854 resultados para ecological genomics


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Understanding how communities of living organisms assemble has been a central question in ecology since the early days of the discipline. Disentangling the different processes involved in community assembly is not only interesting in itself but also crucial for an understanding of how communities will behave under future environmental scenarios. The traditional concept of assembly rules reflects the notion that species do not co-occur randomly but are restricted in their co-occurrence by interspecific competition. This concept can be redefined in a more general framework where the co-occurrence of species is a product of chance, historical patterns of speciation and migration, dispersal, abiotic environmental factors, and biotic interactions, with none of these processes being mutually exclusive. Here we present a survey and meta-analyses of 59 papers that compare observed patterns in plant communities with null models simulating random patterns of species assembly. According to the type of data under study and the different methods that are applied to detect community assembly, we distinguish four main types of approach in the published literature: species co-occurrence, niche limitation, guild proportionality and limiting similarity. Results from our meta-analyses suggest that non-random co-occurrence of plant species is not a widespread phenomenon. However, whether this finding reflects the individualistic nature of plant communities or is caused by methodological shortcomings associated with the studies considered cannot be discerned from the available metadata. We advocate that more thorough surveys be conducted using a set of standardized methods to test for the existence of assembly rules in data sets spanning larger biological and geographical scales than have been considered until now. We underpin this general advice with guidelines that should be considered in future assembly rules research. This will enable us to draw more accurate and general conclusions about the non-random aspect of assembly in plant communities.

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Staphylococcus aureus, especially when it is methicillin resistant, has been recognised as a major cause of nosocomial and community-acquired infections. It has also been shown that certain strains were able to cause clonal epidemics whereas others showed a more incidental occurrence. On the basis of this behavioural distinction, a genetic feature underlying this difference in epidemicity can be assumed. Understanding the difference will not only contribute to the development of markers for the identification of epidemic strains but will also shed light on the evolution of clones. Genomes of strains from two independent collections (n=18 and n=10 strains) were analysed. Both collections were composed of carefully selected, genetically diverse strains with clinically well-defined epidemic and sporadic behaviour. Comparative genome hybridisation (CGH) was performed using an Agilent array for one collection (up to 11 probes per open reading frame - ORF), and an Affymetrix array for the other (up to 30 probes per ORF). Presence and absence information of probe homologues and ORFs was taken for analysis of molecular variance (AMOVA) at the strain and behaviour levels. Not a single probe showed 100% concordant differences between epidemic and sporadic strains. Moreover, probe differences between groups were always smaller than those within groups. This was also true, when the analysis was focussed on presence versus absence of ORF's or when probe information was transformed into allelic profiles. These findings present strong evidence against the presence or absence of a single common specific genetic factor differentiating epidemic from sporadic S. aureus clones.

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Arbuscular mycorrhizal fungi are thought to have remained asexual for 400 million years although recent studies have suggested that considerable genetic and phenotypic variation could potentially exist in populations. A brief discussion of these multigenomic organisms is presented. (C) 2003 The Linnean Society of London.

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PURPOSE OF REVIEW: One of the seven key scientific priorities identified in the road map on HIV cure research is to 'determine the host mechanisms that control HIV replication in the absence of therapy'. This review summarizes the recent work in genomics and in epigenetic control of viral replication that is relevant for this mission. RECENT FINDINGS: New technologies allow the joint analysis of host and viral transcripts. They identify the patterns of antisense transcription of the viral genome and its role in gene regulation. High-throughput studies facilitate the assessment of integration at the genome scale. Integration site, orientation and host genomic context modulate the transcription and should also be assessed at the level of single cells. The various models of latency in primary cells can be followed using dynamic study designs to acquire transcriptome and proteome data of the process of entry, maintenance and reactivation of latency. Dynamic studies can be applied to the study of transcription factors and chromatin modifications in latency and upon reactivation. SUMMARY: The convergence of primary cell models of latency, new high-throughput quantitative technologies applied to the study of time series and the identification of compounds that reactivate viral transcription bring unprecedented precision to the study of viral latency.

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The genetic determinants and phenotypic traits which make a Staphylococcus aureus strain a successful colonizer are largely unknown. The genetic diversity and population structure of 133 S. aureus isolates from healthy, generally risk-free adult carriers were investigated using four different typing methods: multilocus sequence typing (MLST), amplified fragment length polymorphism analysis (AFLP), double-locus sequence typing (DLST), and spa typing were compared. Carriage isolates displayed great genetic diversity which could only be revealed fully by DLST. Results of AFLP and MLST were highly concordant in the delineation of genotypic clusters of closely related isolates, roughly equivalent to clonal complexes. spa typing and DLST provided considerably less phylogenetic information. The resolution of spa typing was similar to that of AFLP and inferior to that of DLST. AFLP proved to be the most universal method, combining a phylogeny-building capacity similar to that of MLST with a much higher resolution. However, it had a lower reproducibility than sequencing-based MLST, DLST, and spa typing. We found two cases of methicillin-resistant S. aureus colonization, both of which were most likely associated with employment at a health service. Of 21 genotypic clusters detected, 2 were most prevalent: cluster 45 and cluster 30 each colonized 24% of the carrier population. The number of bacteria found in nasal samples varied significantly among the clusters, but the most prevalent clusters were not particularly numerous in the nasal samples. We did not find much evidence that genotypic clusters were associated with different carrier characteristics, such as age, sex, medical conditions, or antibiotic use. This may provide empirical support for the idea that genetic clusters in bacteria are maintained in the absence of adaptation to different niches. Alternatively, carrier characteristics other than those evaluated here or factors other than human hosts may exert selective pressure maintaining genotypic clusters.

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A few bacterial species are known to produce and excrete hydrogen cyanide (HCN), a potent inhibitor of cytochrome c oxidase and several other metalloenzymes. In the producer strains, HCN does not appear to have a role in primary metabolism and is generally considered a secondary metabolite. HCN synthase of proteobacteria (especially fluorescent pseudomonads) is a membrane-bound flavoenzyme that oxidizes glycine, producing HCN and CO2. The hcnABC structural genes of Pseudomonas fluorescens and P. aeruginosa have sequence similarities with genes encoding various amino acid dehydrogenases/oxidases, in particular with nopaline oxidase of Agrobacterium tumefaciens. Induction of the hcn genes of P. fluorescens by oxygen limitation requires the FNR-like transcriptional regulator ANR, an ANR recognition sequence in the -40 region of the hcn promoter, and nonlimiting amounts of iron. In addition, expression of the hcn genes depends on a regulatory cascade initiated by the GacS/GacA (global control) two-component system. This regulation, which is typical of secondary metabolism, manifests itself during the transition from exponential to stationary growth phase. Cyanide produced by P. fluorescens strain CHA0 has an ecological role in that this metabolite accounts for part of the biocontrol capacity of strain CHA0, which suppresses fungal diseases on plant roots. Cyanide can also be a ligand of hydrogenases in some anaerobic bacteria that have not been described as cyanogenic. However, in this case, as well as in other situations, the physiological function of cyanide is unknown.

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BACKGROUND: Hepatitis C Virus (HCV) infection is spontaneously resolved in about 30% of acutely infected individuals. In those who progress to chronic hepatitis C, HCV therapy permanently eradicates infection in about 40% of cases. It has long been suspected that host genetic factors are key determinants for the control of HCV infection. DESIGN: We will review in this study four genome-wide association studies (GWAS) and two large candidate gene studies that assessed the role of host genetic variation for the natural and treatment-induced control of HCV infection. RESULTS: The studies consistently identified genetic variation in interleukin 28B (IL28B) as the strongest predictor for the control of HCV infection. Importantly, single nucleotide polymorphisms (SNPs) in IL28B strongly predicted both spontaneous and treatment-induced HCV recovery. IL28B is located on chromosome 19 and encodes interferon-λ, a type III interferon with antiviral activity, which is mediated through the JAK-STAT pathway by inducing interferon-stimulated genes. The SNPs identified in the GWAS are in high linkage disequilibrium with coding or functional non-coding SNPs that might modulate function and/or expression of IL28B. The role of the different IL28B alleles on gene expression and cytokine function has not yet been established. CONCLUSIONS: These findings provide strong genetic evidence for the influence of interferon-λ for both the natural and treatment-induced control of HCV infection, and support the further investigation of interferon-λ for the treatment of chronic hepatitis C. Furthermore, genetic testing before HCV therapy could provide important information towards an individualized HCV treatment.

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It has been known for some time that different arbuscular mycorrhizal fungal (AMF) taxa confer differences in plant growth. Although genetic variation within AMF species has been given less attention, it could potentially be an ecologically important source of variation. Ongoing studies on variability in AMF genes within Glomus intraradices indicate that at least for some genes, such as the BiP gene, sequence variability can be high, even in coding regions. This suggests that genetic variation within an AMF may not be selectively neutral. This clearly needs to be investigated in more detail for other coding regions of AMF genomes. Similarly, studies on AMF population genetics indicate high genetic variation in AMF populations, and a considerable amount of variation seen in phenotypes in the population can be attributed to genetic differences among the fungi. The existence of high within-species genetic variation could have important consequences for how investigations on AMF gene expression and function are conducted. Furthermore, studies of within-species genetic variability and how it affects variation in plant growth will help to identify at what level of precision ecological studies should be conducted to identify AMF in plant roots in the field. A population genetic approach to studying AMF genetic variability can also be useful for inoculum development. By knowing the amount of genetic variability in an AMF population, the maximum and minimum numbers of spores that will contain a given amount of genetic diversity can be estimated. This could be particularly useful for developing inoculum with high adaptability to different environments.

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Progress in genomics with, in particular, high throughput next generation sequencing is revolutionizing oncology. The impact of these techniques is seen on the one hand the identification of germline mutations that predispose to a given type of cancer, allowing for a personalized care of patients or healthy carriers and, on the other hand, the characterization of all acquired somatic mutation of the tumor cell, opening the door to personalized treatment targeting the driver oncogenes. In both cases, next generation sequencing techniques allow a global approach whereby the integrality of the genome mutations is analyzed and correlated with the clinical data. The benefits on the quality of care delivered to our patients are extremely impressive.

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Speciation is a fundamental evolutionary process, the knowledge of which is crucial for understanding the origins of biodiversity. Genomic approaches are an increasingly important aspect of this research field. We review current understanding of genome-wide effects of accumulating reproductive isolation and of genomic properties that influence the process of speciation. Building on this work, we identify emergent trends and gaps in our understanding, propose new approaches to more fully integrate genomics into speciation research, translate speciation theory into hypotheses that are testable using genomic tools and provide an integrative definition of the field of speciation genomics.

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1. Identifying the boundary of a species' niche from observational and environmental data is a common problem in ecology and conservation biology and a variety of techniques have been developed or applied to model niches and predict distributions. Here, we examine the performance of some pattern-recognition methods as ecological niche models (ENMs). Particularly, one-class pattern recognition is a flexible and seldom used methodology for modelling ecological niches and distributions from presence-only data. The development of one-class methods that perform comparably to two-class methods (for presence/absence data) would remove modelling decisions about sampling pseudo-absences or background data points when absence points are unavailable. 2. We studied nine methods for one-class classification and seven methods for two-class classification (five common to both), all primarily used in pattern recognition and therefore not common in species distribution and ecological niche modelling, across a set of 106 mountain plant species for which presence-absence data was available. We assessed accuracy using standard metrics and compared trade-offs in omission and commission errors between classification groups as well as effects of prevalence and spatial autocorrelation on accuracy. 3. One-class models fit to presence-only data were comparable to two-class models fit to presence-absence data when performance was evaluated with a measure weighting omission and commission errors equally. One-class models were superior for reducing omission errors (i.e. yielding higher sensitivity), and two-classes models were superior for reducing commission errors (i.e. yielding higher specificity). For these methods, spatial autocorrelation was only influential when prevalence was low. 4. These results differ from previous efforts to evaluate alternative modelling approaches to build ENM and are particularly noteworthy because data are from exhaustively sampled populations minimizing false absence records. Accurate, transferable models of species' ecological niches and distributions are needed to advance ecological research and are crucial for effective environmental planning and conservation; the pattern-recognition approaches studied here show good potential for future modelling studies. This study also provides an introduction to promising methods for ecological modelling inherited from the pattern-recognition discipline.

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Animal dispersal in a fragmented landscape depends on the complex interaction between landscape structure and animal behavior. To better understand how individuals disperse, it is important to explicitly represent the properties of organisms and the landscape in which they move. A common approach to modelling dispersal includes representing the landscape as a grid of equal sized cells and then simulating individual movement as a correlated random walk. This approach uses a priori scale of resolution, which limits the representation of all landscape features and how different dispersal abilities are modelled. We develop a vector-based landscape model coupled with an object-oriented model for animal dispersal. In this spatially explicit dispersal model, landscape features are defined based on their geographic and thematic properties and dispersal is modelled through consideration of an organism's behavior, movement rules and searching strategies (such as visual cues). We present the model's underlying concepts, its ability to adequately represent landscape features and provide simulation of dispersal according to different dispersal abilities. We demonstrate the potential of the model by simulating two virtual species in a real Swiss landscape. This illustrates the model's ability to simulate complex dispersal processes and provides information about dispersal such as colonization probability and spatial distribution of the organism's path

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DNA-binding proteins mediate a variety of crucial molecular functions, such as transcriptional regulation and chromosome maintenance, replication and repair, which in turn control cell division and differentiation. The roles of these proteins in disease are currently being investigated using microarray-based approaches. However, these assays can be difficult to adapt to routine diagnosis of complex diseases such as cancer. Here, we review promising alternative approaches involving protein-binding microarrays (PBMs) that probe the interaction of proteins from crude cell or tissue extracts with large collections of synthetic or natural DNA sequences. Recent studies have demonstrated the use of these novel PBM approaches to provide rapid and unbiased characterization of DNA-binding proteins as molecular markers of disease, for example cancer progression or infectious diseases.

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BACKGROUND: Fourmidable is an infrastructure to curate and share the emerging genetic, molecular, and functional genomic data and protocols for ants. DESCRIPTION: The Fourmidable assembly pipeline groups nucleotide sequences into clusters before independently assembling each cluster. Subsequently, assembled sequences are annotated via Interproscan and BLAST against general and insect-specific databases. Gene-specific information can be retrieved using gene identifiers, searching for similar sequences or browsing through inferred Gene Ontology annotations. The database will readily scale as ultra-high throughput sequence data and sequences from additional species become available. CONCLUSION: Fourmidable currently houses EST data from two ant species and microarray gene expression data for one of these. Fourmidable is publicly available at http://fourmidable.unil.ch.

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Complexity of biological function relies on large networks of interacting molecules. However, the evolutionary properties of these networks are not fully understood. It has been shown that selective pressures depend on the position of genes in the network. We have previously shown that in the Drosophila insulin/target of rapamycin (TOR) signal transduction pathway there is a correlation between the pathway position and the strength of purifying selection, with the downstream genes being most constrained. In this study, we investigated the evolutionary dynamics of this well-characterized pathway in vertebrates. More specifically, we determined the impact of natural selection on the evolution of 72 genes of this pathway. We found that in vertebrates there is a similar gradient of selective constraint in the insulin/TOR pathway to that found in Drosophila. This feature is neither the result of a polarity in the impact of positive selection nor of a series of factors affecting selective constraint levels (gene expression level and breadth, codon bias, protein length, and connectivity). We also found that pathway genes encoding physically interacting proteins tend to evolve under similar selective constraints. The results indicate that the architecture of the vertebrate insulin/TOR pathway constrains the molecular evolution of its components. Therefore, the polarity detected in Drosophila is neither specific nor incidental of this genus. Hence, although the underlying biological mechanisms remain unclear, these may be similar in both vertebrates and Drosophila.