| 1. |
- Horie, Masayuki, et al.
(author)
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Endogenous non-retroviral RNA virus elements in mammalian genomes.
- 2010
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 463:7277, s. 84-87
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Journal article (peer-reviewed)abstract
- Retroviruses are the only group of viruses known to have left a fossil record, in the form of endogenous proviruses, and approximately 8% of the human genome is made up of these elements. Although many other viruses, including non-retroviral RNA viruses, are known to generate DNA forms of their own genomes during replication, none has been found as DNA in the germline of animals. Bornaviruses, a genus of non-segmented, negative-sense RNA virus, are unique among RNA viruses in that they establish persistent infection in the cell nucleus. Here we show that elements homologous to the nucleoprotein (N) gene of bornavirus exist in the genomes of several mammalian species, including humans, non-human primates, rodents and elephants. These sequences have been designated endogenous Borna-like N (EBLN) elements. Some of the primate EBLNs contain an intact open reading frame (ORF) and are expressed as mRNA. Phylogenetic analyses showed that EBLNs seem to have been generated by different insertional events in each specific animal family. Furthermore, the EBLN of a ground squirrel was formed by a recent integration event, whereas those in primates must have been formed more than 40 million years ago. We also show that the N mRNA of a current mammalian bornavirus, Borna disease virus (BDV), can form EBLN-like elements in the genomes of persistently infected cultured cells. Our results provide the first evidence for endogenization of non-retroviral virus-derived elements in mammalian genomes and give novel insights not only into generation of endogenous elements, but also into a role of bornavirus as a source of genetic novelty in its host.
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| 2. |
- Ishigaki, Kazuyoshi, et al.
(author)
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Multi-ancestry genome-wide association analyses identify novel genetic mechanisms in rheumatoid arthritis
- 2022
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In: Nature Genetics. - : Springer Nature. - 1061-4036 .- 1546-1718. ; 54:11, s. 1640-1651
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Journal article (peer-reviewed)abstract
- Rheumatoid arthritis (RA) is a highly heritable complex disease with unknown etiology. Multi-ancestry genetic research of RA promises to improve power to detect genetic signals, fine-mapping resolution and performances of polygenic risk scores (PRS). Here, we present a large-scale genome-wide association study (GWAS) of RA, which includes 276,020 samples from five ancestral groups. We conducted a multi-ancestry meta-analysis and identified 124 loci (P < 5 × 10−8), of which 34 are novel. Candidate genes at the novel loci suggest essential roles of the immune system (for example, TNIP2 and TNFRSF11A) and joint tissues (for example, WISP1) in RA etiology. Multi-ancestry fine-mapping identified putatively causal variants with biological insights (for example, LEF1). Moreover, PRS based on multi-ancestry GWAS outperformed PRS based on single-ancestry GWAS and had comparable performance between populations of European and East Asian ancestries. Our study provides several insights into the etiology of RA and improves the genetic predictability of RA.
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| 3. |
- Rutter, Nick, et al.
(author)
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Evaluation of forest snow processes models (SnowMIP2)
- 2009
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In: Journal of Geophysical Research. - : American Geophysical Union (AGU). - 0148-0227 .- 2156-2202. ; 114:6
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Journal article (peer-reviewed)abstract
- Thirty-three snowpack models of varying complexity and purpose were evaluated across a wide range of hydrometeorological and forest canopy conditions at five Northern Hemisphere locations, for up to two winter snow seasons. Modeled estimates of snow water equivalent (SWE) or depth were compared to observations at forest and open sites at each location. Precipitation phase and duration of above-freezing air temperatures are shown to be major influences on divergence and convergence of modeled estimates of the subcanopy snowpack. When models are considered collectively at all locations, comparisons with observations show that it is harder to model SWE at forested sites than open sites. There is no universal "best'' model for all sites or locations, but comparison of the consistency of individual model performances relative to one another at different sites shows that there is less consistency at forest sites than open sites, and even less consistency between forest and open sites in the same year. A good performance by a model at a forest site is therefore unlikely to mean a good model performance by the same model at an open site (and vice versa). Calibration of models at forest sites provides lower errors than uncalibrated models at three out of four locations. However, benefits of calibration do not translate to subsequent years, and benefits gained by models calibrated for forest snow processes are not translated to open conditions.
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