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Genetic parameters were estimated for egg production, egg quality, and eggshell colors in eight lineages of Brazilian laying hens. Age at first egg (AFE), total egg production up to the 45th week (PROD), egg weight (EW), albumen height (AH), yolk color (YC), the Haugh units (HU), eggshell strength (ESS), eggshell thickness (EST), yolk weight (YW), eggshell weight (ESW), and eggshell color (L*, a*, and b*) were measured in 2030 eggs obtained from 645 laying hens. Variance components were estimated from a mixed animal model, which included the fixed effects of contemporary groups, cage location, and hen line, and the additive genetic, permanent environmental, and residual as random effects. In general, heritabilities were low to moderate (h 2 = 0.11 to 0.48). Genetic correlations among eggshell quality traits were moderate to high (0.36 and 0.69). High genetic correlations were obtained between the eggshell color traits [r g = -0.90 (L* and a*); r g = -0.64 (L* and b*); and r g = 0.65 (a* and b*)]. Results suggest that EW is strongly correlated with ESW, but the genetic correlations between EW and ESS and between EW and EST were low. Genetic correlations between L* and eggshell quality traits were low to moderate, suggesting that L* has little or no relation with external egg quality. However, genetic correlations between a* and b* values and eggshell quality traits were high. The genetic correlations between eggshell color and eggshell quality traits were low, suggesting that the eggshell color does not influence external egg quality. Genetic correlations between PROD and egg quality traits were negative and varied between -0.42 and -0.05. This antagonistic relationship emphasizes the importance of adopting breeding schemes that allow the simultaneous genetic progress of these traits by considering their genetic correlation and economic relevance, such as the selection index., (© 2023. The Author(s), under exclusive licence to Springer Nature B.V.)

Due to the high milk production of Holstein cows, many countries have chosen to import semen to improve local dairy herds. This strategy would be more effective if this semen was used in the same environment conditions in which the bulls were selected. If the effect of genotype by environment (G × E) interaction is not considered, the estimated breeding values (EBVs) may vary, potentially reducing the selection response. We evaluate the impact of heat stress on selection for milk yield and composition of Holstein cows using random regression models. To verify the interference of heat stress in milk yield (MY) and composition traits (fat, protein, total saturated, and total unsaturated fatty acids content in milk), temperature-humidity index (THI) on test-day milk records was used. The threshold value to divide the environments using test-day information from Brazilian Holstein cows was 72 units of THI, i.e., < 72 represented no heat stress and > 72 represented heat stress. Legendre polynomials of second-order (Leg 2) model and two lactation points (33 and 122 DIM) were used to estimate heritabilities and EBVs for five important dairy traits. The heritabilities of milk components and fatty acids were low (0.09-0.29), regardless of lactation period and degree of heat stress, with the exception of protein content (0.30-0.35). Fat content was the only milk component that was reduced according to the degree of heat stress and lactation period. The EBVs tended to decrease in heat stress conditions, thus animals with high genetic potential demonstrated evidence of G × E interaction. However, acclimatization of dairy cows to heat stress in the farm production systems may have been responsible for the low differences among genetic parameters and EBVs with and without heat stress found in this study., (© 2022. The Author(s) under exclusive licence to International Society of Biometeorology.)

Measurements of milk yield (MY), somatic cell score (SCS), percentage of fat (FP), protein (PP), lactose (LP), casein (CP) and percentage of palmitic (C16:0), stearic (C18:0), oleic (C18:1), total saturated (SFA), unsaturated (UFA), monounsaturated (MUFA) and polyunsaturated (PUFA) fatty acids in milk from 5,224 Holstein cows were evaluated as a function of a temperature and humidity index (THI). Legendre orthogonal polynomials from second to seventh order were tested. The best fit order for MY, PP and C18:0 was the third, whereas the second for all other traits. The heritability estimates decreased for MY (0.31 to 0.14), FP (0.28 to 0.16), LP (0.43 to 0.30), SCS (0.14 to 0.09), SFA (0.33 to 0.22) and C16:0 (0.31 to 0.26), whereas increased for CP (0.32 to 0.42), MUFA (0.08 to 0.13), UFA (0.07 to 0.11) and C18:1 (0.07 to 0.11) as the THI level increased. For PP, heritabilities (0.26 to 0.39) presented larger values in intermediate THI. For PUFA and C18:0, heritabilities were approximately constant (0.13 to 0.14 and 0.15, respectively). However, the greatest variations may have been the result of the limitations of Legendre polynomials at the extreme points of the curve, and the pattern of heritabilities curves was approximately constant for the evaluated traits. Spearman's rank correlations between breeding values in extreme THI levels were greater than 0.80 for all traits considering all animals, only cows and only bulls. When considering the top 1% and the top 50% animals (only cows, only bulls and all), Spearman correlations smaller than 0.70 were found, suggesting reranking of the animals. Although there was little variation in the variance components over THI, it is possible that there is no heat stress in the animals studied, because, on average, there was no great impact of the thermal load on the traits. One possible explanation is the use of herds with little climatic difference among herds, as well as the use of fans and sprinklers into the barns. However, the THI levels may be important factors in the selection process, as reranking of animals was verified., (© 2021 John Wiley & Sons Ltd.)

Advances in the molecular area of selection have expanded knowledge of the genetic architecture of complex traits through genome-wide association studies (GWAS). Several GWAS have been performed so far, but confirming these results is not always possible due to several factors, including environmental conditions. Thus, our objective was to identify genomic regions associated with traditional milk production traits, including milk yield, somatic cell score, fat, protein and lactose percentages, and fatty acid composition in a Holstein cattle population producing under tropical conditions. For this, 75,228 phenotypic records from 5,981 cows and genotypic data of 56,256 SNP from 1,067 cows were used in a weighted single-step GWAS. A total of 46 windows of 10 SNP explaining more than 1% of the genetic variance across 10 Bos taurus autosomes (BTA) harbored well-known and novel genes. The MGST1 (BTA5), ABCG2 (BTA6), DGAT1 (BTA14), and PAEP (BTA11) genes were confirmed within some of the regions identified in our study. Potential novel genes involved in tissue damage and repair of the mammary gland (COL18A1), immune response (LTTC19), glucose homeostasis (SLC37A1), synthesis of unsaturated fatty acids (LTBP1), and sugar transport (SLC37A1 and MFSD4A) were found for milk yield, somatic cell score, fat percentage, and fatty acid composition. Our findings may assist genomic selection by using these regions to design a customized SNP array to improve milk production traits on farms with similar environmental conditions., (Copyright © 2019 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.)

For genomic selection to be successful, there must be sufficient linkage disequilibrium between the markers and the causal mutations. The objectives of this study were to evaluate the extent of LD in ovine using the Santa Inês breed and to infer the minimum number of markers required to reach reasonable prediction accuracy. In total, 38,168 SNPs and 395 samples were used. The mean LD between adjacent marker pairs measured by r 2 and |D'| were 0.166 and 0.617, respectively. LD values between adjacent marker pairs ranged from 0.135 to 0.194 and from 0.568 to 0.650 for r 2 for |D'| across all chromosomes. The average r 2 between all pairwise SNPs on each chromosome was 0.018. SNPs separated by between 0.10 to 0.20 Mb had an estimated average r 2 equal to 0.1033. The identified haplotype blocks consisted of 2 to 21 markers. Moreover, estimates of average coefficients of inbreeding and effective population size were 0.04 and 96, respectively. LD estimated in this study was lower than that reported in other species and was characterized by short haplotype blocks. Our results suggest that the use of a higher density SNP panel is recommended for the implementation of genomic selection in the Santa Inês breed.

Background: Despite the health concerns and nutritional importance of fatty acids, there is a relative paucity of studies in the literature that report genetic or genomic parameters, especially in the case of sheep populations. To investigate the genetic architecture of fatty acid composition of sheep, we conducted genome-wide association studies (GWAS) and estimated genomic heritabilities for fatty acid profile in Longissimus dorsi muscle of 216 male sheep., Results: Genomic heritability estimates for fatty acid content ranged from 0.25 to 0.46, indicating that substantial genetic variation exists for the evaluated traits. Therefore, it is possible to alter fatty acid profiles through selection. Twenty-seven genomic regions of 10 adjacent SNPs associated with fatty acids composition were identified on chromosomes 1, 2, 3, 5, 8, 12, 14, 15, 16, 17, and 18, each explaining ≥0.30% of the additive genetic variance. Twenty-three genes supporting the understanding of genetic mechanisms of fat composition in sheep were identified in these regions, such as DGAT2, TRHDE, TPH2, ME1, C6, C7, UBE3D, PARP14, and MRPS30., Conclusions: Estimates of genomic heritabilities and elucidating important genomic regions can contribute to a better understanding of the genetic control of fatty acid deposition and improve the selection strategies to enhance meat quality and health attributes.

Performance traits are economically important and are targets for selection in breeding programs, especially in the poultry industry. To identify regions on the chicken genome associated with performance traits, different genomic approaches have been applied in the last years. The aim of this study was the application of CornellGBS approach (134,528 SNPs generated from a PstI restriction enzyme) on Genome-Wide Association Studies (GWAS) in an outbred F 2 chicken population. We have validated 91.7% of these 134,528 SNPs after imputation of missed genotypes. Out of those, 20 SNPs were associated with feed conversion, one was associated with body weight at 35 days of age (P < 7.86E-07) and 93 were suggestively associated with a variety of performance traits (P < 1.57E-05). The majority of these SNPs (86.2%) overlapped with previously mapped QTL for the same performance traits and some of the SNPs also showed novel potential QTL regions. The results obtained in this study suggests future searches for candidate genes and QTL refinements as well as potential use of the SNPs described here in breeding programs., Competing Interests: The authors declare no competing financial interests.

Information about genetic parameters is essential for selection decisions and genetic evaluation. These estimates are population specific; however, there are few studies with dairy cattle populations reared under tropical and sub-tropical conditions. Thus, the aim was to obtain estimates of heritability and genetic correlations for milk yield and quality traits using pedigree and genomic information from a Holstein population maintained in a tropical environment. Phenotypic records (n = 36 457) of 4203 cows as well as the genotypes for 57 368 single nucleotide polymorphisms from 755 of these cows were used. Covariance components were estimated using the restricted maximum likelihood method under a mixed animal model, considering a pedigree-based relationship matrix or a combined pedigree-genomic matrix. High heritabilities (around 0.30) were estimated for lactose and protein content in milk whereas moderate values (between 0.19 and 0.26) were obtained for percentages of fat, saturated fatty acids and palmitic acid in milk. Genetic correlations ranging from -0.38 to -0.13 were determined between milk yield and composition traits. The smaller estimates compared to other similar studies can be due to poor environmental conditions, which may reduce genetic variability. These results highlight the importance in using genetic parameters estimated in the population under evaluation for selection decisions., (© 2016 Blackwell Verlag GmbH.)

Repeated measures from the same individual have been analyzed by using repeatability and finite dimension models under univariate or multivariate analyses. However, in the last decade, the use of random regression models for genetic studies with longitudinal data have become more common. Thus, the aim of this research was to estimate genetic parameters for body weight of four experimental chicken lines by using univariate random regression models. Body weight data from hatching to 84 days of age (n = 34,730) from four experimental free-range chicken lines (7P, Caipirão da ESALQ, Caipirinha da ESALQ and Carijó Barbado) were used. The analysis model included the fixed effects of contemporary group (gender and rearing system), fixed regression coefficients for age at measurement, and random regression coefficients for permanent environmental effects and additive genetic effects. Heterogeneous variances for residual effects were considered, and one residual variance was assigned for each of six subclasses of age at measurement. Random regression curves were modeled by using Legendre polynomials of the second and third orders, with the best model chosen based on the Akaike Information Criterion, Bayesian Information Criterion, and restricted maximum likelihood. Multivariate analyses under the same animal mixed model were also performed for the validation of the random regression models. The Legendre polynomials of second order were better for describing the growth curves of the lines studied. Moderate to high heritabilities (h(2) = 0.15 to 0.98) were estimated for body weight between one and 84 days of age, suggesting that selection for body weight at all ages can be used as a selection criteria. Genetic correlations among body weight records obtained through multivariate analyses ranged from 0.18 to 0.96, 0.12 to 0.89, 0.06 to 0.96, and 0.28 to 0.96 in 7P, Caipirão da ESALQ, Caipirinha da ESALQ, and Carijó Barbado chicken lines, respectively. Results indicate that genetic gain for body weight can be achieved by selection. Also, selection for body weight at 42 days of age can be maintained as a selection criterion., (© 2016 Poultry Science Association Inc.)

Artificial insemination has been used to improve production in Brazilian dairy cattle; however, this can lead to problems due to increased inbreeding. To evaluate the effect of the magnitude of inbreeding coefficients on predicted transmitting abilities (PTAs) for milk traits of Holstein and Jersey breeds, data on 392 Holstein and 92 Jersey sires used in Brazil were tabulated. The second-degree polynomial equations and points of maximum or minimal response were estimated to establish the regression equation of the variables as a function of the inbreeding coefficients. The mean inbreeding coefficient of the Holstein bulls was 5.10%; this did not significantly affect the PTA for percent milk fat, protein percentage and protein (P = 0.479, 0.058 and 0.087, respectively). However, the PTAs for milk yield and fat decreased significantly after reaching inbreeding coefficients of 6.43 (P = 0.034) and 5.75 (P = 0.007), respectively. The mean inbreeding coefficient of Jersey bulls was 6.45%; the PTAs for milk yield, fat and protein, in pounds, decreased significantly after reaching inbreeding coefficients of 15.04, 9.83 and 12.82% (P < 0.001, P = 0.002, and P = 0.001, respectively). The linear regression was only significant for fat and protein percentages in the Jersey breed (P = 0.002 and P = 0.005, respectively). The PTAs of Holstein sires were more affected by smaller magnitudes of inbreeding coefficients than those of Jersey sires. It is necessary to monitor the inbreeding coefficients of sires used for artificial insemination in breeding schemes in Brazil, since the low genetic variability of the available sires may lead to reduced production.