Genetic analysis of protein yield,udder health,and female fertility in first-parity Danish Holstein cows

Abstract

Genetic parameters for protein yield, clinical mastitis, SCS, number of inseminations (NI), and days from first to last insemination (FLI) were estimated for first-parity Danish Holstein cows. The objective was to estimate genetic correlations between the five traits mentioned above and to study whether NI and FLI are measures of the same trait. Records containing information on approximately 200 000 cows were analysed using tri-variate animal models. The genetic correlations between the udder health traits and the fertility traits were favourable and in the range from 0.17 to 0.42, whereas the genetic correlations between protein yield and the fertility traits were unfavourable and ranged from 0.43 to 0.52. These results highlight the importance of continuing to emphasize functional traits in future breeding programmes. The genetic correlation between the fertility traits was 0.82. Based on this result, it cannot be concluded that NI and FLI are measures of the same trait.     

Genetic parameters for mastitis incidence and its indicators based on somatic cell score for Holsteins in Hokkaido,Japan

The objectives of this study were to estimate the heritability of mastitis incidence and genetic correlations between the mastitis and the somatic cell score (SCS) statistics, and to compare the practicability between different models. We used test‐day records with the mastitis incidence and SCS collected from Holstein cows calving from 1988 to 2015 in Hokkaido, Japan. As indicators of mastitis, the average SCS (avSCS), the standard deviation of SCS (sdSCS), and the maximum SCS (maxSCS) were calculated using test‐day records up to the first 305 days in milk within a lactation. We compared a four‐trait repeatability animal model (MTRP) with a four‐trait multiple‐lactation animal model (MTML). The heritability for mastitis was equal to or lower than 0.05 in all the models. Genetic correlations between lactations with MTML within the same trait were positive and close to 1. With MTRP, the estimated genetic correlations of the mastitis incidence with avSCS, sdSCS, and maxSCS were 0.66, 0.79, and 0.82, respectively. A joint evaluation with SCS statistics is expected to give an extra reliability for mastitis because of high and positive genetic correlations among the traits.     

Genetic parameters and single versus multi-trait evaluation of udder health traits

Abstract

Genetic parameters were estimated for lactation average somatic cell score (SCS) and clinical mastitis (CM) for the first three lactations of multiparous Finnish Ayrshire cows. A multi-trait linear sire model was used for estimation of covariance components, and the efficiencies of single- versus multi-trait multi-lactation (MT) sire evaluations were compared. Heritability of SCS and CM in the first three lactations ranged from 0.11 to 0.13 and 0.02 to 0.03, respectively. Within lactation, genetic correlations between SCS and CM ranged from 0.68 to 0.72. Within both traits, across-lactation genetic correlations were lowest between 1 and 3, and highest between 2 and 3, with estimates ranging from 0.75 to 0.86 and from 0.81 to 0.98 for CM and SCS, respectively. Residual and phenotypic correlations were low and ranged from 0.09 to 0.13 and from 0.10 to 0.13, respectively. The absolute difference between genetic and residual correlations was from 0.5 to 0.6. Within-lactation genetic correlations between traits that are much less than unity suggest a multi-trait model for genetic evaluation of mastitis resistance. Comparison of model prediction performance between single-trait (ST) and MT models using a data splitting method showed that the MT model was more stable in predicting breeding values in future records of animals. Especially, for young sires and CM, the SD of EBVs from the MT model was 14 to 23% higher than the ST model, indicating more effective use of information in terms of revealing more genetic variation.     

Genetic association between milk yield,stayability, and mastitis in Holstein cows under tropical conditions

The objective of this study was to estimate genetic parameters for milk yield, stayability, and the occurrence of clinical mastitis in Holstein cows, as well as studying the genetic relationship between them, in order to provide subsidies for the genetic evaluation of these traits. Records from 5,090 Holstein cows with calving varying from 1991 to 2010, were used in the analysis. Two standard multivariate analyses were carried out, one containing the trait of accumulated 305-day milk yields in the first lactation (MY1), stayability (STAY) until the third lactation, and clinical mastitis (CM), as well as the other traits, considering accumulated 305-day milk yields (Y305), STAY, and CM, including the first three lactations as repeated measures for Y305 and CM. The covariance components were obtained by a Bayesian approach. The heritability estimates obtained by multivariate analysis with MY1 were 0.19, 0.28, and 0.13 for MY1, STAY, and CM, respectively, whereas using the multivariate analysis with the Y305, the estimates were 0.19, 0.31, and 0.14, respectively. The genetic correlations between MY1 and STAY, MY1 and CM, and STAY and CM, respectively, were 0.38, 0.12, and ?0.49. The genetic correlations between Y305 and STAY, Y305 and CM, and STAY and CM, respectively, were 0.66, ?0.25, and ?0.52.     

Genetic associations between somatic cell score and pathogen‐specific subclinical mastitis in Norwegian Red cows

The aim of this study was to estimate heritabilities of and genetic correlations between pathogen‐specific subclinical mastitis (SCM) traits and lactation mean somatic cell score (LSCS) in Norwegian Red cattle. Based on data from 130 733 first‐lactation cows four binary pathogen‐specific SCM traits, Staphylococcus aureus, Streptococcus dysgalactiae, Streptococcus uberis and coagulase‐negative staphylococci SCM, were analysed together with unspecific SCM and LSCS using a multivariate sire model with threshold models for binary traits and a linear model for LSCS. Posterior means (SD) of heritabilities were 0.17 (0.01) for LSCS, 0.11 (0.01) for liability to unspecific SCM and ranged from 0.04 (Staph. aureus) to 0.14 (Strep. dysgalactiae) for liability to pathogen‐specific SCM. Genetic correlations were positive and moderate to high, ranging from 0.37 to 0.98. All genetic correlations except the one between LSCS and unspecific SCM were lower than 1, indicating that SCM caused by different pathogens can be considered as partly different traits.     

Influence of population structure on estimates of direct and maternal parameters.

The estimation of (co)variance components for multiple traits with maternal genetic effects was found to be influenced by population structure. Two traits in a closed breeding herd with random mating were simulated over nine generations. Population structures were simulated on the basis of different proportions of dams not having performance records (0, 0.1, 0.5, 0.8 and 0.9): three genetic correlations (-0.5, 0.0 and +0.5) between direct and maternal effects and three genetic correlations (0, 0.3 and 0.8) between two traits. Three ratios of direct to maternal genetic variances, (1:3, 1:1, 3:1), were also considered. Variance components were estimated by restricted maximum likelihood. The proportion of dams without records had an effect on the SE of direct-maternal covariance estimates when the proportion was 0.8 or 0.9 and the true correlation between direct and maternal effects was negative. The ratio of direct to maternal genetic variances influenced the SE of the (co)variance estimates more than the proportion of dams with missing records. The correlation between two traits did not have an effect on the SE of the estimates. The proportion of dams without records and the correlation between direct and maternal effects had the strongest effects on bias of estimates. The largest biases were obtained when the proportion of dams without records was high, the correlation between direct and maternal effects was positive, and the direct variance was greater than the maternal variance, as would be the situation for most growth traits in livestock. Total bias in all parameter estimates for two traits was large in the same situations. Poor population structure can affect both bias and SE of estimates of the direct-maternal genetic correlation, and can explain some of the large negative estimates often obtained.     

Genetic associations of in-line recorded milkability traits and udder conformation with udder health

Milkability and udder conformation traits of Swedish Holstein (SH) and Swedish Red (SR) cows from 93 herds with automatic milking systems or conventional milking parlors were used to study genetic relationships to lactation average somatic cell score (LSCS) and incidence of clinical mastitis (CM). Estimated genetic correlations between measures of milking speed (average flow rate, milking time and box time) and LSCS ranged between 0.29 and 0.57 and showed that high milking speed is associated with increasing LSCS. Regressions indicated a curvilinear relationship. Genetic correlations between milking speed and CM showed similar values as for LSCS in SH cows, but were inconsistent in SR cows. Shallow udder and strong fore udder attachment were consistently correlated with good udder health. The unfavorable relationships between milking speed and udder health traits should be considered together with a few udder conformation traits when selecting for better milkability.     

Genetic relations of yolk proportion and chick weight with production traits in a White Leghorn line

1. The main purpose of this study was to estimate genetic correlations between yolk proportion, chick weight and production traits using an animal model. 2. Direct-direct genetic correlations were estimated between yolk proportion and age at first egg (-0.34), body weight at 20 (0.10), 40 (0.58) and 60 (0.52) weeks of age, egg number (0.56), egg mass (0.59), feed intake (0.64) and feed conversion (-0.25). 3. Maternal-direct genetic correlations were estimated between chick weight and age at first egg (0.40), body weight at 20 (0.57), 40 (0.66) and 60 (0.56) weeks of age, egg number (-0.50), egg mass (0.21), feed intake (0.45) and feed conversion (0.17), respectively. 4. In conclusion, the results suggest that selection on a higher yolk proportion would not have any unfavourable effects on egg production. Maternal-direct genetic correlations between chick weight and production traits resembled direct-direct genetic correlations between egg weight and production traits found in other studies.     

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.     

Genetic parameters for blood oxygen saturation, body weight and breast conformation in 4 meat-type chicken lines

1. The objective of the study was to explore the genetic architecture of blood oxygen saturation (SaO) (an indicator trait, negatively correlated with ascites susceptibility), body weight (Weight) and fleshing score (Flesh, a measure of breast conformation) for 4 meat-type chicken lines reared in commercial conditions. 2. Genetic components, including heritabilities and genetic correlations, were estimated by Restricted Maximum likelihood for these traits measured at 6 weeks of age. 3. Data were collected over eight generations of selection and pedigrees comprised in excess of 130,000 birds. 4. Univariate analyses were performed to allow model definition and to obtain starting values for trivariate analyses. The basic model included a random animal effect and, in further models explored, a maternal environmental effect or a genetic maternal effect or both were fitted. Models were compared using likelihood ratio tests. 5. Estimated heritabilities for SaO ranged from 0.1 to 0.2, and there was no evidence of genetic maternal effects for SaO. The environmental maternal component was significant for one of the populations only. Estimated heritabilities for both Weight and Flesh were between 0.2 and 0.4, and there was evidence of environmental and genetic maternal effects for these traits in all populations. 6. Genetic correlations between SaO and Weight and between SaO and Flesh were low and negative. This suggests that, in principle, genetic selection to simultaneously increase SaO, and therefore decrease ascites susceptibility, and WEight and Flesh could be performed using traditional (marker-free) selection methods. We discuss how a putative interaction between ascites and production traits could jeopardise the success of such methods.     

Genetic evaluation of Australian dairy cattle for somatic cell scores using multi-trait random regression test-day model

Summary A multi-trait (MT) random regression (RR) test day (TD) model has been developed for genetic evaluation of somatic cell scores for Australian dairy cattle, where first, second and third lactations were considered as three different but correlated traits. The model includes herd-test-day, year-season, age at calving, heterosis and lactation curves modelled with Legendre polynomials as fixed effects, and random genetic and permanent environmental effects modelled with Legendre polynomials. Residual variance varied across the lactation trajectory. The genetic parameters were estimated using asreml . The heritability estimates ranged from 0.05 to 0.16. The genetic correlations between lactations and between test days within lactations were consistent with most of the published results. Preconditioned conjugate gradient algorithm with iteration on data was implemented for solving the system of equations. For reliability approximation, the method of Tier and Meyer was used. The genetic evaluation system was validated with Interbull validation method III by comparing proofs from a complete evaluation with those from an evaluation based on a data set excluding the most recent 4 years. The genetic trend estimate was in the allowed range and correlations between the two sets of proofs were very high. Additionally, the RR model was compared to the previous test day model. The correlations of proofs between both models were high (0.97) for bulls with high reliabilities. The correlations of bulls decreased with increasing incompleteness of daughter performance information. The correlations between the breeding values from two consecutive runs were high ranging from 0.97 to 0.99. The MT RR TD model was able to make effective use of available information on young bulls and cows, and could offer an opportunity to breeders to utilize estimated breeding values for first and later lactations.     

Estimation of genetic parameters for preweaning growth traits of Brahman cattle in Southeastern Mexico

The genetic parameters for Brahman cattle under the tropical conditions of Mexico are scarce. Therefore, heritabilities, additive direct and maternal correlations, and genetic correlations for birth weight (BW) and 205 days adjusted weaning weight (WW205) were estimated in four Brahman cattle herds in Yucatan, Mexico. Parameters were estimated fitting a bivariate animal model, with 4,531 animals in the relationship matrix, of which 2,905 had BW and 2,264 had WW205. The number of sires and dams identified for both traits were 122 and 962, respectively. Direct heritability estimates for BW and WW205 were 0.41?±?0.09 and 0.43?±?0.09, and maternal heritabilities were 0.15?±?0.07 and 0.38?±?0.08, respectively. Genetic correlations between direct additive and maternal genetic effects for BW and WW205 were ?0.41?±?0.22 and ?0.50?±?0.15, respectively. The direct genetic, maternal, and phenotypic correlations between BW and WW205 were 0.77?±?0.09, 0.61?±?0.18, and 0.35, respectively. The moderate to high genetic parameter estimates suggest that genetic improvement by selection is possible for those traits. The maternal effects and their correlation with direct effects should be taken into account to reduce bias in genetic evaluations.     

Genetic parameters and trends for production traits and their relationship with litter traits in Landrace and Yorkshire pigs

Genetic parameters and trends in the average daily gain (ADG), backfat thickness (BF), loin muscle area (LMA), lean percentage (LP), and age at 90 kg (D90) were estimated for populations of Landrace and Yorkshire pigs. Additionally, the correlations between these production traits and litter traits were estimated. Litter traits included total born (TB) and number born alive (NBA). The data used for this study were obtained from eight farms during 1999 to 2016. Analyses were carried out with a multivariate animal model to estimate genetic parameters for production traits while bivariate analyses were performed to estimate the correlations between production and litter traits. The heritability estimates were 0.52 and 0.43 for ADG; 0.54 and 0.45 for BF; 0.25 and 0.26 for LMA; 0.54 and 0.48 for LP; and 0.56 and 0.46 for D90 in the Landrace and Yorkshire breeds, respectively. The ADG and D90 showed low genetic correlation with BF and LP. The LMA had ?0.40, ?0.32, 0.49, and 0.39 genetic correlations with ADG, BF, LP, and D90, respectively. Genetic correlations between production and litter traits were generally low, except for the correlations between LMA and TB (?0.23) in Landrace and ADG and TB (?0.16), ADG and NBA (?0.18), D90 and TB (0.19), and D90 and NBA (0.20) in Yorkshire. Genetic trends in production traits were all favorable except for LMA.     

Genetic parameters for energy balance, fat /protein ratio, body condition score and disease traits in German Holstein cows

Various health problems in dairy cows have been related to the magnitude and duration of the energy deficit post partum. Energy balance indicator traits like fat/protein ratio in milk and body condition score could be used in selection programmes to help predicting breeding values for health traits, but currently there is a lack of appropriate genetic parameters. Therefore, genetic correlations among energy balance, fat/protein ratio, and body condition score, and mastitis, claw and leg diseases, and metabolic disorders were estimated using linear and threshold models on data from 1693 primiparous cows recorded within the first 180 days in milk. Average daily energy balance, milk fat/protein ratio and body condition score were 8 MJ NEL, 1.13 and 2.94, respectively. Disease frequencies (% cows with at least one case) were 24.6% for mastitis, 9.7% for metabolic disorders and 28.2% for claw and leg diseases. Heritability estimates were 0.06, 0.30 and 0.34 for energy balance, fat/protein ratio and body condition score, respectively. For the disease traits, heritabilities ranged between 0.04 and 0.15. The genetic correlations were, in general, associated with large standard errors, but, although not significant, the results suggest that an improvement of overall health can be expected if energy balance traits are included into future breeding programmes. A low fat/protein ratio might serve as an indicator for metabolic stability and health of claw and legs. Between body condition and mastitis, a significant negative correlation of -0.40 was estimated. The study provides a new insight into the role energy balance traits can play as auxiliary traits for robustness of dairy cows. It was concluded that both, fat/protein ratio and body condition score, are potential variables to describe how well cows can adapt to the challenge of early lactation. However, the genetic parameters should be re-estimated on a more comprehensive data set.     

Heritability, genetic and phenotypic correlations of egg quality traits in Iranian native fowl

1. The objective was to estimate heritability, genetic and phenotypic correlations for egg quality traits of Iranian native fowl at the Yazd Breeding Centre. 2. External and internal egg quality traits were measured on 1200 eggs from 794 hens of the 6th generation. A multivariate animal model with restricted maximum likelihood procedure was applied to estimate heritability, genetic and phenotypic correlations for egg quality traits using ASREML. 3. Heritability estimates for external egg quality traits ranged from 0·18 to 0·57 and for internal egg quality traits from 0·24 to 0·60. 4. For external egg quality traits, genetic correlation between egg weight and eggshell thickness (EST) was positive (0·36) and EST showed high genetic correlations with eggshell weight (0·84) and eggshell strength (0·55). This implies that heavier eggs tend to have thicker and stronger shells. 5. For internal egg quality traits, albumen height showed high positive genetic correlations with albumen weight (0·52), albumen index (0·98), yolk height (0·72) and yolk index (0·57). 6. Our results show that it is feasible to improve egg quality in Iranian fowl through selection for albumen height.     

Direct and maternal (co)variance components, genetic parameters, and annual trends for growth traits of Makooei sheep in Iran

Genetic parameters and genetic trends for birth weight (BW), weaning weight (WW), 6-month weight (6MW), and yearling weight (YW) traits were estimated by using records of 5,634 Makooei lambs, descendants of 289 sires and 1,726 dams, born between 1996 and 2009 at the Makooei sheep breeding station, West Azerbaijan, Iran. The (co)variance components were estimated with different animal models using a restricted maximum likelihood procedure and the most appropriate model for each trait was determined by Akaike’s Information Criterion. Breeding values of animals were predicted with best linear unbiased prediction methodology under multi-trait animal models and genetic trends were estimated by regression mean breeding values on birth year. The most appropriate model for BW was a model including direct and maternal genetic effects, regardless of their covariance. The model for WW and 6MW included direct additive genetic effects. The model for YW included direct genetic effects only. Direct heritabilities based on the best model were estimated 0.15?±?0.04, 0.16?±?0.03, 0.21?±?0.04, and 0.22?±?0.06 for BW, WW, 6MW, and YW, respectively, and maternal heritability obtained 0.08?±?0.02 for BW. Genetic correlations among the traits were positive and varied from 0.28 for BW–YW to 0.66 for BW–WW and phenotypic correlations were generally lower than the genetic correlations. Genetic trends were 8.1?±?2, 67.4?±?5, 38.7?±?4, and 47.6?±?6 g per year for BW, WW, 6MW, and YW, respectively.     

Genetic correlations between lean growth and litter traits in U.S. Yorkshire,Duroc, Hampshire,and Landrace pigs

The objective of this study was to estimate breed-specific genetic correlations between lean growth and litter traits for four U.S. swine breeds. Records for lean growth and litter traits on Yorkshire, Duroc, Hampshire, and Landrace pigs collected between 1990 and April 2000 in herds on the National Swine Registry Swine Testing and Genetic Evaluation System were analyzed. A bivariate animal model and restricted maximum likelihood procedures were used to estimate genetic and environmental correlations between lean growth rate, days to 113.5 kg, backfat, and loin muscle area with litter traits of number born alive, litter weight at 21 d, and number weaned. Most genetic correlation estimates between lean growth and litter traits were small in magnitude and consistent across breeds. Backfat had the largest within-breed genetic correlations with number born alive (0.18 to 0.20) and litter weight at 21 d (-0.27 to -0.30). Estimates of genetic correlations between lean growth traits and number weaned were very small. Estimates of the environmental correlations between lean growth and litter traits also were very small for all traits and for all four breeds. Results indicate that selection for lean growth traits could have a long-term effect on litter traits. Including lean growth traits in a maternal-line evaluation using a multiple-trait model could increase the accuracy of the genetic evaluation for litter traits.     

Multiple-trait restricted maximum likelihood for simulated measures of ovulation rate with underlying multivariate normal distributions.

A data set that was used to estimate covariance components with REML for an animal model with eight measures of ovulation rate treated as separate traits was used as a template to simulate data sets of eight multivariate normal traits that were then truncated to binomial traits. The model for simulation included eight measures on 610 animals with 1,071 animals in the numerator relationship matrix. Heritabilities were equal for the eight measures, and both genetic and phenotypic correlations among the measures were equal. Ten replications for each combination of heritability (.15, .25, and .35) and genetic correlation (.50, .66, and .90) were simulated on the normal scale. For each replicate, estimates of the eight heritabilities and 28 genetic correlations were obtained by multiple-trait REML. The usual transformation of heritability estimated on the binomial scale overestimated heritability on the normal scale. Genetic correlations on the binomial scale seriously underestimated the correlations on the normal scale. Standard errors of the estimates obtained by replication were somewhat larger than the approximate SE from REMLPK (the multi-trait REML program of K. Meyer). A final set of 10 simulated replications with heritability of .25 and genetic correlation of 1.00 resulted in average estimates of .18 for heritability and of .66 for genetic correlation that agree closely with those from the analysis of measures of ovulation at eight estrous cycles used as a template; averages for heritability of .16 and for genetic correlation of .66 were obtained.     

Genetic parameters for carcass and meat quality traits and their relationships to liveweight and wool production in hogget Merino rams.

Genetic parameters for carcass and meat quality traits of about 18-month-old Merino rams (n = 5870), the progeny of 543 sires from three research resource flocks, were estimated. The estimates of heritability for hot carcass weight (HCW) and the various fat and muscle dimension measurements were moderate and ranged from 0.20 to 0.37. The brightness of meat (colour L*, 0.18 +/- 0.03 standard error) and meat pH (0.22 +/- 0.03) also had moderate estimates of heritability, although meat relative redness (colour a*, 0.10 +/- 0.03) and relative yellowness (colour b*, 0.10 +/- 0.03) were lower. Heritability estimates for live weights were moderate and ranged from 0.29 to 0.41 with significant permanent maternal environmental effects (0.13 to 0.10). The heritability estimates for the hogget wool traits were moderate to high and ranged from 0.27 to 0.60. The ultrasound measurements of fat depth (FATUS) and eye muscle depth (EMDUS) on live animals were highly genetically correlated with the corresponding carcass measurements (0.69 +/- 0.09 FATC and 0.77 +/- 0.07 EMD). Carcass tissue depth (FATGR) had moderate to low genetic correlations with carcass muscle measurements [0.18 +/- 0.10 EMD and 0.05 +/- 0.10 eye muscle area (EMA)], while those with FATC were negative. The genetic correlation between EMD and eye muscle width (EMW) was 0.41 +/- 0.08, while EMA was highly correlated with EMD (0.89 +/- 0.0) and EMW (0.78 +/- 0.04). The genetic correlations for muscle colour with muscle measurements were moderately negative, while those with fat measurements were close to zero. Meat pH was positively correlated with muscle measurements (0.14 to 0.17) and negatively correlated with fat measurements (-0.06 to -0.18). EMDUS also showed a similar pattern of correlations to EMD with meat quality indicator traits, although FATUS had positive correlations with these traits which were generally smaller than their standard error. The genetic correlations among the meat colour traits were high and positive while those with meat pH were high and negative, which were all in the favourable direction. Generally, phenotypic correlations were similar or slightly lower than the corresponding genetic correlations. There were generally small to moderate negative genetic correlations between clean fleece weight (CFW) and carcass fat traits while those with muscle traits were close to zero. As the Merino is already a relatively lean breed, this implies that particular attention should be given to this relationship in Merino breeding programmes to prevent the reduction of fat reserves as a correlated response to selection for increased fleece weight. The ultrasound scan traits generally showed a similar pattern to the corresponding carcass fat and muscle traits. There was a small unfavourable genetic correlation between CFW and meat pH (0.19 +/- 0.07).     

"Quasi-REML" correlation estimates between production and health traits in the presence of selection and confounding: a simulation study

Performance of the "quasi-REML" method for estimating correlations between a continuous trait and a categorical trait, and between two categorical traits, was studied with Monte Carlo simulations. Three continuous, correlated traits were simulated for identical populations and three scenarios with either no selection, selection for one moderately heritable trait (Trait 1, h2 = .25), and selection for the same trait plus confounding between sires and management groups. The "true" environmental correlations between Traits 2 (h2 = .10) and 3 (h2 = .05) were always of the same absolute size (.20), but further data scenarios were generated by setting the sign of environmental correlation to either positive or negative. Observations for Traits 2 and 3 were then reassigned to binomial categories to simulate health or reproductive traits with incidences of 15 and 5%, respectively. Genetic correlations (r(g12), r(g13), and r(g23) and environmental correlations (r(e12), r(e13), and r(e23)) were estimated for the underlying continuous scale (REML) and the visible categorical scales ("quasi-REML") with linear multiple-trait sire and animal models. Contrary to theory, practically all "quasi-REML" genetic correlations were underestimated to some extent with the sire and animal models. Selection inflated this negative bias for sire model estimates, and the sign of r(e23) noticeably affected r(g23) estimates for the animal model, with greater bias and SD for estimates when the "true" r(e23) was positive. Transformed "quasi-REML" environmental correlations between a continuous and a categorical trait were estimated with good efficiency and little bias, and corresponding correlations between two categorical traits were systematically overestimated. Confounding between sires and contemporary groups negatively affected all correlation estimates on the underlying and the visible scales, especially for sire model "quasi-REML" estimates of genetic correlation. Selection, data structure, and the (co)variance structure influences how well correlations involving categorical traits are estimated with "quasi-REML" methods.