Search

Traits related to calving have a significant impact on animal welfare and farm profitability in dairy production systems. Identifying genomic regions associated with calving traits could contribute to refining dairy cattle breeding programs and management practices in the dairy industry. Therefore, the primary objectives of this study were to estimate genetic parameters and perform GWAS and functional enrichment analyses for stillbirth, gestation length, calf size, and calving ease traits in North American Jersey cattle. A total of 40,503 animals with phenotypic records and 5,398 animals genotyped for 45,101 SNPs were included in the analyses. Genetic parameters were estimated based on animal models and Bayesian methods. The effects of SNPs were estimated using the single-step GBLUP method. The heritability (SE) estimates ranged from 0.01 (0.01) for stillbirths in heifers to 0.11 (0.01) for gestation length in cows. The genetic correlations ranged from -0.58 (0.11) between calving ease and stillbirths in heifers to 0.44 (0.14) between calving ease and calf size in cows. Calving ease showed the highest genetic correlation between heifers and cows, 0.8 (0.22) respectively. The candidate genes identified, including MTHFR, SERPINA5, IGFBP3, and ZRANB1, are involved in key biological processes and metabolic pathways related to the studied traits. Reducing environmental variation and identifying novel indicators of reproduction traits in the Jersey breed are needed given the low heritability estimates for most traits evaluated in this study. In conclusion, this study provides a characterization of the genetic background of calving-related traits in Jersey cattle. The estimates obtained can be used to improve or build selection indexes in Jersey cattle breeding programs in North America., (© 2024, The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Body conformation traits are directly associated with longevity, fertility, health, and workability in dairy cows and have been under direct genetic selection for many decades in various countries worldwide. The main objectives of this study were to perform genome-wide association studies and functional enrichment analyses for fourteen body conformation traits using imputed high-density single nucleotide polymorphism (SNP) genotypes. The traits analyzed include body condition score (BCS), body depth (BD), bone quality (BQ), chest width (CW), dairy capacity (DC), foot angle (FAN), front legs view (FLV), heel depth (HDe), height at front end (HFE), locomotion (LOC), rear legs rear view (RLRV), rear legs side view (RLSV), stature (ST), and a composite feet and legs score index (FL) of Holstein cows scored in Canada. De-regressed estimated breeding values from a dataset of 39,135 North American Holstein animals were used as pseudo-phenotypes in the genome-wide association analyses. A mixed linear model was used to estimate the SNP effects, which ranged from 239,533 to 242,747 markers depending on the trait analyzed. Genes and quantitative trait loci (QTL) located up to 100 Kb upstream or downstream of the significant SNPs previously cited in the Animal QTLdb were detected, and functional enrichment analyses were performed for the candidate genes identified for each trait. A total of 20, 60, 13, 17, 27, 8, 7, 19, 4, 10, 13, 15, 7, and 13 genome-wide statistically significant SNPs for Bonferroni correction based on independent chromosomal segments were identified for BCS, BD, BQ, CW, DC, FAN, FLV, HDe, HFE, LOC, RLRV, RLSV, ST, and FL, respectively. The significant SNPs were located across the whole genome, except on chromosomes BTA24, BTA27, and BTA29. Four markers (for BCS, BD, HDe, and RLRV) were statistically significant when considering a much stricter threshold for the Bonferroni correction for multiple tests. Moreover, the genomic regions identified overlap with various QTL previously reported for the trait groups of exterior, health, meat and carcass, milk, production, and reproduction. The functional enrichment analyses revealed 27 significant gene ontology terms. These enriched genomic regions harbor various candidate genes previously reported as linked to bone development, metabolism, as well as infectious and immunological diseases., Competing Interests: Author TC was employed by the company PEAK. FM was employed by the company Lactanet Canada. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Sousa Junior, Pinto, Cruz, Oliveira Junior, Oliveira, Chud, Pedrosa, Miglior, Schenkel and Brito.)

Temperament (docility) is a key breeding goal in the cattle industry due to its direct relationship with animal welfare, cattle handler's safety and animal productivity. Over the past six decades, numerous studies have reported heritability estimates for temperament-related traits in cattle populations ranging from low to high values. Therefore, the primary objective of this study was to perform a comprehensive systematic review with meta-analysis to obtain weighted estimates of heritability for temperament-related traits in worldwide cattle populations. After data editing and quality control, 106 studies were included in the systematic review, of which 29.2% and 70.8% reported estimates of heritability for temperament-related traits in dairy and beef cattle populations, respectively. Meta-analyses were performed for 95 heritability estimates using a random model approach. The weighted heritability estimates were as follow: (a) flight score at weaning = 0.23 (95% CI: 0.15-0.32); (b) flight speed at weaning = 0.30 (95% CI: 0.26-0.33); (c) joint analysis of flight speed and flight score at weaning = 0.27 (95% CI: 0.22-0.31); (d) flight speed at yearling = 0.26 (95% CI: 0.21-0.30); (e) joint analysis of flight speed at weaning and yearling = 0.27 (95% CI: 0.24-0.30); (f) movement score = 0.12 (95% CI: 0.08-0.15); (g) crush score at weaning = 0.21 (95% CI: 0.17-0.25); (h) pen score at weaning = 0.27 (95% CI: 0.19-0.34); (i) pen score at yearling = 0.20 (95% CI: 0.17-0.23); (j) joint analysis of pen score at weaning and yearling = 0.22 (95% CI: 0.18-0.26); (k) cow's aggressiveness at calving = 0.10 (95% CI: 0.01-0.19); (l) general temperament = 0.13 (95% CI: 0.06-0.19); (m) milking temperament = 0.16 (95% CI: 0.11-0.21); and (n) joint analysis of general and milking temperament = 0.14 (95% CI: 0.11-0.18). The heterogeneity index ranged from 0% to 77%, and the Q-test was significant (p < 0.05) for four single-trait meta-analyses. In conclusion, temperament is moderately heritable in beef cattle populations, and flight speed at weaning had the highest weighted heritability estimate. Moreover, between-study heterogeneity was low or moderate in beef cattle traits, suggesting reasonable standardization across studies. On the other hand, low-weighted heritability and high between-study heterogeneity were estimated for temperament-related traits in dairy cattle, suggesting that more studies are needed to better understand the genetic inheritance of temperament in dairy cattle populations., (© 2024 The Author(s). Journal of Animal Breeding and Genetics published by John Wiley & Sons Ltd.)

Udder conformation is directly related to milk yield, cow health, workability, and welfare. Automatic milking systems (AMS, also known as milking robots) have become popular worldwide, and the number of dairy farms adopting these systems has increased considerably over the past years. In each milking visit, AMS record the location of the 4 teats as Cartesian coordinates in an xyz plan, which can then be used to derive udder conformation traits. Because AMS generate a large amount of data for individual cows per milking visit, they can contribute to an accurate assessment of important traits such as udder conformation without the addition of human classifier errors (in subjective scoring systems). Therefore, the primary objectives of this study were to estimate genomic-based genetic parameters for udder conformation traits derived from AMS records in North American Holstein cattle and to assess the genetic correlation between the derived traits for evaluating the feasibility of multitrait genomic selection for breeding cows that are more suitable for milking in AMS. The Cartesian teat coordinates measured during each milking visit were collected by 36 milking robots in 4,480 Holstein cows from 2017 to 2021, resulting in 5,317,488 records. A total of 4,118 of these Holstein cows were also genotyped for 57,600 SNPs. Five udder conformation traits were derived: udder balance (UB, mm), udder depth (UD, mm), front teat distance (FTD, mm), rear teat distance (RTD, mm), and distance front-rear (DFR, mm). In addition, 2 traits directly related to cow productivity in the system were added to the study: daily milk yield (DY) and milk electroconductivity (EC; as an indicator of mastitis). Variance components and genetic parameters for UB, UD, FTD, RTD, DFR, DY, and EC were estimated based on repeatability animal models. The estimates of heritability (± SE) for UB, UD, FTD, RTD, DFR, DY, and EC were 0.41 ± 0.02, 0.79 ± 0.01, 0.53 ± 0.02, 0.40 ± 0.02, 0.65 ± 0.02, 0.20 ± 0.02, and 0.46 ± 0.02, respectively. The repeatability estimates (± SE) for UB, UD, FTD, RTD, and DFR were 0.82 ± 0.01, 0.93 ± 0.01, 0.87 ± 0.01, 0.83 ± 0.01, and 0.88 ± 0.01, respectively. The strongest genetic correlations were observed between FTD and RTD (0.54 ± 0.03), UD and DFR (-0.47 ± 0.03), DFR and FTD (0.32 ± 0.03), and UD and FTD (-0.31 ± 0.03). These results suggest that udder conformation traits derived from Cartesian coordinates from AMS are moderately to highly heritable. Furthermore, the moderate genetic correlations between these traits should be considered when developing selection subindexes. The most relevant genetic correlations between traits related to cow milk productivity and udder conformation traits were between UD and EC (-0.25 ± 0.03) and between DFR and DY (0.30 ± 0.04), in which both genetic correlations are favorable. These findings will contribute to the design of genomic selection schemes for improving udder conformation in North American Holstein cattle, especially in precision dairy farms., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

The linear conformation of animals exerts an influence on health, reproduction, production, and welfare, in addition to longevity, which directly affects the profitability of milk-producing farms. The objectives of this study were (1) to perform genome-wide association studies (GWASs) of conformation traits, namely the Rump, Feet and Legs, Mammary System, Dairy Strength, and Final Classification traits, and (2) to identify genes and related pathways involved in physiological processes associated with conformation traits in Brazilian Holstein cattle. Phenotypic and genotypic data from 2339 Holstein animals distributed across the states of Rio Grande do Sul, Paraná, São Paulo, and Minas Gerais were used. The genotypic data were obtained with a 100 K SNP marker panel. The single-step genome-wide association study (ssGWAS) method was employed in the analyses. Genes close to a significant SNP were identified in an interval of 100 kb up- and downstream using the Ensembl database available in the BioMart tool. The DAVID database was used to identify the main metabolic pathways and the STRING program was employed to create the gene regulatory network. In total, 36 significant SNPs were found on 15 chromosomes; 27 of these SNPs were linked to genes that may influence the traits studied. Fourteen genes most closely related to the studied traits were identified, as well as four genes that showed interactions in important metabolic pathways such as myogenesis, adipogenesis, and angiogenesis. Among the total genes, four were associated with myogenesis ( TMOD2 , TMOD3 , CCND2 , and CTBP2 ), three with angiogenesis ( FGF23 , FGF1 , and SCG3 ), and four with adipogenesis and body size and development ( C5H12orf4 , CCND2 , EMILIN1 , and FGF6 ). These results contribute to a better understanding of the biological mechanisms underlying phenotypic variability in conformation traits in Brazilian Holstein cattle.

Background: A heterozygous-enriched region (HER) is a genomic region with high variability generated by factors such as balancing selection, introgression, and admixture processes. In this study, we evaluated the genomic background of HERs and the impact of different parameters (i.e., minimum number of SNPs in a HER, maximum distance between two consecutive SNPs, minimum length of a HER, maximum number of homozygous allowed in a HER) and scenarios [i.e., different SNP panel densities and whole-genome sequence (WGS)] on the detection of HERs. We also compared HERs characterized in Holstein cattle with those identified in Angus, Jersey, and Norwegian Red cattle using WGS data., Results: The parameters used for the identification of HERs significantly impact their detection. The maximum distance between two consecutive SNPs did not impact HERs detection as the same average of HERs (269.31 ± 787.00) was observed across scenarios. However, the minimum number of markers, maximum homozygous markers allowed inside a HER, and the minimum length size impacted HERs detection. For the minimum length size, the 10 Kb scenario showed the highest average number of HERs (1,364.69 ± 1,483.64). The number of HERs decreased as the minimum number of markers increased (621.31 ± 1,271.83 to 6.08 ± 21.94), and an opposite pattern was observed for the maximum homozygous markers allowed inside a HER (54.47 ± 195.51 to 494.89 ± 1,169.35). Forty-five HER islands located in 23 chromosomes with high Tajima's D values and differential among the observed and estimated heterozygosity were detected in all evaluated scenarios, indicating their ability to potentially detect regions under balancing selection. In total, 3,440 markers and 28 genes previously related to fertility (e.g., TP63, ZSCAN23, NEK5, ARHGAP44), immunity (e.g., TP63, IGC, ARHGAP44), residual feed intake (e.g., MAYO9A), stress sensitivity (e.g., SERPINA6), and milk fat percentage (e.g., NOL4) were identified. When comparing HER islands among breeds, there were substantial overlaps between Holstein with Angus (95.3%), Jersey (94.3%), and Norwegian Red cattle (97.1%), indicating conserved HER across taurine breeds., Conclusions: The detection of HERs varied according to the parameters used, but some HERs were consistently identified across all scenarios. Heterozygous genotypes observed across generations and breeds appear to be conserved in HERs. The results presented could serve as a guide for defining HERs detection parameters and further investigating their biological roles in future studies., (© 2024. The Author(s).)

Identifying genome-enabled methods that provide more accurate genomic prediction is crucial when evaluating complex traits such as dairy cow behavior. In this study, we aimed to compare the predictive performance of traditional genomic prediction methods and deep learning algorithms for genomic prediction of milking refusals (MREF) and milking failures (MFAIL) in North American Holstein cows measured by automatic milking systems (milking robots). A total of 1,993,509 daily records from 4,511 genotyped Holstein cows were collected by 36 milking robot stations. After quality control, 57,600 SNPs were available for the analyses. Four genomic prediction methods were considered: Bayesian least absolute shrinkage and selection operator (LASSO), multiple layer perceptron (MLP), convolutional neural network (CNN), and GBLUP. We implemented the first 3 methods using the Keras and TensorFlow libraries in Python (v.3.9) but the GBLUP method was implemented using the BLUPF90+ family programs. The accuracy of genomic prediction (mean square error) for MREF and MFAIL was 0.34 (0.08) and 0.27 (0.08) based on LASSO, 0.36 (0.09) and 0.32 (0.09) for MLP, 0.37 (0.08) and 0.30 (0.09) for CNN, and 0.35 (0.09) and 0.31(0.09) based on GBLUP, respectively. Additionally, we observed a lower reranking of top selected individuals based on the MLP versus CNN methods compared with the other approaches for both MREF and MFAIL. Although the deep learning methods showed slightly higher accuracies than GBLUP, the results may not be sufficient to justify their use over traditional methods due to their higher computational demand and the difficulty of performing genomic prediction for nongenotyped individuals using deep learning procedures. Overall, this study provides insights into the potential feasibility of using deep learning methods to enhance genomic prediction accuracy for behavioral traits in livestock. Further research is needed to determine their practical applicability to large dairy cattle breeding programs., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Selection for resilience indicator (RIND) traits in Holstein cattle is becoming an important breeding objective as the worldwide population is expected to be exposed to increased environmental stressors due to both climate change and changing industry standards. However, genetic correlations between RIND and productivity indicator (PIND) traits, which are already being selected for and have the most economic value, are often unfavorable. As a result, it is necessary to fully understand these genetic relationships when incorporating novel traits into selection indices, so that informed decisions can be made to fully optimize selection for both groups of traits. In the past 2 decades, there have been many estimates of RIND traits published in the literature, albeit in small populations. To provide valuable pooled summary estimates, a random-effects meta-analysis was conducted for heritability and genetic correlation estimates for PIND and RIND traits in worldwide Holstein cattle. In total, 926 heritability estimates for 9 PIND and 27 RIND traits, along with 362 estimates of genetic correlation (PIND × RIND traits) were collected. Resilience indicator traits were grouped into the following subgroups: Metabolic Diseases, Hoof Health, Udder Health, Fertility, Heat Tolerance, Longevity, and Other. Pooled estimates of heritability for PIND traits ranged from 0.201 ± 0.05 (energy-corrected milk) to 0.377 ± 0.06 (protein content), while pooled estimates of heritability for RIND traits ranged from 0.032 ± 0.02 (incidence of lameness, incidence of milk fever) to 0.497 ± 0.05 (measures of body weight). Pooled estimates of genetic correlations ranged from -0.360 ± 0.25 (protein content vs. milk acetone concentration) to 0.535 ± 0.72 (measures of fat-to-protein ratio vs. milk acetone concentration). Additionally, out of 243 potential genetic correlations between PIND and RIND traits that could have been reported, only 40 had enough published estimates to implement the meta-analysis model. Our results confirmed that the interactions between PIND and RIND traits are complex, and all relationships should be evaluated when incorporating novel traits into selection indices. This study provides a valuable reference for breeders looking to incorporate RIND traits for Holstein cattle into selection indices., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Calving interval (CI) measures the number of days between two consecutive calves of the same cow, and previous studies based on phenotype and pedigree data reported low heritability for this trait. However, the genetic architecture of CI in the Nellore breed was not evaluated based on genomic data. Thus, this study aimed to estimate the heritability based on genomic data and carry out a genome-wide association study (GWAS) for CI in the Nellore breed, using 12,599 pedigree records, 5078 CI records, and 3818 animals genotyped with 50k SNPchip panel. Both quality control and GWAS were performed in BLUPF90 family packages, which use the single-step genomic best linear unbiased predictor (ssGBLUP) method. The average CI was 427.6 days, with a standard deviation of 106.9 and a total range of 270-730 days. The heritability estimate was 0.04 ± 0.04. The p-values of GWAS analysis resulted in a genomic inflation factor (lambda) of 1.08. The only significant SNP (rs136725686) at the genome-wide level (p-value = 1.53E-06) was located on BTA13. Other 19 SNPs were significant at the chromosome-wide level, distributed on BTA1, 2, 3, 6, 10, 13, 14, 17, 18, 22, and 26. Functional annotation analysis found thirty-six protein-coding genes, including genes related to cell cycle (RAD21, BCAR3), oocyte function (LHX8, CLPX, UTP23), immune system (TXK, TEC, NFATC2), endocrine function (LRRFIP2, GPR158), estrous cycle (SLC38A7), and female fertility (CCK, LYZL4, TRAK1, FOXP1, STAC). Therefore, CI is a complex trait with small heritability in Nellore cattle, and various biological processes may be involved with the genetic architecture of CI in Nellore cattle., Competing Interests: Declaration of competing interest None., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Hoof diseases are a major welfare and economic issue in the global dairy cattle production industry, which can be minimized through improved management and breeding practices. Optimal genetic improvement of hoof health could benefit from a deep understanding of the genetic background and biological underpinning of indicators of hoof health. Therefore, the primary objectives of this study were to perform genome-wide association studies, using imputed high-density genetic markers data from North American Holstein cattle, for 8 hoof-related traits: digital dermatitis, sole ulcer, sole hemorrhage, white line lesion, heel horn erosion, interdigital dermatitis, interdigital hyperplasia, and toe ulcer, and a hoof health index. De-regressed estimated breeding values from 25,580 Holstein animals were used as pseudo-phenotypes for the association analyses. The genomic quality control, genotype phasing, and genotype imputation were performed using the PLINK (version 1.9), Eagle (version 2.4.1), and Minimac4 software, respectively. The functional genomic analyses were performed using the GALLO R package and the DAVID platform. We identified 22, 34, 14, 22, 28, 33, 24, 43, and 15 significant markers for digital dermatitis, heel horn erosion, interdigital dermatitis, interdigital hyperplasia, sole hemorrhage, sole ulcer, toe ulcer, white line lesion disease, and the hoof health index, respectively. The significant markers were located across all autosomes, except BTA10, BTA12, BTA20, BTA26, BTA27, and BTA28. Moreover, the genomic regions identified overlap with various previously reported quantitative trait loci for exterior, health, meat and carcass, milk, production, and reproduction traits. The enrichment analyses identified 44 significant gene ontology terms. These enriched genomic regions harbor various candidate genes previously associated with bone development, metabolism, and infectious and immunological diseases. These findings indicate that hoof health traits are highly polygenic and influenced by a wide range of biological processes., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Precision livestock farming technologies, such as automatic milk feeding machines, have increased the availability of on-farm data collected from dairy operations. We analyzed feeding records from automatic milk feeding machines to evaluate the genetic background of milk feeding traits and bovine respiratory disease (BRD) in North American Holstein calves. Data from 10,076 preweaning female Holstein calves were collected daily over a period of 6 yr (3 yr included per-visit data), and daily milk consumption (DMC), per-visit milk consumption (PVMC), daily sum of drinking duration (DSDD), drinking duration per-visit, daily number of rewarded visits (DNRV), and total number of visits per day were recorded over a 60-d preweaning period. Additional traits were derived from these variables, including total consumption and duration variance (TCV and TDV), feeding interval, drinking speed (DS), and preweaning stayability. A single BRD-related trait was evaluated, which was the number of times a calf was treated for BRD (NTT). The NTT was determined by counting the number of BRD incidences before 60 d of age. All traits were analyzed using single-step genomic BLUP mixed-model equations and fitting either repeatability or random regression models in the BLUPF90+ suite of programs. A total of 10,076 calves with phenotypic records and genotypic information for 57,019 SNP after the quality control were included in the analyses. Feeding traits had low heritability estimates based on repeatability models (0.006 ± 0.0009 to 0.08 ± 0.004). However, total variance traits using an animal model had greater heritabilities of 0.21 ± 0.023 and 0.23 ± 0.024, for TCV and TDV, respectively. The heritability estimates increased with the repeatability model when using only the first 32 d preweaning (e.g., PVMC = 0.040 ± 0.003, DMC = 0.090 ± 0.009, DSDD = 0.100 ± 0.005, DS = 0.150 ± 0.007, DNRV = 0.020 ± 0.002). When fitting random regression models (RRM) using the full dataset (60-d period), greater heritability estimates were obtained (e.g., PVMC = 0.070 [range: 0.020, 0.110], DMC = 0.460 [range: 0.050, 0.680], DSDD = 0.180 [range: 0.010, 0.340], DS = 0.19 [range: 0.070, 0.430], DNRV = 0.120 [range: 0.030, 0.450]) for the majority of the traits, suggesting that RRM capture more genetic variability than the repeatability model with better fit being found for RRM. Moderate negative genetic correlations of -0.59 between DMC and NTT were observed, suggesting that automatic milk feeding machines records have the potential to be used for genetically improving disease resilience in Holstein calves. The results from this study provide key insights of the genetic background of early in-life traits in dairy cattle, which can be used for selecting animals with improved health outcomes and performance., (The Authors. Published by Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Breeding more resilient animals will benefit the dairy cattle industry in the long term, especially as global climate changes become more severe. Previous studies have reported genetic parameters for various milk yield-based resilience indicators, but the underlying genomic background of these traits remain unknown. In this study, we conducted GWAS of 62,029 SNPs with 4 milk yield-based resilience indicators, including the weighted occurrence frequency (wfPert) and accumulated milk losses (dPert) of milk yield perturbations, and log-transformed variance (LnVar) and lag-1 autocorrelation (r auto ) of daily yield residuals. These variables were previously derived from 5.6 million daily milk yield records from 21,350 lactations (parities 1-3) of 11,787 North American Holstein cows. The average daily milk yield (ADMY) throughout lactation was also included to compare the shared genetic background of resilience indicators with milk yield. The differential genetic background of these indicators was first revealed by the significant genomic regions identified and significantly enriched biological pathways of positional candidate genes, which confirmed the genetic difference among resilience indicators. Interestingly, the functional analyses of candidate genes suggested that the regulation of intestinal homeostasis is most likely affecting resilience derived based on variability in milk yield. Based on Mendelian randomization analyses of multiple instrumental SNPs, we further found an unfavorable causal association of ADMY with LnVar. In conclusion, the resilience indicators evaluated are genetically different traits, and there are causal associations of milk yield with some of the resilience indicators evaluated. In addition to providing biological insights into the molecular regulation mechanisms of resilience derived based on variability in milk yield, this study also indicates the need for developing selection indexes combining multiple indicator traits and taking into account their genetic relationship for breeding more resilient dairy cattle., (The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

This study aimed to assess the predictive ability of parametric models and artificial neural network method for genomic prediction of the following indicator traits of resistance to gastrointestinal nematodes in Santa Inês sheep: packed cell volume (PCV), fecal egg count (FEC), and Famacha© method (FAM). After quality control, the number of genotyped animals was 551 (PCV), 548 (FEC), and 565 (FAM), and 41,676 SNP. The average prediction accuracy (ACC) calculated by Pearson correlation between observed and predicted values and mean squared errors (MSE) were obtained using genomic best unbiased linear predictor (GBLUP), BayesA, BayesB, Bayesian least absolute shrinkage and selection operator (BLASSO), and Bayesian regularized artificial neural network (three and four hidden neurons, BRANN&#95;3 and BRANN&#95;4, respectively) in a 5-fold cross-validation technique. The average ACC varied from moderate to high according to the trait and models, ranging between 0.418 and 0.546 (PCV), between 0.646 and 0.793 (FEC), and between 0.414 and 0.519 (FAM). Parametric models presented nearly the same ACC and MSE for the studied traits and provided better accuracies than BRANN. The GBLUP, BayesA, BayesB and BLASSO models provided better accuracies than the BRANN&#95;3 method, increasing by around 23% for PCV, and 18.5% for FEC. In conclusion, parametric models are suitable for genome-enabled prediction of indicator traits of resistance to gastrointestinal nematodes in sheep. Due to the small differences in accuracy found between them, the use of the GBLUP model is recommended due to its lower computational costs., Competing Interests: Declaration of Competing Interest The authors Luara A. Freitas, Rodrigo P. Savegnago, Anderson A. C. Alves, Nedenia B. Stafuzza, Victor B. Pedrosa, Raquel A. Rocha, Guilherme J. M. Rosa, and Claudia C. P. Paz declare that we don't have any potential conflict of interest including any financial, personal or other relationships with other people or organizations within three years of beginning the work submitted that could inappropriately influence the present work., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Background: Automatic and continuous recording of vaginal temperature (T V ) using wearable sensors causes minimal disruptions to animal behavior and can generate data that enable the evaluation of temporal body temperature variation under heat stress (HS) conditions. However, the genetic basis of T V in lactating sows from a longitudinal perspective is still unknown. The objectives of this study were to define statistical models and estimate genetic parameters for T V in lactating sows using random regression models, and identify genomic regions and candidate genes associated with HS indicators derived from automatically-recorded T V ., Results: Heritability estimates for T V ranged from 0.14 to 0.20 over time (throughout the day and measurement period) and from 0.09 to 0.18 along environmental gradients (EG, - 3.5 to 2.2, which correspond to dew point values from 14.87 to 28.19 ˚C). Repeatability estimates of T V over time and along EG ranged from 0.57 to 0.66 and from 0.54 to 0.77, respectively. T V measured from 12h00 to 16h00 had moderately high estimates of heritability (0.20) and repeatability (0.64), indicating that this period might be the most suitable for recording T V for genetic selection purposes. Significant genotype-by-environment interactions (GxE) were observed and the moderately high estimates of genetic correlations between pairs of extreme EG indicate potential re-ranking of selection candidates across EG. Two important genomic regions on chromosomes 10 (59.370-59.998 Mb) and16 (21.548-21.966 Mb) were identified. These regions harbor the genes CDC123, CAMK1d, SEC61A2, and NUDT5 that are associated with immunity, protein transport, and energy metabolism. Across the four time-periods, respectively 12, 13, 16, and 10 associated genomic regions across 14 chromosomes were identified for T V . For the three EG classes, respectively 18, 15, and 14 associated genomic windows were identified for T V , respectively. Each time-period and EG class had uniquely enriched genes with identified specific biological functions, including regulation of the nervous system, metabolism and hormone production., Conclusions: T V is a heritable trait with substantial additive genetic variation and represents a promising indicator trait to select pigs for improved heat tolerance. Moderate GxE for T V exist, indicating potential re-ranking of selection candidates across EG. T V is a highly polygenic trait regulated by a complex interplay of physiological, cellular and behavioral mechanisms., (© 2023. The Author(s).)

This study aimed to identify genomic regions, pathways, and putative candidate genes associated with resistance to gastrointestinal nematode in Santa Ines sheep. The phenotypic information comprised 5529 records from 1703 naturally infected animals. After genomic data quality control, 37,511 SNPs from 589 animals were available. The weighted single-step approach for genome-wide association study was performed to estimate the SNP effects and variances accounted by 10-SNP sliding windows. Confirming the polygenic nature of the studied traits, 20, 22, 21, and 19 genomic windows that explained more than 0.5% of the additive genetic variance were identified for fecal egg counts (FEC), Famacha© (FAM), packed cell volume (PCV), and total plasma protein (TPP), respectively. A total of 81, 122, 106, and 101 protein-coding genes were found in windows associated with FEC, FAM, PCV, and TPP, respectively. Several protein-coding genes related to the immune system and inflammatory response functions were identified within those genomic regions, such as ADCY9, ADRB2, BRAF, CADM1, CCL20, CD70, CREBBP, FNBP1, HTR4, IL16, IL22, IL26, MAPK8, NDFIP1, NLRC3, PAK5, PLCB1, PLCB4, ROCK1, TEK, TNFRSF12A, and VAV1. Functional enrichment analysis by DAVID tool also revealed many significant (P < 0.05) pathways and Gene Ontology terms that could be related to resistance to gastrointestinal nematode in Santa Ines sheep, such as chemokine signaling pathway (oas04062), cAMP signaling pathway (oas04024), cGMP-PKG signaling pathway (Oas04022), platelet activation (Oas04611), Rap1 signaling pathway (oas04015), and oxidoreductase activity, acting on paired donors, with incorporation or reduction of molecular oxygen (GO:0016705). These results contribute to improving the knowledge of the genetic architecture of resistance to gastrointestinal nematode in Santa Ines sheep., Competing Interests: Declaration of Competing Interest None., (Copyright © 2023 Elsevier B.V. All rights reserved.)

This research communication describes the reproductive and productive parameters and somatic cell count (SCC) of primiparous and multiparous cows from specialized dairy Holstein herds in South region of Brazil, and correlates these parameters using test-day records. A total of 24 011 records of animals from 75 producers obtained between 2017 and 2018 were used. The variables analyzed included milk production, SCC, milk fat, protein and urea nitrogen contents and reproductive characteristics (number of services per conception, service period and percentage of pregnant cows). Data were analyzed using multivariate logistic regression and the statistical differentiation between the classes of SCC and milk production. Milk production, SCC, number of services per conception and service period were all higher in multiparous cows. The percentage of pregnant cows was higher when the SCC was less than 200 000 cells/ml and was higher in primiparous cows. There was no adverse effect of milk production on reproductive parameters in high producing cows (>40 kg milk/d), however, the percentage of pregnant cows with this production level was significantly higher in multiparous cows. In conclusion, the milk production level need not affect the reproduction of specialized dairy cows if the animals are kept under adequate environmental conditions.

This study investigated the age at first calving in Holstein heifers and its impact on various production parameters. A sample of 737 Holstein heifers born between 2015 and 2018 and finishing their first lactations between 2018 and 2020 was included. Cluster analysis revealed three groups based on age at first calving: high precocity, medium precocity and low precocity. Medium-precocity group exhibited the highest 305-day milk yield and peak milk production. Additionally, the same group demonstrated superior mean production per lactation, 305-day milk protein content, and 305-day milk yield. The lowest somatic cell count was found in the low-precocity group. In conclusion, medium-precocity cows showed better results such as higher 305-day milk yield and peak milk production.

The decision of premature culling cows directly impacts the profitability of dairy farms. A comprehensive characterization of the primary causes of culling reasons would greatly improve both management and selection objectives in dairy cattle breeding programs. Therefore, this study aimed to analyze the temporal frequencies of 34 culling reasons in Canadian Holstein cows. After data editing and quality control, records from 3,096,872 cows culled from 9,683 herds spread across Canada were used for the analyses covering the periods from 1996 to 2020. Reproductive issues were the main culling reason accounting for 23.02%, followed by milk production (20.82%), health (20.39%), conformation problems (13.69%), economic factors (13.10%), accidents (5.67%), age-related causes (1.67%), and workability (1.63%). Nearly fifty-eight percent of cows were culled after 47 months of age. The observed frequencies of culling due to economic factors were lower than expected from 1996 to 2014 and higher than expected between 2015 and 2020. Reproduction issues had the highest culling frequencies during fall (24.54%), winter (24.02%), and spring (22.51%), while health issues were the most frequent (22.51%) culling reason in the summer season. Health issues (25.50%) and milk production (27.71%) were the most frequent culling reasons in the provinces of Quebec and Ontario, respectively. Reproductive issues showed the highest frequency across climates based on the Köppen climate classification, except for Csb (Dry-summer subtropical or Mediterranean climate) and Bsk (Middle latitude steppe climate), which correspond to small regions in Canada, where production was the most frequent culling reason (29.42% and 21.56%, respectively). Reproductive and milk performance issues were the two main culling reasons in most ecozones, except in Boreal Shield and Atlantic Marine, where health issues had the highest frequencies (25.12 and 23.75%, respectively). These results will contribute to improving management practices and selective decisions to reduce involuntary culling of Holstein cows., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Society of Animal Science.)

Considering the increasing challenges imposed by climate change and the need to improve animal welfare, breeding more resilient animals capable of better coping with environmental disturbances is of paramount importance. In dairy cattle, resilience can be evaluated by measuring the longitudinal occurrences of abnormal daily milk yield throughout lactation. Aiming to estimate genetic parameters for dairy cattle resilience, we collected 5,643,193 daily milk yield records on automatic milking systems (milking robots) and milking parlors across 21,350 lactations 1 to 3 of 11,787 North American Holstein cows. All cows were genotyped with 62,029 SNPs. After determining the best fitting models for each of the 3 lactations, daily milk yield residuals were used to derive 4 resilience indicators: weighted occurrence frequency of yield perturbations (wfPert), accumulated milk losses of yield perturbations (dPert), and log-transformed variance (LnVar) and lag-1 autocorrelation (r auto ) of daily yield residuals. The indicator LnVar presented the highest heritability estimates (±standard error), ranging from 0.13 ± 0.01 in lactation 1 to 0.15 ± 0.02 in lactation 2; the other 3 indicators had relatively lower heritabilities across the 3 lactations (0.01-0.06). Based on bivariate analyses of each resilience indicator across lactations, stronger genetic correlations were observed between lactations 2 and 3 (0.88-0.96) than between lactations 1 and 2 or 3 (0.34-0.88) for dPert, LnVar, and r auto . For the pairwise comparisons of different resilience indicators within each lactation, dPert had the strongest genetic correlations with wfPert (0.64) and r auto (0.53) in lactation 1, whereas the correlations in lactations 2 and 3 were more variable and showed relatively high standard errors. The genetic correlation results indicated that different resilience indicators across lactations might capture additional biological mechanisms and should be considered as different traits in genetic evaluations. We also observed favorable genetic correlations of these resilience indicators with longevity and Net Merit index, but further biological validation of these resilience indicators is needed. In conclusion, this study provided genetic parameter estimates for different resilience indicators derived from daily milk yields across the first 3 lactations in Holstein cattle, which will be useful when potentially incorporating these traits in dairy cattle breeding schemes., (The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

The number of dairy farms adopting automatic milking systems (AMS) has considerably increased around the world aiming to reduce labor costs, improve cow welfare, increase overall performance, and generate a large amount of daily data, including production, behavior, health, and milk quality records. In this context, this study aimed to (1) estimate genomic-based variance components for milkability traits derived from AMS in North American Holstein cattle based on random regression models; and (2) derive and estimate genetic parameters for novel behavioral indicators based on AMS-derived data. A total of 1,752,713 daily records collected using 36 milking robot stations and 70,958 test-day records from 4,118 genotyped Holstein cows were used in this study. A total of 57,600 SNP remained after quality control. The daily-measured traits evaluated were milk yield (MY, kg), somatic cell score (SCS, score unit), milk electrical conductivity (EC, mS), milking efficiency (ME, kg/min), average milk flow rate (FR, kg/min), maximum milk flow rate (FRM, kg/min), milking time (MT, min), milking failures (MFAIL), and milking refusals (MREF). Variance components and genetic parameters for MY, SCS, ME, FR, FRM, MT, and EC were estimated using the AIREMLF90 software under a random regression model fitting a third-order Legendre orthogonal polynomial. A threshold Bayesian model using the THRGIBBS1F90 software was used for genetically evaluating MFAIL and MREF. The daily heritability estimates across days in milk (DIM) ranged from 0.07 to 0.28 for MY, 0.02 to 0.08 for SCS, 0.38 to 0.49 for EC, 0.45 to 0.56 for ME, 0.43 to 0.52 for FR, 0.47 to 0.58 for FRM, and 0.22 to 0.28 for MT. The estimates of heritability (± SD) for MFAIL and MREF were 0.02 ± 0.01 and 0.09 ± 0.01, respectively. Slight differences in the genetic correlations were observed across DIM for each trait. Strong and positive genetic correlations were observed among ME, FR, and FRM, with estimates ranging from 0.94 to 0.99. Also, moderate to high and negative genetic correlations (ranging from -0.48 to -0.86) were observed between MT and other traits such as SCS, ME, FR, and FRM. The genetic correlation (± SD) between MFAIL and MREF was 0.25 ± 0.02, indicating that both traits are influenced by different sets of genes. High and negative genetic correlations were observed between MFAIL and FR (-0.58 ± 0.02) and MFAIL and FRM (-0.56 ± 0.02), indicating that cows with more MFAIL are those with lower FR. The use of random regression models is a useful alternative for genetically evaluating AMS-derived traits measured throughout the lactation. All the milkability traits evaluated in this study are heritable and have demonstrated selective potential, suggesting that their use in dairy cattle breeding programs can improve dairy production efficiency in AMS., (The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Background: Given the economic relevance of fertility and reproductive traits for the beef cattle industry, investigating their genetic background and developing effective breeding strategies are paramount. Considering their late and sex-dependent phenotypic expression, genomic information can contribute to speed up the rates of genetic progress per year. In this context, the main objectives of this study were to estimate variance components and genetic parameters, including heritability and genetic correlations, for fertility, female precocity, and semen production and quality (andrological attributes) traits in Nellore cattle incorporating genomic information., Results: The heritability estimates of semen quality traits were low-to-moderate, while moderate-to-high estimates were observed for semen morphological traits. The heritability of semen defects ranged from low (0.04 for minor semen defects) to moderate (0.30 for total semen defects). For seminal aspect (SMN&#95;ASPC) and bull reproductive fitness (BULL&#95;FIT), low (0.19) and high (0.69) heritabilities were observed, respectively. The heritability estimates for female reproductive traits ranged from 0.16 to 0.39 for rebreeding of precocious females (REBA) and probability of pregnancy at 14 months (PP14), respectively. Semen quality traits were highly genetically correlated among themselves. Moderate-to-high genetic correlations were observed between the ability to remain productive in the herd until four years of age (stayability; STAY) and the other reproductive traits, indicating that selection for female reproductive performance will indirectly contribute to increasing fertility rates. High genetic correlations between BULL&#95;FIT and female reproductive traits related to precocity (REBA and PP14) and STAY were observed. The genetic correlations between semen quality and spermatic morphology with female reproductive traits ranged from -0.22 (REBA and scrotal circumference) to 0.48 (REBA and sperm vigor). In addition, the genetic correlations between REBA with semen quality traits ranged from -0.23 to 0.48, and with the spermatic morphology traits it ranged from -0.22 to 0.19., Conclusions: All male and female fertility and reproduction traits evaluated are heritable and can be improved through direct genetic or genomic selection. Selection for better sperm quality will positively influence the fertility and precocity of Nellore females. The findings of this study will serve as background information for designing breeding programs for genetically improving semen production and quality and reproductive performance in Nellore cattle., (© 2023. The Author(s).)

Body conformation traits assessed based on visual scores are widely used in Zebu cattle breeding programs. The aim of this study was to identify genomic regions and biological pathways associated with body conformation (CONF), finishing precocity (PREC), and muscling (MUSC) in Nellore cattle. The measurements based on visual scores were collected in 20,807 animals raised in pasture-based systems in Brazil. In addition, 2775 animals were genotyped using a 35 K SNP chip, which contained 31,737 single nucleotide polymorphisms after quality control. Single-step GWAS was performed using the BLUPF90 software while candidate genes were identified based on the Ensembl Genes 69. PANTHER and REVIGO platforms were used to identify key biological pathways and STRING to create gene networks. Novel candidate genes were revealed associated with CONF, including ALDH9A1 , RXRG , RAB2A , and CYP7A1 , involved in lipid metabolism. The genes associated with PREC were ELOVL5 , PID1 , DNER , TRIP12 , and PLCB4 , which are related to the synthesis of long-chain fatty acids, lipid metabolism, and muscle differentiation. For MUSC, the most important genes associated with muscle development were SEMA6A , TIAM2 , UNC5A , and UIMC1 . The polymorphisms identified in this study can be incorporated in commercial genotyping panels to improve the accuracy of genomic evaluations for visual scores in beef cattle.

Purunã is a composite beef cattle breed, developed in Southern Brazil by crossing the Angus, Charolais, Canchim, and Caracu breeds. The goal of this study was to perform the first genetic characterization of the Purunã breed, based on both pedigree and genomic information. For this, 100 randomly selected animals were genotyped, and 11,205 animals born from 1997 to 2019 had pedigree information. The genetic analyses performed were principal component analysis, admixture, phylogenic tree, pedigree and genomic inbreeding, linkage disequilibrium (LD), effective population size (Ne), consistency of the gametic phase, runs of homozygosity (ROH), heterozygosity-enriched regions (HERs), and functional analyses of the ROH and HER regions identified. Our findings indicate that Purunã is more genetically related to the Charolais, Canchim, and Angus breeds than Caracu or Nellore. The levels of inbreeding were shown to be small based on all the metrics evaluated and ranged from -0.009 to 0.029. A low (-0.12-0.31) correlation of the pedigree-based inbreeding compared to all the genomic inbreeding coefficients evaluated was observed. The LD average was 0.031 (±0.0517), and the consistency of the gametic phase was shown to be low for all the breed pairs, ranging from 0.42 to 0.27 to the distance of 20 Mb. The Ne values based on pedigree and genomic information were 158 and 115, respectively. A total of 1,839 ROHs were found, and the majority of them are of small length (<4 Mb). An important homozygous region was identified on BTA5 with pathways related to behavioral traits (sensory perception, detection of stimulus, and others), as well as candidate genes related to heat tolerance ( MY O 1A ), feed conversion rate ( RDH5 ), and reproduction ( AMDHD1 ). A total of 1,799 HERs were identified in the Purunã breed with 92.3% of them classified within the 0.5-1 Mb length group, and 19 HER islands were identified in the autosomal genome. These HER islands harbor genes involved in growth pathways, carcass weight ( SDCBP ), meat and carcass quality ( MT2A ), and marbling deposition ( CISH ). Despite the genetic relationship between Purunã and the founder breeds, a multi-breed genomic evaluation is likely not feasible due to their population structure and low consistency of the gametic phase among them., Competing Interests: Author LD is employed by the company NEOGEN Corporation. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Mulim, Brito, Batista Pinto, Moletta, Da Silva and Pedrosa.)

Background: Genetic progress for fertility and reproduction traits in dairy cattle has been limited due to the low heritability of most indicator traits. Moreover, most of the quantitative trait loci (QTL) and candidate genes associated with these traits remain unknown. In this study, we used 5.6 million imputed DNA sequence variants (single nucleotide polymorphisms, SNPs) for genome-wide association studies (GWAS) of 18 fertility and reproduction traits in Holstein cattle. Aiming to identify pleiotropic variants and increase detection power, multiple-trait analyses were performed using a method to efficiently combine the estimated SNP effects of single-trait GWAS based on a chi-square statistic., Results: There were 87, 72, and 84 significant SNPs identified for heifer, cow, and sire traits, respectively, which showed a wide and distinct distribution across the genome, suggesting that they have relatively distinct polygenic nature. The biological functions of immune response and fatty acid metabolism were significantly enriched for the 184 and 124 positional candidate genes identified for heifer and cow traits, respectively. No known biological function was significantly enriched for the 147 positional candidate genes found for sire traits. The most important chromosomes that had three or more significant QTL identified are BTA22 and BTA23 for heifer traits, BTA8 and BTA17 for cow traits, and BTA4, BTA7, BTA17, BTA22, BTA25, and BTA28 for sire traits. Several novel and biologically important positional candidate genes were strongly suggested for heifer (SOD2, WTAP, DLEC1, PFKFB4, TRIM27, HECW1, DNAH17, and ADAM3A), cow (ANXA1, PCSK5, SPESP1, and JMJD1C), and sire (ELMO1, CFAP70, SOX30, DGCR8, SEPTIN14, PAPOLB, JMJD1C, and NELL2) traits., Conclusions: These findings contribute to better understand the underlying biological mechanisms of fertility and reproduction traits measured in heifers, cows, and sires, which may contribute to improve genomic evaluation for these traits in dairy cattle., (© 2022. The Author(s).)

Myostatin and MyoD family genes play vital roles in myogenesis and this study aimed to identify association of variants in MyoD1 , MyoG , MyF5 , MyF6 , and MSTN genes with meat traits in Santa Inês sheep. A dataset with 44 variants and records of seven meat traits in 192 lambs (pH0, pH24, a*, b*, L*, tenderness assessed by shear force, and water-holding capacity) was used. Single-locus and haplotype association analyses were performed, and the significance threshold was established according to Bonferroni's method. Single-locus analysis revealed two associations at a Bonferroni level, where the variant c.935-185C > G in MyoD1 had an additive effect (-4.31 ± 1.08 N) on tenderness, while the variant c.464 + 185G > A in MyoG had an additive effect (-2.86 ± 0.64) on a*. Additionally, the haplotype replacement GT > AC in MSTN was associated with pH0 (1.26 ± 0.31), pH24 (1.07 ± 0.27), a* (-1.40 ± 0.51), and tenderness (3.83 ± 1.22 N), while the replacement GT > AG in MyoD1 was associated with pH0 (1.43 ± 0.26), pH24 (1.25 ± 0.22), b* (-1.06 ± 0.39), and tenderness (-4.13 ± 1.16 N). Our results have demonstrated that some variants in MyoG , MyF6 , MyoD1 , and MSTN can be associated with physicochemical meat traits in Santa Inês sheep.

The present study aimed to estimate covariance components of milk fatty acids (FA) and to compare the genomic estimated breeding values under general and heat-stress effects. Data consisted of 38,762 test-day records from 6,344 Holstein cows obtained from May 2012 through January 2018 on 4 dairy herds from Brazil. Single-trait repeatability test-day models with random regressions as a function of temperature-humidity index values were used for genetic analyses. The models included contemporary groups, parity order (1-6), and days in milk classes as fixed effects, and general and thermotolerance additive genetic and permanent environmental as random effects. Notably, differences in heritability estimates between environments (general and heat stress) increased (0.03 to 0.06) for unsaturated FA traits, such as unsaturated, monounsaturated, and polyunsaturated, at higher heat-stress levels. In contrast, heritability estimated between environments for saturated FA traits, including saturated FA, palmitic acid (C16:0), and stearic acid (C18:0) did not observe significant differences between environments. In addition, our study revealed negative genetic correlations between general and heat-stress additive genetic effects (antagonistic effect) for the saturated FA, C16:0, C18:0, and C18:1, which ranged from -0.007 to -0.32. Spearman's ranking correlation between genomic estimated breeding values ranged from -0.27 to 0.99. Results indicated a moderate to strong interaction of genotype by the environment for most FA traits comparing a heat-stress environment with thermoneutral conditions. Our findings point out novel opportunities to explore the use of FA milk profile and heat-stress models., (The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)

Background: A decline in the level of genetic diversity in livestock can result in reduced response to selection, greater incidence of genetic defects, and inbreeding depression. In this context, various metrics have been proposed to assess the level of genetic diversity in selected populations. Therefore, the main goals of this study were to: 1) investigate the population structure of 16 cattle populations from 15 different pure breeds or composite populations, which have been selected for different breeds goals; and, 2) identify and compare runs of homozygosity (ROH) and heterozygosity-enriched regions (HER) based on different single nucleotide polymorphism (SNP) panels and whole-genome sequence data (WGS), followed by functional genomic analyses., Results: A total of 24,187 ROH were found across all cattle populations, with 55% classified in the 2-4 Mb size group. Fourteen homozygosity islands were found in five populations, where four ROH islands located on BTA1, BTA5, BTA16, and BTA19 overlapped between the Brahman (BRM) and Gyr (GIR) breeds. A functional analysis of the genes found in these islands revealed candidate genes known to play a role in the melanogenesis, prolactin signaling, and calcium signaling pathways. The correlations between inbreeding metrics ranged from 0.02 to 0.95, where the methods based on homozygous genotypes (F HOM ), uniting of gametes (F UNI ), and genotype additive variance (F GRM ) showed strong correlations among them. All methods yielded low to moderate correlations with the inbreeding coefficients based on runs of homozygosity (F ROH ). For the HER, 3576 runs and 26 islands, distributed across all autosomal chromosomes, were found in regions containing genes mainly related to the immune system, indicating potential balancing selection. Although the analyses with WGS did not enable detection of the same island patterns, it unraveled novel regions not captured when using SNP panel data., Conclusions: The cattle populations that showed the largest amount of ROH and HER were Senepol (SEN) and Montana (MON), respectively. Overlapping ROH islands were identified between GIR and BRM breeds, indicating a possible historical connection between the populations. The distribution and pattern of ROH and HER are population specific, indicating that different breeds have experienced divergent selection processes or different genetic processes., (© 2022. The Author(s).)

Lactation persistency and milk production are among the most economically important traits in the dairy industry. In this study, we explored the association of over 6.1 million imputed whole-genome sequence variants with lactation persistency (LP), milk yield (MILK), fat yield (FAT), fat percentage (FAT%), protein yield (PROT), and protein percentage (PROT%) in North American Holstein cattle. We identified 49, 3991, 2607, 4459, 805, and 5519 SNPs significantly associated with LP, MILK, FAT, FAT%, PROT, and PROT%, respectively. Various known associations were confirmed while several novel candidate genes were also revealed, including ARHGAP35 , NPAS1 , TMEM160 , ZC3H4 , SAE1 , ZMIZ1 , PPIF , LDB2 , ABI3 , SERPINB6 , and SERPINB9 for LP; NIM1K , ZNF131 , GABRG1 , GABRA2 , DCHS1 , and SPIDR for MILK; NR6A1 , OLFML2A , EXT2 , POL D1 , GOT1 , and ETV6 for FAT; DPP6 , LRRC26 , and the KCN gene family for FAT%; CDC14A , RTCA , HSTN , and ODAM for PROT; and HERC3 , HERC5 , LALBA , CCL28 , and NEURL1 for PROT%. Most of these genes are involved in relevant gene ontology (GO) terms such as fatty acid homeostasis, transporter regulator activity, response to progesterone and estradiol, response to steroid hormones, and lactation. The significant genomic regions found contribute to a better understanding of the molecular mechanisms related to LP and milk production in North American Holstein cattle.

The age at first calving has a great economic impact on the beef cattle system and calving at 24 months is an objective of selection for a more efficient herd. However, an age at first calving around 36 months has been observed for Nellore cattle in Brazil. Thus, a genome-wide association study (GWAS) was carried out with 8376 records of age at first calving and 3239 animals genotyped with the GGP-Indicus 35K, which has been developed specifically for Bos taurus indicus. The weighted single-step genomic best linear unbiased prediction method was used, with adjacent SNPs (single nucleotide polymorphisms) in genomic windows of 1.0 Mb. After quality control, 3239 (2161 males and 1078 females) animals genotyped for 30,519 SNPs were used in GWAS analysis. The average and standard deviation of age at first calving were 1041.7 and 140.6 days, respectively. The heritability estimate was 0.10 ± 0.02. The GWAS analysis found seven genomic regions in BTA1, 2, 5, 12, 18, 21, and 24, which explained a total of 11.24% of the additive genetic variance of age at first calving. In these regions were found 62 protein coding genes, and the genes HSD17B2, SERPINA14, SERPINA1, SERPINA5, STAT1, NFATC1, ATP9B, CTDP1, THPO, ECE2, PSMD2, EIF4G1, EIF2B2, DVL3, POLR2H, TMTC2, and GPC6 are possible candidates for age at first birth due their function. Moreover, two molecular functions ("serine-type endopeptidase inhibitor activity" and "negative regulation of endopeptidase activity") were significant, which depend on several serpin genes. The use of a SNP chip developed especially for Bos taurus indicus allowed to find genomic regions for age at first calving, which are close to QTLs previously reported for other reproduction-related traits. Future studies can reveal the causal variants and their effects on reproductive precocity of Nellore cows., Competing Interests: Declaration of competing interest None., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Identifying genes or genomic regions influencing carcass-quality traits such as fatness (FTN) is essential to optimize the genetic selection processes in beef cattle. The aim of this study was to identify genomic regions associated with FTN in Nellore cattle as well as to elucidate the metabolic pathways related to the phenotypic expression. Ultrasound-based measurements of FTN were collected in 11 750 animals, with 39 903 animals in the pedigree file. Additionally, 1440 animals were genotyped using the GGP-indicus 35K SNP panel, which contained 33 623 SNPs after quality control. Twenty genes related to FTN were found on 11 chromosomes, explaining 12.96% of the total additive genetic variance. Gene ontology revealed seven genes: NR1L2, PKD2, GSK3β, EXT1, RAD51B, SORCS1 and DPH6, associated with important processes related to FTN. In addition, novel candidate genes (MAATS1, LYPD1, CDK5RAP2, RAD51B, c13H2Oorf96 and TRAPPC11) were detected and could provide further knowledge to uncover genetic regions associated to carcass fatness in beef cattle., (© 2021 Stichting International Foundation for Animal Genetics.)

Genome-wide association study (GWAS) is a powerful tool to identify candidate genes and genomic regions underlying key biological mechanisms associated with economically important traits. In this context, the aim of this study was to identify genomic regions and metabolic pathways associated with backfat thickness (BFT) and rump fat thickness (RFT) in Nellore cattle, raised in pasture-based systems. Ultrasound-based measurements of BFT and RFT (adjusted to 18 months of age) were collected in 11,750 animals, with 39,903 animals in the pedigree file. Additionally, 1,440 animals were genotyped using the GGP-indicus 35K SNP chip, containing 33,623 SNPs after the quality control. The single-step GWAS analyses were performed using the BLUPF90 family programs. Candidate genes were identified through the Ensembl database incorporated in the BioMart tool, while PANTHER and REVIGO were used to identify the key metabolic pathways and gene networks. A total of 18 genomic regions located on 10 different chromosomes and harbouring 23 candidate genes were identified for BFT. For RFT, 22 genomic regions were found on 14 chromosomes, with a total of 29 candidate genes identified. The results of the pathway analyses showed important genes for BFT, including TBL1XR1, AHCYL2, SLC4A7, AADAT, VPS53, IDH2 and ETS1, which are involved in lipid metabolism, synthesis of cellular amino acids, transport of solutes, transport between Golgi Complex membranes, cell differentiation and cellular development. The main genes identified for RFT were GSK3β, LRP1B, EXT1, GRB2, SORCS1 and SLMAP, which are involved in metabolic pathways such as glycogen synthesis, lipid transport and homeostasis, polysaccharide and carbohydrate metabolism. Polymorphisms located in these candidate genes can be incorporated in commercial genotyping platforms to improve the accuracy of imputation and genomic evaluations for carcass fatness. In addition to uncovering biological mechanisms associated with carcass quality, the key gene pathways identified can also be incorporated in biology-driven genomic prediction methods., (© 2020 Wiley-VCH GmbH.)

Objective: The objective of this study was to evaluate the genetic behavior of a population of Holstein cattle in response to the variation of environmental temperature by analyzing the effects of genotype by environment interaction (GEI) through reaction norms for the somatic cell score (SCS)., Methods: Data was collected for 67,206 primiparous cows from the database of the Paraná Holstein Breeders Association in Brazil, with the aim of evaluating the temperature effect, considered as an environmental variable, distinguished under six gradients, with the variation range found being 17°C to 19.5°C, over the region. A reaction norm model was adopted utilizing the fourth order under the Legendre polynomials, using the mixed models of analysis by the restricted maximum likelihood method by the WOMBAT software. Additionally, the genetic behavior of the 15 most representative bulls was assessed, in response to the changes in the temperature gradient., Results: A mean score of 2.66 and a heritability variation from 0.17 to 0.23 was found in the regional temperature increase. The correlation between the environmental gradients proved to be higher than 0.80. Distinctive genetic behaviors were observed according to the increase in regional temperature, with an observed increase of up to 0.258 in the breeding values of some animals, as well as a reduction in the breeding of up to 0.793, with occasional reclassifications being observed as the temperature increased., Conclusion: Non-relevant GEI for SCS were observed in Holstein cattle herds of southern Brazil. Thus, the inclusion of the temperature effect in the model of genetic evaluation of SCS for the southern Brazilian Holstein breed is not required.

Our objective was to evaluate the genetic merit of Holstein cattle population in southern Brazil in response to variations in the regional temperature by analyzing the genotype by environment interaction using reaction norms. Fat yield (FY) and protein yield (PY) data of 67 360 primiparous cows were obtained from the database of the Paraná Holstein Breeders Association, Brazil (APCBRH). The regional average annual temperature was used as the environmental variable. A random regression model was adopted applying mixed models with Restricted Maximum Likelihood (REML) algorithm using WOMBAT software. The genetic merit of the 15 most representative bulls, depending on the temperature gradient, was evaluated. Heritability ranged from 0.21 to 0.27 for FY and from 0.14 to 0.20 for PY. The genetic correlation observed among the environmental gradients proved to be higher than 0.80 for both traits. Slight reranking of bulls for both traits was detected, demonstrating that non-relevant genotype by environment interaction for FY and PY were observed. Consequently, no inclusion of the temperature effect in the model of genetic evaluation in southern Brazilian Holstein breed is required.

The present study estimated genetic parameters and evaluated the genetic and phenotypic correlations between meat quality characteristics of Nellore cattle evaluated at different anatomical points of the longissimus. Data from 1329 Nellore young bulls were used to evaluate, in the 5th and 12th ribs, marbling score (MAR), shear force (SF), cooking weight losses (CWL) and intramuscular fat (IMF). In addition, the subcutaneous fat thickness was measured at the 12th rib (SFT 12 ) and between the last lumbar and the first sacral vertebrae (SFT LR ), in the separation of loin and round. Results yielded moderate heritability coefficients for evaluated characteristics, except CWL. High genetic correlations (0.61) were found between measurements of SFT 12 and SFT LR . MAR, IMF and SF were evaluated at the 5th and 12th rib. Meat quality and subcutaneous fat thickness measured at different anatomical points of the longissimus are genetically correlated and can be used in genetic selection programs to improve meat quality characteristics in Nellore cattle., Competing Interests: Declaration of Competing Interest The authors declare no conflicts of interest., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Milking speed (MS) and temperament (MT) are 2 workability traits of great importance in dairy cattle production and breeding. This is mainly due to an increased intensification of the worldwide production systems and greater adoption of precision technologies with less human-cattle interaction. Both MS and MT are heritable traits and thus, genomic selection is a promising tool to expedite their genetic progress. However, the genetic architecture and biological mechanisms underlying the phenotypic expression of these traits remain underexplored. In this study, we investigated the association of >5.7 million imputed whole-genome sequence variants with MT and MS in 4,381 and 4,219 North American Holstein cattle, respectively. The statistical analyses were performed using a mixed linear model fitting a polygenic effect. We detected 40 and 35 significant SNPs independently associated with MT and MS, respectively, which were distributed across 26 chromosomes. Eight candidate genes (GRIN3A, KCNJ3, BOSTAUV1R417, BOSTAUV1R419, MAP2K5, KCTD3, GAP43, and LSAMP) were suggested to play an important role in MT as they are involved in biologically relevant pathways, such as glutamatergic synapse, vomeronasal receptor and oxytocin signaling. Within their coding and upstream sequences, we used an independent data set to further detect or validate significantly differentiated SNP between cattle breeds with known differences in MT. There were fewer candidate genes potentially implicated in MS, but immunity-related genes (e.g., BOLA-NC1 and LOC512672), also identified in other populations, were validated in this study. The significant SNP and novel candidate genes identified contribute to a better understanding of the biological mechanisms underlying both traits in dairy cattle. This information will also be useful for the optimization of prediction of genomic breeding values by giving greater weights to SNP located in the genomic regions identified., (Copyright © 2020 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

Scrotal hernias (SH) are common congenital defects in commercial pigs, characterized by the presence of abdominal contents in the scrotal sac, leading to considerable production and animal welfare losses. Since the etiology of SH remains obscure, we aimed to identify the biological and genetic mechanisms involved in its occurrence through the whole transcriptome analysis of SH affected and unaffected pigs' inguinal rings. From the 22,452 genes annotated in the pig reference genome, 13,498 were expressed in the inguinal canal tissue. Of those, 703 genes were differentially expressed (DE, FDR < 0.05) between the two groups analyzed being, respectively, 209 genes upregulated and 494 downregulated in the SH-affected group. Thirty-seven significantly overrepresented GO terms related to SH were enriched, and the most relevant biological processes were muscular system, cell differentiation, sarcome reorganization, and myofibril assembly. The calcium signaling, hypertrophic cardiomyopathy, dilated cardiomyopathy, and cardiac muscle contraction were the major pathways possibly involved in the occurrence of the scrotal hernias. The expression profile of the DE genes was associated with the reduction of smooth muscle differentiation, followed by low calcium content in the cell, which could lead to a decreased apoptosis ratio and diminished muscle contraction of the inguinal canal region. We have demonstrated that genes involved with musculature are closely linked to the physiological imbalance predisposing to scrotal hernia. According to our study, the genes MYBPC1, BOK, SLC25A4, SLC8A3, DES, TPM2, MAP1CL3C , and FGF1 were considered strong candidates for future evaluation., Competing Interests: The authors declare no conflict of interest.

Many economic losses occur in the poultry industry due to leg fragility. Knowing the genomic regions that influence traits associated with the growth and composition of the leg's bone can help to improve the selection process leading to increased leg resistance to fracture. The present study aimed to map quantitative trait loci (QTL) for mineral composition and morphometric traits of the tibia in 478 animals from an F2 broiler × layer cross. The measurement of weight, length and width of Tibia was carried out at 42 days of age. Ash, dry matter, levels of calcium (Ca), phosphorus (P), magnesium (Mg), Zinc (Zn) and Calcium:Phosphorus (Ca:P) ratio were also recorded. The population was genotyped for 128 microsatellite markers and one single nucleotide polymorphism, covering 2630 cM of the chicken genome. A likelihood ratio test was performed to find QTLs. Additive and dominance effects of the QTLs were included in the model. In the chromosomes 2 (GGA2), 6 (GGA6), 8 (GGA8), 24 (GGA24) and 26 (GGA26) some suggestive QTLs (P&lt;0.00276) were mapped for tibia weight (GGA2 and GGA26), ash percentage (GGA2 and GGA6), dry matter percentage (GGA2), Ca (GGA8 and GGA24) and Ca:P ratio (GGA8), many of which are close to genes already identified as good candidates for those traits. The suggestive QTL on GGA2 has a pleiotropic effect on ash percentage, dry matter and bone weight, whereas in the GGA8 there seems to be two QTLs, one for Ca and another for Ca:P ratio. Thus, this study identified at least five genomic regions, in different chromosomes, that can be targeted for further research to identify potential mutations influencing the development and composition of leg bones in Gallus gallus.

The study aimed to evaluate pregnancy per artificial insemination (P/AI) of cows subjected to synchronization and resynchronization in ovulation protocols using intravaginal progesterone-releasing insert (P4) before pregnancy diagnosis (PD) and the relationship of PR with the diameter of preovulatory follicles (ØPOF) before TAI. Cows (n = 378) were distributed into two groups: a resynchronization group with new devices (GRN; n = 185) and resynchronization group with used devices (GRU; n = 193). On Day 0, both groups received a new P4 and estradiol benzoate (EB). On D8, P4 removal + D-cloprostenol + eCG + estradiol cypionate (EC) was done. On d10, TAI was conducted. On d32, cows were resynchronized and divided into two groups, GRN (n = 185) and GRU (n = 193). The GRN group received a new P4 + EB, and the GRU group received a used P4 + EB. On d40, the P4 was removed + PD. The non-pregnant cows received D-cloprostenol + eCG + EC. US was done again on d42 to determine ØPOF before the second TAI. The P/AI of the GRN and GRU groups after synchronization were 56.2% and 57.0% (p = 0.87), respectively, and those after resynchronization were 58.0% and 37.3% (p < 0.008), respectively. The P/AI of the GRN and GRU groups observed after TAI (synchronization + resynchronization) were 81.6% and 73.1%, respectively (p = 0.047). No difference (p = 0.067) in ØPOF between the pregnant and non-pregnant cows in the GRN was found, whereas the GRU group showed a significant difference (p = 0.003). Resynchronization protocols optimized the P/AI in both groups. New intravaginal devices resulted in greater P/AI and P/AI accumulation in resynchronization as compared with the GRU; the ØPOF was related with P/AI., (© 2019 Blackwell Verlag GmbH.)

Objective: This study assessed the possible existence of genotype by environment interactions for milk, fat and protein yields in Holstein cattle raised in one of the most important milk production basins in Brazil., Methods: Changes in the genetic parameters and breeding values were evaluated for 57,967 animals from three distinct regions of southern Brazil, divided according to differences in climate. The genotype by environment interaction was determined by genetic correlations between regions, estimated by the restricted maximum likelihood, considering the animal model. Bull rankings were investigated to verify the ratio of coincident selected animals between regions for each trait., Results: The estimates of heritability coefficients were similar between two regions, but were lower in the third evaluated area, for all traits. Genetic correlations between regions were high, ranging from 0.91 to 0.99 for milk, fat and protein yields, representing the absence of a genotype by environment interaction for productive traits. The percentage of selection error between regions for the top 10% of animals ranged from 0.88% to 2.07% for milk yield, 0.99% to 2.46% for fat yield and 0.59% to 3.15% for protein yield., Conclusion: A slight change in genotype between areas was expected since no significant genotype by environment interactions were identified, facilitating the process of selecting Holstein cattle in southern Brazil.

Polymorphisms in the growth hormone (GH) and IGF type-1 (IGF1) genes have been associated with the economic traits in farm animals, including BW of some sheep breeds. However, it remains unknown if these polymorphisms also affect carcass traits in sheep. Thus, we aimed to identify polymorphisms in the GH and IGF1 genes in Santa Ines sheep in order to describe their allelic and genotypic frequencies as well as to test the hypotheses that they are associated with the carcass traits. Fragments of 4550 bp (IGF1) and 1194 bp (GH) were sequenced in up to 191 lambs. In all, 18 polymorphisms were identified in the IGF1 and 21 in the GH gene. The IGF1 polymorphisms rs430457475, rs412470350, rs409110739 and rs400113576 showed an additive effect on the internal carcass length (-0.9265±0.4223), rump girth (-2.9285±1.1473), rib yield (-1.0003±0.4588) and neck weight (-0.0567±0.0278), respectively. In addition, the polymorphisms rs58957314 in the GH affected the rib weight (-0.4380±0.1272) and rib yield (-2.2680±0.6970), loin weight (-0.1893±0.0516) and loin yield (-0.9423±0.3259), palette weight (-0.2265±0.0779) and palette yield (-0.9424±0.4184), leg weight (-0.3960±0.1375), neck weight (-0.0851±0.0394) and carcass finishing score (-0.1700±0.0839). These results allow us to conclude that there are polymorphisms in the IGF1 and GH genes associated with carcass traits in Santa Ines sheep, which can provide important information for marker-assisted selection.

This study aimed to evaluate the effect of recombinant bovine somatotropin (bST) in combination with progesterone (P4) and estradiol benzoate (EB) on ovarian follicular dynamics using a protocol for estrus and ovulation synchronization in crossbred Bos taurus taurus cows. Twenty-four non-lactating multiparous cows were randomly assigned to two groups: the recombinant bovine somatotropin group (GbST; n&#x202F;=&#x202F;11) received an intravaginal P4 device (1.5&#x202F;g), estradiol benzoate (EB&#x202F;=&#x202F;1.0&#x202F;mg IM), bST (500&#x202F;mg SC), and an ovarian ultrasonography (US) on day zero (d0&#x202F;=&#x202F;beginning of the study); d-cloprostenol (150&#x202F;μg, IM), US, and P4 removal on d8; 1.0&#x202F;mg of EB (IM) on d9; and US on d10 and d15. On the other hand, to the control group (GC; n&#x202F;=&#x202F;13), the same protocol as the GbST was applied, except for the non-receipt of bST on d0. The follicles were measured and evaluated on d0, d8, and d10, as were the corpora lutea (CL) on d15 (using ultrasonography). The effect of the two treatments (GbST vs. GC) on the follicle size, CL (F-test), and ovulation rate (logistic regression) were evaluated. The GbST showed a greater follicle diameter on d10 (14.5&#x202F;mm) than the GC (12.1&#x202F;mm; P&#x202F;<&#x202F;0.03), as well as a greater diameter of CL on d15 (19.7 vs. 16.9&#x202F;mm, P&#x202F;<&#x202F;0.01). In addition, in the former, the ovulation rate (90.9 vs. 69.2%, P&#x202F;=&#x202F;0.09) was observed to be greater. It was concluded that the combination of bST, P4, and EB in synchronization for estrus and ovulation protocols significantly increased the diameter of the preovulatory follicle, produced a higher follicular growth rate, and a greater diameter of the corpus luteum. Additionally, there was a higher percentage of cows with ovulation compared to the group that did not receive bST., (Copyright © 2018 Elsevier Inc. All rights reserved.)

This study aimed to correlate the inflammatory reaction (IR) caused by a progesterone-releasing intravaginal device (P4) with ovarian activity and pregnancy rate (PR) in embryo-recipient anestrus mares (to decrease the spring transitional period). 50 animals were assigned to three groups: GP4 (P4 group; n = 16), GP4OH (P4 + oxytetracycline hydrochloride and hydrocortisone sprayed onto the device; n = 14), and GNP4 (no intravaginal P4; n = 20). The administration protocol for GP4 was: Day 0, 750 mg P4 + ovarian examination by ultrasonography (US) + vaginal sample collection; Day 8, US; Day 11, P4 removal + 7.5 mg PGF2α + US + second vaginal sample collection; Days 13 to 16, US; Days 17 to 21, US + 750 IU hCG to mares with follicles 35 mm or more in diameter; Days 19 to 23 US (ovulation check); Days 24 to 28, embryo transfer + intravenous flunixin meglumine; and Days 30, US pregnancy diagnosis. The GP4OH and GNP4 mares received the same administration protocol as GP4, except that no P4 device was administered to the GNP4 group on Day 0. Although neutrophil-mediated IR occurred in the GP4 and GP4OH groups, the IR was significantly reduced in GP4OH as compared with that in GP4 (P < 0.0001). From Day 0 to Day 17, the GP4 and GP4OH mares developed a greater number of follicles per animal than did the GNP4 mares (P < 0.05), and the average diameter of the follicles was larger in the GP4 and GP4OH mares. The ovulation rates in GP4, GP4OH, and GNP4 mares were, respectively, 43.7%, 64.3%, and 30.0%, and ovulation occurred at 6.8, 6.5, and 23 days after P4 removal (P < 0.05). On Day 17, endometrial edema was verified in 50%, 64.2%, and 35.0% of the GP4, GP4OH, and GNP4 mares, and the PRs after embryo transfer were 80%, 100%, and 66.6%, respectively. Although intravaginal devices caused IR in both the device-recipient groups (P = 0.0001), IR and vaginitis had no negative impact on follicle diameter, ovulation rate, period to ovulation after the removal of P4, endometrial edema, or PR. In addition, P4 reactivated the ovarian function and the IR eliminated a large percentage of bacteria (Bacillus spp., Enterobacter spp., Proteus spp., Pseudomonas spp., and Staphylococcus spp.), especially in GP4; the application of oxytetracycline hydrochloride and hydrocortisone on the devices reduced the severity of vaginitis., (Copyright © 2016 Elsevier Inc. All rights reserved.)

This study aimed to evaluate the effects of birth type and family on quantitative and qualitative meat traits in Santa Ines lambs and to do a descriptive study of variation inside of breed. A total of 50 carcass and meat traits were evaluated in up to 101 lambs slaughtered at 424 days of age. Random effect of family, the fixed effect of birth type (single or double) and year, and the covariates of dam's weight at weaning and age (in days) at slaughter were inserted in the model. This study shows that some carcass and meat traits in Santa Ines raised on pasture has large variability, specially for meat cut yields, several carcass non-components yields, and rib eye area, subcutaneous fat thickness, shear force, cooking losses, and b* color parameter. The birth type effect influenced (P < 0.05) rump width; reticulum, leg, heart and kidney yields; and the carcass pH at 24 h after slaughter. The family effect was significant (P < 0.05) for cold carcass weight; hot, cold and true carcass yields; external carcass and leg lengths; perimeter and width of the rump; kidney, liver and tail yields; and carcass pH at slaughter.

Genetic parameters, genetic trends, and genetic progress of carcass traits were estimated for 12,447 Nellore individuals from different Brazilian herds. The following carcass traits were analyzed: visual body scores of conformation (CONF), precocity (PREC), and muscularity (MUSC); rump width (RW) and rump length (RL), body size (frame); and ultrasound evaluation of ribeye area (REA), backfat thickness (BFT), and rump fat thickness (RFT). Heritability estimates (± SE) for CONF, PREC, and MUSC were 0.23 ± 0.02, 0.33 ± 0.03, and 0.31 ± 0.02, respectively. The heritability estimates (± SE) for RW, RL, and frame were 0.25 ± 0.05, 0.16 ± 0.04, and 0.31 ± 0.03, respectively. Ultrasound of the REA, BFT, and RFT presented mean heritability estimates (± SE) of 0.38 ± 0.03, 0.44 ± 0.04, and 0.47 ± 0.04, respectively. The visual body score of CONF had high genetic correlations with RW, RL, and frame (0.74 ± 0.09, 0.82 ± 0.08, and 0.83 ± 0.04, respectively), indicating a high association of CONF with the measurements related to body structure. The REA had no correlation with BFT and RFT (-0.09 ± 0.04 and -0.03 ± 0.04, respectively) and showed only a moderate genetic correlation with MUSC (0.39 ± 0.05). The BFT and RFT had moderate genetic correlations with PREC (0.36 ± 0.07 and 0.29 ± 0.07, respectively) and no correlation with frame (-0.02 ± 0.03 and 0.05 ± 0.05, respectively), suggesting that selection for frame had no effect on the subcutaneous fat content of the carcass. Low genetic trends and low genetic progress were obtained for REA (0.026 cm, 0.02%), BFT (0.0031 mm, 0.05%), and RFT (0.0013 mm, 0.02%), with no significant values of genetic progress detected throughout the studied period. The CONF, PREC, and MUSC presented high genetic trends (0.030 points, 0.030 points, and 0.029 points, respectively) and high genetic progress (0.60%, 0.56%, and 0.59%, respectively), indicating a significant genetic progress for these traits throughout the evaluated period. Carcass traits evaluated by ultrasound and visual body scores are eligible for selection and can be used in genetic improvement programs in Nellore cattle; however, visual body score selection for carcass traits can result in slower genetic progress for carcass quality when compared to selection performed by ultrasound.

For genetic evaluation of beef cattle, univariate or bivariate analyses are often performed as an alternative to decrease the complexity of matrices and mathematical models compared to multivariate analysis, which considers a larger number of joint traits. The use of bivariate methods to calculate genetic predictors may cause bias in the estimation of breeding values and, as a consequence, reclassification of the rank of top-selected sires, resulting in a loss of genetic gain in future generations. The objective of this study was to compare the bivariate and multivariate joint methods of genetic evaluation, verifying the selection loss, and reclassification of the ranking of the best animals with different selection intensities. Records of 431,224 Nellore breed animals were evaluated for birth weight, weaning weight, post-weaning gain, muscle score, scrotal circumference, and selection index. The pedigree file consisted of 505,848 animals, including 218,727 males and 287,121 females. The predicted breeding values were obtained using the program PEST 2, and the complete pedigree analysis was performed by the PopReport software. The results showed that, for the four different selection intensities considered (TOP 10 and 1, 10, and 30%), selection loss and reclassification of animals in ranking, were detected for all traits evaluated when the two methods of analysis were compared.

Data from 69,525 animals were used to compare two types of analyses, one of them having the weaning management group (WEMANG) included as an effect in the contemporary group (F&#95;WEMANG) and the other considering the weaning management group as a random effect, not related to the mathematical model (R&#95;WEMANG) for post-weaning traits. The components of (co)variance were estimated for pre-weaning traits (birth weight and weaning weight) and for post-weaning traits [scrotal circumference (SC), weight gain from weaning to 18 months of age (WG) and muscle score (MUSC)] in Nellore cattle, based on a complete animal model. Heritability of SC, WG and MUSC for the F&#95;WEMANG model was equal to 0.46 ± 0.02, 0.38 ± 0.03 and 0.26 ± 0.01, and for the R&#95;WEMANG model it was 0.45 ± 0.02, 0.31 ± 0.03 and 0.25 ± 0.01, respectively. Genetic correlations between all the studied traits varied between 0.07 ± 0.01 and 0.77 ± 0.03 in F&#95;WEMANG and between 0.02 ± 0.01 and 0.76 ± 0.04 in R&#95;WEMANG. The R&#95; WEMANG model allowed a decrease in the number of contemporary groups as well as an increase in the number of observations per group without significant alterations in heritability coefficients, for the post-weaning traits. Consequently, the analysis became more robust and avoided having contemporary groups with low variability.