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

Conserved Expression Patterns Predict microRNA Targets

microRNAs (miRNAs) are major regulators of gene expression and thereby modulate many biological processes. Computational methods have been instrumental in understanding how miRNAs bind to mRNAs to induce their repression but have proven inaccurate. Here we describe a novel method that combines expression data from human and mouse to discover conserved patterns of expression between orthologous miRNAs and mRNA genes. This method allowed us to predict thousands of putative miRNA targets. Using the luciferase reporter assay, we confirmed 4 out of 6 of our predictions. In addition, this method predicted many miRNAs that act as expression enhancers. We show that many miRNA enhancer effects are mediated through the repression of negative transcriptional regulators and that this effect could be as common as the widely reported repression activity of miRNAs. Our findings suggest that the indirect enhancement of gene expression by miRNAs could be an important component of miRNA regulation that has been widely neglected to date

CpG island hypermethylation-associated silencing of non-coding RNAs transcribed from ultraconserved regions in human cancer

Although only 1.5% of the human genome appears to code for proteins, much effort in cancer research has been devoted to this minimal fraction of our DNA. However, the last few years have witnessed the realization that a large class of non-coding RNAs (ncRNAs), named microRNAs, contribute to cancer development and progression by acting as oncogenes or tumor suppressor genes. Recent studies have also shown that epigenetic silencing of microRNAs with tumor suppressor features by CpG island hypermethylation is a common hallmark of human tumors. Thus, we wondered whether there were other ncRNAs undergoing aberrant DNA methylation-associated silencing in transformed cells. We focused on the transcribed-ultraconserved regions (T-UCRs), a subset of DNA sequences that are absolutely conserved between orthologous regions of the human, rat and mouse genomes and that are located in both intra- and intergenic regions. We used a pharmacological and genomic approach to reveal the possible existence of an aberrant epigenetic silencing pattern of T-UCRs by treating cancer cells with a DNA-demethylating agent followed by hybridization to an expression microarray containing these sequences. We observed that DNA hypomethylation induces release of T-UCR silencing in cancer cells. Among the T-UCRs that were reactivated upon drug treatment, Uc.160+, Uc283+A and Uc.346+ were found to undergo specific CpG island hypermethylation-associated silencing in cancer cells compared with normal tissues. The analysis of a large set of primary human tumors (n=283) demonstrated that hypermethylation of the described T-UCR CpG islands was a common event among the various tumor types. Our finding that, in addition to microRNAs, another class of ncRNAs (T-UCRs) undergoes DNA methylation-associated inactivation in transformed cells supports a model in which epigenetic and genetic alterations in coding and non-coding sequences cooperate in human tumorigenesis

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

Does Reading to Children Enhance their Educational Success?

Drawing on two unique German datasets, we explore the possible short- and long-term effects that reading aloud in early childhood has on children’s language abilities, their reading behavior, and their school marks in kindergarten and at the end of both primary and secondary school. By applying propensity score matching,we found a positive effect of reading on the language abilities of preschool children and of students at the end of primary school. Additionally, a high frequency of reading to children in early childhood positively affects their own reading behavior. However, differences in reading in early childhood appear to be unrelated to school marks in the subject of German language at the end of primary school. Furthermore, we found no long-term effects of reading among secondary school leavers. Overall, our results confirm positive immediate and mid-term effects, but hardly any long-term effects, of reading to children during their early childhood