Desenvolvimento morfofisiológico de sementes de ipê-amarelo (Tabeluia serratifolia Vahl Nich.)

Tabebuia serratifolia é utilizada no reflorestamento de áreas degradadas. Devido à sua exploração indevida, encontra-se em perigo de extinção, apesar de protegida por lei para preservação permanente. Foram investigadas as alterações morfofisiológicas de sementes de ipê-amarelo ao longo do desenvolvimento, para fins de auxiliar a conservação dessa espécie. Os frutos foram coletados a partir da antese, em sete estádios de desenvolvimento, em árvores localizadas na região de Lavras, MG, Brasil. Em cada coleta, as sementes foram submetidas às análises radiográficas e microscópicas, avaliando-se as colorações e tamanho, o grau de umidade e matéria seca tanto dos frutos como das sementes, a germinação in vitro e ex vitro, bem como os teores de açúcares, polifenóis e proteínas resistentes ao calor. Durante o desenvolvimento os frutos que inicialmente eram verdes passaram para amarronzados e o comprimento de 7 para 18 cm, apresentando fendas que iniciam a dispersão de suas sementes. As sementes tiveram sua cor variando de verde-folha a amarronzado e comprimento de 1 a 3 cm. As alterações iniciais indicativas da maturidade fisiológica de sementes de ipê-amarelo ocorreram a partir dos 39 dias após a antese, quando ocorreram variações na coloração, no tamanho de frutos e sementes e na visualização das estruturas internas, além de aumentos nos teores de água, matéria seca e porcentagem de germinação de sementes e embriões e ainda, redução dos açúcares redutores e das proteínas resistentes ao calor. A maturidade fisiológica das sementes de Tabebuia serratifolia é alcançada aos 53 dias após a antese, coincidindo com o acúmulo máximo de matéria seca, germinação (e índice de velocidade de germinação), além de decréscimo no teor de polifenóis e maior intensidade de bandas inidicadoras de proteínas resistentes ao calor e o início da abertura dos frutos.Tabebuia serratifolia is used for the reforestation of degraded areas. Despite protection by law for permanent preservation, the species is in danger of extinction due to improper exploitation. With the objective to aid preservation and long term storage of the species we evaluated morphophysiological alterations of T. serratifolia seeds during the maturation process in order to identify markers that can be used for harvesting and storage. Fruits were collected at anthesis and seven developmental stages from trees growing in Lavras, state of Minas Gerais, Brazil. At each harvest, fruits and seeds were evaluated for color and size, moisture content, dry matter, internal morphology (by X-ray analysis), germination parameters (in vitro and ex vitro), as well as sugar and polyphenol content and heat resistant proteins. During the maturation process the initially green fruits changed to a brownish color and grew from a length of 7 to 18 cm; cracks appeared at the beginning of seed dispersal. The seed color varied from leaf-green to brownish and the length from 1 to 3 cm. The first indicatior of physiological maturity should be observed at 39 days post-anthesis, when variations the color and size of both fruits and seeds were observed. Increase in the moisture content, dry matter and germination, percentage of seeds and embryos in vitro, as well as a reduction in sugar content and LEA proteins were also observed. The physiological maturity of T. serratifolia seeds was reached 53 days after anthesis, coinciding with a maximum of dry matter accumulation and germination (and index of germination speed ex vitro), decrease in phenol levels, higher intensity of heat-resistant protein bands and the beginning of fruit opening

Phase transition in a 2-dimensional Heisenberg model

We investigate the two-dimensional classical Heisenberg model with a nonlinear nearest-neighbor interaction V(s,s')=2K[(1+s.s')/2 ]^p. The analogous nonlinear interaction for the XY model was introduced by Domany, Schick, and Swendsen, who find that for large p the Kosterlitz-Thouless transition is preempted by a first-order transition. Here we show that, whereas the standard (p=1) Heisenberg model has no phase transition, for large enough p a first-order transition appears. Both phases have only short range order, but with a correlation length that jumps at the transition.Comment: 6 pages, 5 encapsulated postscript figures; to appear in Physical Review Letter

Estimation of metabolite networks with regard to a specific covariable: applications to plant and human data

In systems biology, where a main goal is acquiring knowledge of biological systems, one of the challenges is inferring biochemical interactions from different molecular entities such as metabolites. In this area, the metabolome possesses a unique place for reflecting “true exposure” by being sensitive to variation coming from genetics, time, and environmental stimuli. While influenced by many different reactions, often the research interest needs to be focused on variation coming from a certain source, i.e. a certain covariable Xm . Objective Here, we use network analysis methods to recover a set of metabolite relationships, by finding metabolites sharing a similar relation to Xm . Metabolite values are based on information coming from individuals’ Xm status which might interact with other covariables. Methods Alternative to using the original metabolite values, the total information is decomposed by utilizing a linear regression model and the part relevant to Xm is further used. For two datasets, two different network estimation methods are considered. The first is weighted gene co-expression network analysis based on correlation coefficients. The second method is graphical LASSO based on partial correlations. Results We observed that when using the parts related to the specific covariable of interest, resulting estimated networks display higher interconnectedness. Additionally, several groups of biologically associated metabolites (very large density lipoproteins, lipoproteins, etc.) were identified in the human data example. Conclusions This work demonstrates how information on the study design can be incorporated to estimate metabolite networks. As a result, sets of interconnected metabolites can be clustered together with respect to their relation to a covariable of interest

The Re-Establishment of Desiccation Tolerance in Germinated Arabidopsis thaliana Seeds and Its Associated Transcriptome

The combination of robust physiological models with “omics” studies holds promise for the discovery of genes and pathways linked to how organisms deal with drying. Here we used a transcriptomics approach in combination with an in vivo physiological model of re-establishment of desiccation tolerance (DT) in Arabidopsis thaliana seeds. We show that the incubation of desiccation sensitive (DS) germinated Arabidopsis seeds in a polyethylene glycol (PEG) solution re-induces the mechanisms necessary for expression of DT. Based on a SNP-tile array gene expression profile, our data indicates that the re-establishment of DT, in this system, is related to a programmed reversion from a metabolic active to a quiescent state similar to prior to germination. Our findings show that transcripts of germinated seeds after the PEG-treatment are dominated by those encoding LEA, seed storage and dormancy related proteins. On the other hand, a massive repression of genes belonging to many other classes such as photosynthesis, cell wall modification and energy metabolism occurs in parallel. Furthermore, comparison with a similar system for Medicago truncatula reveals a significant overlap between the two transcriptomes. Such overlap may highlight core mechanisms and key regulators of the trait DT. Taking into account the availability of the many genetic and molecular resources for Arabidopsis, the described system may prove useful for unraveling DT in higher plants