The effect of frequency-specific sound signals on the germination of maize seeds

Objective: the effects of sound treatments on the germination of maize seeds were determined. - Results: white noise and bass sounds (300 Hz) had a positive effect on the germination rate. Only 3 h treatment produced an increase of about 8%, and 5 h increased germination in about 10%. Fast-green staining shows that at least part of the effects of sound are due to a physical alteration in the integrity of the pericarp, increasing the porosity of the pericarp and facilitating oxygen availability and water and oxygen uptake. Accordingly, by removing the pericarp from the seeds the positive effect of the sound on the germination disappeared

Integrative meta-analysis of protein interaction data identified multiple GID/MRCTLH protein complexes in plants

GID/MRCTLH is a protein complex involved in the regulation of several cellular processes through the polyubiquitination and proteosome degradation. It has been described in yeast and mammals. Genes coding for homologous proteins are also present in plant genomes but have been little studied. BLAST analyses revealed that genes coding for members of the GID/MRCTLH complex are found in multiple copies in plants, compared to mammals and yeast. The potential structure of the Arabidopsis GID/MRCTLH complex was estimated based on the Arabidopsis protein interaction database Interactome 2.0. According to these data, Arabidopsis may contain two GID/MRCTLH complexes instead of the one described in yeast and mammals. The structure of the two Arabidopsis complexes seem to be similar to the yeast GID complex, and seem to interact with several other proteins out of the complex. These data suggest that, similarly to yeast and mammals, the plant GID/MRCTLH complexes are involved in the regulation of several cellular processes through proteosome protein degradation

Use of ultrasonication to increase germination rates of Arabidopsis seeds

Background: Arabidopsis thaliana is widely used as model organism in plant biology. Although not of agronomic significance, it offers important advantages for basic research in genetics and molecular biology including the availability of a large number of mutants and genetically modified lines. However, Arabidopsis seed longevity is limited and seeds stored for more than 10 years usually show a very low capacity for germination. - Results: the influence of ultrasonic stimulation was investigated on the germination of A. thaliana L. seeds. All experiments have been performed using a frequency of 45 kHz at constant temperature (24 °C). No germination rate differences were observed when using freshly collected seeds. However, using artificially deteriorated seeds, our results show that short ultrasonic stimulation (<1 min) significantly increased germination. Ultrasonic stimulation application of 30 s is the optimal treatment. A significant increase in the germination rate was also verified in naturally aged seeds after ultrasonic stimulation. Scanning electron microscopy observations showed an increase in the presence of pores in the seed coat after sonication that may be the cause, at least in part, of the increase in germination. The ultrasound treated seeds developed normally to mature fertile plants. - Conclusions: ultrasound technology can be used to enhance the germination process of old Arabidopsis seeds without negatively affecting seedling development. This effect seems to be, at least in part, due to the opening of pores in the seed coat. The use of ultrasonic stimulation in Arabidopsis seeds may contribute to the recovering of long time stored lines

Genome-wide identification of Reverse Transcriptase domains of recently inserted endogenous plant pararetrovirus (Caulimoviridae)

Altres ajuts: CERCA Programme/Generalitat de CatalunyaEndogenous viral elements (EVEs) are viral sequences that have been integrated into the nuclear chromosomes. Endogenous pararetrovirus (EPRV) are a class of EVEs derived from DNA viruses of the family Caulimoviridae. Previous works based on a limited number of genome assemblies demonstrated that EPRVs are abundant in plants and are present in several species. The availability of genome sequences has been immensely increased in the recent years and we took advantage of these resources to have a more extensive view of the presence of EPRVs in plant genomes. We analyzed 278 genome assemblies corresponding to 267 species (254 from Viridiplantae) using tBLASTn against a collection of conserved domains of the Reverse Transcriptases (RT) of Caulimoviridae. We concentrated our search on complete and well-conserved RT domains with an uninterrupted ORF comprising the genetic information for at least 300 amino acids. We obtained 11.527 sequences from the genomes of 202 species spanning the whole Tracheophyta clade. These elements were grouped in 57 clusters and classified in 13 genera, including a newly proposed genus we called Wendovirus. Wendoviruses are characterized by the presence of four open reading frames and two of them encode for aspartic proteinases. Comparing plant genomes, we observed important differences between the plant families and genera in the number and type of EPRVs found. In general, florendoviruses are the most abundant and widely distributed EPRVs. The presence of multiple identical RT domain sequences in some of the genomes suggests their recent amplification

Computational and experimental analysis identifies Arabidopsis genes specifically expressed during early seed development

BACKGROUND: Plant seeds are complex organs in which maternal tissues, embryo and endosperm, follow distinct but coordinated developmental programs. Some morphogenetic and metabolic processes are exclusively associated with seed development. The goal of this study was to explore the feasibility of incorporating the available online bioinformatics databases to discover Arabidopsis genes specifically expressed in certain organs, in our case immature seeds. RESULTS: A total of 11,032 EST sequences obtained from isolated immature seeds were used as the initial dataset (178 of them newly described here). A pilot study was performed using EST virtual subtraction followed by microarray data analysis, using the Genevestigator tool. These techniques led to the identification of 49 immature seed-specific genes. The findings were validated by RT-PCR analysis and in situ hybridization. CONCLUSION: We conclude that the combined in silico data analysis is an effective data mining strategy for the identification of tissue-specific gene expression

Additional ORFs in plant LTR-retrotransposons

Altres ajuts: CERCA Programme/Generalitat de CatalunyaLTR-retrotransposons share a common genomic organization in which the 5' long terminal repeat (LTR) is followed by the gag and pol genes and terminates with the 3' LTR. Although GAG-POL-encoded proteins are considered sufficient to accomplish the LTR-retrotransposon transposition, a number of elements carrying additional open reading frames (aORF) have been described. In some cases, the presence of an aORF can be explained by a phenomenon similar to retrovirus gene transduction, but in these cases the aORFs are present in only one or a few copies. On the contrary, many elements contain aORFs, or derivatives, in all or most of their copies. These aORFs are more frequently located between pol and 3' LTR, and they could be in sense or antisense orientation with respect to gag-pol. Sense aORFs include those encoding for ENV-like proteins, so called because they have some structural and functional similarities with retroviral ENV proteins. Antisense aORFs between pol and 3' LTR are also relatively frequent and, for example, are present in some characterized LTR-retrotransposon families like maize Grande, rice RIRE2, or Silene Retand, although their possible roles have been not yet determined. Here, we discuss the current knowledge about these sense and antisense aORFs in plant LTR-retrotransposons, suggesting their possible origins, evolutionary relevance, and function

Experimental and theoretical study of the pressure profile in the melt channel of a Helibar®-Extruder.

In diesem Projekt wurde ein Programm getestet, welches den Druckaufbau in einem HELIBAR® Extruder modellieren kann. Das bereitgestellte Programm wurde am Institut für Kunststofftechnik in Stuttgart (IKT) entwickelt. Zuerst wird hierzu das Zugrundeliegende mathematische Modell beschrieben. Dieses wird anschließend mit Hilfe der Finiten Differenzen Methode gelöst. Zuletzt erfolgt eine Implementierung des Modells in MATLAB, wobei die theoretisch erhaltenen Ergebnisse mit experimentellen verglichen werden. Das Programm analysiert zweidimensional die Schmelzeförderung im Kanal und kann so den Druck am Ende der Schnecke mit guten Ergebnis vorhersagen.Outgoin

Moving towards the semantic web: enabling new technologies through the semantic annotation of social contents.

La Web Social ha causat un creixement exponencial dels continguts disponibles deixant enormes quantitats de recursos textuals electrònics que sovint aclaparen els usuaris. Aquest volum d’informació és d’interès per a la comunitat de mineria de dades. Els algorismes de mineria de dades exploten característiques de les entitats per tal de categoritzar-les, agrupar-les o classificar-les segons la seva semblança. Les dades per si mateixes no aporten cap mena de significat: han de ser interpretades per esdevenir informació. Els mètodes tradicionals de mineria de dades no tenen com a objectiu “entendre” el contingut d’un recurs, sinó que extreuen valors numèrics els quals esdevenen models en aplicar-hi càlculs estadístics, que només cobren sentit sota l’anàlisi manual d’un expert. Els darrers anys, motivat per la Web Semàntica, molts investigadors han proposat mètodes semàntics de classificació de dades capaços d’explotar recursos textuals a nivell conceptual. Malgrat això, normalment aquests mètodes depenen de recursos anotats prèviament per poder interpretar semànticament el contingut d’un document. L’ús d’aquests mètodes està estretament relacionat amb l’associació de dades i el seu significat. Aquest treball es centra en el desenvolupament d’una metodologia genèrica capaç de detectar els trets més rellevants d’un recurs textual descobrint la seva associació semàntica, es a dir, enllaçant-los amb conceptes modelats a una ontologia, i detectant els principals temes de discussió. Els mètodes proposats són no supervisats per evitar el coll d’ampolla generat per l’anotació manual, independents del domini (aplicables a qualsevol àrea de coneixement) i flexibles (capaços d’analitzar recursos heterogenis: documents textuals o documents semi-estructurats com els articles de la Viquipèdia o les publicacions de Twitter). El treball ha estat avaluat en els àmbits turístic i mèdic. Per tant, aquesta dissertació és un primer pas cap a l'anotació semàntica automàtica de documents necessària per possibilitar el camí cap a la visió de la Web Semàntica.La Web Social ha provocado un crecimiento exponencial de los contenidos disponibles, dejando enormes cantidades de recursos electrónicos que a menudo abruman a los usuarios. Tal volumen de información es de interés para la comunidad de minería de datos. Los algoritmos de minería de datos explotan características de las entidades para categorizarlas, agruparlas o clasificarlas según su semejanza. Los datos por sí mismos no aportan ningún significado: deben ser interpretados para convertirse en información. Los métodos tradicionales no tienen como objetivo "entender" el contenido de un recurso, sino que extraen valores numéricos que se convierten en modelos tras aplicar cálculos estadísticos, los cuales cobran sentido bajo el análisis manual de un experto. Actualmente, motivados por la Web Semántica, muchos investigadores han propuesto métodos semánticos de clasificación de datos capaces de explotar recursos textuales a nivel conceptual. Sin embargo, generalmente estos métodos dependen de recursos anotados previamente para poder interpretar semánticamente el contenido de un documento. El uso de estos métodos está estrechamente relacionado con la asociación de datos y su significado. Este trabajo se centra en el desarrollo de una metodología genérica capaz de detectar los rasgos más relevantes de un recurso textual descubriendo su asociación semántica, es decir, enlazándolos con conceptos modelados en una ontología, y detectando los principales temas de discusión. Los métodos propuestos son no supervisados para evitar el cuello de botella generado por la anotación manual, independientes del dominio (aplicables a cualquier área de conocimiento) y flexibles (capaces de analizar recursos heterogéneos: documentos textuales o documentos semi-estructurados, como artículos de la Wikipedia o publicaciones de Twitter). El trabajo ha sido evaluado en los ámbitos turístico y médico. Esta disertación es un primer paso hacia la anotación semántica automática de documentos necesaria para posibilitar el camino hacia la visión de la Web Semántica.Social Web technologies have caused an exponential growth of the documents available through the Web, making enormous amounts of textual electronic resources available. Users may be overwhelmed by such amount of contents and, therefore, the automatic analysis and exploitation of all this information is of interest to the data mining community. Data mining algorithms exploit features of the entities in order to characterise, group or classify them according to their resemblance. Data by itself does not carry any meaning; it needs to be interpreted to convey information. Classical data analysis methods did not aim to “understand” the content and the data were treated as meaningless numbers and statistics were calculated on them to build models that were interpreted manually by human domain experts. Nowadays, motivated by the Semantic Web, many researchers have proposed semantic-grounded data classification and clustering methods that are able to exploit textual data at a conceptual level. However, they usually rely on pre-annotated inputs to be able to semantically interpret textual data such as the content of Web pages. The usability of all these methods is related to the linkage between data and its meaning. This work focuses on the development of a general methodology able to detect the most relevant features of a particular textual resource finding out their semantics (associating them to concepts modelled in ontologies) and detecting its main topics. The proposed methods are unsupervised (avoiding the manual annotation bottleneck), domain-independent (applicable to any area of knowledge) and flexible (being able to deal with heterogeneous resources: raw text documents, semi-structured user-generated documents such Wikipedia articles or short and noisy tweets). The methods have been evaluated in different fields (Tourism, Oncology). This work is a first step towards the automatic semantic annotation of documents, needed to pave the way towards the Semantic Web vision

Transcriptomic and proteomic profiling of maize embryos exposed to camptothecin

<p>Abstract</p> <p>Background</p> <p>Camptothecin is a plant alkaloid that specifically binds topoisomerase I, inhibiting its activity and inducing double stranded breaks in DNA, activating the cell responses to DNA damage and, in response to severe treatments, triggering cell death.</p> <p>Results</p> <p>Comparative transcriptomic and proteomic analyses of maize embryos that had been exposed to camptothecin were conducted. Under the conditions used in this study, camptothecin did not induce extensive degradation in the genomic DNA but induced the transcription of genes involved in DNA repair and repressed genes involved in cell division. Camptothecin also affected the accumulation of several proteins involved in the stress response and induced the activity of certain calcium-dependent nucleases. We also detected changes in the expression and accumulation of different genes and proteins involved in post-translational regulatory processes.</p> <p>Conclusions</p> <p>This study identified several genes and proteins that participate in DNA damage responses in plants. Some of them may be involved in general responses to stress, but others are candidate genes for specific involvement in DNA repair. Our results open a number of new avenues for researching and improving plant resistance to DNA injury.</p

Development of retrotransposon-based markers IRAP and REMAP for cassava (Manihot esculenta)

Retrotransposons are abundant in the genomes of plants. In the present study, inter-retrotransposon amplified polymorphism (IRAP) and retrotransposon-microsatellite amplified polymorphism (REMAP) markers were developed for the cassava genome (Manihot esculenta Crantz). Four cassava cultivars (Fécula Branca, IPR-União, Olho Junto, and Tamboara, two samples per cultivar) were used to obtain IRAP and REMAP fingerprints. Twelve designed primers were amplified alone and in combinations. The 42 IRAP/REMAP primer combinations amplified 431 DNA segments (bands; markers) of which 36 (8.36%) were polymorphic. The largest number of informative markers (16) was detected using the primers AYF2 and AYF2xAYF4. The number of bands for each primer varied from 3 to 16, with an average of 10.26 amplified segments per primer. The size of the amplified products ranged between 100 and 7000 bp. The AYF2 primer generated the highest number of amplified segments and showed the highest number of polymorphic bands (68.75%). Two samples of each cassava cultivar were used to illustrate the usefulness and the polymorphism of IRAP/REMAP markers. IRAP and REMAP markers produced a high number of reproducible bands, and might be informative and reliable for investigation of genetic diversity and relationships among cassava cultivars