,442 performance records on type traits, BW, animal value, or carcass traits from 17,225 commercial herds. (Co)variance components were estimated using linear mixed animal models. Genetic correlations between the muscular type traits in commercial animals and feed conversion ratio (-0.33 to -0.25), residual feed intake (RFI; -0.33 to -0.22), and residual BW gain (RG; 0.24 to 0.27) suggest that selection for improved feed efficiency should increase muscling. This is further evidenced by the genetic correlations between carcass conformation of commercial animals and feed conversion ratio (-0.46), RFI (-0.37), and residual BW gain (0.35) measured in performance-tested animals. Furthermore, the genetic correlations between RFI and both ultrasonic fat depth and carcass fat score (0.39 and 0.33, respectively) indicated that selection for improved RFI will result in leaner animals. It can be concluded from the genetic correlations estimated in this study that selection for feed efficiency will have no unfavorable effects on the performance traits measured in this study and will actually lead to an improvement in performance for some traits, such as muscularity, animal price, and carcass conformation. Conversely, this suggests that genetic selection for traits such as carcass quality, muscling traits, and animal value might also be indirectly selecting for more efficient animals.

Genetic structure of the European Charolais and Limousin cattle metapopulations using pedigree analyses.

Pedigree collected by the Interbeef service allowed genetic diversity to be assessed by using pedigree analyses for the European Charolais (CHA) and Limousin (LIM) cattle populations registered in national herdbooks in Denmark (DNK), France (FRA), Ireland (IRL), Sweden (SWE), and, solely for the LIM breed, the United Kingdom (UK). The CHA data set included 2,563,189 calves with weaning performance, of which 96.1% were recorded in FRA, 3.0% in SWE, 0.5% in IRL, and 0.4% in DNK. The LIM data set included 1,652,734 calves with weaning performance, of which 91.9% were recorded in FRA, 4.9% in UK, 1.8% in DNK, 0.9% SWE, and 0.5% in IRL. Pedigree files included 3,191,132 CHA and 2,409,659 LIM animals. Gene flows were rather limited between populations, except from FRA toward other countries. Pedigree completeness was good in all subpopulations for both breeds and allowed the pedigree to be traced back to the French population. A relatively high level of genetic diversity was assessed in each CHA and LIM subpopulation by estimating either effective population sizes (N(e) >244 and N(e) >345 in the CHA and LIM subpopulations, respectively), relationship coefficients within subpopulations (<1.3% in both breeds), or probability of gene origins. However, in each subpopulation, it was shown that founders and also ancestors had unbalanced genetic contributions, leading to a moderate but continuous reduction in genetic diversity. Analyses between populations suggested that all European CHA and LIM populations were differentiated very little. The Swedish CHA population was assessed as genetically more distant from the other CHA populations because of fewer gene flows from other countries and because of the use of North American sires to introgress the polled phenotype. In each European subpopulation, most of the main ancestors, which explained 50% of gene origin, were born in FRA. However, those main ancestors were different between countries. Moreover, in both breeds, the main ancestors, which explained 50% of the gene origin in DNK, IRL, SWE, and UK for the LIM breed, were found to be infrequently used in FRA. Those results were consistent with the low relationship coefficients estimated between subpopulations (<0.6% in both the CHA and LIM breeds). Therefore, in both breeds, each subpopulation may constitute a reservoir of genetic diversity for the other ones.

Genetic variation in wholesale carcass cuts predicted from digital images in cattle.

The objective of this study was to quantify the genetic variation in carcass cuts predicted using digital image analysis in commercial cross-bred cattle. The data set comprised 38,404 steers and 14,318 heifers from commercial Irish herds. The traits investigated included the weights of lower value cuts (LVC), medium value cuts (MVC), high value cuts (HVC), very high value cuts (VHVC) and total meat weight. In addition, the weights of total fat and total bones were available on the steers. Heritability of carcass cut weights, within gender, was estimated using an animal linear model, whereas genetic and phenotypic correlations among cuts were estimated using a sire linear model. Carcass weight was included as a covariate in all models. In the steers, heritability ranged from 0.13 (s.e. = 0.02) for VHVC to 0.49 (s.e. = 0.03) for total bone weight, and in the heifers heritability ranged from 0.15 (s.e. = 0.04) for MVC to 0.72 (s.e. = 0.06) for total meat weight. The coefficient of genetic variation for the different cuts varied from 1.4% to 3.6%. Genetic correlations between the different cut weights were all positive and ranged from 0.45 (s.e. = 0.08) to 0.89 (s.e. = 0.03) in the steers, and from 0.47 (s.e. = 0.14) to 0.82 (s.e. = 0.06) in the heifers. Genetic correlations between the wholesale cut weights and carcass conformation ranged from 0.32 (s.e. = 0.06) to 0.45 (s.e. = 0.07) in the steers, and from 0.10 (s.e. = 0.12) to 0.38 (s.e. = 0.09) in the heifers. Genetic correlations between the same wholesale cut traits in steers and heifers ranged from 0.54 (s.e. = 0.14) for MVC to 0.79 (s.e. = 0.06) for total meat weight; genetic correlations between carcass weight and carcass classification for conformation and fat score in both genders varied from 0.80 to 0.87. The existence of genetic variation in carcass cut traits, coupled with the routine availability of predicted cut weights from digital image analysis, clearly shows the potential to genetically improve carcass value.