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.