Genetic analyses of elbow and hip dysplasia in the German shepherd dog

Results from radiographic screening for canine hip dysplasia (CHD) and elbow dysplasia (CED) of 48 367 German shepherd dogs born in 2001–07 were used for the population genetic analyses. Available information included CHD scores for 47 730 dogs, CED scores for 28 011 dogs and detailed veterinary diagnoses of primary ED lesions for a subsample of 18 899 dogs. Quasi‐continuous traits were CHD, CED and cases of CED without radiographically visible primary lesion (CED‐ARTH). Binary coding was used for fragmented medial coronoid process of the ulna (FCP), borderline findings and mild to severe signs of dysplasia in hip and elbow joints. Genetic parameters were estimated in univariate threshold and multivariate linear and mixed linear‐threshold models using Gibbs sampling. Correlations between univariately predicted breeding values (BV) indicated genetic differences between borderline and affected disease status for both CHD (r_BV = 0.5) and CED (r_BV = 0.3). Multivariate genetic analyses with separate consideration of borderline findings revealed moderate heritabilities of 0.2–0.3 for the quasi‐continuous traits with positive additive genetic correlation of 0.3 between CHD and both CED and CED‐ARTH. For FCP, heritability of 0.6 and additive genetic correlations of +0.1 to CHD and ?0.1 to CED‐ARTH were estimated. Results supported the relevant genetic determination of CHD and CED, argued for both diseases against interpretation of borderline findings as healthy and implied genetic heterogeneity of CED. Accordingly, future breeding strategies to reduce the prevalences of CHD and CED in the German shepherd dog should be most efficient when based on BV from multivariate genetic evaluation for CHD, CED‐ARTH and FCP with use of the whole scale of categories for classification of CHD and CED.     

Genetic variation of in vivo muscle glycerol,glycogen, and pigment in Danish purebred pigs

Heritability values of glycerol, glycogen and pigment concentrations measured on muscle biopsy samples from longissimus dorsi obtained from 85?kg boars of Danish purebred pigs (Landrace, Yorkshire, and Duroc) and their genetic correlations to performance and meat quality traits were calculated. The heritability values of glycogen, pigment, and glycerol were 0.38±0.02, 0.17±0.02, and 0.065±0.016, respectively. Glycogen was negatively related to the feed conversion ratio (FCR) (r _g =?0.25±0.06) and ultimate meat pH (r _g =?0.41±0.04), and positively to the carcass meat percentage (r _g =0.35±0.04), L* (lightness of meat, r _g =0.32±0.04) and a* (redness of meat, r _g =0.12±0.03). Pigment was positively related to the FCR (r _g =0.12±0.05), the meat percentage (r _g =0.28±0.05), and a* (r _g =0.59±0.04), and negatively to the L* (r _g =?0.46±0.06). The concentrations of pigment and glycogen (r _g =0.27±0.05) were interrelated. Based on the heritability values and the signs of the genetic correlations the present data suggest that it is possible to select for higher ultimate pH and improved colour by selection for either lower muscle glycogen or higher pigment concentration, respectively. However, the positive genetic correlation between these two traits may restrict the efficiency of simultaneous selection for lower glycogen and higher pigment. All genetic parameter estimates presented are calculated across three purebreds. Values for each breed are warranted for use in pig production. However, this requires more animals per breed.     

Estimates of genetic parameters for milkability from automatic milking

Genetic parameters were estimated by restricted maximum likelihood with a multi-trait animal model for three milkability traits with serial data from an automatic milking system from a research farm (401 dairy cows) collected between September 2000 and June 2003 (320834 milkings). Furthermore, daily values for milk yield and milkability were formed from all single milkings resulting in 104 132 records and, subsequently, an estimation of genetic parameters was carried out based on these daily values.The resulting estimated heritability coefficients (based on daily values) are h² = 0.55, h² = 0.55 and h² = 0.39 for average milk flow, maximum milk flow and milking time, respectively. The heritabilities are at a high level and thus breeding for good milkability makes sense. The genetic correlations between the three milkability traits are near unity with r_g = 0.98 between average and maximum milk flow, r_g = − 0.89 between average milk flow and milking time and r_g = − 0.86 between maximum milk flow and milking time. Thus it may be sufficient to record only one of these traits in performance tests. The genetic correlations between milk yield and average milk flow, maximum milk flow and milking time are r_g = 0.51, r_g = 0.44 and r_g = − 0.23, respectively.In future, serial data on milkability, already existing on many farms with automatic milk yield recording, should be used to greater extent for selective breeding with the aim of achieving good milkability.     

Genetic correlations between production with disease resistance and fertility in dairy cattle and consequences for total merit selection

Twelve years of data from progeny‐test results of 1486 Swedish Red and White (SRB) and 756 Swedish Black and White (SLB) AI bulls were analysed to provide estimates of genetic correlations between yield of protein and three health‐ and fertility traits. For both breeds, the correlations were unfavourable (r_G= —0.13 to —0.37). The effects of negative genetic correlations (compared to a situation with genetic correlations with zero values) on the b‐values in the total merit index of bulls were rather small but the effects on the estimated genetic gain were large. The effect of not including health and fertility traits in the index, although included in the breeding goal, resulted in a 9–10% reduced accuracy of estimated breeding values for total merit and thus a corresponding loss in total gain.     

Multivariate genetic analysis to account for preselection and disqualified races in the genetic evaluation of racing performances in German trotters

Abstract

The genetic associations between racing performance and preselection of horses considered as the binary trait racing status (trotters without or with at least one racing performance in life were classified as 0 and 1, respectively) as well as disqualified races (disqualified and non-disqualified trotters were classified as 1 and 0, respectively) were analysed in German trotters. Variance components for racing performance traits square root of rank at finish, racing time per km, and log of earnings with racing status were estimated based on an animal model using REML. Heritabilities of racing status, racing time and rank at finish were 0.30, 0.21, and 0.06, respectively. The genetic correlations between racing status and racing time or rank at finish were ?0.74 and ?0.32, indicating that horses started at least once showed a higher genetic potential in racing time or finishing ability than never started horses. This showed the high preselection of German trotters especially based on racing time. To account for this preselection, it was recommended for additional use of racing status in the German evaluation system. Breeding values of the three racing performance traits were estimated by two distinct models, in- or excluding racing status and compared by using three criteria. Racing time per km showed the highest correlation (r=0.98) between breeding values evaluated by these two distinct models. Therefore, incorrect selection rate of horses using breeding values from the model without racing status, was lowest for racing time per km (9.7%). Selection response increased about 1% for this trait after including racing status in the model. For the estimation of rank at finish, inclusion of racing status in the multiple trait model was much more important as indicated by a low correlation between breeding values (r=0.29) and high percentage of incorrectly selected stallions (97.5%). The trait disqualified races was first analysed using an univariate threshold model. Heritability of this trait was low (h ²=0.12) and repeatability (r=0.43) showed a moderate magnitude. Using a linear multiple trait animal model, disqualified races showed a low heritability (h ²=0.05) and a moderate favourable genetic correlation (r _g=0.43) with racing time per km. Consequently, selection on racing time per km is expected to improve indirectly the reliability of racing performance. Combined selection of reduction in disqualified races and racing time may even further improve the reliability of racing trotters.     

Hip dysplasia in Estrela mountain dogs: prevalence and genetic trends 1991-2005

Three hundred and thirteen Estrela mountain dogs were examined for hip dysplasia (HD) using the standard ventrodorsal hip extended view, and graded into five categories (A, B, C, D and E) using the Fédération Cynologique Internationale’s (FCI) scoring system. The Ortolani method was performed to evaluate hip joint laxity. Pedigree information was obtained from the Portuguese Kennel Club and the genetic trend was evaluated by calculating the mean breeding values (BVs) for the last 15 years, using the threshold model.HD was found in 66% of the dogs. There was low-moderate correlation between the results of the Ortolani test and FCI hip scores (r_s = 0.386; P < 0.001). Grades of hip dysplasia were equal in both males and females (P = 0.14) and in the animals’ right and left sides (P = 0.51). The mean BVs for HD were stable in dogs born between 1991 and 2003, and showed an improvement in 2004 and 2005. The data confirm the high prevalence and severity of HD in predisposed breeds that do not have breeding programmes in place. It also confirms an initial favourable change in BVs that is a likely consequence of the voluntary radiographic hip-screening programme.     

Canine hip and elbow dysplasia in UK Labrador retrievers

This paper examines the outcomes from recent genetic analyses of hip and elbow scores from British Veterinary Association (BVA)/UK Kennel Club (KC) screening programmes targeted at reducing the prevalence of hip dysplasia (HD) and elbow dysplasia in UK Labrador retrievers. The analyses made use of 25,243 hip scores and 3613 elbow scores. Heritabilities (± standard error) for hip score, analysed on a log scale, and for elbow score were 0.35±0.02 and 0.19±0.04, respectively, with a genetic correlation of 0.41±0.09. For both hip and elbow scores, there was a near perfect genetic correlation between the left and right joint; analysis of hip score showed a predictive benefit of using the total of left and right scores rather than worst score and the benefit of using all component scores rather than their aggregate score. Downward genetic trends were observed in both hip and elbow scores, although the latter was consistent with it being correlated to response to genetic change in hip score. Estimated breeding values (EBVs) offered substantial benefits in accuracy and hence genetic progress when compared to the use of phenotypes for both hip and elbow scores. There are major opportunities for improving selection against elbow dysplasia through the use of bivariate evaluations, although progress against dysplasia would be improved by more widespread elbow scoring. The studies highlighted a number of ways in which data recording for addressing complex traits may be improved in the future. Ongoing advances in genomic technology may be utilised for increasing the rate of genetic progress in selection against HD and for complex diseases in general, through the use of genomic evaluations.     

Prevalence and co-occurrence of hip dysplasia and elbow dysplasia in Dutch pure-bred dogs

Hip as well as elbow dysplasia (HD, ED) are developmental disorders leading to malformation of their respective joints. For a long time both disorders have been scored and targeted for improvement using selective breeding in several Dutch dog populations. In this paper all scores for both HD and ED, given to pure bred dogs in the Netherlands from 2002 to 2010, were analyzed. Heritabilities and correlations between HD and ED were calculated for the 4 most frequently scored breeds. Heritabilities ranged from 0.0 to 0.37 for HD related traits (FCI-score, osteoarthritis, congruity, shape and laxity (Norberg angle); FCI: Fédération Cynologique Internationale) and from 0.0 to 0.39 for ED related traits (IEWG score, osteoarthritis, sclerosis and indentation; IEWG: International Elbow Working Group). HD related traits showed high genetic and residual correlations among each other but were only to a minor extent correlated with ED related traits, which also showed high correlations among each other. Genetic correlations were higher than residual correlations. Phenotypic and genetic trends since 2001 for the four most scored breeds were slightly positive but decreasing over time, indicating that selection over the past decade has not been effective.     

ImmuneDEX: a strategy for the genetic improvement of immune competence in Australian Angus cattle

In animal breeding and genetics, the ability to cope with disease, here defined as immune competence (IC), with minimal detriment to growth and fertility is a desired objective which addresses both animal production and welfare considerations. However, defining and objectively measuring IC phenotypes using testing methods which are practical to apply on-farm has been challenging. Based on previously described protocols, we measured both cell-mediated immune response (Cell-IR) and antibody-mediated immune response (Ab-IR) and combined these measures to determine an animal’s IC. Using a population of 2,853 Australian Angus steers and heifers, we compared 2 alternative methods to combine both metrics into a single phenotype to be used as a tool for the genetic improvement of IC. The first method, named Z_MEAN, is obtained by taking the average of the individual metrics after subjecting each to a Z-score standardization. The second, ImmuneDEX (IDEX), is a weighted average that considers the correlation between Cell-IR and Ab-IR, as well as the difference in ranking of individuals by each metric, and uses these as weights in the averaging. Both simulation and real data were used to understand the behavior of Z_MEAN and IDEX. To further ascertain the relationship between IDEX and other traits of economic importance, we evaluated a range of traits related to growth, feedlot performance, and carcass characteristics. We report estimates of heritability of 0.31 ± 0.06 for Cell-IR, 0.42 ± 0.06 for Ab-IR, 0.42 ± 0.06 for Z_MEAN and 0.370 ± 0.06 for IDEX, as well as a unity genetic correlation (r_g) between Z_MEAN and IDEX. While a moderately positive r_g was estimated between Cell-IR and Ab-IR (r_g = 0.33 ± 0.12), strongly positive estimates were obtained between IDEX and Cell-IR (r_g = 0.80 ± 0.05) and between IDEX and Ab-IR (r_g = 0.85 ± 0.04). We obtained a moderately negative r_g between IC traits and growth including an r_g = −0.38 ± 0.14 between IDEX and weaning weight, and negligible with carcass fat measurements, including an r_g = −0.03 ± 0.12 between IDEX and marbling. Given that breeding with a sole focus on production might inadvertently increase susceptibility to disease and associated antibiotic use, our analyses suggest that ImmuneDEX will provide a basis to breed animals that are both highly productive and with an enhanced ability to resist disease.     

Genotype environment interaction in pig breeding programmes: Methods of estimation and relevance of the estimates

In pig breeding programmes breeding values for growth and carcass traits are generally estimated in test environments, e.g. central test or on-farm test. The breeding goal, however, should be defined at the level of commercial growing. Genotype × environment (G × E) interaction (test and commercial environment) will lower the efficiency of a breeding scheme based on testing in test environments. The effect of G × E interaction on the response to selection can be examined by interpreting the interaction as a genetic correlation between a trait measured in one environment and a similar trait in another environment. Here, two types of genetic correlation need to be considered: r_G for the correlation between test and commercial environment, and r_g, for the correlation among various commercial environments. In this paper procedures to estimate these genetic correlations are reviewed. Furthermore, some testing strategies are compared in model calculations. The objective was to determine at which (low) levels of r_G testing of individuals, sibs or progeny in commercial environments is more efficient than testing in a test environment. It is concluded that generally central testing is to be preferred and that additional testing of sibs in commercial environments may be of value.     

Improving production efficiency in the presence of genotype by environment interactions in pig genomic selection breeding programmes

We simulated a genomic selection pig breeding schemes containing nucleus and production herds to improve feed efficiency of production pigs that were cross‐breed. Elite nucleus herds had access to high‐quality feed, and production herds were fed low‐quality feed. Feed efficiency in the nucleus herds had a heritability of 0.3 and 0.25 in the production herds. It was assumed the genetic relationships between feed efficiency in the nucleus and production were low (r_g = 0.2), medium (r_g = 0.5) and high (r_g = 0.8). In our alternative breeding schemes, different proportion of production animals were recorded for feed efficiency and genotyped with high‐density panel of genetic markers. Genomic breeding value of the selection candidates for feed efficiency was estimated based on three different approaches. In one approach, genomic breeding value was estimated including nucleus animals in the reference population. In the second approach, the reference population was containing a mixture of nucleus and production animals. In the third approach, the reference population was only consisting of production herds. Using a mixture reference population, we generated 40–115% more genetic gain in the production environment as compared to only using nucleus reference population that were fed high‐quality feed sources when the production animals were offspring of the nucleus animals. When the production animals were grand offspring of the nucleus animals, 43–104% more genetic gain was generated. Similarly, a higher genetic gain generated in the production environment when mixed reference population was used as compared to only using production animals. This was up to 19 and 14% when the production animals were offspring and grand offspring of nucleus animals, respectively. Therefore, in genomic selection pig breeding programmes, feed efficiency traits could be improved by properly designing the reference population.     

GxE interactions for growth and carcass leanness: Re-ranking of boars in organic and conventional pig production

The objective of this study was to evaluate genotype by environment interactions for growth rate and carcass leanness in organic and conventional pig production environments. Organic breeding values for fattening traits were estimated for 37 Hampshire AI-boars based on slaughter records registered for 1805 crossbred offspring raised in an organic environment. The offspring were born and raised in herds certified for organic production. The statistical model included the fixed effects of sex, litter size at 2 weeks and herd. It also included the random effects of herd-year-season, birth litter and animal. Conventional breeding values for the same boars were captured from the breeding organization’s genetic evaluation. In the organic environment h² was estimated to 0.30 and 0.37 for growth rate and carcass leanness, respectively (r_g = − 0.11). Spearman rank correlations between organic and conventional breeding values, based on 29 boars with ≥ 20 progenies, were 0.48 for growth rate and 0.42 for carcass leanness. Both correlations were significantly different from 0 and 1. In conclusion, the results of the present study indicate weak genotype by environment interactions for both growth rate and carcass leanness in organic and conventional pig production environments, and there is some re-ranking of boars’ breeding values between environments.     

On farm observations to increase genetic gain in breeding schemes for village poultry production – A simulation study

To improve genetic gain of breeding programs for village poultry production, breeding schemes with observations obtained in village production systems using individual (VIO) and group recording (VGO) were examined under different levels of genotype-by-environment-interactions (GxE). GxE was modeled by varying the correlation between traits measured in the breeding station and village environments for bodyweight (r_{g_BW}) and egg production (r_{g_EP}). Relative and absolute genetic gains obtained from VIO and VGO were used for comparison between the schemes. Results showed that village observations significantly improved genetic gains compared to the scheme without birds tested in the village. The improvement was only slightly larger with individual observations than with group observations. Higher r_{g_BW} and r_{g_EP} led to lower relative genetic gain, but a higher absolute gain of VIO and VGO. It is recommended to apply a breeding scheme using group recording of village performance when strong GxE in breeding for village poultry is expected.     

Genotype by climate interaction in the genetic evaluation for growing traits of Braunvieh cattle in Mexico

The objective of this study was to determine the magnitude of genotype by climate interaction (GCI) in the national genetic evaluation for weaning (WW) and yearling (YW) weights of Mexican Braunvieh cattle. The numbers of performance records and animals in the pedigree were 12,364 and 25,173 for WW, and 7,991 and 18,072 for YW, respectively. Performance records were clustered based on climatological variables into: dry tropic (DT), wet tropic (WT), and temperate (TE) climates. Animal models were used to estimate genetic parameters and predict breeding values in each of the climates. Bivariate analyses were carried out for pairwise combinations of climates on each trait, considering the same trait in different climates as a different trait. Criteria to evaluate GCI were genetic correlations (r _g), correlations between predicted breeding values (r _BV), and frequencies of coincidence (FC) in the ranking of the top 25 sires. Results of comparisons between pairs of climates were variable, depending on specific cases. For WW, the r _g, r _BV, and FC ranged from ?0.36 to 0.84, ?0.60 to 0.97, and 0.16 to 0.92, respectively; whereas for YW, they fluctuated between 0.23 and 0.99, 0.33 and 1.00, and 0.60 and 1.00, respectively. For both traits, the results suggest absence of GCI between DT and TE; however, GCI was detected in the other pairs of climates, where WT was involved. To maximize genetic progress, the joint genetic evaluation should be performed only for animals with performance data in DT and TE, whereas a separated evaluation is suggested for animals with performance records generated under WT conditions.     

Estimates of phenotypic and genetic parameters for birth weight of Brown Swiss calves in Turkey using an animal model

A study was conducted to assess the influence of genetic and environmental factors on Brown Swiss calf birth weight, and to estimate variance components, genetic parameters, and breeding values. Data were collected on 1,761 Brown Swiss calves born from 1990 to 2005 in the Konuklar State Farm in Turkey. Mean birth weight for all calves was 39.3 ± 0.09 kg. Least squares mean birth weights for male and female Brown Swiss calves were 40.3 ± 0.02 and 39.0 ± 0.02 kg, respectively. Variance components, genetic parameters, and breeding values for birth weight in Brown Swiss calves were estimated by restricted error maximum likelihood (REML)–best linear unbiased prediction(BLUP) procedures using an MTDFREML (multiple trait derivative free restricted maximum likelihood) program employing an animal model. Direct heritability (h _d²), maternal heritability (h _m²), total heritability (h _T²), r _am and c _am estimates were 0.12, 0.09, 0.23, −0.58, and −0.06, respectively. The estimated maternal permanent environmental variance expressed as a proportion of the phenotypic variance (c ²) was 0.05. Breeding values were estimated for the trait and used to evaluate genetic trends across the time period investigated. The genetic trend linear regression was not different from zero. No genetic trend for birth weight was expected, since there had been no direct selection pressure on the trait. Absence of a trend confirms that there was no change due to selection pressure on correlated traits. Genetic and environmental parameter estimates were similar to literature values indicating that effective selection methods used in more developed improvement programs would be effective in Turkey as well.     

Implications of genetic selection on yolk proportion on the dry matter content of eggs in a White Leghorn population

1. The responses to genetic selection on yolk proportion as a technique for increasing egg dry matter content, an important criterion for the egg-product industry, was investigated in a pedigree flock of White Leghorn hens.

2. Parents were preselected on high and low yolk proportion from a base population. The absolute estimated breeding value for yolk proportion of both groups differed by 3%. The realised selection difference in dry matter content of eggs between groups was more than 1% in the analysed offspring population.

3. Heritability estimates were moderate and dry matter had a lower heritability (h² = 0.39) than yolk proportion (h² = 0.44).

4. The genetic correlation between yolk proportion and dry matter content was highly positive (r_g = 0.91). Genetic correlations with egg weight were negative and would have to be compensated for in a breeding programme (r_g = ?0.76 with yolk proportion and r_g = ?0.64 with dry matter content). The genetic correlation between the laying performance and yolk proportion was r_g = 0.28 and close to zero (r_g = ?0.05) for dry matter content.

5. Easy recording and lower undesirable correlations make yolk proportion more suitable for commercial selection compared with egg dry matter content in layer breeding.     

Familial clustering and risk analysis for fragmented coronoid process and elbow joint incongruity in Bernese Mountain Dogs in The Netherlands.

OBJECTIVE: To analyze familial clustering and genetic risk for various forms of elbow dysplasia (ED) in Bernese Mountain Dogs (BMD) in The Netherlands and define possible means to select against ED. ANIMALS: 98 BMD born in 1992 and 64 BMD born in 1995. PROCEDURE: Dogs were examined radiographically when 12 to 18 months old. The population was resolved into familial clusters, and distribution of ED for the clusters was analyzed. Common ancestors associated with each form of ED were identified, and risk for having ED in the 64 offspring born in 1995 was calculated by relatedness to common ancestors. Risk was compared with radiographic outcome. RESULTS: The 2 forms of ED identified were fragmented coronoid process (FCP) and elbow joint incongruity (INC). Incidence of ED decreased from 63/98 (64%) in 1992 to 29/64 (45%) in 1995. None of the familial clusters was free of FCP or INC. Common ancestors associated with FCP differed from those associated with INC. There was more potential variation in risk for FCP and INC in the 64 offspring than was achieved by breeders, indicating a decrease in population heterogeneity. CONCLUSIONS AND CLINICAL RELEVANCE: FCP and INC had differing familial sources; thus, they most likely are different genetic traits. Although incidence of ED decreased from 1992 through 1995, we did not detect variation among pedigrees in genetic risk for ED remaining in the offspring born in 1995; thus, selection among families cannot further improve ED health status of BMD in The Netherlands. Phenotypic selection within families remains the only alternative.     

Genetic parameters for the prediction of abdominal fat traits using blood biochemical indicators in broilers

1. Excessive deposition of body fat, especially abdominal fat, is detrimental in chickens and the prevention of excessive fat accumulation is an important problem. The aim of this study was to identify blood biochemical indicators that could be used as criteria to select lean Yellow-feathered chicken lines.

2. Levels of blood biochemical indicators in the fed and fasted states and the abdominal fat traits were measured in 332 Guangxi Yellow chickens. In the fed state, the genetic correlations (r_g) of triglycerides and very low density lipoprotein levels were positive for the abdominal fat traits (0.47 ≤ r_g ≤ 0.67), whereas total cholesterol, high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) showed higher negative correlations with abdominal fat traits (–0.59 ≤ r_g ≤ ?0.33). Heritabilities of these blood biochemical parameters were high, varying from 0.26 to 0.60.

3. In the fasted state, HDL-C:LDL-C level was positively correlated with abdominal fat traits (0.35 ≤ r_g ≤ 0.38), but triglycerides, total cholesterol, HDL-C, LDL-C, total protein, albumin, aspartate transaminase, uric acid and creatinine levels were negatively correlated with abdominal fat traits (–0.79 ≤ r_g ≤ ?0.35). The heritabilities of these 10 blood biochemical parameters were high (0.22 ≤ h² ≤ 0.59).

4. In the fed state, optimal multiple regression models were constructed to predict abdominal fat traits by using triglycerides and LDL-C. In the fasted state, triglycerides, total cholesterol, HDL-C, LDL-C, total protein, albumin and uric acid could be used to predict abdominal fat content.

5. It was concluded that these models in both nutritional states could be used to predict abdominal fat content in Guangxi Yellow broiler chickens.     

Genetic analysis of production traits in turbot (Scophthalmus maximus) using random regression models based on molecular relatedness

Reliable estimates of genetic parameters for growth traits as a trajectory of age are needed to optimize existing turbot breeding programmes. To evaluate the potential of early selection strategies, the use of biometric body measurements, length (L), width (W) and area (A), at early ages as alternative indicators for the selection trait at harvest was explored. Random regression model (RRM) based on molecular relatedness (MR) was used to analyse the trajectory of genetic parameters for growth traits in turbot from 162 to 756 days posthatch (dph). Heritability estimates for body weight (BW) ranged from 0.34 to 0.54. Heritability estimates for W, A and L were also moderate to high ranging from 0.18 to 0.43. Estimates for L and W declined with age, while those for A increased towards harvest age. Genetic (r_G) and phenotypic (r_P) correlations between BW and the three morphometric traits L, A and W were estimated using simple bivariate animal models at young (AC1), medium (AC2) and old (AC3) age classes. Correlations between BW and morphometric body traits were high, ranging from 0.7 to 0.9 in all three age groups. Genetic correlations between traits were highest (>0.9) in AC3. To explore the potential for early selection, genetic correlations were derived from the RRM between all days of measurement for all traits separately. From dph 300 onwards, intratrait estimates of r_G were moderate to high (above 0.7 for dph 410 and higher ages for traits BW, L and A). Results showed that genetic selection for BW, L and A is promising and that A and L could be successfully used as alternative indicator traits if measurements of BW are not available. Large BW and A at harvest could be achieved as a correlated response to early selection for these traits at around 500 dph.     

Evaluation criterion for response to selection with constraint

The aims of the present study are to represent the concept of restricted breeding values algebraically and to propose a criterion for evaluating the genetic responses achieved by using a restricted selection procedure. An additive genetic mixed model characterized by multiple traits with constraints was assumed. If the random errors approach zero and the fixed effects can be completely estimated correctly in the model, the restricted best linear unbiased predictor of breeding values ( u _R) is equal to , where G ₀, C ₀, and u are the additive genetic variance‐covariance matrix for the q traits, the matrix for restriction, and the vector of breeding values, respectively. Therefore, if we want to evaluate the response to restricted selection, such as by a stochastic computer simulation study with known breeding values, we can use u _R as only one criterion.