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

Molecular Evolution of the Neuropeptide S Receptor

The neuropeptide S receptor (NPSR) is a recently deorphanized member of the G protein-coupled receptor (GPCR) superfamily and is activated by the neuropeptide S (NPS). NPSR and NPS are widely expressed in central nervous system and are known to have crucial roles in asthma pathogenesis, locomotor activity, wakefulness, anxiety and food intake. The NPS-NPSR system was previously thought to have first evolved in the tetrapods. Here we examine the origin and the molecular evolution of the NPSR using in-silico comparative analyses and document the molecular basis of divergence of the NPSR from its closest vertebrate paralogs. In this study, NPSR-like sequences have been identified in a hemichordate and a cephalochordate, suggesting an earlier emergence of a NPSR-like sequence in the metazoan lineage. Phylogenetic analyses revealed that the NPSR is most closely related to the invertebrate cardioacceleratory peptide receptor (CCAPR) and the group of vasopressin-like receptors. Gene structure features were congruent with the phylogenetic clustering and supported the orthology of NPSR to the invertebrate NPSR-like and CCAPR. A site-specific analysis between the vertebrate NPSR and the well studied paralogous vasopressin-like receptor subtypes revealed several putative amino acid sites that may account for the observed functional divergence between them. The data can facilitate experimental studies aiming at deciphering the common features as well as those related to ligand binding and signal transduction processes specific to the NPSR

QTLs and candidates genes for wood properties in maritime pine (Pinus pinaster Ait.)

A three-generation outbred pedigree of 186 individuals was used to identify the genomic regions involved in the variability of chemical and physical wood properties of Pinus pinaster. A total of 54 quantitative trait loci (QTLs) was detected, with an average of 2.4 QTLs per trait. Clusters of wood properties QTLs were found at several points in the genome, suggesting the existence of pleiotropic effects of a limited number of genes. The colocalizations observed in this study are in accordance with the genetic correlations previously reported in the literature. In addition, in an attempt to identify the genes underlying the QTLs, nine wood quality candidate genes involved in cell wall structure were localized on the genetic map. Only one of them, Korrigan, a gene encoding for a β 1-4 endo-glucanase known in Arabidopis thaliana to be involved in polysaccharide biosynthesis, co-localized with a wood quality QTL cluster involved in hemicellulose content and fibre characteristics. This finding is in accordance with results previously reported for this gene regarding its expression variability (transcriptome and proteome levels) and patterns of molecular evolution. The pertinence of this result will be tested in more rigorous designs in order to identify early selection predictors for wood quality