Journal of Animal Breeding and Genetics最新文献

In models with direct and maternal genetic effects, structural features of the data are a potential source of bias and low accuracy of estimates for genetic covariance parameters. One of the well-known reasons for such poor practical identifiability is the lack of dams with own observations. So far, however, no attention has been paid to the impact close relationships may have. Therefore, this genetic-statistical analysis of growth traits in two unselected mouse lines includes investigations on practical identifiability of genetic (co-)variances in the light of the observed high levels of co-ancestry, resulting from massively deep pedigrees. Body weight data had been collected over 33 years (from 1978 to 2011; 145 and 118 generations per line), amounting to approximately 115,000 observations in total for body weight at three developmental stages. Additional analyses of simulated data using the original pedigree structure of one line provided insight into the bias and precision of estimates. Further, closeness to pair-wise structural non-identifiability of genetic (co-)variances was quantified. In univariate analyses, we found genetic correlations between direct and maternal effects all positive for body mass traits at different ages up to mating, except for a single small negative estimate. Overall, multivariate analyses returned somewhat stronger correlations, whereby signs remained unchanged. Simulations showed a tendency toward an upward bias of the direct–maternal genetic correlations and other parameters, especially when the true correlations were higher. For all traits indicators for structural non-identifiability were narrowly close (> 0.998) to unity, the point at which a pair of covariance components no longer can be identified. This narrowness was stronger for separate partitions of data from later generations with higher average inbreeding and within-generation co-ancestry. In conclusion, in models with direct and maternal genetic effects, strong co-ancestry between parents is another feature of the data structure that may result in bias and inflated standard errors of estimated genetic parameters.

Genetic trends were estimated for production and reproduction traits in an Uruguayan Merino genetic nucleus. Two consecutive periods with different selection objectives were studied. During the first period (1999–2010), the selection objective of this flock focused on reducing fibre diameter (FD), while allowing for a slight loss in clean fleece weight (CFW). From 2011 to 2018, the breeding objective was shifted and then focused on maintaining FD, while increasing both CFW and live weight (LW). Data from approximately 5380 yearling lambs and 2000 ewes born between 1999 and 2018 were analysed. Genetic trends were estimated for yearling and adult FD (Y_FD and A_FD, respectively), yearling and adult CFW (Y_CFW and A_CFW, respectively), yearling LW (Y_LW), 2-year-old ewe mating live weight and mating body condition score (2-yo_LWM and 2-yo_BCSM, respectively) and the number of lambs weaned per ewe joined (NLWEJ). Estimated breeding values were predicted to calculate genetic trends for the two periods of selection. From 1999 to 2010, yearling lambs showed significant reductions in FD (−0.210 μm/year, corresponding to −1.28% of the mean of the trait for that period). Before 2010, yearling lambs showed reductions of −0.013 kg/year (−0.62%) in CFW, whereas from 2011 to 2018, this trait increased by 0.052 kg/year (1.88%). The annual genetic gain for Y_LW was greater in the second period than in the first period (0.286 vs. 0.091 kg/year). The genetic trends for FD, CFW and LW were affected by period (p < 0.001), indicating that the change in the selection index applied in the genetic nucleus was effective. Over the entire study period (1999–2018), the total genetic responses for 2-yo_BCSM and NLWEJ were near zero. These results indicate that the breeding programme utilised in the genetic nucleus improved the traits under selection (FD, CFW and LW) and had a marginal impact on 2-yo_BCSM and NLWEJ. To also achieve relevant genetic gains in ewe reproductive performance, in the future, reproduction traits should be incorporated into the selection programme for Uruguayan fine-wool sheep. The results obtained in this study will be used to refine the breeding programmes for Merino sheep in Uruguay.

Fitness traits described as a ratio often display non-normal distributions; consequently, transformations are frequently applied to improve normality prior to the estimation of genetic parameters. However, the impact of different transformations on genetic parameter estimates depends on the dataset at hand. The objective of this study was to evaluate the effects of eight common transformations (z-score, log, square root, probit, arcsine, logit, Box-Cox and Yeo-Johnson) on genetic parameter estimates for non-normal fitness traits in turkeys. Three fertility traits in turkeys were analysed. Egg production rate, egg fertility rate and hatch of fertile eggs rate phenotypes were collected on 6667 turkeys. All three phenotypes exhibited a significant level of non-normality. An informative pedigree file for the phenotyped birds was generated and consisted of 8612 animals. A mixed linear model that included the hatch year and regression on body weight at 18 weeks of age as fixed effects was used to analyse the transformed and untransformed phenotypes. To make the untransformed and transformed data comparable, they were all standardised to the same mean and variance. Results showed that the transformations significantly impacted genetic parameter estimates. In fact, the percentage variations in the estimates of the heritabilities of the three traits compared to the non-transformed data ranged from −80% to 45%. Across the different comparison criteria, the Box-Cox transformation seems to have the advantage compared to the other methods. Furthermore, it resulted in the highest heritability estimates. Although the genetic correlations showed fewer differences across transformations, the Spearman rank correlations ranged between 0.87 and 1, indicating some re-ranking. These findings suggest that the choice of data transformation impacts inferences on the genetic properties of non-normal traits, and careful consideration of the transformation method is needed prior to genetic analysis of skewed fitness data in turkeys and potentially other agricultural species. The results provide guidelines for the appropriate choice of transformations given observed levels of deviation from normality.

In genomic selection, balancing genetic gain with the preservation of genetic diversity is a critical challenge, requiring innovative approaches to parent selection. Traditional methods risk losing valuable genetic diversity by not fully accounting for the complex patterns of haplotype distribution. To address this, we developed a novel haplotype similarity measure that estimates the genetic similarity amongst offspring from parent pairs by analysing segregating marker patterns and the covariance of additive genetic effects between potential parental gametes. This measure is encapsulated in a novel similarity matrix that quantifies parental genetic relationships and their Mendelian sampling variance, facilitating the selection of parents with diverse haplotypes to maintain genetic diversity. Our method was evaluated through simulation studies and empirical data analysis, indicating that the similarity matrix can help preserve haplotype diversity and potentially improve long-term genetic gains compared to traditional selection methods. These results suggest that the similarity matrix could contribute to more efficient and sustainable genomic selection programs, although further research is necessary to fully understand its impact.

Change in climate over the past years and its impact on the environment have necessitated the inclusion of resilience traits in the breeding objectives of dairy cattle. However, the relationship between resilience and other traits of economic importance in dairy production is currently not well known. This study examined the genetic parameters and relationships among resilience, fertility and milk production traits in dairy cattle in Kenya. Indicators of general resilience and heat tolerance were defined from the first parity test-day milk yield records. Indicators of general resilience included variance of actual deviations (LnVar1), variance of standardised deviations (LnVar2), lag-1 autocorrelation (r_auto) and skewness (Skew) of standardised deviations in milk yield. Heat tolerance indicators at temperature-humidity index 80 included the slope of the reaction norm (Slope), absolute slope of the reaction norm (Absolute), and the intercept of the reaction norm model (Intercept). Cows with > 50% taurine genes had lower age at first calving (AFC), longer calving intervals (CI) and higher test-day milk yield (MY). The heritability estimates of AFC, CI and MY were 0.17 ± 0.033, 0.06 ± 0.012 and 0.35 ± 0.021, respectively. The repeatability estimates of CI and MY were 0.06 ± 0.012 and 0.47 ± 0.009, respectively. The low heritability and non-significant permanent environmental variance of CI showed that CI is heavily influenced by external factors, such as management practices. AFC was negatively genetically correlated with both CI (−0.88 ± 0.077) and MY (−0.53 ± 0.059) showing that animals that attain sexual maturity earlier exhibit longer CI and higher milk production. A positive genetic correlation (0.62 ± 0.077) between CI and MY shows that high-yielding cows face challenges in maintaining shorter calving intervals. Heritability estimates of nearly all resilience indicators were significant and ranged from 0.05 to 0.34. Heat tolerance indicators showed low to non-significant genetic correlations with general resilience indicators, suggesting that different genetic factors are involved in responses to different types of disturbances. There was a generally positive genetic correlation between resilience and fertility, implying that resilient animals might have better fertility. All indicators, except LnVar1 and LnVar2, revealed an antagonistic genetic relationship between resilience and milk production. The findings present an opportunity for including resilience in the development and application of selection indices in dairy cattle, especially for the tropics.

Barrel racing is a competitive timed rodeo event that challenges horses and riders to complete a cloverleaf pattern around three barrels in the fastest time possible. In this study, we aimed to estimate the genetic parameters of barrel racing time (BRT) and evaluate the most suitable statistical model for its analysis. We compared a repeatability model and three random regression models (RRM) to analyse the longitudinal BRT data in Brazilian Quarter Horses. A total of 356,877 BRT records from 14,108 horses that competed in various events held across Brazil between 2010 and 2024 were analysed. The cubic RRM provided the best fit to the data, and therefore, the results from this model were presented in detail. Heritability estimates for BRT varied by age (0.15–0.24), with the highest estimates observed between 36 and 54 months, suggesting that selection at younger ages could be most effective. Genetic correlations between BRT at different ages were generally strong (> 0.8). The lowest mean genetic correlation of 0.65 (0.09) was observed between BRT at 36 and 144 months of age. Thus, selecting the best-performing horses at younger ages should result in favourable genetic progress at older ages. Phenotypic trends showed an improvement in BRT over the years, although no significant genetic progress was observed, likely due to the absence of an official breeding programme and the lack of use of estimated breeding values for BRT. These findings highlight the need for a more strategic approach to genetic selection in Quarter Horses to optimise BRT performance. The substantial genetic variation identified for BRT indicates that, if properly exploited, this trait could be significantly improved in the future, ultimately enhancing competition outcomes for Brazilian Quarter Horses in barrel racing.