The predicted benefits of genomic selection on pig breeding objectives.

The premise was tested that the additional genetic gain was achieved in the overall breeding objective in a pig breeding program using genomic selection (GS) compared to a conventional breeding program, however, some traits achieved larger gain than other traits. GS scenarios based on different reference population sizes were evaluated. The scenarios were compared using a deterministic simulation model to predict genetic gain in scenarios with and without using genomic information as an additional information source. All scenarios were compared based on selection accuracy and predicted genetic gain per round of selection for objective traits in both sire and dam lines. The results showed that GS scenarios increased overall response in the breeding objectives by 9% to 56% and 3.5% to 27% in the dam and sire lines, respectively. The difference in response resulted from differences in the size of the reference population. Although all traits achieved higher selection accuracy in GS, traits with limited phenotypic information at the time of selection or with low heritability, such as sow longevity, number of piglets born alive, pre- and post-weaning survival, as well as meat and carcass quality traits achieved the largest additional response. This additional response came at the expense of smaller responses for traits that are easy to measure, such as back fat and average daily gain in GS compared to the conventional breeding program. Sow longevity and drip loss percentage did not change in a favourable direction in GS with a reference population of 500 pigs. With a reference population of 1000 pigs or onwards, sow longevity and drip loss percentage began to change in a favourable direction. Despite the smaller responses for average daily gain and back fat thickness in GS, the overall breeding objective achieved additional gain in GS.

Genetic architecture of white striping in turkeys (Meleagris gallopavo).

White striping (WS) is a myopathy of growing concern to the turkey industry. It is rising in prevalence and has negative consequences for consumer acceptance and the functional properties of turkey meat. The objective of this study was to conduct a genome-wide association study (GWAS) and functional analysis on WS severity. Phenotypic data consisted of white striping scored on turkey breast fillets (N = 8422) by trained observers on a 0-3 scale (none to severe). Of the phenotyped birds, 4667 genotypic records were available using a proprietary 65 K single nucleotide polymorphism (SNP) chip. The SNP effects were estimated using a linear mixed model with a 30-SNP sliding window approach used to express the percentage genetic variance explained. Positional candidate genes were those located within 50 kb of the top 1% of SNP windows explaining the most genetic variance. Of the 95 positional candidate genes, seven were further classified as functional candidate genes because of their association with both a significant gene ontology and molecular function term. The results of the GWAS emphasize the polygenic nature of the trait with no specific genomic region contributing a large portion to the overall genetic variance. Significant pathways relating to growth, muscle development, collagen formation, circulatory system development, cell response to stimulus, and cytokine production were identified. These results help to support published biological associations between WS and hypoxia and oxidative stress and provide information that may be useful for future-omics studies in understanding the biological associations with WS development in turkeys.

Bacterial culture and susceptibility test results for clinical mastitis samples from Australia's subtropical dairy region.

This study aimed to identify the pathogens isolated from the milk of cows with clinical mastitis in the subtropical region of Australia and to determine the antimicrobial susceptibility of these bacteria. Thirty dairy herds in the subtropical dairy region were asked to submit milk samples for the first 5 cases of clinical mastitis each month for 12 mo. Samples underwent aerobic culture, and isolates were identified via MALDI-TOF mass spectrometry. Antimicrobial susceptibility was determined for Escherichia coli, Enterococcus spp., Streptococcus agalactiae, Streptococcus uberis, Streptococcus dysgalactiae, Staphylococcus aureus, and non-aureus staphylococci and mammaliicocci (NASM). Between March 2021 and July 2022, 1,230 milk samples were collected. A positive culture result was recorded for 812 (66%) of the milk samples; from these samples, 909 isolates were obtained, including 49 isolates where no identification was possible. The remaining samples were classified as having no growth (16.8%) or as being contaminated (17.2%). The most common isolates with a MALDI-TOF diagnosis (n = 909) were Strep. uberis (23.6%), followed by the NASM group (15.0%). Farms enrolled in the study were in 3 distinct locations within the subtropical dairy region: North Queensland, Southeast Queensland, and Northern New South Wales. Some variation in isolate prevalence occurred between these 3 locations. We found lower odds of a sample being positive for E. coli in North Queensland (odds ratio [OR]: 0.25; 95% confidence interval [CI]: 0.07-0.87) and higher odds in Southeast Queensland (OR: 4.01; 95% CI: 1.96-8.20) compared with the reference, Northern New South Wales. We further found higher odds of Strep. dysgalactiae in North Queensland (OR: 5.69; 95% CI: 1.85-17.54) and Southeast Queensland compared with Northern New South Wales (OR: 3.99; 95% CI: 1.73-9.22). Although some seasonal patterns were observed, season was not significant for any of the analyzed isolates. Farm-level differences in pathogen profiles were obvious. Overall, clinical mastitis pathogens had low levels of resistance to the antimicrobials tested. This research demonstrates that Strep. uberis and the NASM bacterial group are the most common pathogens causing clinical mastitis in the subtropical dairy region. It highlights the importance of understanding pathogenic causes of mastitis at the farm and regional level for targeted control and therapy.

Growth Rate Distribution and Potential Non-Linear Relationship between Body Weight and Walking Ability in Turkeys.

The aim of this study was to investigate the potential non-linear relationship between growth and walking ability (WA). The phenotypic data included body weights at 12 and 20 weeks and WA at 20 weeks of age measured on 276,059 male turkeys. The growth rate at three age periods (0 to 12, 12 to 20 and 0 to 20 weeks) was calculated. Each bird was assigned to one of the quartiles of the growth rate distribution for each age period. Between the first and fourth quartiles, the incidence of score 1 (bad WA) increased by 31, 18, and 33% for the first, second, and third age periods, respectively. For good WA (scores 4, 5, and 6), the incidence decreased by 55, 66, and 72% between the first and fourth quartiles for the first, second, and third age periods, respectively. Estimates of heritability of WA ranged between 0.18 and 0.26. The genetic correlations between adjacent growth rate quartiles were high and decayed as the interval between quartiles increased. The magnitude of the variation in the incidence of walking scores and genetic correlations across the growth rate quartiles point towards a non-linear relationship between growth and mobility suggesting other factors may affect walking ability.

Bacterial culture and antimicrobial susceptibility results from bovine milk samples submitted to four veterinary diagnostic laboratories in Australia from 2015 to 2019.

A 5-year retrospective study was conducted to describe the mastitis-causing organisms isolated from bovine milk samples submitted to four veterinary diagnostic laboratories in Australia. The aim of this study was to identify temporal, geographical, and seasonal patterns of occurrence for the organisms and report the in vitro susceptibility of the most common mastitis-causing pathogens. In total, 22,102 milk samples were submitted between 2015 and 2019. The results were reported as positive growth for at least one significant organism (n = 11,407; 51.6%), no growth (n = 5,782; 26.2%), and mixed/contaminated growth (n = 4,913; 22.2%). Culture results for no growth, gram-negative bacteria, and eukaryotic organisms were combined for each region, and they were accounted for between 23 and 46% of submissions. These results represent a subset of mastitis cases for which the antibiotic treatment may not be warranted. A total of 11,907 isolates were cultured from 11,407 milk samples. The most common isolated organisms were Streptococcus uberis [41.3%; 95% confidence interval (CI): 40.4-42.1%] and Staphylococcus aureus (23.6%; 95% CI: 22.8-24.3%). For S. uberis and S. aureus, there was an association between a positive culture result and the dairy region. All regions except for the Sub-tropical Dairy region were more likely to culture S. uberis compared to the reference, Dairy NSW (P < 0.001). Similarly, for S. aureus, a positive culture result was more likely in all other dairy regions compared to Dairy NSW (P < 0.001). The LISA cluster analysis identified differences between High-High (hotspot) postcodes for S. aureus and S. uberis throughout all the analyzed dairy regions. These results highlight the need for further investigations into specific risk factors, such as environmental factors and herd-level predictors, which may have influenced the observed regional variations. Common mastitis-causing pathogens showed overall good susceptibility to a range of antimicrobials used in the treatment of mastitis. On-going surveillance of mastitis-causing pathogens and their antimicrobial susceptibilities will facilitate targeted mastitis control and treatment programs.

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.

The usual suspects: Co-occurrence of integument injuries in turkey flocks.

The present study investigated the prevalence and co-occurrence of integument injuries in Canadian turkeys. Participating farmers scored 30 birds in their flock for integument injuries to the head/neck (HN), back/tail (BT), and footpad (FP) using a simplified scoring system (0: no sign of injury, 1: mild injury, 2: severe injury). Information from 62 flocks was used to calculate the prevalence of any (score ≥1) and severe (score 2) injuries on a flock- and individual-level. Chi-square analyses were performed to determine the likelihood of integument injury co-occurrence. The prevalence of each type of injury varied between flocks. While the majority of flocks reported injuries, the within-flock prevalence was relatively low and largely comprised of mild cases (score 1). Given their higher prevalence, the data indicate that FP injuries are overall more widespread and more severe among Canadian turkey flocks than HN and BT injuries. Co-occurrence of different integument injuries was observed in 7% of birds and 58.1% of flocks reported at least one bird with co-occurring injury types. Despite the low prevalence of multiple injury types, birds with one type of injury were more likely to present with other injury types. Indeed, birds with HN injuries were 4 times more likely to have BT injuries, and birds with FP injuries were 1.5 times more likely to have BT injuries compared to birds that do not have these respective injuries. The data increase our understanding of the co-occurrence of these common integument injuries which can help inform a holistic management approach to rear turkeys with healthy skin and feather cover.

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.

Describing the relationships among meat quality traits in domestic turkey (Meleagris gallopavo) populations.

The presence of meat quality defects is increasing in the turkey industry. While the main strategy for mitigating these issues is through improved housing, management, and slaughter conditions, it may be possible to incorporate meat quality into a turkey breeding strategy with the intent to improve meat quality. Before this can occur, it is important to describe the current state of turkey meat quality as well as the correlations among the different meat quality traits and important production traits. The main objective of the present study was to provide a descriptive analysis of 8 different meat quality traits for turkey breast meat from 3 different purebred lines (A, B, and C), and their correlation with a selection of production traits. Using a total of 7,781 images, the breast meat (N = 590-3,892 birds depending on trait) was evaluated at 24 h postmortem for color (L*, a*, b*), pH, and physiochemical characteristics (drip loss, cooking loss, shear force). Descriptive statistics (mean and standard deviation) and Pearson correlations were computed to describe the relationships among traits within each genetic line. A one-factor ANOVA and post hoc t-test were conducted for each trait and between each of the genetic lines. We found significant differences between genetic lines for some color traits (L* and a*), pHinitial, drip loss, and cooking loss. The lightest line in weight (line B) had meat that was the lightest (L*) in color. The heaviest line (line C) had meat that was less red (a*) with a higher pHinitial and greater cooking loss. Unfavorable correlations between production traits and meat quality were also found for each of the genetic lines where increases in production (e.g., body weight, growth rate) resulted in meat that was lighter and redder in color and in some cases (line B and C), with an increased moisture loss. The results of this study provide an important benchmark for turkey meat quality in purebred lines and provide an updated account of the relationships between key production traits and meat quality. Although the magnitude of these correlations is low, their cumulative effect on meat quality can be more significant especially with continued selection pressure on growth and yield.

Environmental variation effects fertility in tropical beef cattle.

The northern Australia beef cattle industry operates in harsh environmental conditions which consistently suppress female fertility. To better understand the environmental effect on cattle raised extensively in northern Australia, new environmental descriptors were defined for 54 commercial herds located across the region. Three fertility traits, based on the presence of a corpus luteum at 600 d of age, indicating puberty, (CL Presence, n = 25,176), heifer pregnancy (n = 20,989) and first lactation pregnancy (n = 10,072) were recorded. Temperature, humidity, and rainfall were obtained from publicly available data based on herd location. Being pubertal at 600 d (i.e. CL Presence) increased the likelihood of success at heifer pregnancy and first lactation pregnancy (P < 0.05), underscoring the importance of early puberty in reproductive success. A temperature humidity index (THI) of 65-70 had a significant (P < 0.05) negative effect on first lactation pregnancy rate, heifer pregnancy and puberty at 600 d of age. Area under the curve of daily THI was significant (P < 0.05) and reduced the likelihood of pregnancy at first lactation and puberty at 600 days. Deviation from long-term average rainfall was not significant (P < 0.05) for any trait. Average daily weight gain had a significant and positive relationship (P < 0.05) for heifer and first lactation pregnancy. The results indicate that chronic or cumulative heat load is more determinantal to reproductive performance than acute heat stress. The reason for the lack of a clear relationship between acute heat stress and reproductive performance is unclear but may be partially explained by peak THI and peak nutrition coinciding at the same time. Sufficient evidence was found to justify the use of average daily weight gain and chronic heat load as descriptors to define an environmental gradient.

Cyclosporin A Prevents Ovarian Graft Rejection, and Permits Normal Germ Cell Maturation Within the First 5 Weeks Post-transplantation, in the Domestic Turkey (Meleagris gallopavo).

Biobanked ovaries collected from recently hatched poults can only be revived through transplantation, using a recipient bird. The main hurdle in transplantation is preventing graft rejection, which appears as lymphocytic infiltration upon histologic evaluation of the graft. In this study, the condition of the transplants [immunological compatibility (auto- vs. allotransplants), donor age, time in holding media, and temperature of holding media] and treatment of recipient poults with varying immunosuppressants [mycophenolate mofetil (MFM), cyclophosphamide (CY), and cyclosporin A (CsA)] were studied to determine which factors could reduce lymphocytic infiltration, during the first 35 days post-transplantation. Lymphocytic infiltration was determined via cytoplasmic CD3 (T cell) and nuclear PAX5 (B cell) expression. There was no significant difference in the percent of cytoplasmic CD3 or nuclear PAX5 immunostained area between the unoperated group and the autotransplants, by 6 days post-transplantation. However, the allotransplants had more (P < 0.05) positive cytoplasmic and nuclear immunostained areas compared to autotransplants, irrespective of donor age, time in holding media or temperature of the media. By 14 days post-transplantation, the CsA 25 and 50 mg/kg/day treatment groups had less (P < 0.05) CD3 and PAX5 positive areas in their allotransplants, compared to the unsuppressed group. At 35 days post-transplantation, the CsA 25 mg/kg/day allotransplant group also had less (P < 0.05) CD3 and PAX5 positive areas compared to the unsuppressed group. The CsA 25 mg/kg/day transplants also had a similar ovarian follicular size compared to the unoperated group, although they contained fewer (P < 0.05) follicles based on follicular density. Donor age, duration in holding media, temperature of media, and treatment of recipients with MFM or CY had no effect on reducing lymphocytic infiltration. However, immunological compatibility was associated with decreased lymphocytic infiltration, as autotransplants had little lymphocytic infiltration. Treatment of recipients with CsA at 25 mg/kg/day was also associated with reduced lymphocytic infiltration and allowed transplants to develop normally during the first 35 days post transplantation.

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.

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.

Influence of Post Mortem Muscle Activity on Turkey Meat Quality.

Wing flapping and body movement can occur during the slaughter of poultry. Wing movement and flapping are driven primarily by the breast muscles (Pectoralis major and minor), and this muscle activity may have implications for meat quality. The objective of this study was to evaluate turkey post mortem activity during slaughter at a commercial poultry processing plant. Post mortem activity (during bleeding) was scored on 5,441 male turkeys, from six different genetic lines, using a 1-4 scale from none to severe wing flapping. Meat quality was measured on these birds in terms of pH (initial, ultimate, delta or change), color (L*, a*, b*), and physiochemical traits (drip loss, cooking loss, shear force). Linear mixed models were used to analyze the effect of activity (score 1-4), genetic line (A-F), and season (summer vs. autumn) on the nine meat quality traits. Post mortem activity influenced a*, drip loss, and shear force although the magnitude of the effects was small. There was an effect (P < 0.05) of genetic line on all the meat quality traits except for L*, cooking loss, and shear force. In general, larger, faster-growing lines had higher pH, but the relationship between the lines for the other traits is not as clear. Season affected all the meat quality traits, except for pHdelta, with meat having a higher pH, L*, b*, drip loss, cooking loss, and shear force in the summer. This study provides an exploratory assessment of post mortem activity in turkeys and identifies meat quality traits which are most affected while also accounting for the effects of genetic line and season. Although identified effect sizes are small, the cumulative effect on turkey meat quality may be more substantial.

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.

A new haplotype-resolved turkey genome to enable turkey genetics and genomics research.

BACKGROUND: The domesticated turkey (Meleagris gallopavo) is a species of significant agricultural importance and is the second largest contributor, behind broiler chickens, to world poultry meat production. The previous genome is of draft quality and partly based on the chicken (Gallus gallus) genome. A high-quality reference genome of M. gallopavo is essential for turkey genomics and genetics research and the breeding industry. RESULTS: By adopting the trio-binning approach, we were able to assemble a high-quality chromosome-level F1 assembly and 2 parental haplotype assemblies, leveraging long-read technologies and genome-wide chromatin interaction data (Hi-C). From a total of 40 chromosomes (2n = 80), we captured 35 chromosomes in a single scaffold, showing much improved genome completeness and continuity compared to the old assembly build. The 3 assemblies are of higher quality than the previous draft quality assembly and comparable to the chicken assemblies (GRCg7) shown by the largest contig N50 (26.6 Mb) and comparable BUSCO gene set completeness scores (96-97%). Comparative analyses confirm a previously identified large inversion of around 19 Mbp on the Z chromosome not found in other Galliformes. Structural variation between the parent haplotypes was identified, which poses potential new target genes for breeding. CONCLUSIONS: We contribute a new high-quality turkey genome at the chromosome level, benefiting turkey genetics and other avian genomics research as well as the turkey breeding industry.

Meta-analysis to predict the effects of temperature stress on meat quality of poultry.

Temperature stress (TS) is a significant issue in poultry production, which has implications for animal health and welfare, productivity, and industry profitability. Temperature stress, including both hot (heat stress) and cold conditions (cold stress), is associated with increased incidence of meat quality defects such as pale, soft, and exudative (PSE) and dark, firm, and dry (DFD) meat costing poultry industries millions of dollars annually. A meta-analysis was conducted to determine the effect of ambient TS on meat quality parameters of poultry. Forty-eight publications which met specific criteria for inclusion were identified through a systematic literature review. Temperature stress was defined by extracting 2 descriptors for each treatment mean from the chosen studies: (1) temperature imposed for the experimental treatments (°C) and duration of temperature exposure. Treatment duration was categorized for analysis into acute (≤24 h) or chronic (>24 h) treatments. Meat quality parameters considered were color (L*-a*-b* scheme), pH (initial and ultimate), drip loss, cooking loss, and shear force. Linear mixed model analysis, including study as a random effect, was used to determine the effect of treatment temperature and duration on meat quality. Model evaluation was conducted by performing a k-fold cross-validation to estimate test error, and via assessment of the root mean square prediction error (RMSPE), and concordance correlation coefficient (CCC). Across both acute and chronic durations, treatment temperature was found to have a significant effect on all studied meat quality parameters. As treatment temperature increased, meat demonstrated characteristics of PSE meat and, as temperature decreased, meat demonstrated characteristics of DFD meat. The interaction between treatment temperature and duration was significant for most traits, however, the relative impact of treatment duration on the studied traits was inconsistent. Acute TS had a larger effect than chronic TS on ultimate pH, and chronic stress had a more considerable impact on color traits (L* and a*). This meta-analysis quantifies the effect of ambient TS on poultry meat quality. However, quantitative effects were generally small, and therefore may or may not be of practical significance from a processing perspective.

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.

The Effect of Egg Laying on Feather and Plasma Corticosterone Concentrations in Turkey (Meleagris gallopavo) Hens.

Phenological differences in energy demand (i.e., reproductive status) might influence the measurement of corticosterone. The objective of this study was to compare corticosterone concentrations in feathers (FCORT) and plasma (PCORT) for turkey hens before and during egg laying. Secondary feathers 1 and 3, and a plasma sample were collected from 50 hens at 30 weeks (before egg laying) from two purebred lines. The hens were reexamined during lay (45 weeks) to collect regrown feathers and plasma samples. Corticosterone concentrations were measured using an ELISA. Linear mixed models were used to assess the effect of genetic line (A vs. B) and period (pre-lay vs. lay) on FCORT and PCORT levels. An increase in FCORT during lay was detected for line B (p < 0.0001), but not line A (p = 0.3076). An increase in FCORT during lay was detectable in both feather types, but there was a difference between secondary 1 and 3 in FCORT concentration within each line studied. Conversely, PCORT decreased between the pre-lay and lay periods for both lines, although the decrease was more substantial for line A (p < 0.0001). Differences in metabolic investment in egg production between the two genetic lines may explain the different FCORT response during lay. The results from this study provide insight into how periods of high energy demand may influence corticosterone which should be considered when interpreting results.

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.