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

Bubble stabilized discontinuous Galerkin methods on conforming and non-conforming meshes

The aim of this paper is to discuss the properties of the bubble stabilized discontinuous Galerkin method with respect to mesh geometry. First we show that on certain non-conforming meshes the bubble stabilized discontinuous Galerkin method allows for hanging nodes/edges. Then we consider the case of conforming meshes and present a post-processing algorithm based on the Crouzeix-Raviart method to obtain the Bubble Stabilized Discontinuous Galerkin (BSDG) method. Although finally the post-processed solution does not coincide with the BSDG-solution in general, they satisfy the same (approximation) properties and are close to each other. Moreover, the post-processed solution has continuous flux over the edge

The clinical and molecular spectrum of the KDM6B-related neurodevelopmental disorder

De novo variants are a leading cause of neurodevelopmental disorders (NDDs), but because every monogenic NDD is different and usually extremely rare, it remains a major challenge to understand the complete phenotype and genotype spectrum of any morbid gene. According to OMIM, heterozygous variants in KDM6B cause “neurodevelopmental disorder with coarse facies and mild distal skeletal abnormalities.” Here, by examining the molecular and clinical spectrum of 85 reported individuals with mostly de novo (likely) pathogenic KDM6B variants, we demonstrate that this description is inaccurate and potentially misleading. Cognitive deficits are seen consistently in all individuals, but the overall phenotype is highly variable. Notably, coarse facies and distal skeletal anomalies, as defined by OMIM, are rare in this expanded cohort while other features are unexpectedly common (e.g., hypotonia, psychosis, etc.). Using 3D protein structure analysis and an innovative dual Drosophila gain-of-function assay, we demonstrated a disruptive effect of 11 missense/in-frame indels located in or near the enzymatic JmJC or Zn-containing domain of KDM6B. Consistent with the role of KDM6B in human cognition, we demonstrated a role for the Drosophila KDM6B ortholog in memory and behavior. Taken together, we accurately define the broad clinical spectrum of the KDM6B-related NDD, introduce an innovative functional testing paradigm for the assessment of KDM6B variants, and demonstrate a conserved role for KDM6B in cognition and behavior. Our study demonstrates the critical importance of international collaboration, sharing of clinical data, and rigorous functional analysis of genetic variants to ensure correct disease diagnosis for rare disorders

The clinical and molecular spectrum of the KDM6B-related neurodevelopmental disorder

International audienceDe novo variants are a leading cause of neurodevelopmental disorders (NDDs), but because every monogenic NDD is different and usually extremely rare, it remains a major challenge to understand the complete phenotype and genotype spectrum of any morbid gene. According to OMIM, heterozygous variants in KDM6B cause "neurodevelopmental disorder with coarse facies and mild distal skeletal abnormalities." Here, by examining the molecular and clinical spectrum of 85 reported individuals with mostly de novo (likely) pathogenic KDM6B variants, we demonstrate that this description is inaccurate and potentially misleading. Cognitive deficits are seen consistently in all individuals, but the overall phenotype is highly variable. Notably, coarse facies and distal skeletal anomalies, as defined by OMIM, are rare in this expanded cohort while other features are unexpectedly common (e.g., hypotonia, psychosis, etc.). Using 3D protein structure analysis and an innovative dual Drosophila gain-of-function assay, we demonstrated a disruptive effect of 11 missense/in-frame indels located in or near the enzymatic JmJC or Zn-containing domain of KDM6B. Consistent with the role of KDM6B in human cognition, we demonstrated a role for the Drosophila KDM6B ortholog in memory and behavior. Taken together, we accurately define the broad clinical spectrum of the KDM6B-related NDD, introduce an innovative functional testing paradigm for the assessment of KDM6B variants, and demonstrate a conserved role for KDM6B in cognition and behavior. Our study demonstrates the critical importance of international collaboration, sharing of clinical data, and rigorous functional analysis of genetic variants to ensure correct disease diagnosis for rare disorders

TRY plant trait database, enhanced coverage and open access

Plant traits-the morphological, ahawnatomical, 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