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.

Genetic correlations and heritability estimates of reproductive traits of Nellore bulls

Estimates of phenotypic, genetics and residual variances for reproductive traits in 5903 Nellore bulls were obtained. The experimental model used was multiple trait derivative-free restricted maximum likelihood. The values obtained for heritability were 0.24 +/- 0.05 for scrotal circumference at 450 days of age and 0.37 +/- 0.05 at 21 months for age at the time of the breeding soundness evaluation; 0.24 +/- 0.05 and 0.26 +/- 0.05 for left and right testicle length; 0.29 +/- 0.05 and 0.31 +/- 0.05 for left and right testicle width; 0.12 +/- 0.04 for testicle format; 0.33 +/- 0.06 for testicle volume; 0.11 +/- 0.03 for gross motility; 0.08 +/- 0.03 for individual motility and 0.05 +/- 0.02 for spermatic vigor; 0.20 +/- 0.04, 0.03 +/- 0.02 and 0.19 +/- 0.04 for larger defects, smaller defects and total defects, respectively. The values for heritability for testicular biometric characteristics were moderate to high while the seminal characteristics, presented low values. Genetic correlations between scrotal circumference with all the reproductive traits were favorable, suggesting the scrotal circumference as a feature of choice in the selection of bulls.

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.

The Kumaraswamy Gumbel distribution

The Gumbel distribution is perhaps the most widely applied statistical distribution for problems in engineering. We propose a generalization-referred to as the Kumaraswamy Gumbel distribution-and provide a comprehensive treatment of its structural properties. We obtain the analytical shapes of the density and hazard rate functions. We calculate explicit expressions for the moments and generating function. The variation of the skewness and kurtosis measures is examined and the asymptotic distribution of the extreme values is investigated. Explicit expressions are also derived for the moments of order statistics. The methods of maximum likelihood and parametric bootstrap and a Bayesian procedure are proposed for estimating the model parameters. We obtain the expected information matrix. An application of the new model to a real dataset illustrates the potentiality of the proposed model. Two bivariate generalizations of the model are proposed.

An extended Lindley distribution

In this paper we introduce an extension of the Lindley distribution which offers a more flexible model for lifetime data. Several statistical properties of the distribution are explored, such as the density, (reversed) failure rate, (reversed) mean residual lifetime, moments, order statistics, Bonferroni and Lorenz curves. Estimation using the maximum likelihood and inference of a random sample from the distribution are investigated. A real data application illustrates the performance of the distribution. (C) 2011 The Korean Statistical Society. Published by Elsevier B.V. All rights reserved.

Bivariate gamma-geometric law and its induced Levy process

In this article we introduce a three-parameter extension of the bivariate exponential-geometric (BEG) law (Kozubowski and Panorska, 2005) [4]. We refer to this new distribution as the bivariate gamma-geometric (BGG) law. A bivariate random vector (X, N) follows the BGG law if N has geometric distribution and X may be represented (in law) as a sum of N independent and identically distributed gamma variables, where these variables are independent of N. Statistical properties such as moment generation and characteristic functions, moments and a variance-covariance matrix are provided. The marginal and conditional laws are also studied. We show that BBG distribution is infinitely divisible, just as the BEG model is. Further, we provide alternative representations for the BGG distribution and show that it enjoys a geometric stability property. Maximum likelihood estimation and inference are discussed and a reparametrization is proposed in order to obtain orthogonality of the parameters. We present an application to a real data set where our model provides a better fit than the BEG model. Our bivariate distribution induces a bivariate Levy process with correlated gamma and negative binomial processes, which extends the bivariate Levy motion proposed by Kozubowski et al. (2008) [6]. The marginals of our Levy motion are a mixture of gamma and negative binomial processes and we named it BMixGNB motion. Basic properties such as stochastic self-similarity and the covariance matrix of the process are presented. The bivariate distribution at fixed time of our BMixGNB process is also studied and some results are derived, including a discussion about maximum likelihood estimation and inference. (C) 2012 Elsevier Inc. All rights reserved.

Evolution of extrafloral nectaries: adaptive process and selective regime changes from forest to savanna

Much effort has been devoted to understanding the function of extrafloral nectaries (EFNs) for antplantherbivore interactions. However, the pattern of evolution of such structures throughout the history of plant lineages remains unexplored. In this study, we used empirical knowledge on plant defences mediated by ants as a theoretical framework to test specific hypotheses about the adaptive role of EFNs during plant evolution. Emphasis was given to different processes (neutral or adaptive) and factors (habitat change and trade-offs with new trichomes) that may have affected the evolution of antplant associations. We measured seven EFN quantitative traits in all 105 species included in a well-supported phylogeny of the tribe Bignonieae (Bignoniaceae) and collected field data on antEFN interactions in 32 species. We identified a positive association between ant visitation (a surrogate of ant guarding) and the abundance of EFNs in vegetative plant parts and rejected the hypothesis of phylogenetic conservatism of EFNs, with most traits presenting K-values < 1. Modelling the evolution of EFN traits using maximum likelihood approaches further suggested adaptive evolution, with static-optimum models showing a better fit than purely drift models. In addition, the abundance of EFNs was associated with habitat shifts (with a decrease in the abundance of EFNs from forest to savannas), and a potential trade-off was detected between the abundance of EFNs and estipitate glandular trichomes (i.e. trichomes with sticky secretion). These evolutionary associations suggest divergent selection between species as well as explains K-values < 1. Experimental studies with multiple lineages of forest and savanna taxa may improve our understanding of the role of nectaries in plants. Overall, our results suggest that the evolution of EFNs was likely associated with the adaptive process which probably played an important role in the diversification of this plant group.

A novel linkage map of sugarcane with evidence for clustering of retrotransposon-based markers

Background: The development of sugarcane as a sustainable crop has unlimited applications. The crop is one of the most economically viable for renewable energy production, and CO2 balance. Linkage maps are valuable tools for understanding genetic and genomic organization, particularly in sugarcane due to its complex polyploid genome of multispecific origins. The overall objective of our study was to construct a novel sugarcane linkage map, compiling AFLP and EST-SSR markers, and to generate data on the distribution of markers anchored to sequences of scIvana_1, a complete sugarcane transposable element, and member of the Copia superfamily. Results: The mapping population parents ('IAC66-6' and 'TUC71-7') contributed equally to polymorphisms, independent of marker type, and generated markers that were distributed into nearly the same number of co-segregation groups (or CGs). Bi-parentally inherited alleles provided the integration of 19 CGs. The marker number per CG ranged from two to 39. The total map length was 4,843.19 cM, with a marker density of 8.87 cM. Markers were assembled into 92 CGs that ranged in length from 1.14 to 404.72 cM, with an estimated average length of 52.64 cM. The greatest distance between two adjacent markers was 48.25 cM. The scIvana_1-based markers (56) were positioned on 21 CGs, but were not regularly distributed. Interestingly, the distance between adjacent scIvana_1-based markers was less than 5 cM, and was observed on five CGs, suggesting a clustered organization. Conclusions: Results indicated the use of a NBS-profiling technique was efficient to develop retrotransposon-based markers in sugarcane. The simultaneous maximum-likelihood estimates of linkage and linkage phase based strategies confirmed the suitability of its approach to estimate linkage, and construct the linkage map. Interestingly, using our genetic data it was possible to calculate the number of retrotransposonscIvana_1 (similar to 60) copies in the sugarcane genome, confirming previously reported molecular results. In addition, this research possibly will have indirect implications in crop economics e. g., productivity enhancement via QTL studies, as the mapping population parents differ in response to an important fungal disease.

Estimation and diagnostics for heteroscedastic nonlinear regression models based on scale mixtures of skew-normal distributions

An extension of some standard likelihood based procedures to heteroscedastic nonlinear regression models under scale mixtures of skew-normal (SMSN) distributions is developed. This novel class of models provides a useful generalization of the heteroscedastic symmetrical nonlinear regression models (Cysneiros et al., 2010), since the random term distributions cover both symmetric as well as asymmetric and heavy-tailed distributions such as skew-t, skew-slash, skew-contaminated normal, among others. A simple EM-type algorithm for iteratively computing maximum likelihood estimates of the parameters is presented and the observed information matrix is derived analytically. In order to examine the performance of the proposed methods, some simulation studies are presented to show the robust aspect of this flexible class against outlying and influential observations and that the maximum likelihood estimates based on the EM-type algorithm do provide good asymptotic properties. Furthermore, local influence measures and the one-step approximations of the estimates in the case-deletion model are obtained. Finally, an illustration of the methodology is given considering a data set previously analyzed under the homoscedastic skew-t nonlinear regression model. (C) 2012 Elsevier B.V. All rights reserved.

THE LOG-BURR XII REGRESSION MODEL FOR GROUPED SURVIVAL DATA

The log-Burr XII regression model for grouped survival data is evaluated in the presence of many ties. The methodology for grouped survival data is based on life tables, where the times are grouped in k intervals, and we fit discrete lifetime regression models to the data. The model parameters are estimated by maximum likelihood and jackknife methods. To detect influential observations in the proposed model, diagnostic measures based on case deletion, so-called global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to these measures, the total local influence and influential estimates are also used. We conduct Monte Carlo simulation studies to assess the finite sample behavior of the maximum likelihood estimators of the proposed model for grouped survival. A real data set is analyzed using a regression model for grouped data.

First evidence of the emergence of novel putative infectious bronchitis virus genotypes in Cuba

The emergence of new infectious bronchitis virus (IBV) genotypes or serotypes along with the poor cross-protection observed among IBV serotypes have complicated the avian infectious bronchitis (IB) control programs in different geographic regions. In Cuba, the lack of genetic information regarding IBV and the increasing epidemiological importance of this virus in Cuban chicken flocks demand further characterization of IBV isolates. In the present work, studies of genetic diversity and phylogenetic relationships among recent IBV isolates from Cuban chicken flocks showing respiratory disorders were performed. Two putative genotypes genetically different to the Massachusetts genotype H120 strain used in the Cuban vaccination program were found in the flocks assessed. In addition, a potential nephropathogenic IBV isolate was found by first time in Cuba. (C) 2012 Elsevier Ltd. All rights reserved.

The 3D structure and function of digestive cathepsin L-like proteinases of Tenebrio molitor larval midgut

Cathepsin L-like proteinases (CAL) are major digestive proteinases in the beetle Tenebrio molitor. Procathepsin Ls 2 (pCAL2) and 3 (pCAL3) were expressed as recombinant proteins in Escherichia coil, purified and activated under acidic conditions. Immunoblot analyses of different T. molitor larval tissues demonstrated that a polyclonal antibody to pCAL3 recognized pCAL3 and cathepsin L 3 (CAD) only in the anterior two-thirds of midgut tissue and midgut luminal contents of T. molitor larvae. Furthermore, immunocytolocalization data indicated that pCAL3 occurs in secretory vesicles and microvilli in anterior midgut Therefore CAL3, like cathepsin L 2 (CAL2), is a digestive enzyme secreted by T. molitor anterior midgut CAD hydrolyses Z-FR-MCA and Z-RR-MCA (typical cathepsin substrates), whereas CAL2 hydrolyses only Z-FR-MCA. Active site mutants (pCAL2C25S and pCAL3C265) were constructed by replacing the catalytic cysteine with serine to prevent autocatalytic processing. Recombinant pCAL2 and pCAL3 mutants (pCAL2C25S and pCAL3C26S) were prepared, crystallized and their 3D structures determined at 1.85 and 2.1 angstrom, respectively. While the overall structure of these enzymes is similar to other members of the papain superfamily, structural differences in the S2 subsite explain their substrate specificities. The data also supported models for CAL trafficking to lysosomes and to secretory vesicles to be discharged into midgut contents. (C) 2012 Elsevier Ltd. All rights reserved.

An extension of the half-normal distribution

In this paper we introduce a new distribution, namely, the slashed half-normal distribution and it can be seen as an extension of the half-normal distribution. It is shown that the resulting distribution has more kurtosis than the ordinary half-normal distribution. Moments and some properties are derived for the new distribution. Moment estimators and maximum likelihood estimators can computed using numerical procedures. Results of two real data application are reported where model fitting is implemented by using maximum likelihood estimation. The applications illustrate the better performance of the new distribution.

Robust modeling using the generalized epsilon-skew-t distribution

In this paper, an alternative skew Student-t family of distributions is studied. It is obtained as an extension of the generalized Student-t (GS-t) family introduced by McDonald and Newey [10]. The extension that is obtained can be seen as a reparametrization of the skewed GS-t distribution considered by Theodossiou [14]. A key element in the construction of such an extension is that it can be stochastically represented as a mixture of an epsilon-skew-power-exponential distribution [1] and a generalized-gamma distribution. From this representation, we can readily derive theoretical properties and easy-to-implement simulation schemes. Furthermore, we study some of its main properties including stochastic representation, moments and asymmetry and kurtosis coefficients. We also derive the Fisher information matrix, which is shown to be nonsingular for some special cases such as when the asymmetry parameter is null, that is, at the vicinity of symmetry, and discuss maximum-likelihood estimation. Simulation studies for some particular cases and real data analysis are also reported, illustrating the usefulness of the extension considered.

Comparative Genome Analysis of Trichophyton rubrum and Related Dermatophytes Reveals Candidate Genes Involved in Infection

The major cause of athlete's foot is Trichophyton rubrum, a dermatophyte or fungal pathogen of human skin. To facilitate molecular analyses of the dermatophytes, we sequenced T. rubrum and four related species, Trichophyton tonsurans, Trichophyton equinum, Microsporum canis, and Microsporum gypseum. These species differ in host range, mating, and disease progression. The dermatophyte genomes are highly colinear yet contain gene family expansions not found in other human-associated fungi. Dermatophyte genomes are enriched for gene families containing the LysM domain, which binds chitin and potentially related carbohydrates. These LysM domains differ in sequence from those in other species in regions of the peptide that could affect substrate binding. The dermatophytes also encode novel sets of fungus-specific kinases with unknown specificity, including nonfunctional pseudokinases, which may inhibit phosphorylation by competing for kinase sites within substrates, acting as allosteric effectors, or acting as scaffolds for signaling. The dermatophytes are also enriched for a large number of enzymes that synthesize secondary metabolites, including dermatophyte-specific genes that could synthesize novel compounds. Finally, dermatophytes are enriched in several classes of proteases that are necessary for fungal growth and nutrient acquisition on keratinized tissues. Despite differences in mating ability, genes involved in mating and meiosis are conserved across species, suggesting the possibility of cryptic mating in species where it has not been previously detected. These genome analyses identify gene families that are important to our understanding of how dermatophytes cause chronic infections, how they interact with epithelial cells, and how they respond to the host immune response. IMPORTANCE Athlete's foot, jock itch, ringworm, and nail infections are common fungal infections, all caused by fungi known as dermatophytes (fungi that infect skin). This report presents the genome sequences of Trichophyton rubrum, the most frequent cause of athlete's foot, as well as four other common dermatophytes. Dermatophyte genomes are enriched for four gene classes that may contribute to the ability of these fungi to cause disease. These include (i) proteases secreted to degrade skin; (ii) kinases, including pseudokinases, that are involved in signaling necessary for adapting to skin; (iii) secondary metabolites, compounds that act as toxins or signals in the interactions between fungus and host; and (iv) a class of proteins (LysM) that appear to bind and mask cell wall components and carbohydrates, thus avoiding the host's immune response to the fungi. These genome sequences provide a strong foundation for future work in understanding how dermatophytes cause disease.