| 1. |
- Campbell, PJ, et al.
(author)
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Pan-cancer analysis of whole genomes
- 2020
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In: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 578:7793, s. 82-
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Journal article (peer-reviewed)abstract
- Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1–3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4–5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10–18.
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| 2. |
- Mahajan, Anubha, et al.
(author)
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Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation
- 2022
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In: Nature Genetics. - : Springer Nature. - 1061-4036 .- 1546-1718. ; 54:5, s. 560-572
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Journal article (peer-reviewed)abstract
- We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 x 10(-9)), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background. Genome-wide association and fine-mapping analyses in ancestrally diverse populations implicate candidate causal genes and mechanisms underlying type 2 diabetes. Trans-ancestry genetic risk scores enhance transferability across populations.
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| 3. |
- Petrescu, Ana Maria Roxana, et al.
(author)
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The uncertain climate footprint of wetlands under human pressure
- 2015
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In: Proceedings of the National Academy of Sciences. - : Proceedings of the National Academy of Sciences. - 1091-6490 .- 0027-8424. ; 112:15, s. 4594-4599
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Journal article (peer-reviewed)abstract
- Significant climate risks are associated with a positive carbon-temperature feedback in northern latitude carbon-rich ecosystems, making an accurate analysis of human impacts on the net greenhouse gas balance of wetlands a priority. Here, we provide a coherent assessment of the climate footprint of a network of wetland sites based on simultaneous and quasi-continuous ecosystem observations of CO2 and CH4 fluxes. Experimental areas are located both in natural and in managed wetlands and cover a wide range of climatic regions, ecosystem types, and management practices. Based on direct observations we predict that sustained CH4 emissions in natural ecosystems are in the long term (i.e., several centuries) typically offset by CO2 uptake, although with large spatiotemporal variability. Using a space-for-time analogy across ecological and climatic gradients, we represent the chronosequence from natural to managed conditions to quantify the "cost" of CH4 emissions for the benefit of net carbon sequestration. With a sustained pulse-response radiative forcing model, we found a significant increase in atmospheric forcing due to land management, in particular for wetland converted to cropland. Our results quantify the role of human activities on the climate footprint of northern wetlands and call for development of active mitigation strategies for managed wetlands and new guidelines of the Intergovernmental Panel on Climate Change (IPCC) accounting for both sustained CH4 emissions and cumulative CO2 exchange.
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| 4. |
- Yi, Chuixiang, et al.
(author)
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Climate control of terrestrial carbon exchange across biomes and continents
- 2010
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In: Environmental Research Letters. - : IOP Publishing. - 1748-9326. ; 5:3
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Journal article (peer-reviewed)abstract
- Understanding the relationships between climate and carbon exchange by terrestrial ecosystems is critical to predict future levels of atmospheric carbon dioxide because of the potential accelerating effects of positive climate-carbon cycle feedbacks. However, directly observed relationships between climate and terrestrial CO2 exchange with the atmosphere across biomes and continents are lacking. Here we present data describing the relationships between net ecosystem exchange of carbon (NEE) and climate factors as measured using the eddy covariance method at 125 unique sites in various ecosystems over six continents with a total of 559 site-years. We find that NEE observed at eddy covariance sites is (1) a strong function of mean annual temperature at mid-and high-latitudes, (2) a strong function of dryness at mid-and low-latitudes, and (3) a function of both temperature and dryness around the mid-latitudinal belt (45 degrees N). The sensitivity of NEE to mean annual temperature breaks down at similar to 16 degrees C (a threshold value of mean annual temperature), above which no further increase of CO2 uptake with temperature was observed and dryness influence overrules temperature influence.
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| 5. |
- Kross, Angela S. E., et al.
(author)
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Phenology and its role in carbon dioxide exchange processes in northern peatlands
- 2014
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In: Journal of Geophysical Research - Biogeosciences. - 2169-8953. ; 119:7, s. 1370-1384
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Journal article (peer-reviewed)abstract
- Ecosystem phenology plays an important role in carbon exchange processes and can be derived from continuous records of carbon dioxide (CO2) exchange data. In this study we examined the potential use of phenological indices for characterizing cumulative annual CO2 exchange in four contrasting northern peatland ecosystems. We used the approach of Jonsson and Eklundh (2004) to derive a set of phenological indices based on the daily time series of gross primary production (GPP), ecosystem respiration (R-e), and net ecosystem production (NEP) measured in the four peatland sites. The main objectives of this study were (a) to examine the variation in phenological indices across sites and (b) to determine the relationships among phenological indices, environmental conditions, and cumulative annual CO2 exchange. The phenological index used to define the "start of the growing season" showed good potential for differentiation among sites based on their average annual site GPP. Sites with earlier growing seasons had the highest average annual site GPP. The "peak CO2 exchange rate" phenological index performed best in reflecting variations among sites and for estimating annual values of GPP, R-e, and NEP (Pearson correlation coefficients ranged between 0.77 and 0.99, p<0.05 for all.). The phenological indices and annual GPP, R-e, and NEP were sensitive to winter (January-March) and summer (July-September) temperature and precipitation, but correlations, though significant, were weak.
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| 6. |
- Lund, Magnus, et al.
(author)
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Variability in exchange of CO2 across 12 northern peatland and tundra sites
- 2010
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In: Global Change Biology. - : Wiley. - 1354-1013 .- 1365-2486. ; 16:9, s. 2436-2448
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Journal article (peer-reviewed)abstract
- Many wetland ecosystems such as peatlands and wet tundra hold large amounts of organic carbon (C) in their soils, and are thus important in the terrestrial C cycle. We have synthesized data on the carbon dioxide (CO2) exchange obtained from eddy covariance measurements from 12 wetland sites, covering 1-7 years at each site, across Europe and North America, ranging from ombrotrophic and minerotrophic peatlands to wet tundra ecosystems, spanning temperate to arctic climate zones. The average summertime net ecosystem exchange of CO2 (NEE) was highly variable between sites. However, all sites with complete annual datasets, seven in total, acted as annual net sinks for atmospheric CO2. To evaluate the influence of gross primary production (GPP) and ecosystem respiration (R-eco) on NEE, we first removed the artificial correlation emanating from the method of partitioning NEE into GPP and R-eco. After this correction neither R-eco (P = 0.162) nor GPP (P = 0.110) correlated significantly with NEE on an annual basis. Spatial variation in annual and summertime R-eco was associated with growing season period, air temperature, growing degree days, normalized difference vegetation index and vapour pressure deficit. GPP showed weaker correlations with environmental variables as compared with R-eco, the exception being leaf area index (LAI), which correlated with both GPP and NEE, but not with R-eco. Length of growing season period was found to be the most important variable describing the spatial variation in summertime GPP and R-eco; global warming will thus cause these components to increase. Annual GPP and NEE correlated significantly with LAI and pH, thus, in order to predict wetland C exchange, differences in ecosystem structure such as leaf area and biomass as well as nutritional status must be taken into account.
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| 7. |
- Qiu, Chunjing, et al.
(author)
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ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO2, water, and energy fluxes on daily to annual scales
- 2018
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In: Geoscientific Model Development. - : Copernicus GmbH. - 1991-959X .- 1991-9603. ; 11:2, s. 497-519
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Journal article (peer-reviewed)abstract
- Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO2 fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5° grid cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation within a grid cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model was evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation (Vcmax) being optimized at each site. Regarding short-term day-to-day variations, the model performance was good for gross primary production (GPP) (r2 Combining double low line 0.76; Nash-Sutcliffe modeling efficiency, MEF Combining double low line 0.76) and ecosystem respiration (ER, r2 Combining double low line 0.78, MEF Combining double low line 0.75), with lesser accuracy for latent heat fluxes (LE, r2 Combining double low line 0.42, MEF Combining double low line 0.14) and and net ecosystem CO2 exchange (NEE, r2 Combining double low line 0.38, MEF Combining double low line 0.26). Seasonal variations in GPP, ER, NEE, and energy fluxes on monthly scales showed moderate to high r2 values (0.57-0.86). For spatial across-site gradients of annual mean GPP, ER, NEE, and LE, r2 values of 0.93, 0.89, 0.27, and 0.71 were achieved, respectively. Water table (WT) variation was not well predicted (r2<0.1), likely due to the uncertain water input to the peat from surrounding areas. However, the poor performance of WT simulation did not greatly affect predictions of ER and NEE. We found a significant relationship between optimized Vcmax and latitude (temperature), which better reflects the spatial gradients of annual NEE than using an average Vcmax value.
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