Random regression test-day models to describe milk production and fatty acid traits in first lactation Walloon Holstein cows.

We investigated the use of different Legendre polynomial orders to estimate genetic parameters for milk production and fatty acid (FA) traits in the first lactation Walloon Holstein cows. The data set comprised 302,684 test-day records of milk yield, fat and protein contents, and FAs generated by mid-infrared (MIR) spectroscopy, C16:0 (palmitic acid), C18:1 cis-9 (oleic acid), LCFAs (long-chain FAs), SFAs (saturated FAs) and UFAs (unsaturated FAs) were studied. The models included random regression coefficients for herd-year of calving (h), additive genetic (a) and permanent environment (p) effects. The selection of the best random regression model (RRM) was based on the deviance information criterion (DIC), and genetic parameters were estimated via a Bayesian approach. For all analysed random effects, DIC values decreased as the order of the Legendre polynomials increased. Best-fit models had fifth-order (degree 4) for the p effect and ranged from second- to fifth-order (degree 1-4) for the a and h effects (LEGhap: LEG555 for milk yield and protein content; LEG335 for fat content and SFA; LEG545 for C16:0 and UFA; and LEG535 for C18:1 cis-9 and LCFA). Based on the best-fit models, an effect of overcorrection was observed in early lactation (5-35 days in milk [DIM]). On the contrary, third-order (LEG333; degree 2) models showed flat residual trajectories throughout lactation. In general, the estimates of genetic variance tended to increase over DIM, for all traits. Heritabilities for milk production traits ranged from 0.11 to 0.58. Milk FA heritabilities ranged from low-to-high magnitude (0.03-0.56). High Spearman correlations (>0.90 for all bulls and >0.97 for top 100) were found among breeding values for 155 and 305 DIM between the best RRM and LEG333 model. Therefore, third-order Legendre polynomials seem to be most parsimonious and sufficient to describe milk production and FA traits in Walloon Holstein cows.

Can Cross-Country Genomic Predictions Be a Reasonable Strategy to Support Germplasm Exchange? - A Case Study With Hydrogen Cyanide in Cassava.

Genomic prediction (GP) offers great opportunities for accelerated genetic gains by optimizing the breeding pipeline. One of the key factors to be considered is how the training populations (TP) are composed in terms of genetic improvement, kinship/origin, and their impacts on GP. Hydrogen cyanide content (HCN) is a determinant trait to guide cassava's products usage and processing. This work aimed to achieve the following objectives: (i) evaluate the feasibility of using cross-country (CC) GP between germplasm's of Embrapa Mandioca e Fruticultura (Embrapa, Brazil) and The International Institute of Tropical Agriculture (IITA, Nigeria) for HCN; (ii) provide an assessment of population structure for the joint dataset; (iii) estimate the genetic parameters based on single nucleotide polymorphisms (SNPs) and a haplotype-approach. Datasets of HCN from Embrapa and IITA breeding programs were analyzed, separately and jointly, with 1,230, 590, and 1,820 clones, respectively. After quality control, ∼14K SNPs were used for GP. The genomic estimated breeding values (GEBVs) were predicted based on SNP effects from analyses with TP composed of the following: (i) Embrapa genotypic and phenotypic data, (ii) IITA genotypic and phenotypic data, and (iii) the joint datasets. Comparisons on GEBVs' estimation were made considering the hypothetical situation of not having the phenotypic characterization for a set of clones for a certain research institute/country and might need to use the markers' effects that were trained with data from other research institutes/country's germplasm to estimate their clones' GEBV. Fixation index (FST) among the genetic groups identified within the joint dataset ranged from 0.002 to 0.091. The joint dataset provided an improved accuracy (0.8-0.85) compared to the prediction accuracy of either germplasm's sources individually (0.51-0.67). CC GP proved to have potential use under the present study's scenario, the correlation between GEBVs predicted with TP from Embrapa and IITA was 0.55 for Embrapa's germplasm, whereas for IITA's it was 0.1. This seems to be among the first attempts to evaluate the CC GP in plants. As such, a lot of useful new information was provided on the subject, which can guide new research on this very important and emerging field.

Oxidative and local histopathological response on skin wound of horses due to Amblyomma sculptum tick parasitism.

Amblyomma sculptum is frequently observed parasitizing horses, responsible for economic losses, damage to the host''s skin and transmission of pathogens. The oxidative stress profile and inflammatory mechanisms involved in this parasitism remain poorly studied. Thus, this study aimed to assess the histopathological changes and oxidative profile responses of horses in the attachment site of A. sculptum to find variations that indicate resistance and susceptibility between the breeds to this tick, based on the hypothesis that resistant animals have a greater inflammatory response and lesser number of attached ticks. We analyzed female horses of two breeds, Mangalarga Marchador and Breton Postier, naturally infested by Amblyomma sculptum. The ticks were counted and full-thickness excisional skin wounds of 10 mm were made on the perineal region on the attachment site of partially engorged females for histological and biochemical analyzes. The occurrence of the tick on the skin caused an increase in cellularity, inflammatory infiltrate, mast cells, pyknotic nuclei, and changes in the fibrous components of the matrix. The negative correlation observed between tick infestation and inflammatory response indicated that animals with greater inflammatory response tend to have less tick infestation. The oxidative stress markers, MDA, PCN and NO not present great variation; however, between the antioxidant enzymes levels, SOD was higher in tick attachment of Breton Postier skin, this may mean that these animals had higher oxidative enzymatic activity and consequently less tissue damage, while the GST dropped in the attachment sites compared to the control, which may indicate that animals were in a state of significant oxidative stress or raises the question of the possibility of enzymatic sequestration by ticks. No significant differences were found in the resistance of the two breeds since most of the analyzes varied due to the presence or absence of the tick attached to the skin. We draw attention to the importance of studying characteristics of the animal's antioxidant responses to the tick and the action of tick saliva on antioxidant enzymes and ROS because these characteristics are interdependent with the inflammatory response.

Multiple-trait model through Bayesian inference applied to Jatropha curcas breeding for bioenergy.

Multiple-trait model tends to be the best alternative for the analysis of repeated measures, since they consider the genetic and residual correlations between measures and improve the selective accuracy. Thus, the objective of this study was to propose a multiple-trait Bayesian model for repeated measures analysis in Jatropha curcas breeding for bioenergy. To this end, the grain yield trait of 730 individuals of 73 half-sib families was evaluated over six harvests. The Markov Chain Monte Carlo algorithm was used to estimate genetic parameters and genetic values. Genetic correlation between pairs of measures were estimated and four selective intensities (27.4%, 20.5%, 13.7%, and 6.9%) were used to compute the selection gains. The full model was selected based on deviance information criterion. Genetic correlations of low (ρg ≤ 0.33), moderate (0.34 ≤ ρg ≤ 0.66), and high magnitude (ρg ≥ 0.67) were observed between pairs of harvests. Bayesian analyses provide robust inference of genetic parameters and genetic values, with high selective accuracies. In summary, the multiple-trait Bayesian model allowed the reliable selection of superior Jatropha curcas progenies. Therefore, we recommend this model to genetic evaluation of Jatropha curcas genotypes, and its generalization, in other perennials.

Genetic parameters for milk, growth, and reproductive traits in Guzerá cattle under tropical conditions.

This study aimed to estimate the genetic parameters of milk (305-day milk yield (MY305)), growth (weaning weight (WW), yearling weight (YW), and weight at 550 days (W550)), and reproductive (age at first calving (AFC)) traits in Guzerá cattle by using Bayesian multiple-trait models. Systematic effects included sex and age at calving for the growth and milk traits, respectively. The additive genetic and contemporary groups (herd and year and season of birth) were included as random effects. Additionally, maternal genetic and permanent effects were also included as random effects for the WW. The heritability estimates were 0.29 (MY305), 0.42 (WW), 0.49 (YW), 0.56 (W550), and 0.25 (AFC). The genetic correlations among the growth traits were higher than 0.83; between the MY305 and WW, MY305 and YW, and MY305 and W550, the genetic correlations were 0.25, 0.32, and 0.36, respectively. The AFC was negatively correlated with the milk and growth traits. These results suggest the viability and potential of the joint selection for milk, beef, and reproductive traits in Guzerá cattle.

Linkage disequilibrium and haplotype block patterns in popcorn populations.

Linkage disequilibrium (LD) analysis provides information on the evolutionary aspects of populations. Recently, haplotype blocks have been used to increase the power of quantitative trait loci detection in genome-wide association studies and the prediction accuracy of genomic selection. Our objectives were as follows: to compare the degree of LD, LD decay, and LD decay extent in popcorn populations; to characterize the number and length of haplotype blocks in the populations; and to determine whether maize chromosomes also have a pattern of interspaced regions of high and low rates of recombination. We used a biparental population, a synthetic, and a breeding population, genotyped for approximately 75,000 single nucleotide polymorphisms (SNPs). The sample size ranged from 190 to 192 plants. For the whole-genome LD and haplotype block analyses, we assumed a window of 500 kb. To characterize the block and step patterns of LD in the populations, we constructed LD maps by chromosome, defining a cold spot as a chromosome segment including SNPs with the same LDU position. The LD and haplotype block analyses were also performed at the intragenic level, selecting 12 genes related to zein, starch, cellulose, and fatty acid biosynthesis. The populations with the higher and lower frequencies of |D'| values greater than 0.75 were the biparental (65-74%) and the breeding population (26-58%), respectively. There were slight differences between the populations regarding the average distance for SNPs with |D'| values greater than 0.75 (in the range of approximately 207 to 229 kb). The level of LD expressed by the r2 values was low in the populations (0.02, 0.04, and 0.04, on average) but comparable to some non-isolated human populations. The frequency of r2 values greater than 0.75 was lower in the biparental population (0.2-0.5%) and higher in the other populations (0.2-1.6%). The average distance for SNPs with r2 values greater than 0.75 was much higher in the biparental population (approximately 80 to 126 kb). In the other populations, the ranges were approximately 6 to 19 and 6 to 35 kb. The heatmaps for the regions covered by the first 100 SNPs in each chromosome, in each population (1 to 3.3 Mb, approximately), provided evidence that the comparatively few high r2 values (close to 1.0) occurred only for SNPs in close proximity, especially in the synthetic and breeding populations. Due to the reduced number of SNPs in the haplotype blocks (2 to 3) in the populations, it is not expected advantage of a haplotype-based association study as well as genomic selection along generations. The results concerning LD decay (rapid decay after 5-10 kb) and LD decay extent (along up to 300 kb) are in the range observed with maize inbred line panels. The LD maps indicate that maize chromosomes had a pattern of regions of extensive LD interspaced with regions of low LD. However, our simulated LD map provides evidence that this pattern can reflect regions with differences in allele frequencies and LD levels (expressed by |D'|) and not regions with high and low rates of recombination.

Genomic selection for productive traits in biparental cassava breeding populations.

Cassava improvement using traditional breeding strategies is slow due to the species' long breeding cycle. However, the use of genomic selection can lead to a shorter breeding cycle. This study aimed to estimate genetic parameters for productive traits based on pedigree (pedigree and phenotypic information) and genomic (markers and phenotypic information) analyses using biparental crosses at different stages of selection. A total of 290 clones were genotyped and phenotyped for fresh root yield (FRY), dry matter content (DMC), dry yield (DY), fresh shoot yield (FSY) and harvest index (HI). The clones were evaluated in clonal evaluation trials (CET), preliminary yield trials (PYT), advanced yield trials (AYT) and uniform yield trials (UYT), from 2013 to 2018 in ten locations. The breeding stages were analyzed as follows: one stage (CET), two stages (CET and PYT), three stages (CET, PYT and AYT) and four stages (CET, PYT, AYT and UYT). The genomic predictions were analyzed via k-fold cross-validation based on the genomic best linear unbiased prediction (GBLUP) considering a model with genetic additive effects and genotype × location interactions. Genomic and pedigree accuracies were moderate to high (0.56-0.72 and 0.62-0.78, respectively) for important starch-related traits such as DY and FRY; when considering one breeding stage (CET) with the aim of early selection, the genomic accuracies ranged from 0.60 (DMC) to 0.71 (HI). Moreover, the correlations between the genomic estimation breeding values of one-stage genomic analysis and the estimated breeding values of the four-stage (full data set) pedigree analysis were high for all traits as well as for a selection index including all traits. The results indicate great possibilities for genomic selection in cassava, especially for selection early in the breeding cycle (saving time and effort).

Genes expression and phenotypic differences in corpus luteum and cumulus cells of commercial line and piau breed gilts.

We aimed to characterize the expression of angiogenesis-related genes in corpus luteum (CL) and cumulus cells (CC) during estrous cycle in gilts of different genetic groups, as well as to study the relation between gene expression and phenotypic data. Forty five gilts were used as follows: L1, Commercial Line 1 (Large White x Landrace x Duroc) (n = 15); L2, Commercial Line 2 (Large White x Landrace x Pietrain) (n = 15); and Piau, Piau breed gilts (n = 15). Estrus observation started from 120 days of age. After the second observed estrus females were slaughtered (n = 3) on days 3, 5, 10, 14 and 18 of estrous cycle (first day of estrous cycle as Day 0). CL sampling was performed on days 3, 5, 10 and 14 and collection of CC and follicular fluid on days 14 and 18. Follicular fluid was used for analysis of estradiol levels and CC and CL samples for analysis of angiogenesis-related genes expression, ANGPT-1/-2 and TEK in CC and MMP-2, VEGFA, VEGFR-1/-2, ANGPT-1/-2 and TEK in CL. Piau gilts showed lower ovulation rate than both L1 and L2 gilts (P < 0.05), lower number of large antral follicles (>6 mm) at 18 days than L2 gilts (P < 0.05), and smaller diameter of the largest follicles at 14 days than L1 gilts (P < 0.05). Piau and L2 gilts showed higher estradiol levels in follicular fluid on day 18. Expression of ANGPT-1 and -2 genes in CC did not differ among genetic groups neither among days of the estrous cycle, but TEK gene expression was higher in L1 than L2 gilts on day 18. Expression of VEGFA, VEGFR-2 and MMP-2 genes in CL did not differ among genetic groups and days of cycle, but VEGFR-1 expression was higher in Piau than L2 gilts on days 10 and 14, and it was higher in L1 than L2 gilts on day 14. The ANGPT-1/-2 and TEK genes expression in CL were significantly higher in Piau than L1 gilts on day 10. The ANGPT-2/ANGPT-1 gene expression ratio in CL was higher in L1 than Piau and L2 gilts at 14 days, suggesting a shorter luteal phase for L1 gilts. Results indicated differences among genetic groups for the pattern of the angiogenesis-related genes expression in CL along estrous cycles, which may be reflected in phenotypic traits such as ovulation rate, estradiol levels in follicular fluid and number and diameter of antral follicles.

Use of nonlinear mixed models for describing testicular volume growth curve in Nellore bulls.

This study aimed to describe longitudinal testicular volume (TV) data of Nellore bulls by using nonlinear mixed models. Dataset consisted of 2,294 TV measurements from 505 bulls with ages ranging from 563 to 4,307 days. Nine nonlinear models were evaluated: Brody, Gompertz, Hill, Logistic I and II, Meloun, Michaelis-Menten, Mitscherlich and von Bertalanffy. Goodness of fit was evaluated by Akaike's information criterion (AIC), Bayesian information criterion (BIC), adjusted R2, percentage of convergence, error sum of squares (ESS), mean absolute deviation (MAD), and average prediction error (APE). These criteria were used to select the best model, then the absolute growth rate (AGR) for TV was estimated by the first derivate of the adjusted model related to time (∂Y/∂t). The values of adjusted R2, ESS, MAD and APE were similar among models. Percentage of convergence was higher for the Logistic I (76.8%), Logistic II (75.5%) and Mitscherlich (78.6%) models, but Logistic I and II showed the lowest values of AIC and BIC, indicating a better fit, so the Logistic I model was chosen for subsequent analyses. The TV growth occurred at a high rate until the inflection point, which was estimated at approximately 22 months of age; it stabilized and reached a plateau at approximately 2,500 days of age. This may suggest that TV is more related to sexual maturity than precocity. Additionally, the Logistic I model was used to estimate the growth curve and the AGR of the testicular length and width. As a result, testicular length increased at a higher rate than testicular width until approximately 1,600 days of age, indicating that the testes become longer with increasing age.

Novel lactic acid bacteria strains as inoculants on alfalfa silage fermentation.

The effects of new strains of lactic acid bacteria on alfalfa silage fermentation were evaluated. The experiment was performed using a completely randomized design (with three replicates) based on a 6 × 6 factorial assay with 6 inoculants (I): Control (CTRL), Commercial inoculant (CI), Lactobacillus pentosus 14.7SE (LPE), Lactobacillus plantarum 3.7E (LP), Pediococcus pentosaceus 14.15SE (PP), and Lactobacillus plantarum 3.7E + Pediococcus pentosaceus 14.15SE (LP + PP), and six fermentation periods (P): 1, 3, 7, 14, 28 and 56 days. Alfalfa was wilted for 6 h in the field, which increased the dry matter content to 368 g/kg as fed. The CP and yeast population decreased during the fermentation process. Silage inoculated with the PP strain had the lowest pH values beginning at 14 d of fermentation and the lowest acetic acid concentration on the last day of fermentation. New strains more efficiently regulated enterobacteria and mold populations at days 56 and 28, respectively. Silages inoculated with the PP strain had a higher coefficient of in vitro dry matter digestibility than LP silages. All of the tested novel strains resulted in positive effects on at least one chemical property of the silage during the fermentation process. However, the adding of P. pentosaceus can be indicated as the better for silage quality considering the tested treatments in the present study.

Genome-Wide Association and Regional Heritability Mapping of Plant Architecture, Lodging and Productivity in Phaseolus vulgaris.

The availability of high-density molecular markers in common bean has allowed to explore the genetic basis of important complex agronomic traits with increased resolution. Genome-Wide Association Studies (GWAS) and Regional Heritability Mapping (RHM) are two analytical approaches for the detection of genetic variants. We carried out GWAS and RHM for plant architecture, lodging and productivity across two important growing environments in Brazil in a germplasm of 188 common bean varieties using DArTseq genotyping strategies. The coefficient of determination of G × E interaction (c2int ) was equal to 17, 21 and 41%, respectively for the traits architecture, lodging, and productivity. Trait heritabilities were estimated at 0.81 (architecture), 0.79 (lodging) and 0.43 (productivity), and total genomic heritability accounted for large proportions (72% to ≈100%) of trait heritability. At the same probability threshold, three marker-trait associations were detected using GWAS, while RHM detected eight QTL encompassing 145 markers along five chromosomes. The proportion of genomic heritability explained by RHM was considerably higher (35.48 to 58.02) than that explained by GWAS (28.39 to 30.37). In general, RHM accounted for larger fractions of the additive genetic variance being captured by markers effects inside the defined regions. Nevertheless, a considerable proportion of the heritability is still missing (∼42% to ∼64%), probably due to LD between markers and genes and/or rare allele variants not sampled. RHM in autogamous species had the potential to identify larger-effect QTL combining allelic variants that could be effectively incorporated into whole-genome prediction models and tracked through breeding generations using marker-assisted selection.

Relevance of genetic relationship in GWAS and genomic prediction.

The objective of this study was to analyze the relevance of relationship information on the identification of low heritability quantitative trait loci (QTLs) from a genome-wide association study (GWAS) and on the genomic prediction of complex traits in human, animal and cross-pollinating populations. The simulation-based data sets included 50 samples of 1000 individuals of seven populations derived from a common population with linkage disequilibrium. The populations had non-inbred and inbred progeny structure (50 to 200) with varying number of members (5 to 20). The individuals were genotyped for 10,000 single nucleotide polymorphisms (SNPs) and phenotyped for a quantitative trait controlled by 10 QTLs and 90 minor genes showing dominance. The SNP density was 0.1 cM and the narrow sense heritability was 25%. The QTL heritabilities ranged from 1.1 to 2.9%. We applied mixed model approaches for both GWAS and genomic prediction using pedigree-based and genomic relationship matrices. For GWAS, the observed false discovery rate was kept below the significance level of 5%, the power of detection for the low heritability QTLs ranged from 14 to 50%, and the average bias between significant SNPs and a QTL ranged from less than 0.01 to 0.23 cM. The QTL detection power was consistently higher using genomic relationship matrix. Regardless of population and training set size, genomic prediction provided higher prediction accuracy of complex trait when compared to pedigree-based prediction. The accuracy of genomic prediction when there is relatedness between individuals in the training set and the reference population is much higher than the value for unrelated individuals.

Weight gain potential affects pregnancy rates in bovine embryo recipients raised under pasture conditions.

The aim of the present study was to evaluate the effect of differences in body weight gain after embryo transfer on the pregnancy rates of crossbred heifers used as recipients and raised under a grazing system. The study was performed during the dry (April to September) and the rainy (October to March) seasons. The embryos transferred were produced by in vitro fertilization. The body weight of each recipient was measured immediately before the embryo transfer and 23 to 25 days later, when the diagnosis of pregnancy was performed by ultrasonography. The associations among initial body weight (IBW), daily body weight gain (DWG), season, and pregnancy rate were evaluated using a logistic procedure that included the effect of the IBW, season, and linear and quadratic effects of the DWG. Altogether, there was no effect of season and pregnancy rates did not change between the dry and rainy seasons (42.3 vs. 45.8%, respectively; P > 0.05). However, the pregnancy rate was greater in the recipients with daily body weight gains over 250 g/day, regardless of the season. In addition, the pregnancy rate of the recipients was better (P < 0.04) explained by a logistic regression model that included the linear and quadratic effects of the DWG. The probability of each heifer to become pregnant according to DWG is explained by the follow equation: P(y = 1) = (Exp((-1.06703 + 0.0108 * DWG - 0.00002 * DWG ^ 2)))/(1 + Exp((-1.6703 + 0.0108 * DWG - 0.00002 * DWG ^ 2))). In conclusion, body weight gain potential is a critical factor for the pregnancy rates of in vitro embryo recipients managed under grazing systems.

Multi-Trait GWAS and New Candidate Genes Annotation for Growth Curve Parameters in Brahman Cattle.

Understanding the genetic architecture of beef cattle growth cannot be limited simply to the genome-wide association study (GWAS) for body weight at any specific ages, but should be extended to a more general purpose by considering the whole growth trajectory over time using a growth curve approach. For such an approach, the parameters that are used to describe growth curves were treated as phenotypes under a GWAS model. Data from 1,255 Brahman cattle that were weighed at birth, 6, 12, 15, 18, and 24 months of age were analyzed. Parameter estimates, such as mature weight (A) and maturity rate (K) from nonlinear models are utilized as substitutes for the original body weights for the GWAS analysis. We chose the best nonlinear model to describe the weight-age data, and the estimated parameters were used as phenotypes in a multi-trait GWAS. Our aims were to identify and characterize associated SNP markers to indicate SNP-derived candidate genes and annotate their function as related to growth processes in beef cattle. The Brody model presented the best goodness of fit, and the heritability values for the parameter estimates for mature weight (A) and maturity rate (K) were 0.23 and 0.32, respectively, proving that these traits can be a feasible alternative when the objective is to change the shape of growth curves within genetic improvement programs. The genetic correlation between A and K was -0.84, indicating that animals with lower mature body weights reached that weight at younger ages. One hundred and sixty seven (167) and two hundred and sixty two (262) significant SNPs were associated with A and K, respectively. The annotated genes closest to the most significant SNPs for A had direct biological functions related to muscle development (RAB28), myogenic induction (BTG1), fetal growth (IL2), and body weights (APEX2); K genes were functionally associated with body weight, body height, average daily gain (TMEM18), and skeletal muscle development (SMN1). Candidate genes emerging from this GWAS may inform the search for causative mutations that could underpin genomic breeding for improved growth rates.

Efficacy of population structure analysis with breeding populations and inbred lines.

The objective was to assess by simulation the efficacy of population structure analysis in plant breeding. Twelve populations and 300 inbred lines were simulated and genotyped using 100 microsatellite loci. The experimental material included populations with and without admixture, ancestry relationship and linkage disequilibrium, and with distinct levels of genetic differentiation and effective sizes. The analyses were performed using Structure software and employed all available models. For all the group number (K) tested, for both populations and inbred lines, the admixture model with correlated allelic frequencies provided the highest value for the logarithm of the marginal likelihood. Fitting appropriate model and using adequate sample size for individuals and markers, Structure was effective in identifying the correct population structure, migrants and individuals with genome from distinct populations. The linkage model did not result in an improvement in clustering relative to the admixture model with correlated allelic frequencies. The inclusion of prior information did not change the results; for some K values the analyses showed slight higher values of the marginal likelihood. The reduction in the number of individuals and markers negatively affected the results. There was a high variation in the most probable K value between the evaluated methods.

Bayesian model-based clustering of temporal gene expression using autoregressive panel data approach.

MOTIVATION: In a microarray time series analysis, due to the large number of genes evaluated, the first step toward understanding the complex time network is the clustering of genes that share similar expression patterns over time. Up until now, the proposed methods do not point simultaneously to the temporal autocorrelation of the gene expression and the model-based clustering. We present a Bayesian method that considers jointly the fit of autoregressive panel data models and hierarchical gene clustering. RESULTS: The proposed methodology was able to cluster genes that share similar expression over time, which was determined jointly by the estimates of autoregression parameters, by the average level of expression) and by the quality of the fitted model. AVAILABILITY AND IMPLEMENTATION: The R codes for implementation of the proposed clustering method and for simulation study, as well as the real and simulated datasets, are freely accessible on the Web http://www.det.ufv.br/~moyses/links.php. CONTACT: moysesnascim@ufv.br.

Epidemiology, clinical signs, histopathology and molecular characterization of canine leproid granuloma: a retrospective study of cases from Brazil.

Thirty-eight cases of canine leproid granuloma were diagnosed between 2000 and 2008. Diagnosis was based upon clinical and histopathological findings and the presence of acid-fast bacilli in skin sections. The clinical lesions were localized predominantly on the pinnae and included papules, plaques and nodules, with or without ulceration. Boxer dogs were the breed most affected. Histopathological findings included nodular to diffuse pyogranulomatous, lymphoplasmocytic inflammatory infiltrates, with or without necrosis, localized in the dermis or subcutaneous tissue. The bacillary loading and morphology were variable among the lesions analysed. There was no significant correlation between bacterial load and histopathological pattern, dominant type of inflammatory infiltration or the amount of necrosis or giant cells. No correlation was observed between giant cells and histopathological pattern. In the majority of cases where a PCR-based assay was done, a novel mycobacterium species as the main aetiological agent was identified, as reported in previous studies.