Effectiveness of adjusting for heterogeneity of variance in genetic evaluation of Japanese Black cattle

Genotype by environment interaction and heteroscedasticity influence the expression of parasite resistance in Katahdin sheep

Increasingly, sheep producers are choosing breeds that express resistance to gastrointestinal parasites due to reduced efficacy of anthelminthic drugs. One such breed is Katahdin. Katahdins are raised in various climates and management systems in the United States, which can be combined into eco-management clusters to describe production environments more holistically. The objectives of this study were to determine if genotype by environment interaction (G × E) and heteroscedasticity existed across these eco-management clusters for traits indicative of parasite resistance. Body weights (BW), FAMACHA scores (FAM), and fecal egg counts (FEC) were collected at around 90 d in 3,527 Katahdin lambs delineated into nine eco-management clusters. A tri-variate animal model including birth-rearing type, sex, and dam age (as a quadratic covariate) as fixed effects, and eco-management cluster, direct additive, uncorrelated maternal environmental (for BW), and residual as random effects, was fitted with ASReml. Heritability estimates for BW, FEC, and FAM were 0.36 ± 0.07, 0.31 ± 0.07, and 0.26 ± 0.05, respectively. The genetic (additive) correlation between BW with FEC was -0.26 ± 0.08 and with FAM was -0.16 ± 0.08, and thereby favorable. Heritabilities were also estimated univariately within eco-management clusters and ranged from 0.30 ± 0.05 to 0.37 ± 0.05 for BW, 0.18 ± 0.12 to 0.50 ± 0.13 for FEC, and 0.07 ± 0.06 to 0.40 ± 0.19 for FAM. Significant genetic and phenotypic heteroscedasticity among eco-management clusters was detected in FEC and FAM. A sire by eco-management cluster interaction term was added to the initial model fitted to evaluate G × E. This interaction defined substantial variation (P < 0.01) in all traits and explained 12% (FEC) to 20% (BW) of the phenotypic variation. Accounting for G × E and heteroscedasticity in the design and implementation of breeding programs may introduce operational challenges. Still, doing so would improve the efficacy of selection programs to improve parasite resistance.

Fitting Genomic Prediction Models with Different Marker Effects among Prefectures to Carcass Traits in Japanese Black Cattle

We fitted statistical models, which assumed single-nucleotide polymorphism (SNP) marker effects differing across the fattened steers marketed into different prefectures, to the records for cold carcass weight (CW) and marbling score (MS) of 1036, 733, and 279 Japanese Black fattened steers marketed into Tottori, Hiroshima, and Hyogo prefectures in Japan, respectively. Genotype data on 33,059 SNPs was used. Five models that assume only common SNP effects to all the steers (model 1), common effects plus SNP effects differing between the steers marketed into Hyogo prefecture and others (model 2), only the SNP effects differing between Hyogo steers and others (model 3), common effects plus SNP effects specific to each prefecture (model 4), and only the effects specific to each prefecture (model 5) were exploited. For both traits, slightly lower values of residual variance than that of model 1 were estimated when fitting all other models. Estimated genetic correlation among the prefectures in models 2 and 4 ranged to 0.53 to 0.71, all <0.8. These results might support that the SNP effects differ among the prefectures to some degree, although we discussed the necessity of careful consideration to interpret the current results.

Ability of sire breeding values to predict progeny bodyweight, fat and muscle using various transformations across environments in terminal sire sheep breeds

Data used for the genetic evaluation of the terminal sire sheep breeds in Australia originate from a large range of genotypes and environments. This means there are large differences in the level of production and therefore contemporary group means and variances within the data. This study examined four transformations to account for the heterogeneity of variance in the observed data and their effect on the ability of estimated breeding values of sires (sire EBV) to predict progeny performance. This predictive ability was described by regressing offspring performance on sire EBV. The expected value of this regression is 0.5, which indicates that half of the sire EBV differences can be expected in the progeny. The transformations of observed data were investigated in low, medium and high production environments for weight and ultrasound scan traits (fat and muscle) in terminal sire sheep breeds. There were records from over 300 000 sheep in the LAMBPLAN terminal sire dataset, predominately from Poll Dorset, Texel, Suffolk and White Suffolk breeds. The transformation methods applied to the observed data were: traits expressed as a percentage of the contemporary group mean; traits re-scaled to a common contemporary group mean in units of measurement; a logarithmic transformation; and a square root transformation. The heritabilities and other variance ratios estimated from the transformed traits were not significantly different from those using the observed data. Phenotypes transformed to a proportion of the contemporary group mean, either as a percentage or in units of measurement, resulted in the most consistent EBV across all production environments for weight and fat traits, with little effect of transformations for muscle traits. The transformation of data to the contemporary mean in units of measurement for weight and fat traits has been implemented in the Sheep Genetics evaluation system. The consistency of the progeny–sire EBV regressions around 0.5 in the data from these purebred industry flocks is heartening for terminal sire evaluation.

Genetic Parameters of Pre-adjusted Body Weight Growth and Ultrasound Measures of Body Tissue Development in Three Seedstock Pig Breed Populations in Korea

The objective of this study was to compare the effects of body weight growth adjustment methods on genetic parameters of body growth and tissue among three pig breeds. Data collected on 101,820 Landrace, 281,411 Yorkshire, and 78,068 Duroc pigs, born in Korean swine breeder farms since 2000, were analyzed. Records included body weights on test day and amplitude (A)-mode ultrasound carcass measures of backfat thickness (BF), eye muscle area (EMA), and retail cut percentage (RCP). Days to 90 kg body weight (DAYS90), through an adjustment of the age based on the body weight at the test day, were obtained. Ultrasound measures were also pre-adjusted (ABF, EMA, AEMA, ARCP) based on their test day measures. The (co)variance components were obtained with 3 multi-trait animal models using the REMLF90 software package. Model I included DAYS90 and ultrasound traits, whereas model II and III accounted DAYS90 and pre-adjusted ultrasound traits. Fixed factors were sex (sex) and contemporary groups (herd-year-month of birth) for all traits among the models. Additionally, model I and II considered a linear covariate of final weight on the ultrasound measure traits. Heritability (h²) estimates for DAYS90, BF, EMA, and RCP ranged from 0.36 to 0.42, 0.34 to 0.43, 0.20 to 0.22, and 0.39 to 0.45, respectively, among the models. The h² estimates of DAYS90 from model II and III were also somewhat similar. The h² for ABF, AEMA, and ARCP were 0.35 to 0.44, 0.20 to 0.25, and 0.41 to 0.46, respectively. Our heritability estimates varied mostly among the breeds. The genetic correlations (r_G) were moderately negative between DAYS90 and BF (−0.29 to −0.38), and between DAYS90 and EMA (−0.16 to −0.26). BF had strong r_G with RCP (−0.87 to −0.93). Moderately positive r_G existed between DAYS90 and RCP (0.20 to 0.28) and between EMA and RCP (0.35 to 0.44) among the breeds. For DAYS90, model II and III, its correlations with ABF, AEMA, and ARCP were mostly low or negligible except the r_G between DAYS90 and AEMA from model III (0.27 to 0.30). The r_G between AEMA and ABF and between AEMA and ARCP were moderate but with negative and positive signs, respectively; also reflected influence of pre-adjustments. However, the r_G between BF and RCP remained non-influential to trait pre-adjustments or covariable fits. Therefore, we conclude that ultrasound measures taken at a body weight of about 90 kg as the test final should be adjusted for body weight growth. Our adjustment formulas, particularly those for BF and EMA, should be revised further to accommodate the added variation due to different performance testing endpoints with regard to differential growth in body composition.

Heterogeneous variances and genetics by environment interactions in genetic evaluation of crossbred lambs

Accounting for environmental heteroscedasticity and genetics by environment interaction (G×E) in genetic evaluation is important because animals may not perform predictably across environments. The objectives of this study were to evaluate the presence and consequences of heteroscedasticity and G×E on genetic evaluation. The population considered was crossbred lambs sired by terminal sires and reared under commercial conditions in the UK. Data on 6325 lambs sired by Charollais, Suffolk and Texel rams were obtained. The experiment was conducted between 1999 and 2002 on three farms located in England, Scotland and Wales. There were 2322, 2137 and 1866 lambs in England, Scotland and Wales, respectively. A total of 89 sires were mated to 1984 ewes of two types (Welsh and Scottish Mules). Most rams were used for two breeding seasons with some rotated among farms to create genetic links. Lambs were reared on pasture and had their parentage, birth, 5 week, 10 week, and slaughter weights recorded. Lambs were slaughtered at a constant fatness, at which they were ultrasonically scanned for fat and muscle depth. Heteroscedasticity was evaluated in two ways. First, data were separated into three subsets by farm. Within-farm variance component estimates were then compared with those derived from the complete data (Model 1). Second, the combined data were fitted, but with a heterogeneous (by farm) environmental variance structure (Model 2). To investigate G×E, a model with a random farm by sire (F×S) interaction was used (Model 3). The ratio of the F×S variance to total variance was a measure of the level of G×E in the population. Heterogeneity in environmental variability across farm was identified for all traits (P<0.01). Rank correlations of sire estimated breeding value between farms differed for Model 1 for all traits. However, sires ranked similarly (rank correlation of 0.99) for weight traits with Model 2, but less so for ultrasonic measures. Including the F×S interaction (Model 3) improved model fit for all traits. However, the F×S term explained a small proportion of variation in weights (<2%) although more in ultrasonic traits (at least 10%). In conclusion, heteroscedasticity and G×E were not large for these data, and can be ignored in genetic evaluation of weight but, perhaps, not ultrasonic traits. Still, before incorporating heteroscedasticity and G×E into routine evaluations of even ultrasonic traits, their consequences on selection response in the breeding goal should be evaluated.