Study of using marker assisted selection on a beef cattle breeding program by model comparison

A data set of a commercial Nellore beef cattle selection program was used to compare breeding models that assumed or not markers effects to estimate the breeding values, when a reduced number of animals have phenotypic, genotypic and pedigree information available. This herd complete data set was composed of 83,404 animals measured for weaning weight (WW), post-weaning gain (PWG), scrotal circumference (SC) and muscle score (MS), corresponding to 116,652 animals in the relationship matrix. Single trait analyses were performed by MTDFREML software to estimate fixed and random effects solutions using this complete data. The additive effects estimated were assumed as the reference breeding values for those animals. The individual observed phenotype of each trait was adjusted for fixed and random effects solutions, except for direct additive effects. The adjusted phenotype composed of the additive and residual parts of observed phenotype was used as dependent variable for models' comparison. Among all measured animals of this herd, only 3160 animals were genotyped for 106 SNP markers. Three models were compared in terms of changes on animals' rank, global fit and predictive ability. Model 1 included only polygenic effects, model 2 included only markers effects and model 3 included both polygenic and markers effects. Bayesian inference via Markov chain Monte Carlo methods performed by TM software was used to analyze the data for model comparison. Two different priors were adopted for markers effects in models 2 and 3, the first prior assumed was a uniform distribution (U) and, as a second prior, was assumed that markers effects were distributed as normal (N). Higher rank correlation coefficients were observed for models 3_U and 3_N, indicating a greater similarity of these models animals' rank and the rank based on the reference breeding values. Model 3_N presented a better global fit, as demonstrated by its low DIC. The best models in terms of predictive ability were models 1 and 3_N. Differences due prior assumed to markers effects in models 2 and 3 could be attributed to the better ability of normal prior in handle with collinear effects. The models 2_U and 2_N presented the worst performance, indicating that this small set of markers should not be used to genetically evaluate animals with no data, since its predictive ability is restricted. In conclusion, model 3_N presented a slight superiority when a reduce number of animals have phenotypic, genotypic and pedigree information. It could be attributed to the variation retained by markers and polygenic effects assumed together and the normal prior assumed to markers effects, that deals better with the collinearity between markers. (C) 2012 Elsevier B.V. All rights reserved.

Depression, fatigue, and health-related quality of life in head and neck cancer patients: a prospective pilot study

To assess the prevalence of depression and fatigue symptoms in head and neck cancer patients during radiotherapy treatment and relate them symptoms with these patients' quality of life. This is a prospective study. The Beck Depression Inventory (BDI), Piper Fatigue Scale-revised and Functional Assessment Cancer Therapy Head and Neck (FACT-H&N) were applied to 41 head and neck cancer patients at three times: at the start of treatment (T1), approximately 15 days after the start of treatment (T2) and at the end of treatment (T3), approximately 30 days after the start of the radiotherapy. The mean BDI and PIPER increased during the radiotherapy treatment. BDI scores did not demonstrate the presence of depression, although the number of symptoms increased, and the presence of fatigue rose as treatment advanced. The mean FACT H&N decreased in the middle and at the end of treatment, indicating worsening in these patients' Quality of Life. Depression and fatigue symptoms increased during radiotherapy treatment, while QoL levels decreased. This demonstrates that these symptoms are strongly correlated and that their presence negatively influenced QoL. At the start of treatment, nurses need to advise patients and plan care, offering interventions to decrease these symptoms and improve QoL.

Assessment of field fertility and several in vitro sperm characteristics following the use of different Angus sires in a timed-AI program with suckled Nelore cows

In order to provide information that may help researchers to understand the main cause(s) of differences in bull fertility frequently observed in field trials, this study aimed to investigate conception rates as well as several in vitro sperm characteristics of different sires of unknown fertility utilized in a Timed-AI (TAI) program. Suckled Nelore cows submitted to the same TAI protocol were allocated into eight breeding groups of approximately 120 animals each. Frozen semen doses from three Angus bulls and three different batches from each bull were utilized. Approximately 100 doses from each batch were used in TAI. Sires, batches and AI technicians were equally distributed across breeding groups. Cows were examined for pregnancy diagnosis 40 d after TAI. For in vitro sperm analyses, the same thawing procedure was repeated in the laboratory to mimic field conditions. The following in vitro sperm characteristics were assessed: computerized motility, thermal resistance, plasma and acrosomal membrane integrity, lipid peroxidation, morphology, morphometry and chromatin structure. No effect of breeding group, body condition score, AI technician and sire was observed. However, some significant differences among bulls were detected in laboratory analyses. Semen from sire presenting numerically lower (P > 0.05) pregnancy/AI also presented lower (P < 0.05) values in all sperm characteristics analyzed in thermal resistance test at 4 h (Total Motility, Progressive Motility, Average Path Velocity, Straight-Line Velocity, Curvilinear Velocity, Amplitude of Lateral Head Displacement, Beat Cross Frequency, Straightness, Linearity, and Percentage of Rapidly Moving Cells), higher (P < 0.05) Major and Total Defects in sperm morphological test, lower (P < 0.05) Length, Ellipticity and Fourier parameter (Fourier 0) in sperm morphometric analysis as well as higher (P < 0.05) chromatin heterogeneity. It was concluded that, although no bull effect was observed in the field experiment, the sire that presented numerically lower pregnancy/AI also presented lower semen quality according to the laboratory analyses performed. (C) 2012 Elsevier B.V. All rights reserved.