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

Cloning of a gene (SR-A1), encoding for a new member of the human Ser/Arg-rich family of pre-mRNA splicing factors: overexpression in aggressive ovarian cancer

By using the positional cloning gene approach, we were able to identify a novel gene encoding for a serine/arginine-rich protein, which appears to be the human homologue of the rat A1 gene. We named this new gene SR-A1. Members of the SR family of proteins have been shown to interact with the C-terminal domain (CTD) of the large subunit of RNA polymerase II and participate in pre-mRNA splicing. We have localized the SR-A1 gene between the known genes IRF3 and RRAS on chromosome 19q13.3. The novel gene spans 16.7 kb of genomic sequence and it is formed of 11 exons and 10 intervening introns. The SR-A1 protein is composed of 1312 amino acids, with a molecular mass of 139.3 kDa and a theoretical isoelectric point of 9.31. The SR-A1 protein contains an SR-rich domain as well as a CTD-binding domain present only in a subset of SR-proteins. Through interactions with the pre-mRNA and the CTD domain of the Polymerase II, SR proteins have been shown to regulate alternative splicing. The SR-A1 gene is expressed in all tissues tested, with highest levels found in fetal brain and fetal liver. Our data suggest that this gene is overexpressed in a subset of ovarian cancers which are clinically more aggressive. Studies with the steroid hormone receptor-positive breast and prostate carcinoma cell lines ZR-75-1, BT-474 and LNCaP, respectively, suggest that SR-A1 is constitutively expressed. Furthermore, the mRNA of the SR-A1 gene in these cell lines appears to increase by estrogens, androgens and glucocorticoids, and to a lesser extend by progestins. © 2001 Cancer Research Campaign http://www.bjcancer.co

Acquisition and Evolution of Plant Pathogenesis–Associated Gene Clusters and Candidate Determinants of Tissue-Specificity in Xanthomonas

is a large genus of plant-associated and plant-pathogenic bacteria. Collectively, members cause diseases on over 392 plant species. Individually, they exhibit marked host- and tissue-specificity. The determinants of this specificity are unknown. lineage. genome and indicate that differentiation with respect to host- and tissue-specificity involved not major modifications or wholesale exchange of clusters, but subtle changes in a small number of genes or in non-coding sequences, and/or differences outside the clusters, potentially among regulatory targets or secretory substrates

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

Quantitative trait loci controlling water use efficiency and related traits in Quercus robur L.

Genetic variation for intrinsic water use efficiency (W i) and related traits was estimated in a full-sib family of Quercus robur L. over 3 years. The genetic linkage map available for this F1 family was used to locate quantitative trait loci (QTL) for W i, as estimated by leaf carbon stable isotope composition (δ 13C) or the ratio of net CO2 assimilation rate (A) to stomatal conductance to water vapour (g w) and related leaf traits. Gas exchange measurements were used to standardize estimates of A and g w and to model the sensitivity of g w to leaf-to-air vapour pressure deficit (sgVPD). δ 13C varied by more than 3‰ among the siblings, which is equivalent to 40% variation of W i. Most of the studied traits exhibited high clonal mean repeatabilities (>50%; proportion of clonal mean variability in global variance). Repeatabilities for δ 13C, leaf mass per area (LMA) and leaf nitrogen content were higher than 70%. For δ 13C, ten QTLs were detected, one of which was detected repeatedly for all 3 years and consistently explained more than 20% of measured variance. Four genomic regions were found in which co-localizing traits linked variation in W i to variations in leaf chlorophyll and nitrogen content, LMA and sgVPD. A positive correlation using clonal means between δ 13C and A/g w, as well as a co-localisation of QTL detected for both traits, can be seen as validation of the theoretical model linking the genetic architecture of these two traits

Continuous generation of single photons with controlled waveform in an ion-trap cavity system

The controlled production of single photons is of fundamental and practical interest; they represent the lowest excited quantum states of the radiation field, and have applications in quantum cryptography and quantum information processing. Common approaches use the fluorescence of single ions, single molecules, colour centres and semiconductor quantum dots. However, the lack of control over such irreversible emission processes precludes the use of these sources in applications (such as quantum networks) that require coherent exchange of quantum states between atoms and photons. The necessary control may be achieved in principle in cavity quantum electrodynamics. Although this approach has been used for the production of single photons from atoms, such experiments are compromised by limited trapping times, fluctuating atomfield coupling and multi-atom effects. Here we demonstrate a single-photon source based on a strongly localized single ion in an optical cavity. The ion is optimally coupled to a well-defined field mode, resulting in the generation of single-photon pulses with precisely defined shape and timing. We have confirmed the suppression of two-photon events up to the limit imposed by fluctuations in the rate of detector dark counts. The stream of emitted photons is uninterrupted over the storage time of the ion, as demonstrated by a measurement of photon correlations over 90 min