Genetic Parameters of Fertility Disorders and Mastitis in the Swedish Friesian Breed

Abstract

Genetic parameters of fertility disorders and mastitis in the Swedish Friesian breed (SLB) were estimated from 9516 observations, using a restricted multiple trait maximum likelihood method. Information on individual cow diagnosis for fertility disorders and mastitis was obtained from registered veterinary treatments matched with AI data and data from the milk-recording scheme, including culling reasons. Heritability estimates for fertility disorders and mastitis using only veterinary treatments as sources of information were 0.008±0.011 and 0.018±0.015, respectively. Including culling reasons gave a significant increase in heritability estimate for mastitis (0.083±0.030), but not for fertility disorders (0.001±0.003). Increased incidence of fertility disorders and decreased incidence of mastitis were found for SLB cows with a high proportion of imported Holstein Friesian genes. Estimates of heterosis effects were small and not significant. Estimated recombination effects were negative for fertility disorders and positive for mastitis.     

“Bending” and beyond: Better estimates of quantitative genetic parameters?

Multivariate estimation of genetic parameters involving more than a handful of traits can be afflicted by problems arising through substantial sampling variation. We present a review of underlying causes and proposals to improve estimates, focusing on linear mixed model‐based estimation via restricted maximum likelihood (REML). Both full multivariate analyses and pooling of results from overlapping subsets of traits are considered. It is suggested to impose a penalty on the likelihood designed to reduce sampling variances at the expense of a little additional bias. Simulation results are discussed which demonstrate that this can yield REML estimates that are on average closer to the population values than their unpenalized counterparts. Suitable penalties can be obtained based on assumed prior distributions of selected parameters. Necessary choices of penalty functions and of the stringency of penalization are examined. We argue that scale‐free penalty functions lend themselves to a simple scheme imposing a mild, default penalty which can yield “better” estimates without being likely to incur detrimental effects.     

Genetic association between leg conformation in young pigs and sow longevity

Longevity is important in pig production with respect to both economic and ethical aspects. Direct selection for longevity might be ineffective because ‘true’ longevity can only be recorded when a sow has been culled or died. Thus, indirect selection for longevity using information from other traits that can be recorded early in life and are genetically correlated with longevity might be an alternative. Leg conformation has been included in many breeding schemes for a number of years. However, proving that leg conformation traits are good early indicators for longevity still remains. Our aim was to study genetic associations between leg conformation traits of young (5 months; 100 kg) Swedish Yorkshire pigs in nucleus herds and longevity traits of sows in nucleus and multiplier herds. Data included 97 533 animals with information on conformation (Movement and Overall score) recorded at performance testing and 26 962 sows with information on longevity. The longevity traits were as follows: stayability from 1st to 2nd parity, lifetime number of litters and lifetime number of born alive piglets. Genetic analyses were performed with both linear models using REML and linear‐threshold models using Bayesian methods. Heritabilities estimated using the Bayesian method were higher than those estimated using REML, ranging from 0.10 to 0.24 and 0.07 to 0.20, respectively. All estimated genetic correlations between conformation and longevity traits were significant and favourable. Heritabilities and genetic correlations between conformation and longevity indicate that selection on leg conformation should improve sow longevity.     

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.     

Response of UK winter wheat cultivars to <Emphasis Type="Italic">Soil-borne cereal mosaic</Emphasis> and <Emphasis Type="Italic">Wheat spindle streak mosaic viruses</Emphasis> across Europe.

Twenty-one UK winter wheat cultivars were grown over three seasons at sites with natural inoculum sources of Soil-borne cereal mosaic virus (SBCMV) and Wheat spindle streak mosaic virus (WSSMV) located in France, Italy and the UK. Plants were assessed visually for virus symptoms and leaf extracts were tested for the presence of each virus using enzyme-linked immunosorbent assays (ELISA). Cultivars showing little or no foliar symptoms and low levels of virus in leaf tissue were classified as resistant to each virus. All the trials were taken to harvest and agronomic data collected. At the most heavily infected sites, severe symptoms of SBCMV were observed in all UK cultivars except Aardvark, Charger, Claire, Cockpit, Hereward and Xi 19. The latter cultivars exhibited either light or no symptoms and little or no SBCMV infection in leaves. In fields with WSSMV, the virus failed to develop in Italy, but was detected in the leaves of all the susceptible control cultivars at a site in France. However, no UK cultivar tested positive for WSSMV. Multi-site analysis indicated that the presence of WSSMV did not increase the impact of SBCMV on the height, thousand-grain weight or yield of UK cultivars. The wheat cultivars on test gave a similar response to SBCMV across three European countries. Possible sources of SBCMV resistance are discussed.     

Evaluating cultivars in unbalanced on-farm participatory trials

Data from on-farm participatory varietal trials are often highly unbalanced. Using statistically robust techniques we showed that such data are amenable to sophisticated analyses. Data from 38 varieties of wheat tested in 44 mother trials (all test varieties compared) and 663 baby trials (single entries compared with local checks) over 6 years in Lunawada, Gujarat, India, were analysed. Two combined analyses for grain yield were performed by using either a fixed effects model within general linear modelling (GLM) or a mixed effects model using the restricted maximum likelihood (REML) procedure. Both analyses made substantial adjustments over the raw means and the estimated mean values from the two analyses for the fixed set of tested varieties were highly correlated (R² = 0.89) as were the t-value that compared test cultivars with the check variety (R² = 0.96). The GLM detected 15 varieties and REML detected 12 varieties that were significantly superior to the check cultivar with 11 varieties in common. Both methods were similar in identifying the top-most promising varieties but REML was more conservative (i.e. more subject to Type II error) with larger standard errors (S.E.s) of variety means for n > 17. However, for both procedures the S.E.s increased sharply when the number of trials decreased below 17.     

九孔鲍幼鲍生长性状的遗传参数估计

采用不平衡巢式设计方法和人工授精技术,1个父本配3个母本,建立九孔鲍(Haliotis diversicolor super-texta)12个半同胞家系和36个全同胞家系.在40日龄、120日龄、180日龄、240日龄时分别对所建36家系个体测量壳长,壳宽与体质量.采用单性状约束最大似然法(Restricted Maximum Likelihood Method, REML)估计九孔鲍(Haliotis diversicolor supertexta)各阶段体质量,壳宽与壳长性状的遗传参数.结果表明,九孔鲍幼鲍在40、120、180、240日龄时壳长遗传力估计值为(0.13±0.09)~(0.56±0.15),壳宽遗传力估计值为(0.13±0.06)~(0.62±0.13),体质量遗传力估计值为(0.18±0.15)~(0.26±0.08),均属于中等遗传力.另外,从性状的表型相关与遗传相关可以得出,九孔鲍稚鲍在不同日龄壳长、壳宽与体质量的表型相关和遗传相关均为正相关(P≤0.05).表型相关系数为0.66~0.94,遗传相关系数为0.85~0.98,研究结果表明,以3个主要生长性状之一作为选育目标,均能达到遗传改良的目的.     

Investigation of long-term field experiments on response of breeding lines to common scab in a potato breeding program

Common scab, caused by Streptomyces scabies, is a disease that produces scab-like surface lesions on potato tubers. Testing for susceptibility/resistance of breeding lines at the Potato Research Centre of Agriculture & Agri-Food Canada (AFC) is carried out in a scab nursery maintained at AFC for the annual scab evaluation field trials. A replicated field trial routinely consists of breeding lines from previous testing season(s) plus newly selected lines. Data of scab scores generated from long-term experiments thus formulate an incomplete 2-way table over combinations of breeding lines (genotypes) and trials (years). This requires an advanced statistical method to estimate genetic parameters for evaluation purposes. A data base with 1,435 scab index scores from 344 breeding lines were extracted from 5 years (1995–1999) of field experiments in the scab nursery maintained at AFC. The statistical method Residual Maximum Likelihood (REML) was employed to estimate variance components of the breeding population and Best Linear Unbiased Predictor (BLUP) was used to predict genetic merit of breeding lines. High heritability was obtained from variance components estimated by REML. The BLUP scores of breeding lines provided reliable evaluation of their responses to common scab. Two data base sub-sets were separately formulated from the original data base for those parents and grandparents of the breeding lines having pedigree records available. They were again subjected to REML and BLUP analyses to compare the responses to common scab and identify sources of resistance at the parental and grandparental levels. Two random data sets with equal sized samples of breeding lines were also generated from the over-all data base. The two sets of BLUP scores between corresponding breeding lines and parents showed high association which provides an assessment of the validity of the evaluation process.     

Estimation of dominance genetic variances for reproductive traits and growth traits of calves in Japanese Black cattle

The dominance genetic effects for reproductive and calf growth abilities in the practical Japanese Black populations were examined using average information (AI) algorithm restricted maximum likelihood (REML) under animal models. The reproductive traits were observed in Japanese Black cattle maintained at Tottori and Okinawa prefectures, and growth traits of calves were observed in cattle at Okinawa. The average of dominance relationships in Tottori ranged from 0.2 to 0.4%, while the level in Okinawa was lower and sparse compared with Tottori. The proportions of the dominance variances to sum of additive and dominance variances () were all 0.02 for reproductive traits in Tottori. In contrast, the proportion was 0.02–0.64 in Okinawa regardless of the level of dominance relationships. These proportions suggested that the dominance might affect the expression of calving interval, days open and gestation length in Okinawa, where breeding units were spread over many islands. Although the dominance variances could not estimate birthweight, w as 0.34 for calf market weight and 0.27 for average daily gain from birth to calf market in Okinawa. These values also suggested that the dominance might affect the early growth of calves. In the near future, genetic relationships will become more complicated with continuation of the current selection and mating systems. Therefore, genetic evaluation accounting for dominance effects would be necessary for particular traits and populations.     

Comparing sampling needs for variograms of soil properties computed by the method of moments and residual maximum likelihood

It has been generally accepted that the method of moments (MoM) variogram, which has been widely applied in soil science, requires about 100 sites at an appropriate interval apart to describe the variation adequately. This sample size is often larger than can be afforded for soil surveys of agricultural fields or contaminated sites. Furthermore, it might be a much larger sample size than is needed where the scale of variation is large. A possible alternative in such situations is the residual maximum likelihood (REML) variogram because fewer data appear to be required. The REML method is parametric and is considered reliable where there is trend in the data because it is based on generalized increments that filter trend out and only the covariance parameters are estimated. Previous research has suggested that fewer data are needed to compute a reliable variogram using a maximum likelihood approach such as REML, however, the results can vary according to the nature of the spatial variation. There remain issues to examine: how many fewer data can be used, how should the sampling sites be distributed over the site of interest, and how do different degrees of spatial variation affect the data requirements? The soil of four field sites of different size, physiography, parent material and soil type was sampled intensively, and MoM and REML variograms were calculated for clay content. The data were then sub-sampled to give different sample sizes and distributions of sites and the variograms were computed again. The model parameters for the sets of variograms for each site were used for cross-validation. Predictions based on REML variograms were generally more accurate than those from MoM variograms with fewer than 100 sampling sites. A sample size of around 50 sites at an appropriate distance apart, possibly determined from variograms of ancillary data, appears adequate to compute REML variograms for kriging soil properties for precision agriculture and contaminated sites.