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.

Arthrospira platensis biomass with high protein content cultivated in continuous process using urea as nitrogen source

Aims: Arthrospira platensis has been studied for single-cell protein production because of its biomass composition and its ability of growing in alternative media. This work evaluated the effects of different dilution rates (D) and urea concentrations (N0) on A.similar to platensis continuous culture, in terms of growth, kinetic parameters, biomass composition and nitrogen removal. Methods and results: Arthrospira platensis was continuously cultivated in a glass-made vertical column photobioreactor agitated with Rushton turbines. There were used different dilution rates (0.040.44 day-1) and urea concentrations (0.5 and 5 mmol l-1). With N0 = 5 mmol l-1, the maximum steady-state biomass concentration was1415 mg l-1, achieved with D = 0.04 day-1, but the highest protein content (71.9%) was obtained by applying D = 0.12 day-1, attaining a protein productivity of 106.41 mg l-1 day-1. Nitrogen removal reached 99% on steady-state conditions. Conclusions: The best results were achieved by applying N0 = 5 mmol l-1; however, urea led to inhibitory conditions at D = 0.16 day-1, inducing the system wash-out. The agitation afforded satisfactory mixture and did not harm the trichomes structure. Significance and Impact of the Study: These results can enhance the basis for the continuous removal of nitrogenous wastewater pollutants using cyanobacteria, with an easily assembled photobioreactor.

Impaired lung function in individuals chronically exposed to biomass combustion

Background: The use of biomass for cooking and heating is considered an important factor associated with respiratory diseases. However, few studies evaluate the amount of particulate matter less than 2.5 mu in diameter (PM2.5), symptoms and lung function in the same population. Objectives: To evaluate the respiratory effects of biomass combustion and compare the results with those of individuals from the same community in Brazil using liquefied petroleum gas (Gas). Methods: 1402 individuals in 260 residences were divided into three groups according to exposure (Gas, Indoor-Biomass, Outside-Biomass). Respiratory symptoms were assessed using questionnaires. Reflectance of paper filters was used to assess particulate matter exposure. In 48 residences the amount of PM2.5 was also quantified. Pulmonary function tests were performed in 120 individuals. Results: Reflectance index correlated directly with PM2.5 (r=0.92) and was used to estimate exposure (ePM2.5). There was a significant increase in ePM2.5 in Indoor-Biomass and Outside-Biomass, compared to Gas. There was a significantly increased odds ratio (OR) for cough, wheezing and dyspnea in adults exposed to Indoor-Biomass (OR=2.93, 2.33, 2.59, respectively) and Outside-Biomass (OR=1.78, 1.78, 1.80, respectively) compared to Gas. Pulmonary function tests revealed both Non-Smoker-Biomass and Smoker-Gas individuals to have decreased %predicted-forced expiratory volume in the first second (FEV1) and FEV1/forced vital capacity (FVC) as compared to Non-Smoker-Gas. Pulmonary function tests data was inversely correlated with duration and ePM2.5. The prevalence of airway obstruction was 20% in both Non-Smoker-Biomass and Smoker-Gas subjects. Conclusion: Chronic exposure to biomass combustion is associated with increased prevalence of respiratory symptoms, reduced lung function and development of chronic obstructive pulmonary disease. These effects are associated with the duration and magnitude of exposure and are exacerbated by tobacco smoke. (C) 2011 Elsevier Inc. All rights reserved.

Homeobox gene expression profile indicates HOXA5 as a candidate prognostic marker in oral squamous cell carcinoma

The search for molecular markers to improve diagnosis, individualize treatment and predict behavior of tumors has been the focus of several studies. This study aimed to analyze homeobox gene expression profile in oral squamous cell carcinoma (OSCC) as well as to investigate whether some of these genes are relevant molecular markers of prognosis and/or tumor aggressiveness. Homeobox gene expression levels were assessed by microarrays and qRT-PCR in OSCC tissues and adjacent non-cancerous matched tissues (margin), as well as in OSCC cell lines. Analysis of microarray data revealed the expression of 147 homeobox genes, including one set of six at least 2-fold up-regulated, and another set of 34 at least 2-fold down-regulated homeobox genes in OSCC. After qRT-PCR assays, the three most up-regulated homeobox genes (HOXA5, HOXD10 and HOXD11) revealed higher and statistically significant expression levels in OSCC samples when compared to margins. Patients presenting lower expression of HOXA5 had poorer prognosis compared to those with higher expression (P=0.03). Additionally, the status of HOXA5, HOXD10 and HOXD11 expression levels in OSCC cell lines also showed a significant up-regulation when compared to normal oral keratinocytes. Results confirm the presence of three significantly upregulated (>4-fold) homeobox genes (HOXA5, HOXD10 and HOXD11) in OSCC that may play a significant role in the pathogenesis of these tumors. Moreover, since lower levels of HOXA5 predict poor prognosis, this gene may be a novel candidate for development of therapeutic strategies in OSCC.

Active crop sensor to detect variability of nitrogen supply and biomass on sugarcane fields

Nitrogen management has been intensively studied on several crops and recently associated with variable rate on-the-go application based on crop sensors. Such studies are scarce for sugarcane and as a biofuel crop the energy input matters, seeking high positive energy balance production and low carbon emission on the whole production system. This article presents the procedure and shows the first results obtained using a nitrogen and biomass sensor (N-Sensor (TM) ALS, Yara International ASA) to indicate the nitrogen application demands of commercial sugarcane fields. Eight commercial fields from one sugar mill in the state of Sao Paulo, Brazil, varying from 15 to 25 ha in size, were monitored. Conditions varied from sandy to heavy soils and the previous harvesting occurred in May and October 2009, including first, second, and third ratoon stages. Each field was scanned with the sensor three times during the season (at 0.2, 0.4, and 0.6 m stem height), followed by tissue sampling for biomass and nitrogen uptake at ten spots inside the area, guided by the different values shown by the sensor. The results showed a high correlation between sensor values and sugarcane biomass and nitrogen uptake, thereby supporting the potential use of this technology to develop algorithms to manage variable rate application of nitrogen for sugarcane.