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- Glasbey, JC, et al.
(author)
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- 2021
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swepub:Mat__t
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- Dornelas, M., et al.
(author)
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BioTIME: A database of biodiversity time series for the Anthropocene
- 2018
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In: Global Ecology and Biogeography. - : Wiley. - 1466-822X .- 1466-8238. ; 27:7, s. 760-786
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Journal article (peer-reviewed)abstract
- Motivation: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene. Main types of variables included: The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record. Spatial location and grain: BioTIME is a global database of 547,161 unique sampling locations spanning the marine, freshwater and terrestrial realms. Grain size varies across datasets from 0.0000000158 km(2) (158 cm(2)) to 100 km(2) (1,000,000,000,000 cm(2)). Time period and grainBio: TIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year. Major taxa and level of measurement: BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates.
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- van der Plas, F., et al.
(author)
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Continental mapping of forest ecosystem functions reveals a high but unrealised potential for forest multifunctionality
- 2018
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In: Ecology Letters. - : Wiley. - 1461-023X .- 1461-0248. ; 21:1, s. 31-42
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Journal article (peer-reviewed)abstract
- Humans require multiple services from ecosystems, but it is largely unknown whether trade-offs between ecosystem functions prevent the realisation of high ecosystem multifunctionality across spatial scales. Here, we combined a comprehensive dataset (28 ecosystem functions measured on 209 forest plots) with a forest inventory dataset (105,316 plots) to extrapolate and map relationships between various ecosystem multifunctionality measures across Europe. These multifunctionality measures reflected different management objectives, related to timber production, climate regulation and biodiversity conservation/recreation. We found that trade-offs among them were rare across Europe, at both local and continental scales. This suggests a high potential for win-win' forest management strategies, where overall multifunctionality is maximised. However, across sites, multifunctionality was on average 45.8-49.8% below maximum levels and not necessarily highest in protected areas. Therefore, using one of the most comprehensive assessments so far, our study suggests a high but largely unrealised potential for management to promote multifunctional forests.
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- Ramilowski, JA, et al.
(author)
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Functional annotation of human long noncoding RNAs via molecular phenotyping
- 2020
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In: Genome research. - : Cold Spring Harbor Laboratory. - 1549-5469 .- 1088-9051. ; 30:7, s. 1060-1072
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Journal article (peer-reviewed)abstract
- Long noncoding RNAs (lncRNAs) constitute the majority of transcripts in the mammalian genomes, and yet, their functions remain largely unknown. As part of the FANTOM6 project, we systematically knocked down the expression of 285 lncRNAs in human dermal fibroblasts and quantified cellular growth, morphological changes, and transcriptomic responses using Capped Analysis of Gene Expression (CAGE). Antisense oligonucleotides targeting the same lncRNAs exhibited global concordance, and the molecular phenotype, measured by CAGE, recapitulated the observed cellular phenotypes while providing additional insights on the affected genes and pathways. Here, we disseminate the largest-to-date lncRNA knockdown data set with molecular phenotyping (over 1000 CAGE deep-sequencing libraries) for further exploration and highlight functional roles for ZNF213-AS1 and lnc-KHDC3L-2.
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- Zheng, Hou-Feng, et al.
(author)
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Whole-genome sequencing identifies EN1 as a determinant of bone density and fracture
- 2015
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 526:7571, s. 112-
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Journal article (peer-reviewed)abstract
- The extent to which low-frequency (minor allele frequency (MAF) between 1-5%) and rare (MAF <= 1%) variants contribute to complex traits and disease in the general population is mainly unknown. Bone mineral density (BMD) is highly heritable, a major predictor of osteoporotic fractures, and has been previously associated with common genetic variants(1-8), as well as rare, population specific, coding variants(9). Here we identify novel non-coding genetic variants with large effects on BMD (n(total) = 53,236) and fracture (n(total) = 508,253) in individuals of European ancestry from the general population. Associations for BMD were derived from whole-genome sequencing (n = 2,882 from UK10K (ref. 10); a population-based genome sequencing consortium), whole-exome sequencing (n = 3,549), deep imputation of genotyped samples using a combined UK10K/1000 Genomes reference panel (n = 26,534), and de novo replication genotyping (n = 20,271). We identified a low-frequency non-coding variant near a novel locus, EN1, with an effect size fourfold larger than the mean of previously reported common variants for lumbar spine BMD8 (rs11692564(T), MAF51.6%, replication effect size510.20 s.d., P-meta = 2 x 10(-14)), which was also associated with a decreased risk of fracture (odds ratio = 0.85; P = 2 x 10(-11); ncases = 98,742 and ncontrols = 409,511). Using an En1cre/flox mouse model, we observed that conditional loss of En1 results in low bone mass, probably as a consequence of high bone turnover. We also identified a novel low frequency non-coding variant with large effects on BMD near WNT16 (rs148771817(T), MAF = 1.2%, replication effect size +10.41 s.d., P-meta = 1 x 10(-11)). In general, there was an excess of association signals arising from deleterious coding and conserved non-coding variants. These findings provide evidence that low-frequency non-coding variants have large effects on BMD and fracture, thereby providing rationale for whole-genome sequencing and improved imputation reference panels to study the genetic architecture of complex traits and disease in the general population.
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