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

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

Haplotype-specific expression of the human PDGFRA gene correlates with the risk of glioblastomas

Aberrant expression of the platelet-derived growth factor a-receptor (PDGFRA) gene has been associated with various diseases, including neural tube defects and gliomas. We have previously identified 5 distinct haplotypes for the PDGFRA promoter region, designated H1, H2 alpha, H2 beta, H2 gamma and H2 delta. Of these haplotypes H1 and H2 alpha: are the most common, whereby H1 drives low and H2 alpha high transcriptional activity in transient transfection assays. Here we have investigated the role of these PDGFRA promoter haplotypes in gliomagenesis at both the genetic and cellular level. In a case-control study on 71 glioblastoma patients, we observed a clear underrepresentation of H1 alleles, with pH1 = 0.141 in patients and pH1 = 0.211 in a combined Western European control group (n = 998, p < 0.05). Furthermore, in 3 out of 4 available H1/H2 alpha heterozygous human glioblastoma cell lines, H1-derived mRNA levels were more than 10-fold lower than from H2 alpha, resulting at least in part from haplotype-specific epigenetic differences such as DNA methylation and histone acetylation. Together, these results indicate that PDGFRA promoter haplotypes may predispose to gliomas. We propose a model in which PDGFRA is upregulated in a haplotype-specific manner during neural stem cell differentiation, which affects the pool size of cells that can later undergo gliomagenesis. (C) 2008 Wiley-Liss, Inc