950 resultados para Function of locally varying complexity
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AbstractIn addition to genetic changes affecting the function of gene products, changes in gene expression have been suggested to underlie many or even most of the phenotypic differences among mammals. However, detailed gene expression comparisons were, until recently, restricted to closely related species, owing to technological limitations. Thus, we took advantage of the latest technologies (RNA-Seq) to generate extensive qualitative and quantitative transcriptome data for a unique collection of somatic and germline tissues from representatives of all major mammalian lineages (placental mammals, marsupials and monotremes) and birds, the evolutionary outgroup.In the first major project of my thesis, we performed global comparative analyses of gene expression levels based on these data. Our analyses provided fundamental insights into the dynamics of transcriptome change during mammalian evolution (e.g., the rate of expression change across species, tissues and chromosomes) and allowed the exploration of the functional relevance and phenotypic implications of transcription changes at a genome-wide scale (e.g., we identified numerous potentially selectively driven expression switches).In a second project of my thesis, which was also based on the unique transcriptome data generated in the context of the first project we focused on the evolution of alternative splicing in mammals. Alternative splicing contributes to transcriptome complexity by generating several transcript isoforms from a single gene, which can, thus, perform various functions. To complete the global comparative analysis of gene expression changes, we explored patterns of alternative splicing evolution. This work uncovered several general and unexpected patterns of alternative splicing evolution (e.g., we found that alternative splicing evolves extremely rapidly) as well as a large number of conserved alternative isoforms that may be crucial for the functioning of mammalian organs.Finally, the third and final project of my PhD consisted in analyzing in detail the unique functional and evolutionary properties of the testis by exploring the extent of its transcriptome complexity. This organ was previously shown to evolve rapidly both at the phenotypic and molecular level, apparently because of the specific pressures that act on this organ and are associated with its reproductive function. Moreover, my analyses of the amniote tissue transcriptome data described above, revealed strikingly widespread transcriptional activity of both functional and nonfunctional genomic elements in the testis compared to the other organs. To elucidate the cellular source and mechanisms underlying this promiscuous transcription in the testis, we generated deep coverage RNA-Seq data for all major testis cell types as well as epigenetic data (DNA and histone methylation) using the mouse as model system. The integration of these complete dataset revealed that meiotic and especially post-meiotic germ cells are the major contributors to the widespread functional and nonfunctional transcriptome complexity of the testis, and that this "promiscuous" spermatogenic transcription is resulting, at least partially, from an overall transcriptionally permissive chromatin state. We hypothesize that this particular open state of the chromatin results from the extensive chromatin remodeling that occurs during spermatogenesis which ultimately leads to the replacement of histones by protamines in the mature spermatozoa. Our results have important functional and evolutionary implications (e.g., regarding new gene birth and testicular gene expression evolution).Generally, these three large-scale projects of my thesis provide complete and massive datasets that constitute valuables resources for further functional and evolutionary analyses of mammalian genomes.
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We study the effect of varying the boundary condition on: the spectral function of a finite one-dimensional Hubbard chain, which we compute using direct (Lanczos) diagonalization of the Hamiltonian. By direct comparison with the two-body response functions and with the exact solution of the Bethe ansatz equations, we can identify both spinon and holon features in the spectra. At half-filling the spectra have the well-known structure of a low-energy holon band and its shadow-which spans the whole Brillouin zone-and a spinon band present for momenta less than the Fermi momentum. Features related to the twisted boundary condition are cusps in the spinon band. We show that the spectral building principle, adapted to account for both the finite system size and the twisted boundary condition, describes the spectra well in terms of single spinon and holon excitations. We argue that these finite-size effects are a signature of spin-charge separation and that their study should help establish the existence and nature of spin-charge separation in finite-size systems.
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In the late seventies, Megiddo proposed a way to use an algorithm for the problem of minimizing a linear function a(0) + a(1)x(1) + ... + a(n)x(n) subject to certain constraints to solve the problem of minimizing a rational function of the form (a(0) + a(1)x(1) + ... + a(n)x(n))/(b(0) + b(1)x(1) + ... + b(n)x(n)) subject to the same set of constraints, assuming that the denominator is always positive. Using a rather strong assumption, Hashizume et al. extended Megiddo`s result to include approximation algorithms. Their assumption essentially asks for the existence of good approximation algorithms for optimization problems with possibly negative coefficients in the (linear) objective function, which is rather unusual for most combinatorial problems. In this paper, we present an alternative extension of Megiddo`s result for approximations that avoids this issue and applies to a large class of optimization problems. Specifically, we show that, if there is an alpha-approximation for the problem of minimizing a nonnegative linear function subject to constraints satisfying a certain increasing property then there is an alpha-approximation (1 1/alpha-approximation) for the problem of minimizing (maximizing) a nonnegative rational function subject to the same constraints. Our framework applies to covering problems and network design problems, among others.
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Hydrological loss is a vital component in many hydrological models, which are usedin forecasting floods and evaluating water resources for both surface and subsurface flows. Due to the complex and random nature of the rainfall runoff process, hydrological losses are not yet fully understood. Consequently, practitioners often use representative values of the losses for design applications such as rainfall-runoff modelling which has led to inaccurate quantification of water quantities in the resulting applications. The existing hydrological loss models must be revisited and modellers should be encouraged to utilise other available data sets. This study is based on three unregulated catchments situated in Mt. Lofty Ranges of South Australia (SA). The paper focuses on conceptual models for: initial loss (IL), continuing loss (CL) and proportional loss (PL) with rainfall characteristics (total rainfall (TR) and storm duration (D)), and antecedent wetness (AW) conditions. The paper introduces two methods that can be implemented to estimate IL as a function of TR, D and AW. The IL distribution patterns and parameters for the study catchments are determined using multivariate analysis and descriptive statistics. The possibility of generalising the methods and the limitations of this are also discussed. This study will yield improvements to existing loss models and will encourage practitioners to utilise multiple data sets to estimate losses, instead of using hypothetical or representative values to generalise real situations.
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Maltose and glucose fermentations by industrial brewing and wine yeasts strains were strongly affected by the structural complexity of the nitrogen source. In this study, four Saccharomyces cerevisiae strains, two brewing and two wine yeasts, were grown in a medium containing maltose or glucose supplemented with a nitrogen source varying from a single ammonium salt (ammonium sulfate) to free amino acids (casamino acids) and peptides (peptone). Diauxie was observed at low sugar concentration for brewing and wine strains, independent of nitrogen supplementation, and the type of sugar. At high sugar concentrations altered patterns of sugar fermentation were observed, and biomass accumulation and ethanol production depended on the nature of the nitrogen source and were different for brewing and wine strains. In maltose, high biomass production was observed under peptone and casamino acids for the brewing and wine strains, however efficient maltose utilization and high ethanol production was only observed in the presence of casamino acids for one brewing and one wine strain studied. Conversely, peptone and casamino acids induced higher biomass and ethanol production for the two other brewing and wine strains studied. With glucose, in general, peptone induced higher fermentation performance for all strains, and one brewing and wine strain produced the same amount of ethanol with peptone and casamino acids supplementation. Ammonium salts always induced poor yeast performance. The results described in this paper suggest that the complex nitrogen composition of the cultivation medium may create conditions resembling those responsible for inducing sluggish/stuck fermentation, and indicate that the kind and concentration of sugar, the complexity of nitrogen source and the yeast genetic background influence optimal industrial yeast fermentation performance.
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We monitored the haul-out behavior of 68 radio-tagged harbor seals (Phoca vitulina) during the molt season at two Alaskan haul-out sites (Grand Island, August-September 1994; Nanvak Bay, August-September 2000). For each site, we created a statistical model of the proportion of seals hauled out as a function of date, time of day, tide, and weather covariates. Using these models, we identified the conditions that would result in the greatest proportion of seals hauled out. Although those “ideal conditions” differed between sites, the proportion of seals predicted to be hauled out under those conditions was very similar (81.3% for Grand Island and 85.7% for Nanvak Bay). The similar estimates for both sites suggest that haul-out proportions under locally ideal conditions may be constant between years and geographic regions, at least during the molt season.
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Complexity in time series is an intriguing feature of living dynamical systems, with potential use for identification of system state. Although various methods have been proposed for measuring physiologic complexity, uncorrelated time series are often assigned high values of complexity, errouneously classifying them as a complex physiological signals. Here, we propose and discuss a method for complex system analysis based on generalized statistical formalism and surrogate time series. Sample entropy (SampEn) was rewritten inspired in Tsallis generalized entropy, as function of q parameter (qSampEn). qSDiff curves were calculated, which consist of differences between original and surrogate series qSampEn. We evaluated qSDiff for 125 real heart rate variability (HRV) dynamics, divided into groups of 70 healthy, 44 congestive heart failure (CHF), and 11 atrial fibrillation (AF) subjects, and for simulated series of stochastic and chaotic process. The evaluations showed that, for nonperiodic signals, qSDiff curves have a maximum point (qSDiff(max)) for q not equal 1. Values of q where the maximum point occurs and where qSDiff is zero were also evaluated. Only qSDiff(max) values were capable of distinguish HRV groups (p-values 5.10 x 10(-3); 1.11 x 10(-7), and 5.50 x 10(-7) for healthy vs. CHF, healthy vs. AF, and CHF vs. AF, respectively), consistently with the concept of physiologic complexity, and suggests a potential use for chaotic system analysis. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4758815]
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The vast majority of known proteins have not yet been experimentally characterized and little is known about their function. The design and implementation of computational tools can provide insight into the function of proteins based on their sequence, their structure, their evolutionary history and their association with other proteins. Knowledge of the three-dimensional (3D) structure of a protein can lead to a deep understanding of its mode of action and interaction, but currently the structures of <1% of sequences have been experimentally solved. For this reason, it became urgent to develop new methods that are able to computationally extract relevant information from protein sequence and structure. The starting point of my work has been the study of the properties of contacts between protein residues, since they constrain protein folding and characterize different protein structures. Prediction of residue contacts in proteins is an interesting problem whose solution may be useful in protein folding recognition and de novo design. The prediction of these contacts requires the study of the protein inter-residue distances related to the specific type of amino acid pair that are encoded in the so-called contact map. An interesting new way of analyzing those structures came out when network studies were introduced, with pivotal papers demonstrating that protein contact networks also exhibit small-world behavior. In order to highlight constraints for the prediction of protein contact maps and for applications in the field of protein structure prediction and/or reconstruction from experimentally determined contact maps, I studied to which extent the characteristic path length and clustering coefficient of the protein contacts network are values that reveal characteristic features of protein contact maps. Provided that residue contacts are known for a protein sequence, the major features of its 3D structure could be deduced by combining this knowledge with correctly predicted motifs of secondary structure. In the second part of my work I focused on a particular protein structural motif, the coiled-coil, known to mediate a variety of fundamental biological interactions. Coiled-coils are found in a variety of structural forms and in a wide range of proteins including, for example, small units such as leucine zippers that drive the dimerization of many transcription factors or more complex structures such as the family of viral proteins responsible for virus-host membrane fusion. The coiled-coil structural motif is estimated to account for 5-10% of the protein sequences in the various genomes. Given their biological importance, in my work I introduced a Hidden Markov Model (HMM) that exploits the evolutionary information derived from multiple sequence alignments, to predict coiled-coil regions and to discriminate coiled-coil sequences. The results indicate that the new HMM outperforms all the existing programs and can be adopted for the coiled-coil prediction and for large-scale genome annotation. Genome annotation is a key issue in modern computational biology, being the starting point towards the understanding of the complex processes involved in biological networks. The rapid growth in the number of protein sequences and structures available poses new fundamental problems that still deserve an interpretation. Nevertheless, these data are at the basis of the design of new strategies for tackling problems such as the prediction of protein structure and function. Experimental determination of the functions of all these proteins would be a hugely time-consuming and costly task and, in most instances, has not been carried out. As an example, currently, approximately only 20% of annotated proteins in the Homo sapiens genome have been experimentally characterized. A commonly adopted procedure for annotating protein sequences relies on the "inheritance through homology" based on the notion that similar sequences share similar functions and structures. This procedure consists in the assignment of sequences to a specific group of functionally related sequences which had been grouped through clustering techniques. The clustering procedure is based on suitable similarity rules, since predicting protein structure and function from sequence largely depends on the value of sequence identity. However, additional levels of complexity are due to multi-domain proteins, to proteins that share common domains but that do not necessarily share the same function, to the finding that different combinations of shared domains can lead to different biological roles. In the last part of this study I developed and validate a system that contributes to sequence annotation by taking advantage of a validated transfer through inheritance procedure of the molecular functions and of the structural templates. After a cross-genome comparison with the BLAST program, clusters were built on the basis of two stringent constraints on sequence identity and coverage of the alignment. The adopted measure explicity answers to the problem of multi-domain proteins annotation and allows a fine grain division of the whole set of proteomes used, that ensures cluster homogeneity in terms of sequence length. A high level of coverage of structure templates on the length of protein sequences within clusters ensures that multi-domain proteins when present can be templates for sequences of similar length. This annotation procedure includes the possibility of reliably transferring statistically validated functions and structures to sequences considering information available in the present data bases of molecular functions and structures.
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In environmental epidemiology, exposure X and health outcome Y vary in space and time. We present a method to diagnose the possible influence of unmeasured confounders U on the estimated effect of X on Y and to propose several approaches to robust estimation. The idea is to use space and time as proxy measures for the unmeasured factors U. We start with the time series case where X and Y are continuous variables at equally-spaced times and assume a linear model. We define matching estimator b(u)s that correspond to pairs of observations with specific lag u. Controlling for a smooth function of time, St, using a kernel estimator is roughly equivalent to estimating the association with a linear combination of the b(u)s with weights that involve two components: the assumptions about the smoothness of St and the normalized variogram of the X process. When an unmeasured confounder U exists, but the model otherwise correctly controls for measured confounders, the excess variation in b(u)s is evidence of confounding by U. We use the plot of b(u)s versus lag u, lagged-estimator-plot (LEP), to diagnose the influence of U on the effect of X on Y. We use appropriate linear combination of b(u)s or extrapolate to b(0) to obtain novel estimators that are more robust to the influence of smooth U. The methods are extended to time series log-linear models and to spatial analyses. The LEP plot gives us a direct view of the magnitude of the estimators for each lag u and provides evidence when models did not adequately describe the data.
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By means of fixed-links modeling, the present study identified different processes of visual short-term memory (VSTM) functioning and investigated how these processes are related to intelligence. We conducted an experiment where the participants were presented with a color change detection task. Task complexity was manipulated through varying the number of presented stimuli (set size). We collected hit rate and reaction time (RT) as indicators for the amount of information retained in VSTM and speed of VSTM scanning, respectively. Due to the impurity of these measures, however, the variability in hit rate and RT was assumed to consist not only of genuine variance due to individual differences in VSTM retention and VSTM scanning but also of other, non-experimental portions of variance. Therefore, we identified two qualitatively different types of components for both hit rate and RT: (1) non-experimental components representing processes that remained constant irrespective of set size and (2) experimental components reflecting processes that increased as a function of set size. For RT, intelligence was negatively associated with the non-experimental components, but was unrelated to the experimental components assumed to represent variability in VSTM scanning speed. This finding indicates that individual differences in basic processing speed, rather than in speed of VSTM scanning, differentiates between high- and low-intelligent individuals. For hit rate, the experimental component constituting individual differences in VSTM retention was positively related to intelligence. The non-experimental components of hit rate, representing variability in basal processes, however, were not associated with intelligence. By decomposing VSTM functioning into non-experimental and experimental components, significant associations with intelligence were revealed that otherwise might have been obscured.
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Several authors have analysed the changes of the probability density function of the solar radiation with different time resolutions. Some others have approached to study the significance of these changes when produced energy calculations are attempted. We have undertaken different transformations to four Spanish databases in order to clarify the interrelationship between radiation models and produced energy estimations. Our contribution is straightforward: the complexity of a solar radiation model needed for yearly energy calculations, is very low. Twelve values of monthly mean of solar radiation are enough to estimate energy with errors below 3%. Time resolutions better than hourly samples do not improve significantly the result of energy estimations.
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Genetic analysis of plant–pathogen interactions has demonstrated that resistance to infection is often determined by the interaction of dominant plant resistance (R) genes and dominant pathogen-encoded avirulence (Avr) genes. It was postulated that R genes encode receptors for Avr determinants. A large number of R genes and their cognate Avr genes have now been analyzed at the molecular level. R gene loci are extremely polymorphic, particularly in sequences encoding amino acids of the leucine-rich repeat motif. A major challenge is to determine how Avr perception by R proteins triggers the plant defense response. Mutational analysis has identified several genes required for the function of specific R proteins. Here we report the identification of Rcr3, a tomato gene required specifically for Cf-2-mediated resistance. We propose that Avr products interact with host proteins to promote disease, and that R proteins “guard” these host components and initiate Avr-dependent plant defense responses.
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The Australian southern continental margin is the world’s largest site of cool-water carbonate deposition, and the Great Australian Bight is its largest sector. The Eyre Peninsula is fringed by coastal beaches with aeolianites and marks the eastern edge of the Great Australian Bight. Five shoreline transects of varying lengths spanned a 150km longitudinal distance and at each the intertidal, beach, dune and secondary dune environments were sampled, for a total of 18 samples. Sediments are a mixture of modern, relict, and Cenozoic carbonates, and quartz grains. Carbonate aeolianites on the western Eyre Peninsula are mostly composed of modern carbonate grains: predominantly molluscs (23-33%) and benthic foraminifera (10-26%), locally abundant coralline algae (3-28%), echinoids (2-22%), and bryozoans (2-14%). Cenozoic grain abundance ranges from 1-6% whereas relict grain abundance ranges from 0-17%. A southward increase in bryozoan particles correlates with a nutrient element abundance and decrease in temperature due to a large seasonal coastal upwelling system that drives 2-3 major upwelling events per year, bringing cold, nutrient rich, Sub-Antarctic Surface Water (<12°C) onto the shelf. In southern, mostly wind protected locations, the beach and dune sediment compositions are similar, indicating that wind energy has successfully carried all sediment components of the beach into the adjacent dunes. In northern, exposed locations, the composition is not the same everywhere, and trends indicate that relative wind energy has the ability to impact grain composition through preferential wind transport. Aeolianite composition is therefore a function of both upwelling and the degree of coastal exposure.
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The tremendous diversity of leaf shapes has caught the attention of naturalists for centuries. In addition to interspecific and intraspecific differences, leaf morphologies may differ in single plants according to age, a phenomenon known as heteroblasty. In Arabidopsis thaliana, the progression from the juvenile to the adult phase is characterized by increased leaf serration. A similar trend is seen in species with more complex leaves, such as the A. thaliana relative Cardamine hirsuta, in which the number of leaflets per leaf increases with age. Although the genetic changes that led to the overall simpler leaf architecture in A. thaliana are increasingly well understood, less is known about the events underlying age-dependent changes within single plants, in either A. thaliana or C. hirsuta. Here, we describe a conserved miRNA transcription factor regulon responsible for an age-dependent increase in leaf complexity. In early leaves, miR319-targeted TCP transcription factors interfere with the function of miR164-dependent and miR164-independent CUC proteins, preventing the formation of serrations in A. thaliana and of leaflets in C. hirsuta. As plants age, accumulation of miR156-regulated SPLs acts as a timing cue that destabilizes TCP-CUC interactions. The destabilization licenses activation of CUC protein complexes and thereby the gradual increase of leaf complexity in the newly formed organs. These findings point to posttranslational interaction between unrelated miRNA-targeted transcription factors as a core feature of these regulatory circuits.
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Background and Aims Summer dormancy in perennial grasses has been studied inadequately, despite its potential to enhance plant survival and persistence in Mediterranean areas. The aim of the present work was to characterize summer dormancy and dehydration tolerance in two cultivars of Dactylis glomerata (dormant 'Kasbah', non-dormant 'Oasis') and their hybrid using physiological indicators associated with these traits. Methods Dehydration tolerance was assessed in a glasshouse experiment, while seasonal metabolic changes which produce putative protectants for drought, such as carbohydrates and dehydrins that might be associated with summer dormancy, were analysed in the field. Key Results The genotypes differed in their ability to survive increasing soil water deficit: lethal soil water potential (ψ(s)) was -3(.)4 MPa for 'Kasbah' (although non-dormant), -1(.)3 MPa for 'Oasis', and -1(.)6 MPa for their hybrid. In contrast, lethal water content of apices was similar for all genotypes (approx. 0(.)45 g H2O g d. wt(-1)), and hence the greater survival of 'Kasbah' can be ascribed to better drought avoidance rather than dehydration tolerance. In autumn-sown plants, 'Kasbah' had greatest dormancy, the hybrid was intermediate and 'Oasis' had none. The more dormant the genotype, the lower the metabolic activity during summer, and the earlier the activity declined in spring. Decreased monosaccharide content was an early indicator of dormancy induction. Accumulation of dehydrins did not correlate with stress tolerance, but dehydrin content was a function of the water status of the tissues, irrespective of the soil moisture. A protein of approx. 55 kDa occurred in leaf bases of the most dormant cultivar even in winter. Conclusions Drought avoidance and summer dormancy are correlated but can be independently expressed. These traits are heritable, allowing selection in breeding programmes.