Accuracy of genomic predictions in Bos indicus (Nellore) cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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.

Atributos polarimétricos de imagem radar na inferência de parâmetros morfológicos de macrófitas

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Correlation of properties of Brazilian Haplustalfs with magnetic susceptibility measurements

Magnetic susceptibility (chi, mass specific) is useful for easy indirect estimation of other soil properties at a low cost. The aim of this study was to assess the use of chi as measured with an analytical balance for predicting properties with a substantial influence on the management of Typic Haplustalfs in southern Brazil. To achieve this 48 topsoil samples were taken at the intersection points in a rectangular grid of 20 m x 20 m cells, with 38 of these used for calibration and 10 for validation in regression analyses. The obtained chi values were slightly higher than, and highly correlated (r = 0.970; P < 0.001) with those measured with a susceptibility meter. Highly significant (P < 0.001) correlations were also found between chi and other soil properties relevant to soil classification and management such as clay content (r = 0.68), cation exchange capacity (r = 0.62), P sorption capacity (r = 0.76) and haematite content (r = 0.82). Results from a principal component analysis of eight properties important for soil classification explained 11% of the variance in the data set. The good predictive ability of chi was consistent with current knowledge on the formation pathways for pedogenic ferrimagnets. In summary, chi, which can be readily measured with an analytical balance, has the potential for quantifying soil attributes and may therefore be used in pedotransfer functions.

Linear and Poisson models for genetic evaluation of tick resistance in cross-bred Hereford x Nellore cattle

Cattle resistance to ticks is measured by the number of ticks infesting the animal. The model used for the genetic analysis of cattle resistance to ticks frequently requires logarithmic transformation of the observations. The objective of this study was to evaluate the predictive ability and goodness of fit of different models for the analysis of this trait in cross-bred Hereford x Nellore cattle. Three models were tested: a linear model using logarithmic transformation of the observations (MLOG); a linear model without transformation of the observations (MLIN); and a generalized linear Poisson model with residual term (MPOI). All models included the classificatory effects of contemporary group and genetic group and the covariates age of animal at the time of recording and individual heterozygosis, as well as additive genetic effects as random effects. Heritability estimates were 0.08 ± 0.02, 0.10 ± 0.02 and 0.14 ± 0.04 for MLIN, MLOG and MPOI models, respectively. The model fit quality, verified by deviance information criterion (DIC) and residual mean square, indicated fit superiority of MPOI model. The predictive ability of the models was compared by validation test in independent sample. The MPOI model was slightly superior in terms of goodness of fit and predictive ability, whereas the correlations between observed and predicted tick counts were practically the same for all models. A higher rank correlation between breeding values was observed between models MLOG and MPOI. Poisson model can be used for the selection of tick-resistant animals. © 2013 Blackwell Verlag GmbH.

Análise genética de resistência ao Rhipicephalus (Boophilus) microplus em bovinos cruzados Hereford x Nelore

Pós-graduação em Genética e Melhoramento Animal - FCAV

Identification of species of the Euterpe genus by rare earth elements using inductively coupled plasma mass spectrometry and linear discriminant analysis

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Predição genômica utilizando painéis de marcadores moleculares com diferentes densidades, em bovinos da raça Nelore

Pós-graduação em Genética e Melhoramento Animal - FCAV

Fast determination of beef quality parameters with time-domain nuclear magnetic resonance spectroscopy and chemometrics

The noteworthy of this study is to predict seven quality parameters for beef samples using time-domain nuclear magnetic resonance (TD-NMR) relaxometry data and multivariate models. Samples from 61 Bonsmara heifers were separated into five groups based on genetic (breeding composition) and feed system (grain and grass feed). Seven sample parameters were analyzed by reference methods; among them, three sensorial parameters, flavor, juiciness and tenderness and four physicochemical parameters, cooking loss, fat and moisture content and instrumental tenderness using Warner Bratzler shear force (WBSF). The raw beef samples of the same animals were analyzed by TD-NMR relaxometry using Carr-Purcell-Meiboom-Gill (CPMG) and Continuous Wave-Free Precession (CWFP) sequences. Regression models computed by partial least squares (PLS) chemometric technique using CPMG and CWFP data and the results of the classical analysis were constructed. The results allowed for the prediction of aforementioned seven properties. The predictive ability of the method was evaluated using the root mean square error (RMSE) for the calibration (RMSEC) and validation (RMSEP) data sets. The reference and predicted values showed no significant differences at a 95% confidence level.

Seleção genômica para características de carcaça em bovinos da raça Nelore

Pós-graduação em Genética e Melhoramento Animal - FCAV

Utilização de informações genômicas para o melhoramento genético de características da carne em bovinos da raça Nelore

Pós-graduação em Genética e Melhoramento Animal - FCAV

Predição genômica para o peso ao sobreano via norma de reação em bovinos de corte

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Thermoresistance sperm tests are not predictive of potential fertility for cryopreserved bull semen

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Testing time-place learning in the cichlid fish Nile tilapia

Time-place learning based on food association was investigated in the fish Nile tilapia. During a 30-day period, food was placed at one side of the aquarium (containing three compartments) in the morning and at the opposite side in the afternoon. Learning was inferred by the number of correct side choices of all fish in each day of test (15th, 30th). During the test day, fish were not fed. The Nile tilapia did not learn to switch sides at the correct day period in order to get food, suggesting thus that this species does not have time-place learning ability.

Testing the ecomorphological hypothesis in a headwater riffles fish assemblage of the rio São Francisco, southeastern Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)