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- 2019
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Tidskriftsartikel (refereegranskat)
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| 2. |
- Kattge, Jens, et al.
(författare)
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TRY plant trait database - enhanced coverage and open access
- 2020
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Ingår i: Global Change Biology. - : Wiley-Blackwell. - 1354-1013 .- 1365-2486. ; 26:1, s. 119-188
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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| 3. |
- Fresard, Laure, et al.
(författare)
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Identification of rare-disease genes using blood transcriptome sequencing and large control cohorts
- 2019
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Ingår i: Nature Medicine. - : NATURE PUBLISHING GROUP. - 1078-8956 .- 1546-170X. ; 25:6, s. 911-919
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Tidskriftsartikel (refereegranskat)abstract
- It is estimated that 350 million individuals worldwide suffer from rare diseases, which are predominantly caused by mutation in a single gene(1). The current molecular diagnostic rate is estimated at 50%, with whole-exome sequencing (WES) among the most successful approaches(2-5). For patients in whom WES is uninformative, RNA sequencing (RNA-seq) has shown diagnostic utility in specific tissues and diseases(6-8). This includes muscle biopsies from patients with undiagnosed rare muscle disorders(6,9), and cultured fibroblasts from patients with mitochondrial disorders(7). However, for many individuals, biopsies are not performed for clinical care, and tissues are difficult to access. We sought to assess the utility of RNA-seq from blood as a diagnostic tool for rare diseases of different pathophysiologies. We generated whole-blood RNA-seq from 94 individuals with undiagnosed rare diseases spanning 16 diverse disease categories. We developed a robust approach to compare data from these individuals with large sets of RNA-seq data for controls (n = 1,594 unrelated controls and n = 49 family members) and demonstrated the impacts of expression, splicing, gene and variant filtering strategies on disease gene identification. Across our cohort, we observed that RNA-seq yields a 7.5% diagnostic rate, and an additional 16.7% with improved candidate gene resolution.
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| 4. |
- Blösch, Günter, et al.
(författare)
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Twenty-three unsolved problems in hydrology (UPH) - a community perspective
- 2019
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Ingår i: Hydrological Sciences Journal. - : Informa UK Limited. - 0262-6667 .- 2150-3435. ; 64:10, s. 1141-1158
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Tidskriftsartikel (refereegranskat)abstract
- This paper is the outcome of a community initiative to identify major unsolved scientific problems in hydrology motivated by a need for stronger harmonisation of research efforts. The procedure involved a public consultation through online media, followed by two workshops through which a large number of potential science questions were collated, prioritised, and synthesised. In spite of the diversity of the participants (230 scientists in total), the process revealed much about community priorities and the state of our science: a preference for continuity in research questions rather than radical departures or redirections from past and current work. Questions remain focused on the process-based understanding of hydrological variability and causality at all space and time scales. Increased attention to environmental change drives a new emphasis on understanding how change propagates across interfaces within the hydrological system and across disciplinary boundaries. In particular, the expansion of the human footprint raises a new set of questions related to human interactions with nature and water cycle feedbacks in the context of complex water management problems. We hope that this reflection and synthesis of the 23 unsolved problems in hydrology will help guide research efforts for some years to come.
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| 5. |
- Davies, Stuart J., et al.
(författare)
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ForestGEO: Understanding forest diversity and dynamics through a global observatory network
- 2021
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Ingår i: Biological Conservation. - : Elsevier BV. - 0006-3207. ; 253
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Tidskriftsartikel (refereegranskat)abstract
- ForestGEO is a network of scientists and long-term forest dynamics plots (FDPs) spanning the Earth's major forest types. ForestGEO's mission is to advance understanding of the diversity and dynamics of forests and to strengthen global capacity for forest science research. ForestGEO is unique among forest plot networks in its large-scale plot dimensions, censusing of all stems ≥1 cm in diameter, inclusion of tropical, temperate and boreal forests, and investigation of additional biotic (e.g., arthropods) and abiotic (e.g., soils) drivers, which together provide a holistic view of forest functioning. The 71 FDPs in 27 countries include approximately 7.33 million living trees and about 12,000 species, representing 20% of the world's known tree diversity. With >1300 published papers, ForestGEO researchers have made significant contributions in two fundamental areas: species coexistence and diversity, and ecosystem functioning. Specifically, defining the major biotic and abiotic controls on the distribution and coexistence of species and functional types and on variation in species' demography has led to improved understanding of how the multiple dimensions of forest diversity are structured across space and time and how this diversity relates to the processes controlling the role of forests in the Earth system. Nevertheless, knowledge gaps remain that impede our ability to predict how forest diversity and function will respond to climate change and other stressors. Meeting these global research challenges requires major advances in standardizing taxonomy of tropical species, resolving the main drivers of forest dynamics, and integrating plot-based ground and remote sensing observations to scale up estimates of forest diversity and function, coupled with improved predictive models. However, they cannot be met without greater financial commitment to sustain the long-term research of ForestGEO and other forest plot networks, greatly expanded scientific capacity across the world's forested nations, and increased collaboration and integration among research networks and disciplines addressing forest science.
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| 6. |
- Sawcer, Stephen, et al.
(författare)
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Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis
- 2011
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 476:7359, s. 214-219
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Tidskriftsartikel (refereegranskat)abstract
- Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis.
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| 7. |
- Falster, Daniel, et al.
(författare)
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AusTraits, a curated plant trait database for the Australian flora
- 2021
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Ingår i: Scientific Data. - : Nature Portfolio. - 2052-4463. ; 8:1
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Tidskriftsartikel (refereegranskat)abstract
- We introduce the AusTraits database - a compilation of values of plant traits for taxa in the Australian flora (hereafter AusTraits). AusTraits synthesises data on 448 traits across 28,640 taxa from field campaigns, published literature, taxonomic monographs, and individual taxon descriptions. Traits vary in scope from physiological measures of performance (e.g. photosynthetic gas exchange, water-use efficiency) to morphological attributes (e.g. leaf area, seed mass, plant height) which link to aspects of ecological variation. AusTraits contains curated and harmonised individual- and species-level measurements coupled to, where available, contextual information on site properties and experimental conditions. This article provides information on version 3.0.2 of AusTraits which contains data for 997,808 trait-by-taxon combinations. We envision AusTraits as an ongoing collaborative initiative for easily archiving and sharing trait data, which also provides a template for other national or regional initiatives globally to fill persistent gaps in trait knowledge.
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| 8. |
- Keck, Michaela Kristina, et al.
(författare)
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Amplification of the PLAG-family genes—PLAGL1 and PLAGL2—is a key feature of the novel tumor type CNS embryonal tumor with PLAGL amplification
- 2023
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Ingår i: Acta Neuropathologica. - : Springer Science and Business Media LLC. - 0001-6322 .- 1432-0533. ; 145:1, s. 49-69
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Tidskriftsartikel (refereegranskat)abstract
- Pediatric central nervous system (CNS) tumors represent the most common cause of cancer-related death in children aged 0–14 years. They differ from their adult counterparts, showing extensive clinical and molecular heterogeneity as well as a challenging histopathological spectrum that often impairs accurate diagnosis. Here, we use DNA methylation-based CNS tumor classification in combination with copy number, RNA-seq, and ChIP-seq analysis to characterize a newly identified CNS tumor type. In addition, we report histology, patient characteristics, and survival data in this tumor type. We describe a biologically distinct pediatric CNS tumor type (n = 31 cases) that is characterized by focal high-level amplification and resultant overexpression of either PLAGL1 or PLAGL2, and an absence of recurrent genetic alterations characteristic of other pediatric CNS tumor types. Both genes act as transcription factors for a regulatory subset of imprinted genes (IGs), components of the Wnt/β-Catenin pathway, and the potential drug targets RET and CYP2W1, which are also specifically overexpressed in this tumor type. A derived PLAGL-specific gene expression signature indicates dysregulation of imprinting control and differentiation/development. These tumors occurred throughout the neuroaxis including the cerebral hemispheres, cerebellum, and brainstem, and were predominantly composed of primitive embryonal-like cells lacking robust expression of markers of glial or neuronal differentiation (e.g., GFAP, OLIG2, and synaptophysin). Tumors with PLAGL1 amplification were typically diagnosed during adolescence (median age 10.5 years), whereas those with PLAGL2 amplification were diagnosed during early childhood (median age 2 years). The 10-year overall survival was 66% for PLAGL1-amplified tumors, 25% for PLAGL2-amplified tumors, 18% for male patients, and 82% for female patients. In summary, we describe a new type of biologically distinct CNS tumor characterized by PLAGL1/2 amplification that occurs predominantly in infants and toddlers (PLAGL2) or adolescents (PLAGL1) which we consider best classified as a CNS embryonal tumor and which is associated with intermediate survival. The cell of origin and optimal treatment strategies remain to be defined.
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| 9. |
- Muscarella, Robert, et al.
(författare)
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The global abundance of tree palms
- 2020
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Ingår i: Global Ecology and Biogeography. - : Wiley. - 1466-822X .- 1466-8238. ; 29:9, s. 1495-1514
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Tidskriftsartikel (refereegranskat)abstract
- AimPalms are an iconic, diverse and often abundant component of tropical ecosystems that provide many ecosystem services. Being monocots, tree palms are evolutionarily, morphologically and physiologically distinct from other trees, and these differences have important consequences for ecosystem services (e.g., carbon sequestration and storage) and in terms of responses to climate change. We quantified global patterns of tree palm relative abundance to help improve understanding of tropical forests and reduce uncertainty about these ecosystems under climate change.LocationTropical and subtropical moist forests.Time periodCurrent.Major taxa studiedPalms (Arecaceae).MethodsWe assembled a pantropical dataset of 2,548 forest plots (covering 1,191 ha) and quantified tree palm (i.e., ≥10 cm diameter at breast height) abundance relative to co‐occurring non‐palm trees. We compared the relative abundance of tree palms across biogeographical realms and tested for associations with palaeoclimate stability, current climate, edaphic conditions and metrics of forest structure.ResultsOn average, the relative abundance of tree palms was more than five times larger between Neotropical locations and other biogeographical realms. Tree palms were absent in most locations outside the Neotropics but present in >80% of Neotropical locations. The relative abundance of tree palms was more strongly associated with local conditions (e.g., higher mean annual precipitation, lower soil fertility, shallower water table and lower plot mean wood density) than metrics of long‐term climate stability. Life‐form diversity also influenced the patterns; palm assemblages outside the Neotropics comprise many non‐tree (e.g., climbing) palms. Finally, we show that tree palms can influence estimates of above‐ground biomass, but the magnitude and direction of the effect require additional work.ConclusionsTree palms are not only quintessentially tropical, but they are also overwhelmingly Neotropical. Future work to understand the contributions of tree palms to biomass estimates and carbon cycling will be particularly crucial in Neotropical forests.
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| 10. |
- Duncanson, Laura, et al.
(författare)
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Aboveground biomass density models for NASA's Global Ecosystem Dynamics Investigation (GEDI) lidar mission
- 2022
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Ingår i: Remote Sensing of Environment. - : Elsevier BV. - 0034-4257 .- 1879-0704. ; 270
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Tidskriftsartikel (refereegranskat)abstract
- NASA's Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI's footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI's waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available.
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