Accuracy of breeding values for production traits in turkeys (Meleagris gallopavo) using recursive models with or without genomics.

BACKGROUND Knowledge about potential functional relationships among traits of interest offers a unique opportunity to understand causal mechanisms and to optimize breeding goals, management practices, and prediction accuracy. In this study, we inferred the phenotypic causal networks among five traits in a turkey population and assessed the effect of the use of such causal structures on the accuracy of predictions of breeding values. METHODS Phenotypic data on feed conversion ratio, residual feed intake, body weight, breast meat yield, and walking score in addition to genotype data from a commercial breeding population were used. Causal links between the traits were detected using the inductive causation algorithm based on the joint distribution of genetic effects obtained from a standard Bayesian multiple trait model. Then, a structural equation model was implemented to infer the magnitude of causal structure coefficients among the phenotypes. Accuracies of predictions of breeding values derived using pedigree- and blending-based multiple trait models were compared to those obtained with the pedigree- and blending-based structural equation models. RESULTS In contrast to the two unconditioned traits (i.e., feed conversion ratio and breast meat yield) in the causal structures, the three conditioned traits (i.e., residual feed intake, body weight, and walking score) showed noticeable changes in estimates of genetic and residual variances between the structural equation model and the multiple trait model. The analysis revealed interesting functional associations and indirect genetic effects. For example, the structural coefficient for the path from body weight to walking score indicated that a 1-unit genetic improvement in body weight is expected to result in a 0.27-unit decline in walking score. Both structural equation models outperformed their counterpart multiple trait models for the conditioned traits. Applying the causal structures led to an increase in accuracy of estimated breeding values of approximately 7, 6, and 20% for residual feed intake, body weight, and walking score, respectively, and different rankings of selection candidates for the conditioned traits. CONCLUSIONS Our results suggest that structural equation models can improve genetic selection decisions and increase the prediction accuracy of breeding values of selection candidates. The identified causal relationships between the studied traits should be carefully considered in future turkey breeding programs

Genome-wide association study reveals candidate genes relevant to body weight in female turkeys (Meleagris gallopavo).

The underlying genetic mechanisms affecting turkey growth traits have not been widely investigated. Genome-wide association studies (GWAS) is a powerful approach to identify candidate regions associated with complex phenotypes and diseases in livestock. In the present study, we performed GWAS to identify regions associated with 18-week body weight in a turkey population. The data included body weight observations for 24,989 female turkeys genotyped based on a 65K SNP panel. The analysis was carried out using a univariate mixed linear model with hatch-week-year and the 2 top principal components fitted as fixed effects and the accumulated polygenic effect of all markers captured by the genomic relationship matrix as random. Thirty-three significant markers were observed on 1, 2, 3, 4, 7 and 12 chromosomes, while 26 showed strong linkage disequilibrium extending up to 410 kb. These significant markers were mapped to 37 genes, of which 13 were novel. Interestingly, many of the investigated genes are known to be involved in growth and body weight. For instance, genes AKR1D1, PARP12, BOC, NCOA1, ADCY3 and CHCHD7 regulate growth, body weight, metabolism, digestion, bile acid biosynthetic and development of muscle cells. In summary, the results of our study revealed novel candidate genomic regions and candidate genes that could be managed within a turkey breeding program and adapted in fine mapping of quantitative trait loci to enhance genetic improvement in this species

Applicability of single-step genomic evaluation with a random regression model for reproductive traits in turkeys (Meleagris gallopavo).

Fertility and hatchability are economically important traits due to their effect on poult output coming from the turkey hatchery. Traditionally, fertility is recorded as the number of fertile eggs set in the incubator (FERT), defined at a time point during incubation by the identification of a developing embryo. Hatchability is recorded as either the number of fertile eggs that hatched (hatch of fertile, HOF) or the number hatched from all the eggs set (hatch of set, HOS). These traits are collected throughout the productive life of the bird and are conventionally cumulated, resulting in each bird having a single record per trait. Genetic evaluations of these traits have been estimated using pedigree relationships. However, the longitudinal nature of the traits and the availability of genomic information have renewed interest in using random regression (RR) to capture the differences in repeatedly recorded traits, as well as in the incorporation of genomic relationships. Therefore, the objectives of this study were: 1) to compare the applicability of a RR model with a cumulative model (CUM) using both pedigree and genomic information for genetic evaluation of FERT, HOF, and HOS and 2) to estimate and compare predictability from the models. For this study, a total of 63,935 biweekly FERT, HOF, and HOS records from 7,211 hens mated to 1,524 toms were available for a maternal turkey line. In total, 4,832 animals had genotypic records, and pedigree information on 11,191 animals was available. Estimated heritability from the CUM model using pedigree information was 0.11 0.02, 0.24 0.02, and 0.24 0.02 for FERT, HOF, and HOS, respectively. With random regression using pedigree relationships, heritability estimates were in the range of 0.04-0.09, 0.11-0.17, and 0.09-0.18 for FERT, HOF, and HOS, respectively. The incorporation of genomic information increased the heritability by an average of 28 and 23% for CUM and RR models, respectively. In addition, the incorporation of genomic information caused predictability to increase by approximately 11 and 7% for HOF and HOS, respectively; however, a decrease in predictability of about 12% was observed for FERT. Our findings suggest that RR models using pedigree and genomic relationships simultaneously will achieve a higher predictability than the traditional CUM model

Nontraditional Feedstuffs as an Alternative in Poultry Feed

Soybean meal and yellow corn are conventional feedstuffs used as the main ingredients in poultry feeds due to their high nutrients availability. On the other hand, these two feedstuffs are high in demand by other animals (soybean meal) and humans (yellow corn). By the year 2050, the world’s population is expected to increase up to 9.1 billion. Global consumption of poultry products, such as meat or eggs is increasing predominantly in developing countries. Consequently, the global demand for poultry feedstuffs would increase. The availability of feedstuffs for poultry nutrition nowadays is becoming more competitive. Thus, food security, especially in the developing countries, would be threatened. Currently, efforts are being made to use alternative feedstuffs to substitute portion of soybean meal and yellow corn in poultry diets. This chapter discusses the alternative feedstuffs that can be incorporated in poultry feeds. In addition, the nutritive content and availability are examined as well as how to improve the nutritive quality of such nontraditional feedstuffs

Genetic Parameters of White Striping and Meat Quality Traits Indicative of Pale, Soft, Exudative Meat in Turkeys (Meleagris gallopavo).

Due to the increasing prevalence of growth-related myopathies and abnormalities in turkey meat, the ability to include meat quality traits in poultry breeding strategies is an issue of key importance. In the present study, genetic parameters for meat quality traits and their correlations with body weight and meat yield were estimated using a population of purebred male turkeys. Information on live body, breast, thigh, and drum weights, breast meat yield, feed conversion ratio, breast lightness (L*), redness (a*), and yellowness (b*), ultimate pH, and white striping (WS) severity score were collected on 11,986 toms from three purebred genetic lines. Heritability and genetic and partial phenotypic correlations were estimated for each trait using an animal model with genetic line, hatch week-year, and age at slaughter included as fixed effects. Heritability of ultimate pH was estimated to be 0.34 ± 0.05 and a range of 0.20 ± 0.02 to 0.23 ± 0.02 for breast meat colour (L*, a*, and b*). White striping was also estimated to be moderately heritable at 0.15 ± 0.02. Unfavorable genetic correlations were observed between body weight and meat quality traits as well as white striping, indicating that selection for increased body weight and meat yield may decrease pH and increase the incidence of pale meat with more severe white striping. The results of this analysis provide insight into the effect of current selection strategies on meat quality and emphasize the need to include meat quality traits into future selection indexes for turkeys

Identification of unique ROH regions with unfavorable effects on production and fertility traits in Canadian Holsteins

Background: The advent of genomic information and the reduction in the cost of genotyping have led to the use of genomic information to estimate genomic inbreeding as an alternative to pedigree inbreeding. Using genomic measures, effects of genomic inbreeding on production and fertility traits have been observed. However, there have been limited studies on the specific genomic regions causing the observed negative association with the trait of interest. Our aim was to identify unique run of homozygosity (ROH) genotypes present within a given genomic window that display negative associations with production and fertility traits and to quantify the effects of these identified ROH genotypes. Methods: In total, 50,575 genotypes based on a 50K single nucleotide polymorphism (SNP) array and 259,871 pedigree records were available. Of these 50,575 genotypes, 46,430 cows with phenotypic records for production and fertility traits and having a first calving date between 2008 and 2018 were available. Unique ROH genotypes identified using a sliding-window approach were fitted into an animal mixed model as fixed effects to determine their effect on production and fertility traits. Results: In total, 133 and 34 unique ROH genotypes with unfavorable effects were identified for production and fertility traits, respectively, at a 1% genome-wise false discovery rate. Most of these ROH regions were located on bovine chromosomes 8, 13, 14 and 19 for both production and fertility traits. For production traits, the average of all the unfavorably identified unique ROH genotypes effects were estimated to decrease milk yield by 247.30 kg, fat yield by 11.46 kg and protein yield by 8.11 kg. Similarly, for fertility traits, an average 4.81-day extension in first service to conception, a 0.16 increase in number of services, and a - 0.07 incidence in 56-day non-return rate were observed. Furthermore, a ROH region located on bovine chromosome 19 was identified that, when homozygous, had a negative effect on production traits. Signatures of selection proximate to this region have implicated GH1 as a potential candidate gene, which encodes the growth hormone that binds the growth hormone receptor. This observed negative effect could be a consequence of unfavorable alleles in linkage disequilibrium with favorable alleles. Conclusions: ROH genotypes with unfavorable effects on production and fertility traits were identified within and across multiple traits on most chromosomes. These identified ROH genotypes could be included in mate selection programs to minimize their frequency in future generations

Genetic analysis of egg production traits in turkeys (Meleagris gallopavo) using a single-step genomic random regression model.

BACKGROUND Egg production traits are economically important in poultry breeding programs. Previous studies have shown that incorporating genomic data can increase the accuracy of genetic prediction of egg production. Our objective was to estimate the genetic and phenotypic parameters of such traits and compare the prediction accuracy of pedigree-based random regression best linear unbiased prediction (RR-PBLUP) and genomic single-step random regression BLUP (RR-ssGBLUP). Egg production was recorded on 7422 birds during 24 consecutive weeks from first egg laid. Hatch-week of birth by week of lay and week of lay by age at first egg were fitted as fixed effects and body weight as a covariate, while additive genetic and permanent environment effects were fitted as random effects, along with heterogeneous residual variances over 24 weeks of egg production. Predictions accuracies were compared based on two statistics: (1) the correlation between estimated breeding values and phenotypes divided by the square root of the trait heritability, and (2) the ratio of the variance of BLUP predictions of individual Mendelian sampling effects divided by one half of the estimate of the additive genetic variance. RESULTS Heritability estimates along the production trajectory obtained with RR-PBLUP ranged from 0.09 to 0.22, with higher estimates for intermediate weeks. Estimates of phenotypic correlations between weekly egg production were lower than the corresponding genetic correlation estimates. Our results indicate that genetic correlations decreased over the laying period, with the highest estimate being between traits in later weeks and the lowest between early weeks and later ages. Prediction accuracies based on the correlation-based statistic ranged from 0.11 to 0.44 for RR-PBLUP and from 0.22 to 0.57 for RR-ssGBLUP using the correlation-based statistic. The ratios of the variances of BLUP predictions of Mendelian sampling effects and one half of the additive genetic variance ranged from 0.17 to 0.26 for RR-PBLUP and from 0.17 to 0.34 for RR-ssGBLUP. Although the improvement in accuracies from RR-ssGBLUP over those from RR-PBLUP was not uniform over time for either statistic, accuracies obtained with RR-ssGBLUP were generally equal to or higher than those with RR-PBLUP. CONCLUSIONS Our findings show the potential advantage of incorporating genomic data in genetic evaluation of egg production traits using random regression models, which can contribute to the genetic improvement of egg production in turkey populations

Genetic parameters of feather corticosterone and fault bars and correlations with production traits in turkeys (Meleagris gallopavo).

Robustness can refer to an animal's ability to overcome perturbations. Intense selection for production traits in livestock has resulted in reduced robustness which has negative implications for livability as well as production. There is increasing emphasis on improving robustness through poultry breeding, which may involve identifying novel phenotypes that could be used in selection strategies. The hypothalamic-pituitary-adrenal (HPA) axis and associated hormones (e.g., corticosterone) participate in many metabolic processes that are related to robustness. Corticosterone can be measured non-invasively in feathers (FCORT) and reflects the average HPA axis activity over the feather growing period, however measurement is expensive and time consuming. Fault bars are visible feather deformities that may be related to HPA axis activity and may be a more feasible indicator trait. In this study, we estimated variance components for FCORT and fault bars in a population of purebred turkeys as well as their genetic and partial phenotypic correlations with other economically relevant traits including growth and efficiency, carcass yield, and meat quality. The estimated heritability for FCORT was 0.21 ± 0.07 and for the fault bar traits (presence, incidence, severity, and index) estimates ranged from 0.09 to 0.24. The genetic correlation of FCORT with breast weight, breast meat yield, fillet weight, and ultimate pH were estimated at -0.34 ± 0.21, -0.45 ± 0.23, -0.33 ± 0.24, and 0.32 ± 0.24, respectively. The phenotypic correlations of FCORT with breast weight, breast meat yield, fillet weight, drum weight, and walking ability were -0.16, -0.23, -0.18, 0.17, and 0.21, respectively. Some fault bar traits showed similar genetic correlations with breast weight, breast meat yield, and walking ability but the magnitude was lower than those with FCORT. While the dataset is limited and results should be interpreted with caution, this study indicates that selection for traits related to HPA axis activity is possible in domestic turkeys. Further research should focus on investigating the association of these traits with other robustness-related traits and how to potentially implement these traits in turkey breeding

Reliability of a White Striping Scoring System and Description of White Striping Prevalence in Purebred Turkey Lines.

To efficiently meet consumer demands for high-quality lean meat, turkeys are selected for increased meat yield, mainly by increasing breast muscle size and growth efficiency. Over time, this has altered muscle morphology and development rates, which are believed to contribute to the prevalence of myopathies. White striping is a myopathy of economic importance which presents as varying degrees of white striations on the surface of skinless breast muscle and can negatively affect consumer acceptance at the point of sale. Breeding for improved meat quality may be a novel strategy for mitigating the development of white striping in turkey meat; however, it is crucial to have a reliable assessment tool before it can be considered as a phenotype. Six observers used a four-category scoring system (0-3) to score severity in several controlled rounds and evaluate intra- and inter-observer reliability of the scoring system. After sufficient inter-observer reliability (Kendall's W > 0.6) was achieved, 12,321 turkey breasts, from four different purebred lines, were scored to assess prevalence of the condition and analyze its relationship with important growth traits. Overall, the prevalence of white striping (Score > 0) was approximately 88% across all genetic lines studied, with most scores being of moderate-severe severity (Score 1 or 2). As was expected, increased white striping severity was associated with higher slaughter weight, breast weight, and breast meat yield (BMY) within each genetic line. This study highlights the importance of training to improve the reliability of a scoring system for white striping in turkeys and was required to provide an updated account on white striping prevalence in modern turkeys. Furthermore, we showed that white striping is an important breast muscle myopathy in turkeys linked to heavily selected traits such as body weight and BMY. White striping should be investigated further as a novel phenotype in future domestic turkey selection through use of a balanced selection index