B-spline polynomials models for analyzing growth patterns of Guzerat young bulls in field performance tests.

OBJECTIVE: The aim of this study was to identify suitable polynomial regression for modeling the average growth trajectory and to estimate the relative development of the rib eye area, scrotal circumference, and morphometric measurements of Guzerat young bulls. METHODS: A total of 45 recently weaned males, aged 325.8±28.0 days and weighing 219.9±38.05 kg, were evaluated. The animals were kept on Brachiaria brizantha pastures, received multiple supplementations, and were managed under uniform conditions for 294 days, with evaluations conducted every 56 days. The average growth trajectory was adjusted using ordinary polynomials, Legendre polynomials, and quadratic B-splines. The coefficient of determination, mean absolute deviation, mean square error, the value of the restricted likelihood function, Akaike information criteria, and consistent Akaike information criteria were applied to assess the quality of the fits. For the study of allometric growth, the power model was applied. RESULTS: Ordinary polynomial and Legendre polynomial models of the fifth order provided the best fits. B-splines yielded the best fits in comparing models with the same number of parameters. Based on the restricted likelihood function, Akaike's information criterion, and consistent Akaike's information criterion, the B-splines model with six intervals described the growth trajectory of evaluated animals more smoothly and consistently. In the study of allometric growth, the evaluated traits exhibited negative heterogeneity (b<1) relative to the animals' weight (p<0.01), indicating the precocity of Guzerat cattle for weight gain on pasture. CONCLUSION: Complementary studies of growth trajectory and allometry can help identify when an animal's weight changes and thus assist in decision-making regarding management practices, nutritional requirements, and genetic selection strategies to optimize growth and animal performance.

Genetic parameters and association between longevity and milk production in buffaloes using the ssGBLUP method

The objectives of this work were to estimate the genetic parameters for the traits longevity (LG) and accumulated milk yield at 305 days (MY305) using a bitrait animal model and the single-step GBLUP method and estimate the genetic gain for LG through direct and indirect selection for MY305. We used 4,057 records of first lactations of Murrah dairy buffaloes, collected between 1987 and 2020, belonging to six Brazilian herds located in the states Ceará, Rio Grande do Norte, and São Paulo and 960 animals genotyped using the 90K Axiom Buffalo Genotyping (Thermo Fisher Scientific, Santa Clara, CA) to estimate the genetic parameters. The heritability estimate was 0.25 for MY305 and 0.13 for LG. The genetic gain for LG was 0.13 months under direct selection, and 0.14 months under indirect selection, which results in a relative selection efficiency of 11% under selection for MY305 compared with the direct selection. The genetic correlation between the two traits was 0.77, indicating that animals with genetic potential for high MY305 tend to live longer. The genetic trends for MY305 and LG were 0.22 kg/year and 5.20 days/year, respectively, indicating a positive response, which reaffirms its relationship with the high genetic correlation between the two traits.(AU)

Polymorphisms in TLR4 Gene Associated With Somatic Cell Score in Water Buffaloes (Bubalus bubalis).

Considering the importance of the diseases affecting the productive performance of animals in the dairy industry worldwide, it is necessary to implement tools that help to control and limit the occurrence of such diseases. As the increased somatic cell counts (SCC) are a direct expression of the inflammatory process, they are candidates to become the usual parameter for assessing udder health regarding milk quality and for monitoring mastitis incidences. Toll-Like Receptors are membrane proteins that play a key role in immunity, recognizing pathogens and, subsequently, activating immune responses. The present study was conducted to identify single nucleotide polymorphisms in the TLR4 gene of buffaloes and to analyze its associations with somatic cell counts. DNA samples of 120 Murrah buffaloes were used. The whole coding region of the TLR4 gene was amplified by polymerase chain reaction reactions and sequenced for polymorphism scanning. A total of 13 polymorphisms were identified for the sequenced regions of the TLR4, most of which are in the coding region. The association with the somatic cell score was highly significant (p < 0.001) for all identified polymorphisms of TLR4 gene (g.54621T>A, g.54429G>T, g.54407T>A, g.46616C>A, g.46613T>G, g.46612A>G, g.46611C>A, g.46609T>G, g.46541C>G, g.46526C>A, g.46516T>C, g.46376C>T, g.46372T>C). Therefore, it is suggested that the markers of the TLR4 gene can be used as molecular markers for mastitis resistance in buffaloes, due to their association with somatic cell counts.

Publisher Correction: Uncovering Sub-Structure and Genomic Profiles in Across-Countries Subpopulations of Angus Cattle.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Uncovering Sub-Structure and Genomic Profiles in Across-Countries Subpopulations of Angus Cattle.

Highlighting genomic profiles for geographically distinct subpopulations of the same breed may provide insights into adaptation mechanisms to different environments, reveal genomic regions divergently selected, and offer initial guidance to joint genomic analysis. Here, we characterized similarities and differences between the genomic patterns of Angus subpopulations, born and raised in Canada (N = 382) and Brazil (N = 566). Furthermore, we systematically scanned for selection signatures based on the detection of autozygosity islands common between the two subpopulations, and signals of divergent selection, via FST and varLD tests. The principal component analysis revealed a sub-structure with a close connection between the two subpopulations. The averages of genomic relationships, inbreeding coefficients, and linkage disequilibrium at varying genomic distances were rather similar across them, suggesting non-accentuated differences in overall genomic diversity. Autozygosity islands revealed selection signatures common to both subpopulations at chromosomes 13 (63.77-65.25 Mb) and 14 (22.81-23.57 Mb), which are notably known regions affecting growth traits. Nevertheless, further autozygosity islands along with FST and varLD tests unravel particular sites with accentuated population subdivision at BTAs 7 and 18 overlapping with known QTL and candidate genes of reproductive performance, thermoregulation, and resistance to infectious diseases. Our findings indicate overall genomic similarity between Angus subpopulations, with noticeable signals of divergent selection in genomic regions associated with the adaptation in different environments.

Random regression models with B-splines to estimate genetic parameters for body weight of young bulls in performance tests

The objective of this study was to estimate genetic parameters for body weight of beef cattle in performance tests. Different random regression models with quadratic B-splines and heterogeneous residual variance were fitted to estimate covariance functions for body weights of Nellore and crossbred Charolais × Nellore bulls. The criteria −2 residual log-likelihood (−2RLL), Akaike Information Criterion (AIC), and consistent AIC (CAIC) were used to choose the most appropriate model. For Nellore bulls, residual variance was modeled with six classes of age, and direct additive genetic and permanent environment effects were modeled with quadratic B-splines with two and one intervals, respectively. For crossbred bulls, quadratic B-splines with one interval fitted direct additive genetic and permanent environment effects and nine classes of age were needed to fit residual variance. Pooling classes of age with up to 40% in difference of residual variances does not compromise the fit of the model. Heritability for body weight in performance tests are moderate (>0.25, for crossbred bulls) to high (>0.5, for Nellore bulls) and genetic correlation between weights over the test are also high (>0.65). Then, selection of young bulls in performance test is an efficient tool to increase body weight in beef cattle.(AU)

Genetic and environmental effects on scores of conformation, precocity and muscling in long yearling Nellore cattle / Efeitos genéticos e de ambiente sobre os escores visuais de conformação, precocidade e musculosidade em bovinos Nelore ao sobreano

The visual scores for conformation (C), precocity (P) and muscle (M) are used to indirectly assess traits related to termination and carcass composition. This study analyzes how age of dam at calving (AC), long yearling age (YA) and long yearling weight (YW) of the animal affect the scores of Nellore cattle, and estimates their heritability. Regression functions were estimated to determine the AC, YA and YW effects on C, P and M scores after the contemporary group (CG) effect being absorbed. The heritabilities were estimated by restricted maximum likelihood using four different models that included animal additive genetic effect as random and different covariates (AC, YA and YW) as fixed effects. The regression analysis showed that the covariates, either linear or quadratic, significantly influenced the scores of C, P and M. The determination coefficients of the models for YA and AC were small, probably due to the CG bias removal. The heritability estimates for the scores ranged from 0.13 to 0.36 for C; 0.32 to 0.36 for P; and, 0.35 to 0.38 for M, for all models, indicating that C, P and M respond to direct selection. The classification of animals according to their breeding values, especially in relation to C, varied according to the environmental effects included in the models.

Os escores visuais de conformação (C), precocidade (P) e musculosidade (M) são usados para acessar indiretamente características relacionadas à terminação e composição de carcaça. Neste estudo, objetivou-se analisar como a idade da vaca ao parto (AC), idade (YA) e peso do animal ao sobreano (YW) influenciam os escores de bovinos da raça Nelore, além de estimar suas herdabilidades. Foram estimadas funções de regressão dos efeitos de AC, YA e YW sobre os escores C, P e M, após a absorção do efeito de grupo de contemporâneos (CG). As herdabilidades foram estimadas por máxima verossimilhança restrita, considerando-se quatro diferentes modelos que incluíram o efeito genético aditivo de animal como aleatório, e diferentes covariáveis (AC, YA e YW) como efeitos fixos. Nas análises de regressão, as covariáveis, tanto linear como quadrática, influenciaram significativamente os escores C, P e M. Os coeficientes de determinação dos modelos para YA e AC foram de pequena magnitude, provavelmente devido à absorção do efeito de CG. As estimativas de herdabilidade para os escores variaram de 0,13 a 0,36 para C, de 0,32 a 0,36 para P, e de 0,35 a 0,38 para M, considerando todos os modelos utilizados, indicando que C, P e M respondem à seleção direta. A classificação dos animais de acordo com seus valores genéticos, principalmente em relação a C, variou de acordo com os efeitos de ambiente incluídos nos modelos.

Genetic and environmental effects on scores of conformation, precocity and muscling in long yearling Nellore cattle / Efeitos genéticos e de ambiente sobre os escores visuais de conformação, precocidade e musculosidade em bovinos Nelore ao sobreano

The visual scores for conformation (C), precocity (P) and muscle (M) are used to indirectly assess traits related to termination and carcass composition. This study analyzes how age of dam at calving (AC), long yearling age (YA) and long yearling weight (YW) of the animal affect the scores of Nellore cattle, and estimates their heritability. Regression functions were estimated to determine the AC, YA and YW effects on C, P and M scores after the contemporary group (CG) effect being absorbed. The heritabilities were estimated by restricted maximum likelihood using four different models that included animal additive genetic effect as random and different covariates (AC, YA and YW) as fixed effects. The regression analysis showed that the covariates, either linear or quadratic, significantly influenced the scores of C, P and M. The determination coefficients of the models for YA and AC were small, probably due to the CG bias removal. The heritability estimates for the scores ranged from 0.13 to 0.36 for C; 0.32 to 0.36 for P; and, 0.35 to 0.38 for M, for all models, indicating that C, P and M respond to direct selection. The classification of animals according to their breeding values, especially in relation to C, varied according to the environmental effects included in the models.(AU)

Os escores visuais de conformação (C), precocidade (P) e musculosidade (M) são usados para acessar indiretamente características relacionadas à terminação e composição de carcaça. Neste estudo, objetivou-se analisar como a idade da vaca ao parto (AC), idade (YA) e peso do animal ao sobreano (YW) influenciam os escores de bovinos da raça Nelore, além de estimar suas herdabilidades. Foram estimadas funções de regressão dos efeitos de AC, YA e YW sobre os escores C, P e M, após a absorção do efeito de grupo de contemporâneos (CG). As herdabilidades foram estimadas por máxima verossimilhança restrita, considerando-se quatro diferentes modelos que incluíram o efeito genético aditivo de animal como aleatório, e diferentes covariáveis (AC, YA e YW) como efeitos fixos. Nas análises de regressão, as covariáveis, tanto linear como quadrática, influenciaram significativamente os escores C, P e M. Os coeficientes de determinação dos modelos para YA e AC foram de pequena magnitude, provavelmente devido à absorção do efeito de CG. As estimativas de herdabilidade para os escores variaram de 0,13 a 0,36 para C, de 0,32 a 0,36 para P, e de 0,35 a 0,38 para M, considerando todos os modelos utilizados, indicando que C, P e M respondem à seleção direta. A classificação dos animais de acordo com seus valores genéticos, principalmente em relação a C, variou de acordo com os efeitos de ambiente incluídos nos modelos.(AU)