Group I introns and associated homing endonuclease genes reveals a clinal structure for Porphyra spiralis var. amplifolia (Bangiales, Rhodophyta) along the Eastern coast of South America

Background: Group I introns are found in the nuclear small subunit ribosomal RNA gene (SSU rDNA) of some species of the genus Porphyra (Bangiales, Rhodophyta). Size polymorphisms in group I introns has been interpreted as the result of the degeneration of homing endonuclease genes (HEG) inserted in peripheral loops of intron paired elements. In this study, intron size polymorphisms were characterized for different Porphyra spiralis var. amplifolia (PSA) populations on the Southern Brazilian coast, and were used to infer genetic relationships and genetic structure of these PSA populations, in addition to cox2-3 and rbcL-S regions. Introns of different sizes were tested qualitatively for in vitro self-splicing. Results: Five intron size polymorphisms within 17 haplotypes were obtained from 80 individuals representing eight localities along the distribution of PSA in the Eastern coast of South America. In order to infer genetic structure and genetic relationships of PSA, these polymorphisms and haplotypes were used as markers for pairwise Fst analyses, Mantel's test and median joining network. The five cox2-3 haplotypes and the unique rbcL-S haplotype were used as markers for summary statistics, neutrality tests Tajima's D and Fu's Fs and for median joining network analyses. An event of demographic expansion from a population with low effective number, followed by a pattern of isolation by distance was obtained for PSA populations with the three analyses. In vitro experiments have shown that introns of different lengths were able to self-splice from pre-RNA transcripts. Conclusion: The findings indicated that degenerated HEGs are reminiscent of the presence of a full-length and functional HEG, once fixed for PSA populations. The cline of HEG degeneration determined the pattern of isolation by distance. Analyses with the other markers indicated an event of demographic expansion from a population with low effective number. The different degrees of degeneration of the HEG do not refrain intron self-splicing. To our knowledge, this was the first study to address intraspecific evolutionary history of a nuclear group I intron; to use nuclear, mitochondrial and chloroplast DNA for population level analyses of Porphyra; and intron size polymorphism as a marker for population genetics.

Var transcription profiling of Plasmodium falciparum 3D7: assignment of cytoadherent phenotypes to dominant transcripts

Background: Cytoadherence of Plasmodium falciparum-infected red blood cells is mediated by var gene-encoded P. falciparum erythrocyte membrane protein-1 and host receptor preference depends in most cases on which of the 50-60 var genes per genome is expressed. Enrichment of phenotypically homogenous parasites by panning on receptor expressing cells is fundamental for the identification of the corresponding var transcript. Methods: P. falciparum 3D7 parasites were panned on several transfected CHO-cell lines and their var transcripts analysed by i) reverse transcription/PCR/cloning/sequencing using a universal DBL alpha specific oligonucleotide pair and ii) by reverse transcription followed by quantitative PCR using 57 different oligonucleotide pairs. Results: Each cytoadherence selected parasite line also adhered to untransfected CHO-745 cells and upregulation of the var gene PFD995/PFD1000c was consistently associated with cytoadherence to all but one CHO cell line. In addition, parasites panned on different CHO cell lines revealed candidate var genes which reproducibly associated to the respective cytoadherent phenotype. The transcription profile obtained by RT-PCR/cloning/sequencing differed significantly from that of RT-quantitative PCR. Conclusion: Transfected CHO cell lines are of limited use for the creation of monophenotypic cytoadherent parasite lines. Nevertheless, 3D7 parasites can be reproducibly selected for the transcription of different determined var genes without genetic manipulation. Most importantly, var transcription analysis by RT-PCR/cloning/sequencing may lead to erroneous interpretation of var transcription profiles.

Bayesian online algorithms for learning in discrete Hidden Markov Models

We propose and analyze two different Bayesian online algorithms for learning in discrete Hidden Markov Models and compare their performance with the already known Baldi-Chauvin Algorithm. Using the Kullback-Leibler divergence as a measure of generalization we draw learning curves in simplified situations for these algorithms and compare their performances.

Haplotype distribution of five nuclear genes based on network genealogies and Bayesian inference indicates that Trypanosoma cruzi hybrid strains are polyphyletic

Chagas disease is still a major public health problem in Latin America. Its causative agent, Trypanosoma cruzi, can be typed into three major groups, T. cruzi I, T. cruzi II and hybrids. These groups each have specific genetic characteristics and epidemiological distributions. Several highly virulent strains are found in the hybrid group; their origin is still a matter of debate. The null hypothesis is that the hybrids are of polyphyletic origin, evolving independently from various hybridization events. The alternative hypothesis is that all extant hybrid strains originated from a single hybridization event. We sequenced both alleles of genes encoding EF-1 alpha, actin and SSU rDNA of 26 T. cruzi strains and DHFR-TS and TR of 12 strains. This information was used for network genealogy analysis and Bayesian phylogenies. We found T. cruzi I and T. cruzi II to be monophyletic and that all hybrids had different combinations of T. cruzi I and T. cruzi II haplotypes plus hybrid-specific haplotypes. Bootstrap values (networks) and posterior probabilities (Bayesian phylogenies) of clades supporting the monophyly of hybrids were far below the 95% confidence interval, indicating that the hybrid group is polyphyletic. We hypothesize that T. cruzi I and T. cruzi II are two different species and that the hybrids are extant representatives of independent events of genome hybridization, which sporadically have sufficient fitness to impact on the epidemiology of Chagas disease.

Bayesian updating rules in continuous opinion dynamics models

Here, I investigate the use of Bayesian updating rules applied to modeling how social agents change their minds in the case of continuous opinion models. Given another agent statement about the continuous value of a variable, we will see that interesting dynamics emerge when an agent assigns a likelihood to that value that is a mixture of a Gaussian and a uniform distribution. This represents the idea that the other agent might have no idea about what is being talked about. The effect of updating only the first moments of the distribution will be studied, and we will see that this generates results similar to those of the bounded confidence models. On also updating the second moment, several different opinions always survive in the long run, as agents become more stubborn with time. However, depending on the probability of error and initial uncertainty, those opinions might be clustered around a central value.

Modeling associations between genetic markers using Bayesian networks

Motivation: Understanding the patterns of association between polymorphisms at different loci in a population ( linkage disequilibrium, LD) is of fundamental importance in various genetic studies. Many coefficients were proposed for measuring the degree of LD, but they provide only a static view of the current LD structure. Generative models (GMs) were proposed to go beyond these measures, giving not only a description of the actual LD structure but also a tool to help understanding the process that generated such structure. GMs based in coalescent theory have been the most appealing because they link LD to evolutionary factors. Nevertheless, the inference and parameter estimation of such models is still computationally challenging. Results: We present a more practical method to build GM that describe LD. The method is based on learning weighted Bayesian network structures from haplotype data, extracting equivalence structure classes and using them to model LD. The results obtained in public data from the HapMap database showed that the method is a promising tool for modeling LD. The associations represented by the learned models are correlated with the traditional measure of LD D`. The method was able to represent LD blocks found by standard tools. The granularity of the association blocks and the readability of the models can be controlled in the method. The results suggest that the causality information gained by our method can be useful to tell about the conservability of the genetic markers and to guide the selection of subset of representative markers.

Using Bayesian networks with rule extraction to infer the risk of weed infestation in a corn-crop

This paper describes the modeling of a weed infestation risk inference system that implements a collaborative inference scheme based on rules extracted from two Bayesian network classifiers. The first Bayesian classifier infers a categorical variable value for the weed-crop competitiveness using as input categorical variables for the total density of weeds and corresponding proportions of narrow and broad-leaved weeds. The inferred categorical variable values for the weed-crop competitiveness along with three other categorical variables extracted from estimated maps for the weed seed production and weed coverage are then used as input for a second Bayesian network classifier to infer categorical variables values for the risk of infestation. Weed biomass and yield loss data samples are used to learn the probability relationship among the nodes of the first and second Bayesian classifiers in a supervised fashion, respectively. For comparison purposes, two types of Bayesian network structures are considered, namely an expert-based Bayesian classifier and a naive Bayes classifier. The inference system focused on the knowledge interpretation by translating a Bayesian classifier into a set of classification rules. The results obtained for the risk inference in a corn-crop field are presented and discussed. (C) 2009 Elsevier Ltd. All rights reserved.

Double generalized linear model for tissue culture proportion data: a Bayesian perspective

Joint generalized linear models and double generalized linear models (DGLMs) were designed to model outcomes for which the variability can be explained using factors and/or covariates. When such factors operate, the usual normal regression models, which inherently exhibit constant variance, will under-represent variation in the data and hence may lead to erroneous inferences. For count and proportion data, such noise factors can generate a so-called overdispersion effect, and the use of binomial and Poisson models underestimates the variability and, consequently, incorrectly indicate significant effects. In this manuscript, we propose a DGLM from a Bayesian perspective, focusing on the case of proportion data, where the overdispersion can be modeled using a random effect that depends on some noise factors. The posterior joint density function was sampled using Monte Carlo Markov Chain algorithms, allowing inferences over the model parameters. An application to a data set on apple tissue culture is presented, for which it is shown that the Bayesian approach is quite feasible, even when limited prior information is available, thereby generating valuable insight for the researcher about its experimental results.

Characterization of tree-rings of Pinus caribaea var. hondurensis Barr. et Golf. trees by X ray densitometry

This work aimed to determining the anatomical structure of wood, through methodology of histology and X-ray densitometry, of resin-tapped and not resin-tapped Pinus caribaea var. hondurensis trees samples, of three diameter classes. Pine trees, in forest plantation established in 1969, in the Ecological Experimental Station of Itirapina, from the Forestry Institute of Sao Paulo State, were measured and stratified into three classes of trunk diameter. The pine trees were resin-tapped since 2004, with the opening of two simultaneous and opposing panels. Sixty samples of pine wood trees were extracted from the tree trunk through a non-destructive method and in the laboratory. Tree rings were determined in the laboratory and wood apparent density by X-ray densitometry. The test results showed that: (i) false tree rings occur in the early wood and late wood of the tree rings due to climate change; (ii) the X-ray densitometry allowed the demarcation of the tree rings limits; (iii) the wood apparent density average was significantly different between the trees in high class diameter and in the medium-low class; (iv) the wood characteristics from the resin-tapped and non resin-tapped faces did not show significant differences.

Pricing farm-level agricultural insurance: a Bayesian approach

This paper applies Hierarchical Bayesian Models to price farm-level yield insurance contracts. This methodology considers the temporal effect, the spatial dependence and spatio-temporal models. One of the major advantages of this framework is that an estimate of the premium rate is obtained directly from the posterior distribution. These methods were applied to a farm-level data set of soybean in the State of the Parana (Brazil), for the period between 1994 and 2003. The model selection was based on a posterior predictive criterion. This study improves considerably the estimation of the fair premium rates considering the small number of observations.

Bayesian ratemaking procedure of crop insurance contracts with skewed distribution

Over the years, crop insurance programs became the focus of agricultural policy in the USA, Spain, Mexico, and more recently in Brazil. Given the increasing interest in insurance, accurate calculation of the premium rate is of great importance. We address the crop-yield distribution issue and its implications in pricing an insurance contract considering the dynamic structure of the data and incorporating the spatial correlation in the Hierarchical Bayesian framework. Results show that empirical (insurers) rates are higher in low risk areas and lower in high risk areas. Such methodological improvement is primarily important in situations of limited data.

Drying and storage of cauliflower (Brassica oleracea var. botrytis) hydroprimed seeds

Literature has documented beneficial effects of seed priming on speed, synchronization and uniformity of germination. often leading to improved stand establishment. However. doubts still persist about the possible reversal effects, after drying and during storage of primed seeds that could overcome, partial or totally, the improved performance. The objectives of this research were to identify drying and storage procedures that would maintain the physiological performance achieved after seed priming, without negative effects on storability. First. hydroprimed cauliflower Seeds cv. Sharon and cv. Teresopolis Gigante, each represented by three seed lots were submitted to fast drying, slow drying, and treatments of pre-drying incubation (exposure to 35 degrees C, to a polyethylene glycol 6000 solution or a heat shock) followed by fast drying. In the second phase of this study, hydroprimed seed samples were submitted to fast drying (30-35 degrees C and 40-50% R.H.) and stored under laboratory conditions or in a chamber at 20 degrees C and 50% relative humidity for six months. Seed physiological potential was evaluated after 60-day intervals for germination (speed and percentage), Seedling emergence and saturated salt accelerated aging tests. All drying treatments efficiently preserved the favourable priming effects, except for the incubation at 35 degrees C for 96-144 hours. The beneficial priming effects followed by fast drying persisted for four months under controlled conditions (20 degrees C and 50% relative humidity).

Overwintering of Sclerotium rolfsii and S-rolfsii var. delphinii in different latitudes of the United States

Previously known only from the southern United States, hosta petiole rot recently appeared in the northern United States. Sclerotium rolfsii var. delphinii is believed to be the predominant petiole rot pathogen in the northern United States, whereas S. rolfsii is most prevalent in the southern United States. In order to test the hypothesis that different tolerance to climate extremes affects the geographic distribution of these fungi, the survival of S. rolfsii and S. rolfsii var. delphinii in the northern and southeastern United States was investigated. At each of four locations, nylon screen bags containing sclerotia were placed on the surface of bare soil and at 20-cm depth. Sclerotia were recovered six times from November 2005 to July 2006 in North Dakota and Iowa, and from December 2005 to August 2006 in North Carolina and Georgia. Survival was estimated by quantifying percentage of sclerotium survival on carrot agar. Sclerotia of S. rolfsii var. delphinii survived until at least late July in all four states. In contrast, no S. rolfsii sclerotia survived until June in North Dakota or Iowa, whereas 18.5% survived until August in North Carolina and 10.3% survived in Georgia. The results suggest that inability to tolerate low temperature extremes limits the northern range of S. rolfsii.

Chemical Composition and Nutritional Value of Unripe Banana Flour (Musa acuminata, var. Nanico)

Banana flour obtained from unripe banana (Musa acuminata, var. Nanico) under specific drying conditions was evaluated regarding its chemical composition and nutritional value. Results are expressed in dry weight (dw). The unripe banana flour (UBF) presented a high amount of total dietary fiber (DF) (56.24 g/100 g), which consisted of resistant starch (RS) (48.99 g/100 g), fructans (0.05 g/100 g) and DF without RS or fructans (7.2 g/100 g). The contents of available starch (AS) (27.78 g/100 g) and soluble sugars (1.81 g/100 g) were low. The main phytosterols found were campesterol (4.1 mg/100 g), stigmasterol (2.5 mg/100 g) and beta-sitosterol (6.2 mg/100 g). The total polyphenol content was 50.65 mg GAE/100 g. Antioxidant activity, by the FRAP and ORAC methods, was moderated, being 358.67 and 261.00 mu mol of Trolox equivalent/100 g, respectively. The content of Zn, Ca and Fe and mineral dialyzability were low. The procedure used to obtain UBF resulted in the recovery of undamaged starch granules and in a low-energy product (597 kJ/100 g).