Genetic Standard Deviation Research Articles

Effects of Genotype by Environment Interaction on Genetic Gain and Genetic Parameter Estimates in Red Tilapia (Oreochromis spp.).

The extent to which genetic gain achieved from selection programs under strictly controlled environments in the nucleus that can be expressed in commercial production systems is not well-documented in aquaculture species. The main aim of this paper was to assess the effects of genotype by environment interaction on genetic response and genetic parameters for four body traits (harvest weight, standard length, body depth, body width) and survival in Red tilapia (Oreochromis spp.). The growth and survival data were recorded on 19,916 individual fish from a pedigreed population undergoing three generations of selection for increased harvest weight in earthen ponds from 2010 to 2012 at the Aquaculture Extension Center, Department of Fisheries, Jitra in Kedah, Malaysia. The pedigree comprised a total of 224 sires and 262 dams, tracing back to the base population in 2009. A multivariate animal model was used to measure genetic response and estimate variance and covariance components. When the homologous body traits in freshwater pond and cage were treated as genetically distinct traits, the genetic correlations between the two environments were high (0.85–0.90) for harvest weight and square root of harvest weight but the estimates were of lower magnitudes for length, width and depth (0.63–0.79). The heritabilities estimated for the five traits studied differed between pond (0.02 to 0.22) and cage (0.07 to 0.68). The common full-sib effects were large, ranging from 0.23 to 0.59 in pond and 0.11 to 0.31 in cage across all traits. The direct and correlated responses for four body traits were generally greater in pond than in cage environments (0.011–1.561 vs. −0.033–0.567 genetic standard deviation units, respectively). Selection for increased harvest body weight resulted in positive genetic changes in survival rate in both pond and cage culture. In conclusion, the reduced selection response and the magnitude of the genetic parameter estimates in the production environment (i.e., cage) relative to those achieved in the nucleus (pond) were a result of the genotype by environment interaction and this effect should be taken into consideration in the future breeding program for Red tilapia.

Genetic analysis of feet and leg conformation traits in Nelore cattle1

Feet and leg conformation scores are important traits in beef cattle because they encompass a wide range of locomotion disorders that can lead to productive and reproductive losses. Thus, the study of feet and legs in beef cattle is essential for evaluating possible responses to selection focusing on minimizing economic losses caused by the occurrence of feet and leg problems. The aim of this study was to estimate variance components for feet and leg conformation traits in Nelore cattle. The data set contained records of approximately 300,000 animals that were born between 2000 and 2013. These animals belonged to the commercial beef cattle breeding program of the CRV Lagoa (). Feet and legs were evaluated by assigning visual scores at 2 different time points: feet and leg evaluated as a binary trait (FL1), measured at yearling (about 550 d of age) to identify whether (or not) an animal has feet and leg defects, and feet and leg score (FL2), ranging from 1 (less desirable) to 5 (more desirable) was assigned to the top 20% of animals according to the selection index adopted by the beef cattle breeding program, which was measured 2 to 5 mo after the yearling evaluation. The FL1 and FL2 traits were analyzed together with yearling weight (YW). The (co)variance components and breeding values were estimated by Bayesian inference using 2-trait animal models. The posterior means (standard errors) of the heritabilities for FL1, FL2, and YW were 0.18 (0.04), 0.39 (0.07), and 0.47 (0.01), respectively. The results indicate that the incidence of feet and leg problems in this population might be reduced by selection. The genetic correlation between FL1 and FL2 (-0.47) was moderate and negative as expected because the classification score that holds up each trait has opposite numerical values. The genetic trends estimated for FL1 and FL2 (-0.042 and 0.021 genetic standard deviations per year, respectively) were favorable and they indicate that the independent culling strategy for feet and leg problems promotes favorable changes and contributes to the genetic progress of these traits in the population under study.

Economic values of growth rate, feed intake, feed conversion ratio, mortality and uniformity for Nile tilapia

The aim of the study was to derive the economic value (s) (EVs) of growth rate, feed intake, feed conversion ratio, mortality and uniformity for Nile tilapia (Oreochromis niloticus). A smallholder production system where fish are cultured in earthen ponds and oxygen is a limiting factor for production, was simulated using a deterministic bio-economic model. Traits of interest were: thermal growth coefficient (TGC), thermal feed intake coefficient (TFC), feed conversion ratio (FCR), mortality rate (M) and uniformity of harvest body weight (U). Two breeding objectives were considered: a breeding objective with TGC, TFC, M and U (H1model), and a breeding objective with TGC, FCR, M and U (H2model). Gross margin (GM) was simulated before and after one genetic standard deviation improvement (σa) on a trait while other breeding objective traits were kept unaltered. EVs (US$/kg/σa) were derived as: change in GM/(farm production before genetic improvement). Results show that EVs of TGC differ depending on the definition of the breeding objective. The EV of TGC was 1.19 when TFC was in the breeding objective. In contrast, EV was only 0.02 when FCR was in the breeding objective. This difference is caused by the way EVs are calculated: the increase in gross margin resulting from a marginal increase in TGC while keeping other traits (FCR or TFC) constant. EV of TFC was 1.25 and the EV for FCR was 0.41. EVs for M and U were 0.06 and 0.02, irrespective of the model used. Improving TGC reduced the overall grow-out period, increasing the number of production cycles in the farm. In H1 model, reduced grow-out period was accompanied by a decrease in the amount of feed used in the farm (−272.24kg/year) and in individual fish oxygen consumption (−1.67g/fish/year), resulting in an increase in gross margin. In H2 model, increasing TGC resulted in a reduced grow out period but also increased feed used in the farm (5.73kg/year) and increased individual fish oxygen consumption (0.57g/fish/year). We conclude that the EV of TGC depends on which breeding objective is used. Faster growing fish consume more oxygen, and unless faster growth is accompanied by improved FCR, this will lead to oxygen limitations, necessitating lower stocking densities. Our results thus strongly confirm the economic importance of reducing FCR, irrespective of the model used.Statement of relevanceThis is the first study that presents the economic values for breeding objective traits for Nile tilapia farmed in earthen ponds using a bio-economic model.

A comparison of nonlinear mixed models and response to selection of tick-infestation on lambs.

Tick-borne fever (TBF) is stated as one of the main disease challenges in Norwegian sheep farming during the grazing season. TBF is caused by the bacterium Anaplasma phagocytophilum that is transmitted by the tick Ixodes ricinus. A sustainable strategy to control tick-infestation is to breed for genetically robust animals. In order to use selection to genetically improve traits we need reliable estimates of genetic parameters. The standard procedures for estimating variance components assume a Gaussian distribution of the data. However, tick-count data is a discrete variable and, thus, standard procedures using linear models may not be appropriate. Thus, the objectives of this study were twofold: 1) to compare four alternative non-linear models: Poisson, negative binomial, zero-inflated Poisson and zero-inflated negative binomial based on their goodness of fit for quantifying genetic variation, as well as heritability for tick-count and 2) to investigate potential response to selection against tick-count based on truncation selection given the estimated genetic parameters from the best fit model. Our results showed that zero-inflated Poisson was the most parsimonious model for the analysis of tick count data. The resulting estimates of variance components and high heritability (0.32) led us to conclude that genetic determinism is relevant on tick count. A reduction of the breeding values for tick-count by one sire-dam genetic standard deviation on the liability scale will reduce the number of tick counts below an average of 1. An appropriate breeding scheme could control tick-count and, as a consequence, probably reduce TBF in sheep.

Optimization of a genomic breeding program for a moderately sized dairy cattle population

Although it now standard practice to genotype thousands of female calves, genotyping of bull calves is generally limited to progeny of elite cows. In addition to genotyping costs, increasing the pool of candidate sires requires purchase, isolation, and identification of calves until selection decisions are made. We economically optimized via simulation a genomic breeding program for a population of approximately 120,000 milk-recorded cows, corresponding to the Israeli Holstein population. All 30,000 heifers and 60,000 older cows of parities 1 to 3 were potential bull dams. Animals were assumed to have genetic evaluations for a trait with heritability of 0.25 derived by an animal model evaluation of the population. Only bull calves were assumed to be genotyped. A pseudo-phenotype corresponding to each animal's genetic evaluation was generated, consisting of the animal's genetic value plus a residual with variance set to obtain the assumed reliability for each group of animals. Between 4 and 15 bulls and between 200 and 27,000 cows with the highest pseudo-phenotypes were selected as candidate bull parents. For all progeny of the founder animals, genetic values were simulated as the mean of the parental values plus a Mendelian sampling effect with variance of 0.5. A probability of 0.3 for a healthy bull calf per mating, and a genomic reliability of 0.43 were assumed. The 40 bull calves with the highest genomic evaluations were selected for general service for 1 yr. Costs included genotyping of candidate bulls and their dams, purchase of the calves from the farmers, and identification. Costs of raising culled calves were partially recovered by resale for beef. Annual costs were estimated as $10,922 + $305 × candidate bulls. Nominal profit per cow per genetic standard deviation was $106. Economic optimum with a discount rate of 5%, first returns after 4 yr, and a profit horizon of 15 yr were obtained with genotyping 1,620 to 1,750 calves for all numbers of bull sires. However, 95% of the optimal profit can be achieved with only 240 to 300 calves. The higher reliabilities achieved through addition of genomic information to the selection process contribute not only in obtaining higher genetic gain, but also in obtaining higher absolute profits. In addition, the optimal profits are obtained for a lower number of calves born in each generation. Inbreeding, as allowed within genomic selection for the Israeli herd, had virtually no effect on genetic gain or on profits, when compared with the case of exclusion of all matings that generate inbreeding. Annual response to selection ranged from 0.35 to 0.4 genetic standard deviation for 4 to 15 bull sires, as compared with 0.25 to 0.3 for a comparable half-sib design without genomic selection.

Derivation of economic values for production traits in aquaculture species

BackgroundIn breeding programs for aquaculture species, breeding goal traits are often weighted based on the desired gains but economic gain would be higher if economic values were used instead. The objectives of this study were: (1) to develop a bio-economic model to derive economic values for aquaculture species, (2) to apply the model to determine the economic importance and economic values of traits in a case-study on gilthead seabream, and (3) to validate the model by comparison with a profit equation for a simplified production system.MethodsA bio-economic model was developed to simulate a grow-out farm for gilthead seabream, and then used to simulate gross margin at the current levels of the traits and after one genetic standard deviation change in each trait with the other traits remaining unchanged. Economic values were derived for the traits included in the breeding goal: thermal growth coefficient (TGC), thermal feed intake coefficient (TFC), mortality rate (M), and standard deviation of harvest weight (sigma_{HW}). For a simplified production system, improvement in TGC was assumed to affect harvest weight instead of growing period. Using the bio-economic model and a profit equation, economic values were derived for harvest weight, cumulative feed intake at harvest, and overall survival.ResultsChanges in gross margin showed that the order of economic importance of the traits was: TGC, TFC, M, and sigma_{HW}. Economic values in € (kg production)−1 (trait unit)−1 were: 0.40 for TGC, −0.45 for TFC, −7.7 for M, and −0.0011 to −0.0010 for sigma_{HW}. For the simplified production system, similar economic values were obtained with the bio-economic model and the profit equation. The advantage of the profit equation is its simplicity, while that of the bio-economic model is that it can be applied to any aquaculture species, because it can include any limiting factor and/or environmental condition that affects production.ConclusionsWe confirmed the validity of the bio-economic model. TGC is the most important trait to improve, followed by TFC and M, and the effect of sigma_{HW} on gross margin is small.

Influence of imported sport horses on the genetic evaluation of Swedish Warmblood stallions

ABSTRACTThere is substantial international influence on the Swedish Warmblood (SWB) sport horse population. The SWB Association suspects that imported horses are pre-selected based on their anticipated performance level, which could lead to biased estimated breeding values (EBVs) for stallions. This study examined different strategies to handle records for imported horses in the genetic evaluation. The stallions were evaluated for 10 traits using 3 different EBV estimation methods that were compared based on ranking comparisons of stallions, accuracy, correlations and absolute differences between EBVs. The results showed that the stallions’ EBVs were affected by imported offspring which, as a group, had higher average scores than horses born in Sweden. Sire EBVs differed by up to 0.6 genetic standard deviation of the trait between methods for stallions with >50% imported offspring. Excluding imported offspring lowered the accuracies and caused larger re-ranking compared with including a fixed effect of origin in the model.

Validation of selection accuracy for the total number of piglets born in Landrace pigs using genomic selection.

ObjectiveThis study was to determine the relationship between estimated breeding value and phenotype information after farrowing when juvenile selection was made in candidate pigs without phenotype information.MethodsAfter collecting phenotypic and genomic information for the total number of piglets born by Landrace pigs, selection accuracy between genomic breeding value estimates using genomic information and breeding value estimates of best linear unbiased prediction (BLUP) using conventional pedigree information were compared.ResultsGenetic standard deviation (σa) for the total number of piglets born was 0.91. Since the total number of piglets born for candidate pigs was unknown, the accuracy of the breeding value estimated from pedigree information was 0.080. When genomic information was used, the accuracy of the breeding value was 0.216. Assuming that the replacement rate of sows per year is 100% and generation interval is 1 year, genetic gain per year is 0.346 head when genomic information is used. It is 0.128 when BLUP is used.ConclusionGenetic gain estimated from single step best linear unbiased prediction (ssBLUP) method is by 2.7 times higher than that the one estimated from BLUP method, i.e., 270% more improvement in efficiency.

Joint estimation of (co) variance components and breeding values for mean and dispersion of days from calving to first service in Holstein cow

The present study explored the possibility of selection for uniformity of days from calving to first service (DFS) in dairy cattle. A double hierarchical generalised linear model with an iterative reweighted least-squares algorithm was used to estimate covariance components for the mean and dispersion of DFS. Data included the records of 27 113 Iranian Holstein cows (parity, 1–6) in 15 herds from 1981 to 2007. The estimated additive genetic variance for the mean and dispersion were 32.25 and 0.0139; both of these values had low standard errors. The genetic standard deviation for dispersion of DFS was 0.117, indicating that decreasing the estimated breeding value of dispersion by one genetic standard deviation can increase the uniformity by 12%. A strong positive genetic correlation (0.689) was obtained between the mean and dispersion of DFS. This genetic correlation is favourable since one of the aims of breeding is to simultaneously decrease the mean and increase the uniformity of DFS. The Spearman rank correlations between estimated breeding values in the mean and dispersion for sires with a different number of daughter observations were 0.907. In the studied population, the genetic trend in the mean of DFS was significant and favourable (–0.063 days/year), but the genetic trend in the dispersion of DFS was not significantly different from zero. The results obtained in the present study indicated that the mean and uniformity of DFS can simultaneously be improved in dairy cows.

Genetic evaluation of a selective breeding program for common carp Cyprinus carpio conducted from 2004 to 2014.

BackgroundThe study evaluated genetic progress of a breeding program for common carp undergoing four generations of selection for increased harvest body weight from 2004 to 2014. The pedigree included 17,351 individual fish which were offspring of 342 sires and 352 dams. Genetic parameters for body weight at about two years of age and survival rate during grow-out period were also estimated using the residual maximum likelihood method applied to a two-trait linear mixed model. Direct response in body weight and correlated changes in survival were measured as the differences in: i) estimated breeding values (EBVs) between the two lines; and ii) EBVs of the selection line between successive generations.ResultsDirect gain in body weight ranged from 0.20 to 0.90 genetic standard deviation units and averaged 7 % of the base population per generation (two years per generation). Correlated changes in survival were negligible, indicating that the selection program for high growth did not have any adverse effect on this trait in the present population. The heritability for body weight was moderate (0.17, s.e. 0.05), whereas the estimate for survival was low (0.05–0.17) but significantly different from zero across linear mixed and threshold generalised statistical models. Our results predict that body weight or/and other growth related traits will continue to respond to selection and that there is potential to improve survival through direct genetic means. Correlated improvement in survival to selection for increased body weight was hardly achieved, as the genetic correlation between the two traits was not different from zero.ConclusionsIt is concluded that selection for increased harvest body weight resulted in significant improvement in growth performance of the present population of common carp Cyprinus carpio.Electronic supplementary materialThe online version of this article (doi:10.1186/s12863-015-0256-2) contains supplementary material, which is available to authorized users.

Effect of feed-related farm characteristics on relative values of genetic traits in dairy cows to reduce greenhouse gas emissions along the chain

Breeding has the potential to reduce greenhouse gas (GHG) emissions from dairy farming. Evaluating the effect of a 1-unit change (i.e., 1 genetic standard deviation improvement) in genetic traits on GHG emissions along the chain provides insight into the relative importance of genetic traits to reduce GHG emissions. Relative GHG values of genetic traits, however, might depend on feed-related farm characteristics. The objective of this study was to evaluate the effect of feed-related farm characteristics on GHG values by comparing the values of milk yield and longevity for an efficient farm and a less efficient farm. The less efficient farm did not apply precision feeding and had lower feed production per hectare than the efficient farm. Greenhouse gas values of milk yield and longevity were calculated by using a whole-farm model and 2 different optimization methods. Method 1 optimized farm management before and after a change in genetic trait by maximizing labor income; the effect on GHG emissions (i.e., from production of farm inputs up to the farm gate) was considered a side effect. Method 2 optimized farm management after a change in genetic trait by minimizing GHG emissions per kilogram of milk while maintaining labor income and milk production at least at the level before the change in trait; the effect on labor income was considered a side effect. Based on maximizing labor income (method 1), GHG values of milk yield and longevity were, respectively, 279 and 143kg of CO2 equivalents (CO2e)/unit change per cow per year on the less efficient farm, and 247 and 210kg of CO2e/unit change per cow per year on the efficient farm. Based on minimizing GHG emissions (method 2), GHG values of milk yield and longevity were, respectively, 538 and 563kg of CO2e/unit change per cow per year on the less efficient farm, and 453 and 441kg of CO2e/unit change per cow per year on the efficient farm. Sensitivity analysis showed that, for both methods, the absolute effect of a change in genetic trait depends on model inputs, including prices and emission factors. Substantial changes in relative importance between traits due to a change in model inputs occurred only in case of maximizing labor income. We concluded that assumptions regarding feed-related farm characteristics affect the absolute level of GHG values, as well as the relative importance of traits to reduce emissions when using a method based on maximizing labor income. This is because optimizing farm management based on maximizing labor income does not give any incentive for lowering GHG emissions. When using a method based on minimizing GHG emissions, feed-related farm characteristics affected the absolute level of the GHG values, but the relative importance of the traits scarcely changed: at each level of efficiency, milk yield and longevity were equally important.

Genetic analysis of within-litter variation in piglets' birth weight using genomic or pedigree relationship matrices.

The objective of this study was to estimate the genetic variance for within-litter variation of birth weight (BW0) using genomic (GRM) or pedigree relationship matrices (PRM) and to compare the accuracy of estimated breeding values (EBV) for within-litter variation of BW0 using GRM and PRM. The BW0 and residual variance of BW0 were modeled by the double hierarchical generalized linear model using GRM or PRM. Data came from 2 dam lines: Landrace and Large White. After editing, the data set in Landrace consisted of 748 sows with 1,938 litters and 29,430 piglets and in Large White of 989 sows with 3,320 litters and 51,818 piglets. To construct GRM, 46,466 (Landrace) and 44,826 (Large White) single nucleotide polymorphisms were used, whereas to construct PRM, 5 generations of pedigree were used. The accuracy of EBV with GRM was estimated with 8-fold cross-validation and compared to PRM. Estimated variance components were highly similar for GRM and PRM. The maternal genetic variance in residual variance of BW0 in Landrace was 0.05 with GRM and 0.06 with PRM. In Large White these were 0.04 with GRM and 0.05 with PRM. The genetic coefficient of variation (GCV SDe) was about 0.10 in both dam lines. This indicates a change of 10% in residual SD of BW0 when achieving a genetic response of 1 genetic standard deviation. The genetic correlation between birth weight and its residual variance was about 0.6 in both dam lines. The accuracies of selection for within-litter variation of birth weight were 0.35 with GRM and 0.23 with PRM in Landrace and 0.29 with GRM and 0.34 with PRM in Large White. In this case, using GRM did not significantly increase accuracies of selection. Results, however, show good opportunities to select for reduced within-litter variation of BW0. Genomic selection can increase accuracy of selection when reference populations contain at least 2,000 sows.

Selection for Duration of Fertility and Mule Duck White Plumage Colour in a Synthetic Strain of Ducks (Anas platyrhynchos).

A synthetic strain of ducks (Anas platyrhynchos) was developed by introducing genes for long duration of fertility to be used as mother of mule ducklings and a seven-generation selection experiment was conducted to increase the number of fertile eggs after a single artificial insemination (AI) with pooled Muscovy semen. Reciprocal crossbreeding between Brown Tsaiya LRI-2 (with long duration of fertility) and Pekin L-201 (with white plumage mule ducklings) ducks produced the G0. Then G1 were intercrossed to produce G2 and so on for the following generations. Each female duck was inseminated 3 times, at 26, 29, and 32 weeks of age. The eggs were collected for 14 days from day 2 after AI. Individual data regarding the number of incubated eggs (Ie), the number of fertile eggs at candling at day 7 of incubation (F), the total number of dead embryos (M), the maximum duration of fertility (Dm) and the number of hatched mule ducklings (H) with plumage colour were recorded. The selection criterion was the breeding values of the best linear unbiased prediction animal model for F. The results show high percentage of exhibited heterosis in G2 for traits to improve (19.1% for F and 12.9% for H); F with a value of 5.92 (vs 3.74 in the Pekin L-201) was improved in the G2. Heritabilities were found to be low for Ie (h2 = 0.07±0.03) and M (h2 = 0.07±0.01), moderately low for Dm (h2 = 0.13±0.02), of medium values for H (h2 = 0.20±0.03) and F (h2 = 0.23±0.03). High and favourable genetic correlations existed between F and Dm (rg = 0.93), between F and H (rg = 0.97) and between Dm and H (rg = 0.90). The selection experiment showed a positive trend for phenotypic values of F (6.38 fertile eggs in G10 of synthetic strain vs 5.59 eggs in G4, and 3.74 eggs in Pekin L-201), with correlated response for increasing H (5.73 ducklings in G10 vs 4.86 in G4, and 3.09 ducklings in Pekin L-201) and maximum duration of the fertile period without increasing the embryo mortality rate. The average predicted genetic response for F was 40% of genetic standard deviation per generation of selection. The mule ducklings’ feather colour also was improved. It was concluded that this study provided results for a better understanding of the genetics of the duration of fertility traits in the common female duck bred for mule and that the selection of a synthetic strain was effective method of improvement.

Environmental variation and breed sensitivity for growth rate and backfat depth in pigs

This study investigated the magnitude of environmental variation and compared the environmental sensitivity of Large White, Landrace and Duroc pigs based on reaction norms analyses for lifetime average daily gain (ADG) and backfat depth (BF). Data comprised 265 165 records collected between 2000 and 2010 on pigs from nine herds in Australia. Four environmental descriptors [the phenotypic mean and three least-squares means of contemporary groups (CG) of linear mixed models fitting fixed effects only or fitting sire or animal as additional random effects] were compared in order to quantify the environmental variation based on herd-by-birth month (HBM) and herd-by-birth week (HBW) CG for ADG and BF. Similar levels of variation were found for environmental descriptors based on HBM or HBW CG definitions for both traits but the accuracy of estimates for environmental descriptors was higher for HBM than HBW. The standard deviations of environmental descriptors were 31 (35) g/day for ADG and 1.0 (1.1) mm for BF based on the animal model fitting HBM (HBW), which are similar to the genetic standard deviations usually observed for these traits. Most of this variation in environmental conditions was also observed within years and within herds. Landrace had the highest ADG and Large White had the lowest BF across the environmental range. Significant breed-by-environment interaction was found for ADG but not for BF. Duroc was least sensitive and Large White was most sensitive indicating that the leaner breed was less able to perform consistently across the observed range of environmental conditions in this study.

Sire effect on early and late embryonic death in French Holstein cattle

We investigated the effect of maternal sire on early pregnancy failure (between D0, day of insemination and D90) in their progeny during the first and second lactations (n=3508) in the Holstein breed. The estimated breeding value (EBV) for cow fertility of 12 bulls (reliability⩾0.95) was used to create the following three groups: low, medium and high EBV (EBV from −0.7 to 1 expressed as genetic standard deviation relative to the mean of the breed). In their daughters (93 to 516 per bull), progesterone measurement was carried out on the day of artificial insemination (AI; D0) to check whether the cows were in the follicular phase and on D18 to 25 to assess non-fertilisation-early embryonic mortality (NF-EEM). Late embryonic mortality (LEM) and early foetal death (FD) were determined by ultrasonography on D45 and D90 and by the return to oestrus after the first AI. Frequencies of NF-EEM, LEM, FD and pregnancy were 33.3%, 11.7%, 1.4% and 48.5% and incidences were 35.1, 19.0, 2.7 and 51.1, respectively. Sire EBV was significantly related to the incidences of pregnancy failure between D0 and D90, fertilisation failure-early embryonic mortality (FF-EEM) and LEM but not to the incidence of FD between D45 and D90 of pregnancy. The relative risk (RR) of FF-EEM was significantly higher (RR=1.2; P<0.05) for the progeny group of low EBV bulls when compared with high EBV bulls. The same effect was observed when comparing LEM of the progeny groups from the low EBV bulls to those from moderate and high EBV bulls (RR, respectively, of 1.3 and 1.4; P<005). The incidence of FF-EEM was significantly higher when cows were inseminated before 80 days postpartum compared with later, and for the extreme values of the difference between milk fat and protein content measured during the first 3 months of lactation. FF-EEM was also significantly related to the year of observation. The incidence of LEM was higher for the highest producing cows and was influenced by interaction between milk yield×lactation rank and milk yield×milk protein content. In conclusion, this study showed large differences in early pregnancy failure between progeny groups and highlights the interest of accurate characterisation of embryonic death in order to identify potential candidate genes for female fertility.

Genetics of bovine respiratory disease in cattle: can breeding programs reduce the problem?

Genetics is responsible for approximately half the observed change in performance internationally in well-structured cattle breeding programs. Almost all, if not all, individual characteristics, including animal health, have a genetic basis. Once genetic variation exists then breeding for improvement is possible. Although the heritability of most health traits is low to moderate, considerable exploitable genetic variation does exist. From the limited studies undertaken, and mostly from limited datasets, the direct heritability of susceptibility to BRD varied from 0.07 to 0.22 and the maternal heritability (where estimated) varied from 0.05 to 0.07. Nonetheless, considerable genetic variation clearly exists; the genetic standard deviation for the direct component (binary trait), although differing across populations, varied from 0.08 to 0.20 while the genetic standard deviation for the maternal component varied from 0.04 to 0.07. Little is known about the genetic correlation between genetic predisposition to BRD and animal performance; the estimation of these correlations should be prioritized. (Long-term) Breeding strategies to reduce the incidence of BRD in cattle should be incorporated into national BRD eradication or control strategies.

Genomic testing interacts with reproductive surplus in reducing genetic lag and increasing economic net return

Until now, genomic information has mainly been used to improve the accuracy of genomic breeding values for breeding animals at a population level. However, we hypothesize that the use of information from genotyped females also opens up the possibility of reducing genetic lag in a dairy herd, especially if genomic tests are used in combination with sexed semen or a high management level for reproductive performance, because both factors provide the opportunity for generating a reproductive surplus in the herd. In this study, sexed semen is used in combination with beef semen to produce high-value crossbred beef calves. Thus, on average there is no surplus of and selection among replacement heifers whether to go into the herd or to be sold. In this situation, the selection opportunities arise when deciding which cows to inseminate with sexed semen, conventional semen, or beef semen. We tested the hypothesis by combining the results of 2 stochastic simulation programs, SimHerd and ADAM. SimHerd estimates the economic effect of different strategies for use of sexed semen and beef semen at 3 levels of reproductive performance in a dairy herd. Besides simulating the operational return, SimHerd also simulates the parity distribution of the dams of heifer calves. The ADAM program estimates genetic merit per year in a herd under different strategies for use of sexed semen and genomic tests. The annual net return per slot was calculated as the sum of operational return and value of genetic lag minus costs of genomic tests divided by the total number of slots. Our results showed that the use of genomic tests for decision making decreases genetic lag by as much as 0.14 genetic standard deviation units of the breeding goal and that genetic lag decreases even more (up to 0.30 genetic standard deviation units) when genomic tests are used in combination with strategies for increasing and using a reproductive surplus. Thus, our hypothesis was supported. We also observed that genomic tests are used most efficiently to decrease genetic lag when the genomic information is used more than once in the lifetime of an animal and when as many selection decisions as possible are based on genomic information. However, all breakeven prices were lower than or equal to €50, which is the current price of low-density chip genotyping in Denmark, Finland, and Sweden, so in the vast majority of cases, it is not profitable to genotype routinely for management purposes under the present price assumptions.

Economic weights for maternal traits of sows, including sow longevity1

The objective of this study was to develop a transparent, comprehensive, and flexible model for each trait for the formulation of breeding objectives for sow traits in swine breeding programs. Economic values were derived from submodels considering a typical Australian pig production system. Differences in timing and expressions of traits were accounted for to derive economic weights that were compared on the basis of their relative size after multiplication by their corresponding genetic standard deviation to account for differences in scale and genetic variability present for each trait. The number of piglets born alive had the greatest contribution (27.1%) to a subindex containing only maternal traits, followed by daily gain (maternal; 22.0%) and sow mature weight (15.0%). Other traits considered in the maternal breeding objective were preweaning survival (11.8%), sow longevity (12.5%), gilt age at puberty (8.7%), and piglet survival at birth (3.1%). The economic weights for number of piglets born alive and preweaning piglet survival were found to be highly dependent on the definition of scale of enterprise, with each economic value increasing by approximately 100% when it was assumed that the value of extra output per sow could be captured, rather than assuming a consequent reduction in the number of sows to maintain a constant level of output from a farm enterprise. In the context of a full maternal line index that must account also for the expression of direct genetic traits by the growing piglet progeny of sows, the maternal traits contributed approximately half of the variation in the overall breeding objective. Deployment of more comprehensive maternal line indexes incorporating the new maternal traits described would lead to more balanced selection outcomes and improved survival of pigs. Future work could facilitate evaluation of the economic impacts of desired-gains indexes, which could further improve animal welfare through improved sow and piglet survival. The results justify further development of selection criteria and breeding value prediction systems for a wider range of maternal traits relevant to pig production systems.

English

The study was conducted to estimate relative economic values (REVs) of survival, body weight, growth rate, reproduction, docility and food intake. Data were obtained from records of grasscutters (Thryonomys swinderianus) kept at the grasscutter section of the Department of Animal Science Education, University of Education, Winneba, Ghana. Average values of production inputs and outputs parameters were computed from records of 502 kids born between 2006 and 2010. Relative economic values of traits were computed by using computer models in Microsoft Excel spreadsheet of Windows 2007. When feed intake was included in the breeding objective and economic evaluation was based on genetic standard deviation, mature body weight emerged as the most important trait. Ranking order of traits was body weight &gt; survival &gt; reproduction &gt; growth rate &gt; feed intake &gt; docility. The ranking order was maintained when feed cost was set to zero. The use of coefficient of variation to estimate REVs changed the ranking order of traits: Growth rate &gt; reproduction &gt; docility &gt; survival &gt; body weight &gt; feed intake. It was concluded that post-weaning growth rate, litter size at weaning and docility should be selected to be included in the breeding objective of grasscutter breeding programmes in Ghana. &nbsp; Key words: Breeding objective, docility, food intake, growth traits, reproduction, survival.

Genetic effects on first antler growth in relation to live-weight of red deer farmed in New Zealand

Deer farmed in New Zealand for venison production are a composite of Cervus elaphus subspecies. Venison production systems target supply of yearling males for slaughter at live-weights of ≥95kg between 8 and 12 months of age when first antler development is occurring. If the antlers exceed 110mm they must be removed before the animal can be transported for slaughter which adds handling and costs which some producers consider unnecessary. We hypothesised that there are associations between live-weight and first antler development that are heritable and it would be possible to select sires on the basis of delayed antler development relative to live-weight of their progeny. Antler and live-weight measurements were recorded on 1033 male progeny from three elite recorded red deer breeding herds, DNA pedigree tested as sired by 106 different stags. Spline models were fitted to the antler length and live-weight data over time. Day-of-the-year was read off these splines to define traits of live-weight when antler length reached 50mm (WA50) or 80mm (WA80), and antler length when live-weight reached 95kg (AW95). The predicted traits were analysed using a single-trait animal model incorporating the extended pedigree of the animals involved to calculate three estimated breeding values (EBVs) WA50, WA80 and AW95. The three antler traits had high heritability estimates of 0.67–0.81 with standard errors of 0.10, and were moderately-highly correlated with weaning and yearling live-weight traits. The phenotypic standard deviation of WA80 of 8.35kg or 8.6% of the mean predicted live-weight and a genetic standard deviation or 6.86kg indicated good variation within the population, providing scope for genetically improving the current New Zealand breeding herd for delayed antler growth relative to live-weight. Such selection could reduce the number of rising yearling males requiring velvet antler removal prior to slaughter.