Localising and quantifying damage by means of a multi-chromosome genetic algorithm

This paper presents a structural damage detection methodology based on genetic algorithms and dynamic parameters. Three chromosomes are used to codify an individual in the population. The first and second chromosomes locate and quantify damage, respectively. The third permits the self-adaptation of the genetic parameters. The natural frequencies and mode shapes are used to formulate the objective function. A numerical analysis was performed for several truss structures under different damage scenarios. The results have shown that the methodology can reliably identify damage scenarios using noisy measurements and that it results in only a few misidentified elements. (C) 2012 Civil-Comp Ltd and Elsevier Ltd. All rights reserved.

Genetic associations between flight speed and growth traits in Nellore cattle

The aim of the present study was to estimate genetic parameters for flight speed and its association with growth traits in Nellore beef cattle. The flight speed (FS) of 7,402 yearling animals was measured, using a device composed of a pair of photoelectric cells. Time interval data (s) were converted to speed (m/s) and faster animals were regarded as more reactive. The growth traits analyzed were weaning weight (WW), ADG from weaning to yearling age, and yearling scrotal circumference (SC). The (co)variance components were estimated using REML in a multitrait analysis applying an animal model. The model included random direct additive genetic and residual effects, fixed effects of contemporary groups, age of dam (classes), and age of animal as covariable. For WW, the model also included maternal genetic and permanent environmental random effects. The direct heritability estimate for FS was 0.26 +/- 0.05 and direct heritability estimates for WW, SC, and ADG were 0.30 +/- 0.01, 0.48 +/- 0.02, and 0.19 +/- 0.01, respectively. Estimates of the genetic correlation between FS and the growth traits were -0.12 +/- 0.07 (WW), -0.13 +/- 0.08 (ADG), and -0.11 +/- 0.07 (SC). Although the values were low, these correlations showed that animals with better temperaments (slower FS) tended to present better performance. It is possible to infer that long-term selection for weight and scrotal circumference can promote a positive genetic response in the temperament of animals. Nevertheless, to obtain faster genetic progress in temperament, it would be necessary to perform direct selection for such trait. Flight speed is an easily measured indicator of temperament and can be included as a selection criterion in breeding programs for Nellore cattle.

Genetic relationship between growth and reproductive traits in Nellore cattle

The objective of this study was to evaluate the genetic relationship between postweaning weight gain (PWG), heifer pregnancy (HP), scrotal circumference (SC) at 18 months of age, stayability at 6 years of age (STAY) and finishing visual score at 18 months of age (PREC), and to determine the potential of these traits as selection criteria for the genetic improvement of growth and reproduction in Nellore cattle. The HP was defined as the observation that a heifer conceived and remained pregnant, which was assessed by rectal palpation at 60 days. The STAY was defined as whether or not a cow calved every year up to the age of 6 years, given that she was provided the opportunity to breed. The Bayesian linear-threshold analysis via the Gibbs sampler was used to estimate the variance and covariance components applying a multitrait model. Posterior mean estimates of direct heritability were 0.15 +/- 0.00, 0.42 +/- 0.02, 0.49 +/- 0.01, 0.11 +/- 0.01 and 0.19 +/- 0.00 for PWG, HP, SC, STAY and PREC, respectively. The genetic correlations between traits ranged from 0.17 to 0.62. The traits studied generally have potential for use as selection criteria in genetic breeding programs. The genetic correlations between all traits show that selection for one of these traits does not imply the loss of the others.

Contribution and perspectives of quantitative genetics to plant breeding in Brazil

The purpose of this article is to show how quantitative genetics has contributed to the huge genetic progress obtained in plant breeding in Brazil in the last forty years. The information obtained through quantitative genetics has given Brazilian breeders the possibility of responding to innumerable questions in their work in a much more informative way, such as the use or not of hybrid cultivars, which segregating population to use, which breeding method to employ, alternatives for improving the efficiency of selection programs, and how to handle the data of progeny and/or cultivars evaluations to identify the most stable ones and thus improve recommendations.

Short communication: Principal components and factor analytic models for test-day milk yield in Brazilian Holstein cattle

A total of 46,089 individual monthly test-day (TD) milk yields (10 test-days), from 7,331 complete first lactations of Holstein cattle were analyzed. A standard multivariate analysis (MV), reduced rank analyses fitting the first 2, 3, and 4 genetic principal components (PC2, PC3, PC4), and analyses that fitted a factor analytic structure considering 2, 3, and 4 factors (FAS2, FAS3, FAS4), were carried out. The models included the random animal genetic effect and fixed effects of the contemporary groups (herd-year-month of test-day), age of cow (linear and quadratic effects), and days in milk (linear effect). The residual covariance matrix was assumed to have full rank. Moreover, 2 random regression models were applied. Variance components were estimated by restricted maximum likelihood method. The heritability estimates ranged from 0.11 to 0.24. The genetic correlation estimates between TD obtained with the PC2 model were higher than those obtained with the MV model, especially on adjacent test-days at the end of lactation close to unity. The results indicate that for the data considered in this study, only 2 principal components are required to summarize the bulk of genetic variation among the 10 traits.

Bayesian analysis of random regression models using B-splines to model test-day milk yield of Holstein cattle in Brazil

The objective of this paper is to model variations in test-day milk yields of first lactations of Holstein cows by RR using B-spline functions and Bayesian inference in order to fit adequate and parsimonious models for the estimation of genetic parameters. They used 152,145 test day milk yield records from 7317 first lactations of Holstein cows. The model established in this study was additive, permanent environmental and residual random effects. In addition, contemporary group and linear and quadratic effects of the age of cow at calving were included as fixed effects. Authors modeled the average lactation curve of the population with a fourth-order orthogonal Legendre polynomial. They concluded that a cubic B-spline with seven random regression coefficients for both the additive genetic and permanent environment effects was to be the best according to residual mean square and residual variance estimates. Moreover they urged a lower order model (quadratic B-spline with seven random regression coefficients for both random effects) could be adopted because it yielded practically the same genetic parameter estimates with parsimony. (C) 2012 Elsevier B.V. All rights reserved.

Genotype by environment interaction for birth and weaning weights of composite beef cattle in different regions of Brazil

The objectives of the present study were to characterize and define homogenous production environments of composite beef cattle in Brazil in terms of climatic and geographic variables using multivariate exploratory techniques and to use them to assess the presence of G x E for birth weight (BW) and weaning weight (WW). Data from animals born between 1995 and 2008 on 36 farms located in 27 municipalities of the Brazilian states were used. Fifteen years of climate observations (mean minimum and maximum annual temperature and mean annual rainfall) and geographic (latitude, longitude and altitude) data were obtained for each municipality where the farms were located for characterization of the production environments. Hierarchical and nonhierarchical cluster analysis was used to group farms located in regions with similar environmental variables into clusters. Six clusters of farms were formed. The effect of sire-cluster interaction was tested by single-trait analysis using deviance information criterion (DIC). Genetic parameters were estimated by multi-trait analysis considering the same trait to be different in each cluster. According to the values of DIC, the inclusion of sire-cluster effect did not improve the fit of the genetic evaluation model for BW and WW. Estimates of genetic correlations among clusters ranged from -0.02 to 0.92. The low genetic correlation among the most studied regions permits us to suggest that a separate genetic evaluation for some regions should be undertaken. (C) 2012 Elsevier B.V. All rights reserved.

Parâmetros genéticos para a produção de leite em caprinos das raças Saanen e Alpina

Objetivou-se com este trabalho estimar parâmetros genéticos para a produção de leite acumulada até os 305 dias (P305) de cabras das raças Saanen e Alpina. Foram utilizadas as duas primeiras parições de cabras pertencentes a rebanhos participantes do programa de controle produtivo e reprodutivo de caprinos (PROCAPRI) da UNESP-FCAV-Jaboticabal-SP. A P305 foi analisada por meio de modelos de repetibilidade e bicaracterísticas. Para verificar a influência dos efeitos fixos sobre a característica analisada foram realizadas análises preliminares, pelo método de quadrados mínimos. Os componentes de covariâncias foram estimados pelo método da máxima verossimilhança restrita (REML), utilizando o programa Wombat. A duração da lactação, a idade da cabra ao parto, o rebanho, o ano de parto e a estação de parto foram importantes fontes de variação para a P305. Não houve diferença significativa entre as raças estudadas. As estimativas de herdabilidade e repetibilidade para a P305, obtidas com o modelo de repetibilidade, foram de 0,29 e 0,36, respectivamente. As estimativas de herdabilidade, obtidas pelos modelos de repetibilidade e bicaracterísticas foram semelhantes. Sendo assim, um modelo de repetibilidade poderia ser indicado para avaliar a P305 pela sua simplicidade.

Epistatic effects on grain yield of soybean [Glycine max (L.) Merrill]

Studies addressing the estimation of genetic parameters in soybean have not emphasized the epistatic effects. The purpose of this study was to estimate the significance of these effects on soybean grain yield, based on the Modified Triple Test Cross design. Thirty-two inbred lines derived from a cross between two contrasting lines were used, which were crossed with two testers (L1 and L2). The experiments were carried out at two locations, in 10 x 10 triple lattice designs with 9 replications, containing 32 lines (Pi ), 64 crosses (32 Pi x L1 and 32 Pi x L2 ) and controls. The variation between ( ͞L1i + ͞L2i - ͞Pi ) revealed the presence of epistasis, as well as an interaction of epistasis x environment. Since the predominant component of epistasis in autogamous species is additive x additive (i type), we suggest postponing the selection for grain yield to later generations of inbreeding in order to exploit the beneficial effects of additive x additive epistasis.

Genetic variability and demographic history of Heliothis virescens (Lepidoptera: Noctuidae) populations from Brazil inferred by mtDNA sequences

Intra-and inter-population genetic variability and the demographic history of Heliothis virescens (F.) populations were evaluated by using mtDNA markers (coxI, coxII and nad6) with samples from the major cotton-and soybean-producing regions in Brazil in the growing seasons 2007/08, 2008/09 and 2009/10. AMOVA indicated low and non-significant genetic structure, regardless of geographical scale, growing season or crop, with most of genetic variation occurring within populations. Clustering analyzes also indicated low genetic differentiation. The haplotype network obtained with combined datasets resulted in 35 haplotypes, with 28 exclusive occurrences, four of them sampled only from soybean fields. The minimum spanning network showed star-shaped structures typical of populations that underwent a recent demographic expansion. The recent expansion was supported by other demographic analyzes, such as the Bayesian skyline plot, the unimodal distribution of paired differences among mitochondrial sequences, and negative and significant values of neutrality tests for the Tajima's D and Fu's F-S parameters. In addition, high values of haplotype diversity ((H) over cap) and low values of nucleotide diversity (pi), combined with a high number of low frequency haplotypes and values of theta(pi)<theta(W), suggested a recent demographic expansion of H. virescens populations in Brazil. This demographic event could be responsible for the low genetic structure currently found; however, haplotypes present uniquely at the same geographic regions and from one specific host plant suggest an initial differentiation among H. virescens populations within Brazil.

Heritability Estimate and Genetic Correlations of Reproductive Features in Nellore Bulls, Offspring of Super Precocious, Precocious and Normal Cows Under Extensive Farming Conditions

The present work aimed to estimate heritability and genetic correlations of reproductive features of Nellore bulls, offspring of mothers classified as superprecocious (M1), precocious (M2) and normal (M3). Twenty one thousand hundred and eighty-six animals with average age of 21.29 months were used, evaluated through the breeding soundness evaluation from 1999 to 2008. The breeding soundness features included physical semen evaluation (progressive sperm motility and sperm vigour), semen morphology (major, minor and total sperm defects), scrotal circumference (SC), testicular volume (TV) and SC at 18 months of age (SC18). The components of variance, heritability and genetic correlations for and between the features were estimated simultaneously by restricted maximum likelihood, with the use of the vce software system vs 6. The heritability estimates were high for SC18, SC and TV (0.43, 0.63 and 0.54; 0.45, 0.45 and 0.44; 0.42, 0.45 and 0.41, respectively for the categories of mothers M1, M2 and M3) and low for physical and morphological semen aspects. The genetic correlations between SC18 and SC were high, as well as between these variables with TV. High and positive genetic correlations were recorded among SC18, SC and TV with the physical aspects of the semen, although no favourable association was verified with the morphological aspects, for the three categories of mothers. It can be concluded that the mothers sexual precocity did not affect the heritability of their offspring reproduction features.

Mating system parameters at hierarchical levels of fruits, individuals and populations in the Brazilian insect-pollinated tropical tree, Tabebuia roseo-alba (Bignoniaceae)

For many tree species, mating system analyses have indicated potential variations in the selfing rate and paternity correlation among fruits within individuals, among individuals within populations, among populations, and from one flowering event to another. In this study, we used eight microsatellite markers to investigate mating systems at two hierarchical levels (fruits within individuals and individuals within populations) for the insect pollinated Neotropical tree Tabebuia roseo-alba. We found that T. roseo-alba has a mixed mating system with predominantly outcrossed mating. The outcrossing rates at the population level were similar across two T. roseo-alba populations; however, the rates varied considerably among individuals within populations. The correlated paternity results at different hierarchical levels showed that there is a high probability of shared paternal parentage when comparing seeds within fruits and among fruits within plants and full-sibs occur in much higher proportion within fruits than among fruits. Significant levels of fixation index were found in both populations and biparental inbreeding is believed to be the main cause of the observed inbreeding. The number of pollen donors contributing to mating was low. Furthermore, open-pollinated seeds varied according to relatedness, including half-sibs, full-sibs, self-sibs and self- half-sibs. In both populations, the effective population size within a family (seed-tree and its offspring) was lower than expected for panmictic populations. Thus, seeds for ex situ conservation genetics, progeny tests and reforestation must be collected from a large number of seed-trees to guarantee an adequate effective population in the sample.

Combining meta-learning and search techniques to select parameters for support vector machines

Support Vector Machines (SVMs) have achieved very good performance on different learning problems. However, the success of SVMs depends on the adequate choice of the values of a number of parameters (e.g., the kernel and regularization parameters). In the current work, we propose the combination of meta-learning and search algorithms to deal with the problem of SVM parameter selection. In this combination, given a new problem to be solved, meta-learning is employed to recommend SVM parameter values based on parameter configurations that have been successfully adopted in previous similar problems. The parameter values returned by meta-learning are then used as initial search points by a search technique, which will further explore the parameter space. In this proposal, we envisioned that the initial solutions provided by meta-learning are located in good regions of the search space (i.e. they are closer to optimum solutions). Hence, the search algorithm would need to evaluate a lower number of candidate solutions when looking for an adequate solution. In this work, we investigate the combination of meta-learning with two search algorithms: Particle Swarm Optimization and Tabu Search. The implemented hybrid algorithms were used to select the values of two SVM parameters in the regression domain. These combinations were compared with the use of the search algorithms without meta-learning. The experimental results on a set of 40 regression problems showed that, on average, the proposed hybrid methods obtained lower error rates when compared to their components applied in isolation.

Comparison of microsatellites and isozymes in genetic diversity studies of Oryza glumaepatula (Poaceae) populations

The study of the genetic structure of wild plant populations is essential for their management and conservation. Several DNA markers have been used in such studies, as well as isozyme markers. In order to provide a better comprehension of the results obtained and a comparison between markers which will help choose tools for future studies in natural populations of Oryza glumaepatula, a predominantly autogamous species, this study used both isozymes and microsatellites to assess the genetic diversity and genetic structure of 13 populations, pointing to similarities and divergences of each marker, and evaluating the relative importance of the results for studies of population genetics and conservation. A bulk sample for each population was obtained, by sampling two to three seeds of each plant, up to a set of 50 seeds. Amplified products of eight SSR loci were electrophoresed on non-denaturing polyacrylamide gels, and the fragments were visualized using silver staining procedure. Isozyme analyses were conducted in polyacrylamide gels, under a discontinuous system, using six enzymatic loci. SSR loci showed higher mean levels of genetic diversity (A=2.83, p=0.71, A(P)=3.17, H-o=0.081, H-e=0.351) than isozyme loci (A=1.20, p=0.20, A(P)=1.38, H-o=0.006, H-e=0.056). Interpopulation genetic differentiation detected by SSR loci (R-ST=0.631, equivalent to F-ST=0.533) was lower than that obtained with isozymes (F-ST=0.772). However, both markers showed high deviation from Hardy-Weinberg expectations (F-IS=0.744 and 0.899, respectively for SSR and isozymes). The mean apparent outcrossing rate for SSR ((t) over bar (a)=0.14) was higher than that obtained using isozymes ((t) over bar (a)=0.043), although both markers detected lower levels of outcrossing in Amazonia compared to the Pantanal. The migrant number estimation was also higher for SSR (Nm=0.219) than isozymes (Nm=0.074), although a small number for both markers was expected due to the mode of reproduction of this species, defined as mixed with predominance of self fertilization. No correlation was obtained between genetic and geographic distances with SSR, but a positive correlation was found between genetic and geographic distances with isozymes. We conclude that these markers are divergent in detecting genetic diversity parameters in O. glumaepatula and that microsatellites are powerful for detecting information at the intra-population level, while isozymes are more powerful for inter-population diversity, since clustering of populations agreed with the expectations based on the geographic distribution of the populations using this marker. Rev. Biol. Trop. 60 (4): 1463-1478. Epub 2012 December 01.

Different approaches for dealing with rare variants in family-based genetic studies: application of a Genetic Analysis Workshop 17 problem

Rare variants are becoming the new candidates in the search for genetic variants that predispose individuals to a phenotype of interest. Their low prevalence in a population requires the development of dedicated detection and analytical methods. A family-based approach could greatly enhance their detection and interpretation because rare variants are nearly family specific. In this report, we test several distinct approaches for analyzing the information provided by rare and common variants and how they can be effectively used to pinpoint putative candidate genes for follow-up studies. The analyses were performed on the mini-exome data set provided by Genetic Analysis Workshop 17. Eight approaches were tested, four using the trait’s heritability estimates and four using QTDT models. These methods had their sensitivity, specificity, and positive and negative predictive values compared in light of the simulation parameters. Our results highlight important limitations of current methods to deal with rare and common variants, all methods presented a reduced specificity and, consequently, prone to false positive associations. Methods analyzing common variants information showed an enhanced sensibility when compared to rare variants methods. Furthermore, our limited knowledge of the use of biological databases for gene annotations, possibly for use as covariates in regression models, imposes a barrier to further research.