Multiple trait and random regression models using linear splines for genetic evaluation of multiple breed populations.

This study aimed to verify if random regression models using linear splines (RRMLS) are suitable for identifying genetic parameters in multiple-breed populations and also to investigate whether an interaction exists between the breeding value (BV) of sires and their progeny breed group. Ten populations were simulated by crossing 2 breeds with distinct genetic variance and nonzero segregation variance. To obtain the genetic parameters, 2 models were used: a multiple-trait model (MULT), in which the trait was considered distinct when evaluated in each group (1/2P1 + 1/2P2, 5/8P1 + 3/8P2, and 3/4P1 + 1/4P2), and a RRMLS with the spline polynomial knots adjusted to these same groups. The genetic parameters estimated through MULT and RRMLS did not differ from the simulated values. The correlations between BV (simulated and estimated) of animals were high and varied from 0.74 to 0.76, which indicates the efficiency of using MULT and RRMLS for predicting BV. Using field data, the traits age at first calving (AFC), first lactation length (LL), and 305-d milk yield (MY-305) from a multiple-breed population of Holstein-Gyr cattle were analyzed. The BV of animals were modeled through RRMLS with 3, 5, and 7 knots, distributed in accordance with the fraction of Holstein breed in each progeny breed group. It was verified that RRMLS with 7 knots for adjusting mean trajectories and genetic effects, with homogeneous residual variance, best fit AFC and LL. For MY-305, the best fit for mean trajectory and genetic effects was the RRMLS with 5 knots and with homogeneous residual variance. The posterior means of heritability varied from 0.21 to 0.48, 0.21 to 0.38, and 0.10 to 0.33 for AFC, LL, and MY-305, respectively. Estimates from genetic parameters obtained by using RRMLS with field data showed that this model is a useful tool for genetic evaluations of populations formed by a great number of breed groups. An interaction occurred between the BV of sires and their progeny breed group, and the genetic parameters for AFC, LL, and MY-305 traits from a multiple-breed population depend on breed composition of the progeny from which the evaluations are based.

Pre- and post-puberty expression of genes and proteins in the uterus of Bos indicus heifers: the luteal phase effect post-puberty.

Progesterone signaling and uterine function are crucial in terms of pregnancy establishment. To investigate how the uterine tissue and its secretion changes in relation to puberty, we sampled tissue and uterine fluid from six pre- and six post-pubertal Brahman heifers. Post-pubertal heifers were sampled in the luteal phase. Gene expression of the uterine tissue was investigated with RNA-sequencing, whereas the uterine fluid was used for protein profiling with mass spectrometry. A total of 4034 genes were differentially expressed (DE) at a nominal P-value of 0.05, and 26 genes were significantly DE after Bonferroni correction (P < 3.1 × 10-6 ). We also identified 79 proteins (out of 230 proteins) that were DE (P < 1 × 10-5 ) in the uterine fluid. When we compared proteomics and transcriptome results, four DE proteins were identified as being encoded by DE genes: OVGP1, GRP, CAP1 and HBA. Except for CAP1, the other three had lower expression post-puberty. The function of these four genes hypothetically related to preparation of the uterus for a potential pregnancy is discussed in the context of puberty. All DE genes and proteins were also used in pathway and ontology enrichment analyses to investigate overall function. The DE genes were enriched for terms related to ribosomal activity. Transcription factors that were deemed key regulators of DE genes are also reported. Transcription factors ZNF567, ZNF775, RELA, PIAS2, LHX4, SOX2, MEF2C, ZNF354C, HMG20A, TCF7L2, ZNF420, HIC1, GTF3A and two novel genes had the highest regulatory impact factor scores. These data can help to understand how puberty influences uterine function.

Genotype × environment interaction in individual performance and progeny tests in beef cattle.

The study reported here evaluated genotype × environment interaction in individual performance and progeny tests in beef cattle. Genetic parameters for final weight (FW), ADG, and scrotal circumference (SC) of 33,013 Nellore young bulls tested on pasture or in feedlots were analyzed. The posterior means (and highest posterior density interval with 90% of samples [HPD90]) of heritability for traits measured on pasture-raised and feedlot-raised animals were 0.44 (HPD90 = 0.40 to 0.48) and 0.50 (HPD90 = 0.43 to 0.56) for FW, 0.26 (HPD90 = 0.23 to 0.29) and 0.26 (HPD90 = 0.20 to 0.32) for ADG, and 0.53 (HPD90 = 0.48 to 0.59) and 0.65 (HPD90 = 0.55 to 0.74) for SC, respectively. The posterior means (and HPD90) of genetic correlations for FW, ADG, and SC on pasture and in feedlots were 0.75 (HPD90 = 0.66 to 0.87), 0.49 (HPD90 = 0.31 to 0.66), and 0.89 (HPD90 = 0.83 to 0.97), respectively. When the selection intensity was kept the same for both the environments, the greatest direct responses for FW and ADG were exhibited by the animals reared and selected in feedlots. The correlated responses relative to production on pasture and based on selection in feedlots were similar to the direct responses, whereas the correlated responses for production in feedlots and based on selection on pasture were lower than the direct responses. When the selection intensity on pasture was higher than the selection intensity in feedlots, the responses to direct selection were similar for both the environments and correlated responses obtained in feedlots by selection on pasture were similar to the direct responses in feedlots. Analyses of few or poor indicators of genotype × environment interaction result in incorrect interpretations of its existence and implications. The present work demonstrated that traits with lower heritability are more susceptible to genotype × environment interaction and that selection intensity plays an important role in the study of genotype × environment interaction in beef cattle.

Probability of pregnancy in beef heifers / Probabilidade de prenhez em novilhas de corte

This study aimed to evaluate the influence of initial weight, initial age, average daily gain in initial weight, average daily gain in total weight and genetic group on the probability of pregnancy in primiparous females of the Nellore, 1/2 Simmental + 1/2 Nellore, and 3/4 Nellore + 1/4 Simmental genetic groups. Data were collected from the livestock file of the Farpal Farm, located in the municipality of Jaíba, Minas Gerais State, Brazil. The pregnancy diagnosis results (success = 1 and failure = 0) were used to determine the probability of pregnancy that was modeled using logistic regression by the Proc Logistic procedure available on SAS (Statistical..., 2004) software, from the regressor variables initial weight, average daily gain in initial weight, average daily gain in total weight, and genetic group. Initial weight (IW) was the most important variable in the probability of pregnancy in heifers, and 1-kg increments in IW allowed for increases of 5.8, 9.8 and 3.4% in the probability of pregnancy in Nellore, 1/2 Simmental + 1/2 Nellore and, 3/4 Nellore + 1/4 Simmental heifers, respectively. The initial age influenced the probability of pregnancy in Nellore heifers. From the estimates of the effects of each variable it was possible to determine the minimum initial weights for each genetic group. This information can be used to monitor the development of heifers until the breeding season and increase the pregnancy rate...

Objetivou-se avaliar a influência do peso inicial, idade inicial, ganho médio diário em peso inicial, ganho médio diário em peso total e grupo genético sobre a probabilidade de prenhez de fêmeas primíparas da raça Nellore, 1/2 Simental + 1/2 Nelore e 3/4 Nelore + 1/4 Simental. Os dados analisados foram do arquivo zootécnico da Fazenda Farpal, localizada no município de Jaíba, Minas Gerais. O resultado do diagnóstico de gestação (sucesso=1 e insucesso=0) foi utilizado para determinar a probabilidade de prenhez que foi modelada por meio de regressão logística pelo procedimento Logistic disponível no SAS, a partir das variáveis regressoras peso inicial, ganho médio diário em peso inicial, ganho médio diário em peso total e grupo genético. O peso inicial foi a variável de maior relevância na probabilidade de prenhez de novilhas e incrementos de 1,0kg no peso inicial possibilitaram acréscimos de 5,8; 9,8 e 3,4% na probabilidade de prenhez de novilhas Nelore, 1/2 Simental + 1/2 Nelore e 3/4 Nelore + 1/4 Simental, respectivamente. Entretanto o ganho médio diário em peso inicial e ganho médio diário em peso total não apresentaram efeito significativo na probabilidade de prenhez das novilhas. A idade inicial influenciou a probabilidade de prenhez das novilhas Nelore. A partir das estimativas dos efeitos de cada variável, foi possível determinar o peso inicial mínimo para cada grupo genético. Essa informação pode ser usada para monitorar o desenvolvimento de novilhas até a estação de monta e aumentar a taxa de prenhez...