Comparison of selective genotyping strategies for prediction of breeding values in a population undergoing selection

Genomewide marker information can improve the reliability of breeding value predictions for young selection candidates in genomic selection. However, the cost of genotyping limits its use to elite animals, and how such selective genotyping affects predictive ability of genomic selection models is an open question. We performed a simulation study to evaluate the quality of breeding value predictions for selection candidates based on different selective genotyping strategies in a population undergoing selection. The genome consisted of 10 chromosomes of 100 cM each. After 5,000 generations of random mating with a population size of 100 (50 males and 50 females), generation G(0) (reference population) was produced via a full factorial mating between the 50 males and 50 females from generation 5,000. Different levels of selection intensities (animals with the largest yield deviation value) in G(0) or random sampling (no selection) were used to produce offspring of G(0) generation (G(1)). Five genotyping strategies were used to choose 500 animals in G(0) to be genotyped: 1) Random: randomly selected animals, 2) Top: animals with largest yield deviation values, 3) Bottom: animals with lowest yield deviations values, 4) Extreme: animals with the 250 largest and the 250 lowest yield deviations values, and 5) Less Related: less genetically related animals. The number of individuals in G(0) and G(1) was fixed at 2,500 each, and different levels of heritability were considered (0.10, 0.25, and 0.50). Additionally, all 5 selective genotyping strategies (Random, Top, Bottom, Extreme, and Less Related) were applied to an indicator trait in generation G(0), and the results were evaluated for the target trait in generation G(1), with the genetic correlation between the 2 traits set to 0.50. The 5 genotyping strategies applied to individuals in G(0) (reference population) were compared in terms of their ability to predict the genetic values of the animals in G(1) (selection candidates). Lower correlations between genomic-based estimates of breeding values (GEBV) and true breeding values (TBV) were obtained when using the Bottom strategy. For Random, Extreme, and Less Related strategies, the correlation between GEBV and TBV became slightly larger as selection intensity decreased and was largest when no selection occurred. These 3 strategies were better than the Top approach. In addition, the Extreme, Random, and Less Related strategies had smaller predictive mean squared errors (PMSE) followed by the Top and Bottom methods. Overall, the Extreme genotyping strategy led to the best predictive ability of breeding values, indicating that animals with extreme yield deviations values in a reference population are the most informative when training genomic selection models.

Analysis of the electrical conductivity in milking fractions as a mean for detecting and characterizing mastitis in goats

The aim of the work was to study the effect of milking fraction on electrical conductivity of milk (EC) to improve its use in dairy goat mastitis detection using automatic EC measurements during milking. The experiment was carried out on a group of 84 Murciano-Granadina goats (28 primiparous and 56 multiparous). Goats were in the fourth month of lactation. A linear mixed model was used to analyse the relationship between EC or somatic cell count (SCC) of gland milk and parity, mammary gland health status, analysed fraction (first 100 mL=F-1; machine milk=F-2; and stripping milk=F-3) and their first order interactions. Additionally, the mastitis detection characteristics (sensitivity, specificity, positive predictive value and negative predictive value) of SCC and EC were studied at different thresholds.All factors considered were significant for EC and SCC. EC decreased significantly as milking progressed (from F-1 to F-3) in both healthy and infected glands. EC was not significantly different between healthy and infected glands in F-1 and F-2 fractions, but EC of healthy glands (5.01 mS/cm) was significantly lower than in infected glands (5.03 mS/cm) at F-3.Mastitis detection characteristics of EC did not differ amongst studied fractions. The small significant difference of EC between healthy and infected glands obtained in F-3 fraction did not yield better sensitivity results compared to F-1 and F-2. The best EC mastitis detection characteristics were obtained at 5.20 mS/cm threshold (sensitivity of 70% and specificity of 50%). The best SCC mastitis detection characteristics were obtained at 300,000 cells/mL threshold and F-3 fraction (sensitivity of 85% and specificity of 65%).It was concluded that mastitis detection characteristics of EC were similar in the three milking fractions analysed, being slightly better for SCC in F-3 fraction. As shown in previous studies, there are no factors other than the mammary gland health status that affect milk EC and should be considered in the algorithms for mastitis detection to improve the results. (C) 2012 Elsevier B.V. All rights reserved.

Sensitivity, specificity and predictive values of linear and nonlinear indices of heart rate variability in stable angina patients

Background: Decreased heart rate variability (HRV) is related to higher morbidity and mortality. In this study we evaluated the linear and nonlinear indices of the HRV in stable angina patients submitted to coronary angiography. Methods. We studied 77 unselected patients for elective coronary angiography, which were divided into two groups: coronary artery disease (CAD) and non-CAD groups. For analysis of HRV indices, HRV was recorded beat by beat with the volunteers in the supine position for 40 minutes. We analyzed the linear indices in the time (SDNN [standard deviation of normal to normal], NN50 [total number of adjacent RR intervals with a difference of duration greater than 50ms] and RMSSD [root-mean square of differences]) and frequency domains ultra-low frequency (ULF) ≤ 0,003 Hz, very low frequency (VLF) 0,003 - 0,04 Hz, low frequency (LF) (0.04-0.15 Hz), and high frequency (HF) (0.15-0.40 Hz) as well as the ratio between LF and HF components (LF/HF). In relation to the nonlinear indices we evaluated SD1, SD2, SD1/SD2, approximate entropy (-ApEn), α1, α2, Lyapunov Exponent, Hurst Exponent, autocorrelation and dimension correlation. The definition of the cutoff point of the variables for predictive tests was obtained by the Receiver Operating Characteristic curve (ROC). The area under the ROC curve was calculated by the extended trapezoidal rule, assuming as relevant areas under the curve ≥ 0.650. Results: Coronary arterial disease patients presented reduced values of SDNN, RMSSD, NN50, HF, SD1, SD2 and -ApEn. HF ≤ 66 ms§ssup§2§esup§, RMSSD ≤ 23.9 ms, ApEn ≤-0.296 and NN50 ≤ 16 presented the best discriminatory power for the presence of significant coronary obstruction. Conclusion: We suggest the use of Heart Rate Variability Analysis in linear and nonlinear domains, for prognostic purposes in patients with stable angina pectoris, in view of their overall impairment. © 2012 Pivatelli et al.; licensee BioMed Central Ltd.

Predictive formulas for food base excess and urine pH estimations of cats

Food base excess (BE, mEq/kg) can be calculated from the diet macroelements, together with either the sulfur amino acids methionine and cysteine (BEaa) or total sulfur (BEs) concentrations. The present study compared the use of sulfur or methionine and cysteine for calculating the food BE (experiment 1) and investigated the influence of food BE on blood gas analysis and the urine pH of cats, and proposes a prediction equation to estimate the urine pH of cats fed kibble diets based on the calculated food BE (experiments 2 and 3). In experiment 1, nine healthy, adult cats were used in a change-over design and fed with nine commercial dry cat foods. The cats were housed in metabolism cages over seven days for adaptation and three days for total urine collection. All of the urine produced over 24h was pooled by cat and diet. The cats' acid-base status was assessed through blood gas analysis after 10 days of diet consumption. A mean difference of -115mEq/kg between BEs and BEaa was observed, which could be explained by a greater concentration of sulfur in the whole diet than in methionine and cysteine. Urine pH presented a stronger correlation with food BEs (R2=0.95; P<0.001) than with food BEaa (R2=0.86; P<0.001). Experiment 2 included 30 kibble diets, and each diet was tested in six cats. The food BEs varied between -180 and +307mEq/kg, and the urine pH of the cats varied between 5.60 and 7.74. A significant correlation was found between the measured urine pH and the food BEs (urinary pH=6.269+[0.0036×BEs]+[0.000003×BEs2]; R2=0.91; P<0.001). In experiment 3, eight kibble diets were tested (food BEs between -187mEq/kg and +381mEq/kg) to validate the equation proposed in experiment 2 and to compare the obtained results with previously published formulae. The results of the proposed formula presented a high concordance correlation coefficient (0.942) and high accuracy (0.979) with the measured values, and the estimates of urine pH did not differ from the values obtained in cats (P>0.05). The cats' venous blood pH, bicarbonate, and blood BE were correlated with food BEs (P<0.001); the consumption of diets with low food BEs induced a reduction in these parameters. In conclusion, food macroelement composition has a strong influence on cats' acid-base equilibrium and food BEs calculation is a useful tool to formulate and balance kibble diets for felines. © 2013 Elsevier B.V.

Mean surface temperature prediction models for broiler chickens-a study of sensible heat flow

Body surface temperature can be used to evaluate thermal equilibrium in animals. The bodies of broiler chickens, like those of all birds, are partially covered by feathers. Thus, the heat flow at the boundary layer between broilers' bodies and the environment differs between feathered and featherless areas. The aim of this investigation was to use linear regression models incorporating environmental parameters and age to predict the surface temperatures of the feathered and featherless areas of broiler chickens. The trial was conducted in a climate chamber, and 576 broilers were distributed in two groups. In the first trial, 288 broilers were monitored after exposure to comfortable or stressful conditions during a 6-week rearing period. Another 288 broilers were measured under the same conditions to test the predictive power of the models. Sensible heat flow was calculated, and for the regions covered by feathers, sensible heat flow was predicted based on the estimated surface temperatures. The surface temperatures of the feathered and featherless areas can be predicted based on air, black globe or operative temperatures. According to the sensible heat flow model, the broilers' ability to maintain thermal equilibrium by convection and radiation decreased during the rearing period. Sensible heat flow estimated based on estimated surface temperatures can be used to predict animal responses to comfortable and stressful conditions. © 2013 ISB.

Comparison of predictive equations for resting energy expenditure in overweight and obese adults

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)