RESUMO
The aim of the present study was to use different models that include body composition phenotypes for the evaluation of residual feed intake (RFI) in Nellore bulls of different ages. Phenotypic and genotypic data of bulls that had participated in feed efficiency tests of a commercial (COM) and an experimental (EXP) herd between 2007 and 2019 were used. The mean entry age in the two herds was 645 and 279 days, respectively. The phenotypes were evaluated: rib eye area (REA), backfat thickness (BFT), residual feed intake (RFIKOCH), RFI adjusted for REA (RFIREA), RFI adjusted for BFT (RFIBFT), and RFI adjusted for REA and BFT (RFIREA BFT). The (co)variance components and prediction of genomic estimated breeding values (GEBV) were obtained by REML using ssGBLUP in single and two-trait analyses. Spearman's correlations were calculated based on the GEBV for RFIKOCH. The RFI phenotypes exhibited moderate heritability estimates in both herds (0.17 ± 0.03 to 0.27 ± 0.04). The genetic correlation between phenotypes was positive and high (0.99) in the two herds, a fact that permitted the creation of a single database (SDB). The heritability estimates of the SDB were also of moderate magnitude for the different definitions of RFI (0.19 ± 0.04 to 0.21 ± 0.04). The genetic correlations were positive and high between RFI traits 0.97 ± 0.01 to 0.99 ± 0.01), and positive and low/moderate between REA and BFT (0.01 ± 0.10 to 0.31 ± 0.12). The selection of animals based on the GEBV for RFIKOCH did not alter the ranking of individuals selected for RFIREA, RFIBFT, and RFIREA BFT. The results of the present study suggest that records of Nellore bulls of different ages and with different body compositions can be combined in a SDB for RFI calculation. Therefore, young animals can be evaluated in feed efficiency tests in order to reduce costs and the generation interval and possibly to obtain a higher response to selection.
Assuntos
Composição Corporal , Ingestão de Alimentos , Animais , Bovinos/genética , Ingestão de Alimentos/genética , Genoma , Masculino , Fenótipo , CostelasRESUMO
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.
Assuntos
Lactação , Leite , Animais , Brasil , Bovinos , Ácidos Graxos , Feminino , Resposta ao Choque Térmico/genética , Lactação/genética , GravidezRESUMO
The objectives of this study were to assess the effects of heat stress on the milk yield and investigate the presence of genotype × environment interaction (G × E) in Brazilian Murrah buffaloes reared under tropical conditions. With this, 58,070 test-day (TD) records for milk yield from 3,459 first lactations of buffaloes collected between 1987 and 2018 were evaluated. A mixed model considering days in milk (DIM) and temperature-humidity index (THI) was applied to quantify milk yield losses due to heat stress. The most detrimental effect of THI on TD milk yield was observed in the mid-stages of lactation, after lactation peak, in DIM 105-154 and 155-204 days (-0.020 and -0.015 kg/day per THI, respectively). The least-squares means of TD milk yield were used to identify a heat stress threshold using a piecewise linear regression model. A substantial reduction in TD milk yield due to heat stress was observed for THI values above 77.8 (-0.251 kg/day per increase of 1 THI unit). An analysis using a single-trait random regression animal model was carried out to estimate variance components and genetic parameters for TD milk yield over THI and DIM values. Increased additive genetic variance and heritability estimates were observed for extreme THI values (THI = 60 and 80) combined with mid-lactation stages. The lowest genetic correlation (0.50) was observed between TD records at opposite extremes of the THI scale (THI = 60 vs. THI = 80). The genetic trends observed for the regression coefficients related to the general level of production (0.02) and specific ability to respond to heat stress (-0.002) indicated that selection to increase milk yield did not affect the specific ability to respond to heat stress until the present moment. These trends reflect the low genetic correlation between these components (0.05 ± 0.14). In this sense, monitoring trends of genetic components related to response to heat stress is recommended.
Assuntos
Transtornos de Estresse por Calor , Leite , Animais , Búfalos/genética , Feminino , Transtornos de Estresse por Calor/genética , Transtornos de Estresse por Calor/veterinária , Resposta ao Choque Térmico/genética , Temperatura Alta , LactaçãoRESUMO
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.
Assuntos
Lactação , Leite , Animais , Bovinos/genética , Feminino , Umidade , Masculino , Fenótipo , TemperaturaRESUMO
Gene-environment (GE) interaction has important implications in the etiology of complex diseases that are caused by a combination of genetic factors and environment variables. Several authors have developed GE analysis in the context of independent subjects or longitudinal data using a gene-set. In this paper, we propose to analyze GE interaction for discrete and continuous phenotypes in family studies by incorporating the relatedness among the relatives for each family into a generalized linear mixed model (GLMM) and by using a gene-based variance component test. In addition, we deal with collinearity problems arising from linkage disequilibrium among single nucleotide polymorphisms (SNPs) by considering their coefficients as random effects under the null model estimation. We show that the best linear unbiased predictor (BLUP) of such random effects in the GLMM is equivalent to the ridge regression estimator. This equivalence provides a simple method to estimate the ridge penalty parameter in comparison to other computationally-demanding estimation approaches based on cross-validation schemes. We evaluated the proposed test using simulation studies and applied it to real data from the Baependi Heart Study consisting of 76 families. Using our approach, we identified an interaction between BMI and the Peroxisome Proliferator Activated Receptor Gamma (PPARG) gene associated with diabetes.