Genomic prediction in Brazilian Guzerá cattle: application of a single-step approach to productive and reproductive traits.

This study aimed to investigate the feasibility of genomic prediction for productive and reproductive traits in Guzerá cattle using single-step genomic best linear unbiased prediction (ssGBLUP). Evaluations included the 305-day cumulative yields (first lactation, in kg) of milk, lactose, protein, fat, and total solids; adjusted body weight (kg) at the ages of 450, 365, and 210 days; and age at first calving (in days), from a database containing 197,283 measurements from Guzerá males and females born between 1954 and 2018. The pedigree included 433,823 animals spanning up to 14 overlapping generations. A total of 1618 animals were genotyped. The analyses were performed using ssGBLUP and traditional BLUP methods. Predictive ability and bias were accessed using cross-validation: predictive ability was similar between the methods and ranged from 0.27 to 0.47 for the genomic-based model and from 0.30 to 0.45 for the pedigree-based model; the bias was also similar between the methods, ranging from 0.88 to 1.35 in the genomic-based model and from 0.96 to 1.41 in the pedigree-based model. The individual accuracies of breeding values were evidently increased in the genomic evaluation, with values ranging from 0.41 to 0.56 in the genomic-based model and from 0.26 to 0.54 in the pedigree-based model. Even based on a small number of genotyped animals and a small database for some traits, the results suggest that ssGBLUP is feasible and may be applied to national genetic evaluation of the breed to increase the accuracy of breeding values without greatly impacting predictive ability and bias.

Genetic parameters for milk, growth, and reproductive traits in Guzerá cattle under tropical conditions.

This study aimed to estimate the genetic parameters of milk (305-day milk yield (MY305)), growth (weaning weight (WW), yearling weight (YW), and weight at 550 days (W550)), and reproductive (age at first calving (AFC)) traits in Guzerá cattle by using Bayesian multiple-trait models. Systematic effects included sex and age at calving for the growth and milk traits, respectively. The additive genetic and contemporary groups (herd and year and season of birth) were included as random effects. Additionally, maternal genetic and permanent effects were also included as random effects for the WW. The heritability estimates were 0.29 (MY305), 0.42 (WW), 0.49 (YW), 0.56 (W550), and 0.25 (AFC). The genetic correlations among the growth traits were higher than 0.83; between the MY305 and WW, MY305 and YW, and MY305 and W550, the genetic correlations were 0.25, 0.32, and 0.36, respectively. The AFC was negatively correlated with the milk and growth traits. These results suggest the viability and potential of the joint selection for milk, beef, and reproductive traits in Guzerá cattle.

Selection for feed efficiency does not change the selection for growth and carcass traits in Nellore cattle.

The objectives were to conduct a genetic evaluation of residual feed intake (RFI) and residual feed intake adjusted for fat (RFIFat) and to analyse the effect of selection for these traits on growth, carcass and reproductive traits. Data from 945 Nellore bulls in seven feed efficiency tests in a feedlot were analysed. Genetic evaluation was performed using an animal model in which the feed efficiency test and age of the animal at the beginning of the test were considered as a systematic effect. Direct additive genetic and residual effects were considered as random effects. Correlations and genetic gains were estimated by two-trait analysis between feed efficiency measures (RFI and RFIFat) and other traits. Feed conversion showed low heritability (0.06), but dry matter intake (DMI), average daily gain, RFI, RFIFat, metabolic body weight and scrotal circumference measured at 450 days of age (SC450) showed moderate to high heritability (0.49, 0.28, 0.33, 0.36, 0.38 and 0.80, respectively). Similarly, ribeye area, backfat thickness, rump cap fat thickness, marbling score and subcutaneous fat thickness also had high heritability values (0.46, 0.37, 0.57, 0.51 and 0.47, respectively). Genetic correlations between RFI and SC450 were null, and between RFIFat and SC450 were strongly positive. Genetic and phenotypic correlations of RFI and RFIFat with carcass traits were not different from zero, as correlated responses for carcass traits were also not different from zero. The Nellore selection for feed efficiency by RFI or RFIFat allows the recognition of feed efficient animals, with DMI reduction and without significant changes in growth and carcass traits. However, because of the observed results between RFIFat and SC450, selection of animals should be analysed with caution and a preselection for reproductive traits is necessary to avoid reproductive impairments in the herd.

Increased STAT1 Expression in High Grade Serous Ovarian Cancer Is Associated With a Better Outcome.

OBJECTIVE: Recently it has been demonstrated that constitutively activated signal transducer and activator of transcription 1 (STAT1) gene expression may act as a biomarker of ovarian cancer chemotherapy response. In this study, our objective was to validate the use of STAT1 immunohistochemistry as a prognostic biomarker for disease outcome using a cohort derived from Latin America. METHODS: We evaluated a cohort of Brazilian high-grade serous ovarian cancer, comprising 65 patients with outcome data covering more than 5 years to determine the prognostic and predictive value of STAT1 expression levels. High-grade serous ovarian cancer tumors were used to construct a tissue microarray. Exploratory analyses were conducted on clinical, histopathological, and STAT1 expression data that included descriptive statistics and Pearson correlative analyses. Survival curves for disease-free survival and overall survival were obtained by the Kaplan-Meier method, and the significance of homogeneity between the classes was assessed by log-rank statistics (Mantel-Cox). RESULTS: High expression of STAT1 in tumors was significantly associated with improved disease-free survival (P = 0.0256) and overall survival (P = 0.0193). Proportional hazards regression analysis showed STAT1 expression had an independent effect on both disease-free survival (P = 0.0358) and overall survival (P = 0.0469). CONCLUSIONS: These findings from a Brazilian cohort of patients with ovarian cancer reinforce the association of high STAT1 expression with better response to chemotherapy, providing additional validation of this protein as both a prognostic and predictive biomarker. Collectively, these results together with other recently published studies increase the feasibility of using the STAT1 pathway for the development of novel immunomodulator drugs that could enhance response to treatment.

Genetic study of quantitative traits supports the use of Guzerá as dual-purpose cattle.

OBJECTIVE: The aim of this study was to estimate genetic parameters for 305-day cumulative milk yield and components, growth, and reproductive traits in Guzerá cattle. METHODS: The evaluated traits were 305-day first-lactation cumulative yields (kg) of milk (MY305), fat (FY305), protein (PY305), lactose (LY305), and total solids (SY305); age at first calving (AFC) in days; adjusted scrotal perimeter (cm) at the ages of 365 (SP365) and 450 (SP450) days; and adjusted body weight (kg) at the ages of 210 (W210), 365 (W365), and 450 (W450) days. The (co)variance components were estimated using the restricted maximum likelihood method for single-trait, bi-trait and tri-trait analyses. Contemporary groups and additive genetic effects were included in the general mixed model. Maternal genetic and permanent environmental effects were also included for W210. RESULTS: The direct heritability estimates ranged from 0.16 (W210) to 0.32 (MY305). The maternal heritability estimate for W210 was 0.03. Genetic correlation estimates among milk production traits and growth traits ranged from 0.92 to 0.99 and from 0.92 to 0.99, respectively. For milk production and growth traits, the genetic correlations ranged from 0.33 to 0.56. The genetic correlations among AFC and all other traits were negative (-0.43 to -0.27). Scrotal perimeter traits and body weights showed genetic correlations ranging from 0.41 to 0.46, and scrotal perimeter and milk production traits showed genetic correlations ranging from 0.11 to 0.30. The phenotypic correlations were similar in direction (same sign) and lower than the corresponding genetic correlations. CONCLUSION: These results suggest the viability and potential of joint selection for dairy and beef traits in Guzerá cattle, taking into account reproductive traits.

Genetic parameters for growth, reproductive, and carcass traits in Tabapuã cattle

We aimed to estimate genetic parameters for growth, reproductive, and carcass traits in Tabapuã cattle. Phenotypic data were collected between 1990 and 2019 in 1,218 farms, and the pedigree file had 340,868 animals. The traits evaluated were body weight at 120 (W120), 210 (W210), 365 (W365), and 550 (W550) days of age; age at first calving (AFC), scrotal circumference at 365 days of age (SC365), ribeye area (REA), backfat thickness (BF), and rump fat thickness (RF). The (co)variance components were estimated using the restricted maximum likelihood method, considering single and two-traits animal models. For all traits, the models considered fixed, direct additive genetic, and residual random effects. In addition, for W120 and W210, the maternal additive genetic and maternal permanent environmental effects were also included. Heritabilities for W120, W210, W365, W550, SC365, REA, BF, and RF were of moderate magnitude (0.15, 0.16, 0.23, 0.19, 0.22, 0.36, 0.31, and 0.27, respectively). Low heritability was observed for AFC (0.07). The genetic correlations between growth traits were higher than 0.90, while AFC and SC365 presented negative moderate correlation (−0.66). The REA showed low genetic correlations with BF (0.07) and RF (0.07), whereas BF and RF were highly correlated (0.77). Considering the heritability estimates, selection for AFC would result in limited genetic gain, while for the other traits, it would be satisfactory. Based on the high genetic correlations between growth traits, selection of Tabapuã animals can be performed at younger ages. Additionally, animals can be indirectly selected for AFC through SC365, and only one fat thickness trait may be used in the selection process considering the high genetic correlation and similar heritability values for BF and RF.(AU)

Modelos multicaracterísticos e de repetibilidade para avaliação genética de características de leitegada em suínos considerando diferentes partos / Multi-trait and repeatability models for genetic evaluation of litter traits in pigs considering different farrowings

Objetivou-se comparar os modelos multicaracterístico e de repetibilidade na estimação de parâmetros genéticos para as características número de leitões nascidos vivos (NLN) e às três semanas de idade (NL3), peso da leitegada ao nascimento (PLN) e às três semanas de idade (PL3), e peso médio do leitão ao nascimento (PMLN) e às três semanas de idade (PML3), considerando os três primeiros partos de fêmeas da raça Landrace. As estimativas de herdabilidade (h2 ) aumentaram até a terceira ordem de parto para as características PLN e PML3. Para NLN, NL3, PL3 e PMLN as h2 aumentaram da primeira para a segunda parição e reduziram da segunda para terceira parição. Em geral, as herdabilidades estimadas via modelo de repetibilidade foram menores que a média das estimativas obtidas utilizando o modelo muticaracterístico. As características PLN, PMLN e PML3 apresentaram altas correlações genéticas entre as diferentes parições (0,961- 0,997), enquanto as características NLN, NL3 e PL3 (0,092-0,986) apresentaram valores irregulares de correlações genéticas entre as parições. Pelo critério de informação de Akaike corrigido o modelo de repetibilidade não foi indicado para a maioria das características estudadas. Esses resultados indicam que o modelo multicaracterístico é recomendado para avaliação genética das características número de leitões nascidos vivos e às três semanas de idade, peso da l(AU)

We aimed to compare multi-trait and repeatability models to estimate genetic parameters for the traits number of piglets born alive (NBA) and alive at 3 week of age (NP3), litter weight at birth (LW0) and at 3 week of age (LW3), and mean piglet weight at birth (MW0) and at 3 week of age (MW3), considering the first three farrowings of Landrace sows. Heritability (h2 ) estimates showed an increasing pattern up to the third farrowing for LW0 and MW3. For NBA, NP3, LW3, and MW0 h 2 increased from the first to the second and decreased from the second to the third farrowing. In general, heritability estimated in the repeatability model was lower than the mean of the estimates in the multi-trait model. The traits LWO, MW0, and MW3 presented high genetic correlation among different farrowings (0.961 0.997), while NBA, NP3, and LW3 (0.0920.986) presented irregular values among farrowings. The corrected Akaike information criterion shows that the repeatability model is not indicated for almost all of the studied traits. These results indicate that the multi-trait model is recommended for genetic evaluation of the traits number of piglets born alive and alive at 3 week of age, litter weight and mean piglet weight at birth and 3 week of age, in different farrowings, as different traits.(AU)

Modelos multicaracterísticos e de repetibilidade para avaliação genética de características de leitegada em suínos considerando diferentes partos / Multi-trait and repeatability models for genetic evaluation of litter traits in pigs considering different farrowings

Objetivou-se comparar os modelos multicaracterístico e de repetibilidade na estimação de parâmetros genéticos para as características número de leitões nascidos vivos (NLN) e às três semanas de idade (NL3), peso da leitegada ao nascimento (PLN) e às três semanas de idade (PL3), e peso médio do leitão ao nascimento (PMLN) e às três semanas de idade (PML3), considerando os três primeiros partos de fêmeas da raça Landrace. As estimativas de herdabilidade (h2 ) aumentaram até a terceira ordem de parto para as características PLN e PML3. Para NLN, NL3, PL3 e PMLN as h2 aumentaram da primeira para a segunda parição e reduziram da segunda para terceira parição. Em geral, as herdabilidades estimadas via modelo de repetibilidade foram menores que a média das estimativas obtidas utilizando o modelo muticaracterístico. As características PLN, PMLN e PML3 apresentaram altas correlações genéticas entre as diferentes parições (0,961- 0,997), enquanto as características NLN, NL3 e PL3 (0,092-0,986) apresentaram valores irregulares de correlações genéticas entre as parições. Pelo critério de informação de Akaike corrigido o modelo de repetibilidade não foi indicado para a maioria das características estudadas. Esses resultados indicam que o modelo multicaracterístico é recomendado para avaliação genética das características número de leitões nascidos vivos e às três semanas de idade, peso da l

We aimed to compare multi-trait and repeatability models to estimate genetic parameters for the traits number of piglets born alive (NBA) and alive at 3 week of age (NP3), litter weight at birth (LW0) and at 3 week of age (LW3), and mean piglet weight at birth (MW0) and at 3 week of age (MW3), considering the first three farrowings of Landrace sows. Heritability (h2 ) estimates showed an increasing pattern up to the third farrowing for LW0 and MW3. For NBA, NP3, LW3, and MW0 h 2 increased from the first to the second and decreased from the second to the third farrowing. In general, heritability estimated in the repeatability model was lower than the mean of the estimates in the multi-trait model. The traits LWO, MW0, and MW3 presented high genetic correlation among different farrowings (0.961 0.997), while NBA, NP3, and LW3 (0.0920.986) presented irregular values among farrowings. The corrected Akaike information criterion shows that the repeatability model is not indicated for almost all of the studied traits. These results indicate that the multi-trait model is recommended for genetic evaluation of the traits number of piglets born alive and alive at 3 week of age, litter weight and mean piglet weight at birth and 3 week of age, in different farrowings, as different traits.

Modelos multicaracterísticos na avaliação genética de tamanho de leitegada em suínos / Multiple trait models in genetic evaluation of litter traits in pigs

O objetivo desse estudo foi avaliar geneticamente características de leitegada em suínos da raça Landrace, com a utilização de modelos bicaracterísticos linear e Poisson via metodologia Bayesiana, modelos tricaracterísticos linear e Poisson via metodologia Bayesiana, e modelos ulticaracterístico e de repetibilidade via máxima verossimilhança restrita (REML). Foram avaliadas as seguintes características: número de leitões nascidos no primeiro parto (NLN1), número de leitões nascidos no segundo parto (NLN2), número de leitões nascidos no terceiro parto (NLN3), número de leitões desmamados no primeiro parto (NLD1), número de leitões desmamados no segundo parto (NLD2) e número de leitões desmamados no terceiro parto (NLD3). Com os modelos bicaracterístico linear e bicaracterístico Poisson foram realizadas análises bicaracterísticas dentro de partos para número de leitões nascidos e número de leitões desmamados. Com os modelos tricaracterístico linear e tricaracterístico Poisson foram realizadas análises tri-características entre partos com três parições para o número de leitões nascidos e três parições para o número de leitões desmamados. Com os modelos multicaracterístico e de repetibilidade também foram realizadas análises entre partos para as mesmas características. Para as análises bi-características dentro de partos observou-se que as correlações genéticas entre o número de leitões nascidos e o número de leitões desmamados foram positivas e altas no primeiro, segundo e terceiro parto, o que indica que a seleção para aumento número de leitões nascidos resultará em ganho genético no número de leitões desmamados, que é uma característica de maior importância econômica. Com base no DIC (critério de informação da deviance) o modelo linear é o mais indicado para se obter as distribuições a posteriori das herdabilidades e correlações genéticas para número de leitões nascidos e número de leitões desmamados nas três primeiras ordens de parto. Conclui-se que as características número de leitões nascidos e número de leitões desmamados são de baixa herdabilidade e estão positivamente correlacionadas entre si nas três ordens de parto avaliadas, e que o modelo bicaracterístico linear misto é o mais indicado para avaliar os animais desta população. Para as análises tri-características entre partos foi observado que as herdabilidades no primeiro, segundo e terceiro partos foram pouco diferentes tanto para o número de leitões nascidos, quanto para o número de leitões desmamados. O modelo linear foi o que melhor se ajustou aos dados nas análises tri-características entre partos, para todas as características avaliadas, considerando o DIC (critério de informação da deviance) como critério de comparação dos modelos. Foi concluído que as características avaliadas neste estudo são de baixa herdabilidade e devem ser analisadas com a utilização de um modelo tricaracterístico linear misto. Para as análises entre partos com os modelos multicaracterístico e de repetibilidade, via REML, observou-se uma tendência de aumento da variância genética aditiva e da herdabilidade ao longo das ordens de parto. Verificou-se que a estimativa de variância genética aditiva para número de leitões nascidos e para número de leitões desmamados no primeiro parto foi a mais discrepante em relação aos valores dessas estimativas para as demais ordens de parto, o que indica que, provavelmente, a expressão dessas características no primeiro parto é controlada por genes ou combinações gênicas diferentes daquelas que regulam a expressão do número de leitões nascidos, e do número de leitões desmamados no segundo e no terceiro parto. Foi possível concluir que o modelo multicaracterístico é o mais indicado para avaliação genética das características número de leitões nascidos número de leitões desmamados nas três primeiras ordens de parto

The aim of this study was to evaluate genetically litter traits in Landrace pigs, with the use of linear and Poisson bi-trait models via Bayesian methodology, linear and Poisson tri-trait models via Bayesian methodology and multi-trait and repeatability models via restricted maximum likelihood (REML). We obtained the following traits: number of piglets at first farrowing (NLN1), number of piglets born at second farrowing (NLN2), number of piglets at third farrowing (NLN3), number of piglets weaned at first farrowing (NLD1) number of piglets weaned at second farrowing (NLD2) and number of piglets weaned at third farrowing (NLD3). The bi-trait linear and bi-trait Poisson models analyzes were performed within parities, and two traits were used in each farrowing: number of piglets born and number of piglets weaned. The tri-trait linear and tri-trait Poisson models were analyzed across three orders of farrowing for the number of piglets born and for number of piglets weaned. Multi-trait models and repeatability model were analyzed across three orders of farrowing with the same traits. For bi-trait analysis within parities was observed that the genetic correlations between the number of piglets born and number of weaned piglets were positive and high in the first, second and third farrowing, which indicates that selection for increased number of piglets born result in genetic gain in the number of piglets weaned, which is a trait of greater economic importance. Based on DIC (deviance information criterion), linear model is the most appropriate to estimate the posterior distributions of heritabilities and genetic correlations for number of piglets born and number of piglets weaned in the first three orders of farrowing because it was the best fit of the data and less degree of complexity based on the criterion used. We conclude that number of piglets born and number of piglets weaned are of low heritability and are positively correlated between then in the three farrowing orders evaluated, and that the bitrait linear mixed model is the most appropriate to evaluate the animals in this population. For tri-trait across parities analysis was observed that the heritabilities in the first, second and third orders of farrowing were unequal both for the number of piglets born, and for the number of piglets weaned. The linear model was the best fit in the data for all traits evaluated considering DIC (deviance information criterion) as the criterion for comparing models. It was concluded that the traits evaluated in this study have low heritability and should be analyzed using a tri-trait linear mixed model. For the analyzes with multi-trait and repeatability models across three orders of farrowing, via REML, there was a trend of increased additive genetic variance and heritability along the orders of farrowing. It was found that the estimate of additive genetic variance for number of piglets born and number of piglets weaned at first farrowing was the most discrepant from the values of these estimates for all other orders of farrowing, indicating that probably the expression these characteristics at the first farrowing is controlled by genes or gene combinations other than those that regulate the expression of number of piglets born, and the number of piglets weaned in the second and third farrowing. It was concluded that the multi-trait is the most suitable for genetic evaluation of number of piglets born and number of piglets weaned in the first three orders of farrowing