A Bayesian approach for constructing genetic maps when markers are miscoded

The advent of molecular markers has created opportunities for a better understanding of quantitative inheritance and for developing novel strategies for genetic improvement of agricultural species, using information on quantitative trait loci (QTL). A QTL analysis relies on accurate genetic marker maps. At present, most statistical methods used for map construction ignore the fact that molecular data may be read with error. Often, however, there is ambiguity about some marker genotypes. A Bayesian MCMC approach for inferences about a genetic marker map when random miscoding of genotypes occurs is presented, and simulated and real data sets are analyzed. The results suggest that unless there is strong reason to believe that genotypes are ascertained without error, the proposed approach provides more reliable inference on the genetic map.

Fractional polynomial response surface models

Second-order polynomial models have been used extensively to approximate the relationship between a response variable and several continuous factors. However, sometimes polynomial models do not adequately describe the important features of the response surface. This article describes the use of fractional polynomial models. It is shown how the models can be fitted, an appropriate model selected, and inference conducted. Polynomial and fractional polynomial models are fitted to two published datasets, illustrating that sometimes the fractional polynomial can give as good a fit to the data and much more plausible behavior between the design points than the polynomial model. © 2005 American Statistical Association and the International Biometric Society.

Genetic effects on preweaning weight gain of Nelore-Hereford calves according to different models and estimation methods

Additive and nonadditive genetic effects on preweaning weight gain (PWG) of a commercial crossbred population were estimated using different genetic models and estimation methods. The data set consisted of 103,445 records on purebred and crossbred Nelore-Hereford calves raised under pasture conditions on farms located in south, southeast, and middle west Brazilian regions. In addition to breed additive and dominance effects, the models including different epistasis covariables were tested. Models considering joint additive and environment (latitude) by genetic effects interactions were also applied. In a first step, analyses were carried out under animal models. In a second step, preadjusted records were analyzed using ordinary least squares (OLS) and ridge regression (RR). The results reinforced evidence that breed additive and dominance effects are not sufficient to explain the observed variability in preweaning traits of Bos taurus x Bos indicus calves, and that genotype x environment interaction plays an important role in the evaluation of crossbred calves. Data were ill-conditioned to estimate the effects of genotype x environment interactions. Models including these effects presented multicolinearity problems. In this case, RR seemed to be a powerful tool for obtaining more plausible and stable estimates. Estimated prediction error variances and variance inflation factors were drastically reduced, and many effects that were not significant under ordinary least squares became significant under RR. Predictions of PWG based on RR estimates were more acceptable from a biological perspective. In temperate and subtropical regions, calves with intermediate genetic compositions (close to 1/2 Nelore) exhibited greater predicted PWG. In the tropics, predicted PWG increased linearly as genotype got closer to Nelore. ©2006 American Society of Animal Science. All rights reserved.

Damage detection in a benchmark structure using AR-ARX models and statistical pattern recognition

Structural health monitoring (SHM) is related to the ability of monitoring the state and deciding the level of damage or deterioration within aerospace, civil and mechanical systems. In this sense, this paper deals with the application of a two-step auto-regressive and auto-regressive with exogenous inputs (AR-ARX) model for linear prediction of damage diagnosis in structural systems. This damage detection algorithm is based on the. monitoring of residual error as damage-sensitive indexes, obtained through vibration response measurements. In complex structures there are. many positions under observation and a large amount of data to be handed, making difficult the visualization of the signals. This paper also investigates data compression by using principal component analysis. In order to establish a threshold value, a fuzzy c-means clustering is taken to quantify the damage-sensitive index in an unsupervised learning mode. Tests are made in a benchmark problem, as proposed by IASC-ASCE with different damage patterns. The diagnosis that was obtained showed high correlation with the actual integrity state of the structure. Copyright © 2007 by ABCM.

HPLC determination of hemoglobins to establish reference values with the aid of statistics and informatics

The purpose of the present study was to establish reference values for hemoglobins (Hb) using HPLC, in samples containing normal Hb (AA), sickle cell trait without alpha-thalassemia (AS), sickle cell trait with alpha-thalassemia (ASH), sickle cell anemia (SS), and Hb SC disease (SC). The blood samples were analyzed by electrophoresis, HPLC and molecular procedures. The Hb A2 mean was 4.30 ± 0.44% in AS, 4.18 ± 0.42% in ASH, 3.90 ± 1.14% in SS, and 4.39 ± 0.35% in SC. They were similar, but above the normal range. Between the AS and ASH groups, only the amount of Hb S was higher in the AS group. The Hb S mean in the AS group was 38.54 ± 3.01% and in the ASH it was 36.54 ± 3.76%. In the qualitative analysis, using FastMap, distinct groups were seen: AA and SS located at opposite extremes, AS and ASH with overlapping values and intermediate distribution, SC between heterozygotes and the SS group. Hb S was confirmed by allele-specific polymerase chain reaction. The Hb values established will be available for use as a reference for the Brazilian population, drawing attention to the increased levels of Hb A2, which should be considered with caution to prevent incorrect diagnoses. ©FUNPEC-RP.

Statistical quark models for the nucleon structure functions

We consider some existing relativistic models for the nucleon structure functions, relying on statistical approaches instead of perturbative ones. These models are based on the Fermi-Dirac distribution for the confined quarks, where a density of energy levels is obtained from an effective confining potential. In this context, it is presented some results obtained with a recent statistical quark model for the sea-quark asymmetry in the nucleon. It is shown, within this model, that experimental available observables, such as the ratio and difference between proton and neutron structure functions, are quite well reproduced with just three parameters: two chemical potentials used to reproduce the valence up and down quark numbers in the nucleon, and a temperature that is being used to reproduce the Gottfried sum rule violation. © 2010 American Institute of Physics.

Latin-American Society Of Forensic Genetics (SLAGF) results of the Interlaboratory Quality Control Exercise 2010-2011

Latin-American Society of Forensic Genetics (SLAGF) Interlaboratory Quality Control Exercise (2010-2011) included the analysis of three bloodstain samples in FTA Classic Card (three persons, biologically unrelated) and one theoretical exercise. There were 56 participating laboratories from 13 Latin-American countries that belong to society, were reported 70 STRs, including autosomal and sex chromosome markers with consensus in 53 STRs with a rate in reporting errors of 2.3%. Fifty-six laboratories reported results in theoretical exercise with mistakes in calculation of IP for each marker. It is necessary to hold meetings to discuss the results of this exercise to reach conclusions and recommendations on all aspects of DNA forensics analysis and paternity test, to improve results and quality in the results of each laboratory. © 2011 Elsevier B.V.

Biologic and genetics aspects of chagas disease at endemic areas

The etiologic agent of Chagas Disease is the Trypanosoma cruzi, transmitted through blood-sucking insect vectors of the Triatominae subfamily, representing one of the most serious public health concerns in Latin America. There are geographic variations in the prevalence of clinical forms and morbidity of Chagas disease, likely due to genetic variation of the T. cruzi and the host genetic and environmental features. Increasing evidence has supported that inflammatory cytokines and chemokines are responsible for the generation of the inflammatory infiltrate and tissue damage. Moreover, genetic polymorphisms, protein expression levels, and genomic imbalances are associated with disease progression. This paper discusses these key aspects. Large surveys were carried out in Brazil and served as baseline for definition of the control measures adopted. However, Chagas disease is still active, and aspects such as host-parasite interactions, genetic mechanisms of cellular interaction, genetic variability, and tropism need further investigations in the attempt to eradicate the disease. Copyright 2012 Marilanda Ferreira Bellini et al.

A precautionary tale when describing species in a world of invaders: Morphology, coloration and genetics demonstrate that Lysmata rauli is not a new species endemic to Brazil but a junior synonym of the Indo-Pacific L. vittata

The objective of this study was to investigate morphological variation in traits of systematic relevance and the phylogenetic position, ecology, and reproductive biology of the shrimp Lysmata rauli Laubenheimer and Rhyne, 2010 (Caridea: Hippolytidae), described based only on a single specimen collected in Salvador, Bahia, Brazil. We analyzed a total of 89 specimens from Camamu Bay, Bahia (n = 88) and from S3o Vicente estuary, São Paulo (n = 1). Considerable morphological variation was detected in the rostral spine series, number of segments on the carpus and merus of pereiopod 2, number of spiniform setae on the ventrolateral margin of merus and on the ventral margin of propodus of pereiopods 3-5. Importantly, L rauli can be distinguished neither using morphology, nor coloration from the Indo-Pacific L. vittata (Stimpson, 1860). Furthermore, molecular phylogenetic analyses (using the 16S mt DNA fragment) did not reveal any considerable genetic dissimilarities between L rauli and L vittata. Thus, our results clearly indicate that L rauli is not a new species but a junior synonym of L vittata. The high density observed within the structures of oyster farming indicates that the invasive L vittata lives in crowds in Brazil. The studied population was composed of males, hermaphrodites, and transitional individuals (having characteristics of males and hermaphrodites). The above information suggests that L rauli is a protandric simultaneous hermaphrodite, as it has been observed in all species of Lysmata that have been investigated. Lysmata vittata has invaded the southwestern Atlantic and is present in Bahia, Rio de Janeiro and S3o Paulo, Brazil. © The Crustacean Society, 2013. Published by Brill NV, Leiden.

Comparison of random regression models to estimate genetic parameters for milk production in Guzerat (Bos indicus) cows

Random regression models have been widely used to estimate genetic parameters that influence milk production in Bos taurus breeds, and more recently in B. indicus breeds. With the aim of finding appropriate random regression model to analyze milk yield, different parametric functions were compared, applied to 20,524 test-day milk yield records of 2816 first-lactation Guzerat (B. indicus) cows in Brazilian herds. The records were analyzed by random regression models whose random effects were additive genetic, permanent environmental and residual, and whose fixed effects were contemporary group, the covariable cow age at calving (linear and quadratic effects), and the herd lactation curve. The additive genetic and permanent environmental effects were modeled by the Wilmink function, a modified Wilmink function (with the second term divided by 100), a function that combined third-order Legendre polynomials with the last term of the Wilmink function, and the Ali and Schaeffer function. The residual variances were modeled by means of 1, 4, 6, or 10 heterogeneous classes, with the exception of the last term of the Wilmink function, for which there were 1, from 0.20 to 0.33. Genetic correlations between adjacent records were high values (0.83-0.99), but they declined when the interval between the test-day records increased, and were negative between the first and last records. The model employing the Ali and Schaeffer function with six residual variance classes was the most suitable for fitting the data. © FUNPEC-RP.

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.

Advances on statistical/thermodynamical models for unpolarized structure functions

During the eights and nineties many statistical/thermodynamical models were proposed to describe the nucleons' structure functions and distribution of the quarks in the hadrons. Most of these models describe the compound quarks and gluons inside the nucleon as a Fermi / Bose gas respectively, confined in a MIT bag[1] with continuous energy levels. Another models considers discrete spectrum. Some interesting features of the nucleons are obtained by these models, like the sea asymmetries d̄/ū and d̄-ū. © 2013 American Institute of Physics.

Genetic evaluation using multi-trait and random regression models in Simmental beef cattle

The Brazilian Association of Simmental and Simbrasil Cattle Farmers provided 29,510 records from 10,659 Simmental beef cattle; these were used to estimate (co)variance components and genetic parameters for weights in the growth trajectory, based on multi-trait (MTM) and random regression models (RRM). The (co)variance components and genetic parameters were estimated by restricted maximum likelihood. In the MTM analysis, the likelihood ratio test was used to determine the significance of random effects included in the model and to define the most appropriate model. All random effects were significant and included in the final model. In the RRM analysis, different adjustments of polynomial orders were compared for 5 different criteria to choose the best fit model. An RRM of third order for the direct additive genetic, direct permanent environmental, maternal additive genetic, and maternal permanent environment effects was sufficient to model variance structures in the growth trajectory of the animals. The (co)variance components were generally similar in MTM and RRM. Direct heritabilities of MTM were slightly lower than RRM and varied from 0.04 to 0.42 and 0.16 to 0.45, respectively. Additive direct correlations were mostly positive and of high magnitude, being highest at closest ages. Considering the results and that pre-adjustment of the weights to standard ages is not required, RRM is recommended for genetic evaluation of Simmental beef cattle in Brazil. ©FUNPEC-RP.

Comparison of factor-analytic and reduced rank models for test-day milk yield in Gyr dairy cattle (Bos indicus)

We analyzed 46,161 monthly test-day records of milk production from 7453 first lactations of crossbred dairy Gyr (Bos indicus) x Holstein cows. The following seven models were compared: standard multivariate model (M10), three reduced rank models fitting the first 2, 3, or 4 genetic principal components, and three models considering a 2-, 3-, or 4-factor structure for the genetic covariance matrix. Full rank residual covariance matrices were considered for all models. The model fitting the first two principal components (PC2) was the best according to the model selection criteria. Similar phenotypic, genetic, and residual variances were obtained with models M10 and PC2. The heritability estimates ranged from 0.14 to 0.21 and from 0.13 to 0.21 for models M10 and PC2, respectively. The genetic correlations obtained with model PC2 were slightly higher than those estimated with model M10. PC2 markedly reduced the number of parameters estimated and the time spent to reach convergence. We concluded that two principal components are sufficient to model the structure of genetic covariances between test-day milk yields. © FUNPEC-RP.

Papel de polimorfismos genéticos nos genes IL10, TNF e LTA na hanseníase

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