TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Genomic Organization of H2Av Containing Nucleosomes in Drosophila Heterochromatin

H2Av is a versatile histone variant that plays both positive and negative roles in transcription, DNA repair, and chromatin structure in Drosophila. H2Av, and its broader homolog H2A.Z, tend to be enriched toward 5′ ends of genes, and exist in both euchromatin and heterochromatin. Its organization around euchromatin genes and other features have been described in many eukaryotic model organisms. However, less is known about H2Av nucleosome organization in heterochromatin. Here we report the properties and organization of individual H2Av nucleosomes around genes and transposable elements located in Drosophila heterochromatic regions. We compare the similarity and differences with that found in euchromatic regions. Our analyses suggest that nucleosomes are intrinsically positioned on inverted repeats of DNA transposable elements such as those related to the “1360” element, but are not intrinsically positioned on retrotransposon-related elements

Paleogene Radiation of a Plant Pathogenic Mushroom

Background: The global movement and speciation of fungal plant pathogens is important, especially because of the economic losses they cause and the ease with which they are able to spread across large areas. Understanding the biogeography and origin of these plant pathogens can provide insights regarding their dispersal and current day distribution. We tested the hypothesis of a Gondwanan origin of the plant pathogenic mushroom genus Armillaria and the currently accepted premise that vicariance accounts for the extant distribution of the species. Methods: The phylogeny of a selection of Armillaria species was reconstructed based on Maximum Parsimony (MP), Maximum Likelihood (ML) and Bayesian Inference (BI). A timeline was then placed on the divergence of lineages using a Bayesian relaxed molecular clock approach. Results: Phylogenetic analyses of sequenced data for three combined nuclear regions provided strong support for three major geographically defined clades: Holarctic, South American-Australasian and African. Molecular dating placed the initial radiation of the genus at 54 million years ago within the Early Paleogene, postdating the tectonic break-up of Gondwana. Conclusions: The distribution of extant Armillaria species is the result of ancient long-distance dispersal rather than vicariance due to continental drift. As these finding are contrary to most prior vicariance hypotheses for fungi, our result

Alzheimer disease models and human neuropathology: similarities and differences

Animal models aim to replicate the symptoms, the lesions or the cause(s) of Alzheimer disease. Numerous mouse transgenic lines have now succeeded in partially reproducing its lesions: the extracellular deposits of Aβ peptide and the intracellular accumulation of tau protein. Mutated human APP transgenes result in the deposition of Aβ peptide, similar but not identical to the Aβ peptide of human senile plaque. Amyloid angiopathy is common. Besides the deposition of Aβ, axon dystrophy and alteration of dendrites have been observed. All of the mutations cause an increase in Aβ 42 levels, except for the Arctic mutation, which alters the Aβ sequence itself. Overexpressing wild-type APP alone (as in the murine models of human trisomy 21) causes no Aβ deposition in most mouse lines. Doubly (APP × mutated PS1) transgenic mice develop the lesions earlier. Transgenic mice in which BACE1 has been knocked out or overexpressed have been produced, as well as lines with altered expression of neprilysin, the main degrading enzyme of Aβ. The APP transgenic mice have raised new questions concerning the mechanisms of neuronal loss, the accumulation of Aβ in the cell body of the neurons, inflammation and gliosis, and the dendritic alterations. They have allowed some insight to be gained into the kinetics of the changes. The connection between the symptoms, the lesions and the increase in Aβ oligomers has been found to be difficult to unravel. Neurofibrillary tangles are only found in mouse lines that overexpress mutated tau or human tau on a murine tau −/− background. A triply transgenic model (mutated APP, PS1 and tau) recapitulates the alterations seen in AD but its physiological relevance may be discussed. A number of modulators of Aβ or of tau accumulation have been tested. A transgenic model may be analyzed at three levels at least (symptoms, lesions, cause of the disease), and a reading key is proposed to summarize this analysis

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives