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Os modelos filogenéticos para evolução de traços (fenotípicos) permitem a estimativa de correlações evolutivas entre um conjunto de traços observados numa amostra de organismos relacionados. Ao modelar diretamente a evolução dos traços numa árvore filogenética num contexto Bayesiano, a estrutura do modelo nos permite controlar para a história evolutiva compartilhada entre os organismos da amostra e evitar as inferências espúrias originadas pelo parentesco. Nestes modelos, as correlações relevantes são definidas por meio do intervalo de credibilidade das correlações marginais. No entanto, as correlações selecionadas por si só podem não fornecer a melhor informação sobre as relações entre as características em estudo. A sua estrutura de associação, em contraste, fornece uma informação clara sobre associações diretas entre os traços em estudo. A fim de empregar um método baseado em modelo para identificar a estrutura de associação subjacente entre as variáveis, exploramos a utilização de modelos Gaussianos com grafos (GGM) para a seleção das covariâncias. Modelamos a matriz de precisão com a distribuição G-Wishart, uma priori conjugada que resulta em estimativas de precisão esparsa. Avaliamos a nossa abordagem através de simulações de Monte Carlo e comparamos os resultados com o método padrão, onde nenhuma estrutura de associação é explicitamente modelada. Também testamos a nossa abordagem para examinar a estrutura de associação e correlações evolutivas em dois conjuntods de dados: um envolvendo traços fenotípicos dos tentilhões de Darwin e outro envolvendo traços genômicos e fenotípicos de procariotos. A nossa abordagem fornece uma solução sistemática para a eliminação de correlações espúrias e melhor inferência para as matrizes de precisão e correlação, especialmente para as variáveis condicionalmente independentes, que são o alvo da esparsidade nos GGMs. Combinar a inferência das correlações evolutivas e da estrutura de associação permite uma seleção mais precisa das características que potencialmente interagiram ou interagem ao longo do processo evolutivo dos organismos estudados. Phylogenetic trait evolution models allow for the estimation of evolutionary correlations between a set of traits observed in a sample of related organisms. By directly modeling the evolution of the traits on a phylogenetic tree in a Bayesian framework, the model’s structure allows us to control for shared evolutionary history between the organisms in the sample and avoid spurious inference that could have been originated from common ancestors. In these models, relevant correlations are obtained through the high posterior density interval of marginal correlations. However, the selected correlations alone may not provide the best information regarding trait relationships. Their association structure, in contrast, provide straightforward information about direct associations. In order to employ a model based method to identify the underlying association structure between the variables we explore the use of Gaussian graphical models (GGM) for covariance selection. We model the precision matrix with a G-Wishart conjugate prior which results in sparse precision estimates. We evaluate our approach through Monte Carlo simulations and compare the results to the standard method, where no association structure is explicitly modeled. We also test our approach to examine the association structure and evolutionary correlations of Darwin’s finches phenotypic traits and prokaryotic genomic and phenotypic traits. Our approach provides a systematic solution for elimination of spurious correlations and better inference for the precision and correlation matrices, especially for conditionally independent variables, which are the target for sparsity in GGMs. Combining correlation and association structure inference allows for a more precise selection of candidate traits that may interact along the evolutionary process of related organisms.

This study describes the synthesis of new pyromellitic diimide (PMDI) derivatives obtained in good yields from the reaction between pyromellitic dianhydride and aminobenzazoles reactive to proton-transfer in the excited state (ESIPT). In this investigation, a non-ESIPT PMDI was also prepared for comparison. These compounds presented absorption maxima in the ultraviolet region attributed to the allowed

Aspects of reproductive success are fundamental to a better understanding of the evolution and management of wild species and therefore to design successful conservation strategies. In this study, we evaluated the reproductive success and population size of Aechmea winkleri, a bromeliad found in southern Brazilian Atlantic rainforest in only two regions known to date. The southernmost population of A. winkleri was sampled for this study, where three sites were evaluated during two years (2009 and 2010). We found high production of flowers, fruits, and seeds, as well as high pollen viability. However, a significant decrease in the number of fruits with seeds was detected in 2010 at one of the sites. This result is probably related to a decrease in the number of flowering ramets detected at the same site in 2010. Differences at the seed set were found among the three localities investigated. The site with the highest seed set was the same that presented the highest number of genets. We did not detect pollen limitation at the southernmost population in 2009. We found 390 genets in the three sites combined in 2010. Most of the ramets were vegetative, indicating high investment by the individuals in clonal reproduction at the southernmost population. Conservation efforts should focus on preserving habitat and protecting adult plants from environmental accidents, destruction, and harvesting.

We investigated the genetic diversity and structure of Aechmea winkleri Reitz, an endemic bromeliad found in Southern Brazilian Atlantic rainforest. Seven nuclear microsatellite markers were used to analyze 162 samples from four localities sampled throughout the entire geographic distribution of the species. Results indicate relatively high levels of genetic diversity with an average of allelic richness of 3.57, and observed and expected heterozygosity of 0.559 and 0.608, respectively. The within-inbreeding coefficient was low, ranging from −0.011 to 0.094. All localities significantly deviated from Hardy–Weinberg equilibrium with three of them showing heterozygosites deficiency. Most of the genetic variation (96.64%) was found within localities. No reduction in population size (bottleneck) was detected. Low levels of genetic differentiation among localities were found with pairwise FST comparisons varying from 0.021 to 0.075. Bayesian analyses revealed that A. winkleri is composed by two genetic groups. The number of migrants per generation was high (>1), which maintain localities' cohesion and gene flow. Despite genetic erosion was not detected in the present study, our results revealed that the four localities sampled actually represent one population, the only known so far in nature. Management strategies for A. winkleri conservation should be undertaken as it is an endemic species which occurs in a biome that has gone through major deforestation and fragmentation. This would avoid the increase of inbreeding rates and the loss of genetic diversity.

This study was aimed at assessing the diversity of putatively diazotrophic rhizobacteria associated with sunflower (Helianthus annuus L.) cropped in the south of Brazil, and to examine key plant growth promotion (PGP) characteristics of the isolates for the purposes of increasing plant productivity. 299 strains were isolated from the roots and rhizosphere of sunflower cultivated in five different areas using N-free media. 16S rDNA PCR-RFLP and 16S rRNA partial sequencing were used for identification and the Shannon index was used to evaluate bacterial diversity. Production of siderophores and indolic compounds (ICs), as well phosphate solubilization activities of each isolate were also evaluated in vitro. On the basis of multiple PGP activities, eight isolates were selected and tested for their N-fixation ability, and their capacity as potential PGPR on sunflower plants was also assessed. All except three Gram-positive strains (phylum Actinobacteria) belonged to the Gram-negative Proteobacteria subgroups [Gamma (167), Beta (78), and Alpha (50)] and the family Flavobacteriaceae (1)]. Shannon indexes ranged from 0.96 to 2.13 between the five sampling sites. Enterobacter and Burkholderia were the predominant genera isolated from roots and rhizosphere, respectively. Producers of siderophores and ICs were widely found amongst the isolates, but only 19.8% of them solubilized phosphate. About 8% of the isolates exhibited all three PGP traits, and these mostly belonged to the genus Burkholderia. Four isolates were able to stimulate the growth of sunflower plants under gnotobiotic conditions. Enterobacter and Burkholderia were the dominant rhizospheric bacterial genera associated with sunflower plants. Inoculation with isolates belonging to the genera Achromobacter, Chryseobacterium, Azospirillum, and Burkholderia had a stimulatory effect on plant growth.

Bromeliaceae is a morphologically distinctive and ecologically diverse family originating in the New World. Three centers of diversity, 58 genera, and about 3,140 bromeliad species are currently recognized. We compiled all of the studies related to the reproductive biology, genetic diversity, and population structure of the Bromeliaceae, and discuss the evolution and conservation of this family. Bromeliads are preferentially pollinated by vertebrates and show marked variation in breeding systems, from predominant inbreeding to predominant outcrossing, as well as constancy in chromosome number (2n = 2x = 50). Autogamous or mixed mating system bromeliads have a high inbreeding coefficient (F(IS)), while outcrossing species show low F(IS). The degree of differentiation among populations (F(ST))of species ranges from 0.043 to 0.961, which can be influenced by pollen and seed dispersal effects, clonal growth, gene flow rates, and connectivity among populations. The evolutionary history of the Bromeliaceae is poorly known, although some studies have indicated that the family arose in the Guayana Shield roughly 100 Mya. We believe that genetic, cytogenetic, and reproductive data will be essential for diagnosing species status and for assisting conservation programs.