74 research outputs found
Oligomerization of ZFYVE27 (Protrudin) Is Necessary to Promote Neurite Extension
ZFYVE27 (Protrudin) was originally identified as an interacting partner of spastin, which is most frequently mutated in hereditary spastic paraplegia. ZFYVE27 is a novel member of FYVE family, which is implicated in the formation of neurite extensions by promoting directional membrane trafficking in neurons. Now, through a yeast two-hybrid screen, we have identified that ZFYVE27 interacts with itself and the core interaction region resides within the third hydrophobic region (HR3) of the protein. We confirmed the ZFYVE27's self-interaction in the mammalian cells by co-immunoprecipitation and co-localization studies. To decipher the oligomeric nature of ZFYVE27, we performed sucrose gradient centrifugation and showed that ZFYVE27 oligomerizes into dimer/tetramer forms. Sub-cellular fractionation and Triton X-114 membrane phase separation analysis indicated that ZFYVE27 is a peripheral membrane protein. Furthermore, ZFYVE27 also binds to phosphatidylinositol 3-phosphate lipid moiety. Interestingly, cells expressing ZFYVE27ΔHR3 failed to produce protrusions instead caused swelling of cell soma. When ZFYVE27ΔHR3 was co-expressed with wild-type ZFYVE27 (ZFYVE27WT), it exerted a dominant negative effect on ZFYVE27WT as the cells co-expressing both proteins were also unable to induce protrusions and showed cytoplasmic swelling. Altogether, it is evident that a functionally active form of oligomer is crucial for ZFYVE27 ability to promote neurite extensions
Glueballs, Hybrids, Multiquarks. Experimental facts versus QCD inspired concepts
The spectroscopy of light and heavy mesons is reviewed with emphasis on
glueballs, hybrids, and tetraquarks.Comment: 266 pages, 117 figures, 39 tables. to be published in Physics Report
Pseudorapidity distributions of charged hadrons in proton-lead collisions at root s(NN)=5:02 and 8.16 TeV
The pseudorapidity distributions of charged hadrons in proton-lead collisions at nucleon-nucleon center-of-mass energies root s(NN) = 5.02 and 8.16 TeV are presented. The measurements are based on data samples collected by the CMS experiment at the LHC. The number of primary charged hadrons produced in non-single-diffractive proton-lead collisions is determined in the pseudorapidity range vertical bar eta(lab)vertical bar vertical bar(vertical bar eta cm vertical bar) <0.5 are 17.1 +/- 0.01 (stat) +/- 0.59 (syst) and 20.10 +/- 0.01 (stat) +/- 0.5(syst) at root s(NN) = 5.02 and 8.16 TeV, respectively. The particle densities per participant nucleon are compared to similar measurements in proton-proton, proton-nucleus, and nucleus-nucleus collisions.Peer reviewe
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A second update on mapping the human genetic architecture of COVID-19
Matters Arising From: COVID-19 Host Genetics Initiative. Nature https://doi.org/10.1038/s41586-021-03767-x (2021)Data availability:
Summary statistics generated by the COVID-19 HGI are available online, including per-ancestry summary statistics for African, admixed American, East Asian, European and South Asian ancestries (https://www.covid19hg.org/results/r7/). The analyses described here used the data release 7. If available, individual-level data can be requested directly from contributing studies, listed in Supplementary Table 1. We used publicly available data from GTEx (https://gtexportal.org/home/), the Neale laboratory (http://www.nealelab.is/uk-biobank/), the Finucane laboratory (https://www.finucanelab.org), the FinnGen Freeze 4 cohort (https://www.finngen.fi/en/access_results) and the eQTL catalogue release 3 (http://www.ebi.ac.uk/eqtl/).Code availability:
The code for summary statistics lift-over, the projection PCA pipeline including precomputed loadings and meta-analyses (https://github.com/covid19-hg/); for heritability estimation (https://github.com/AndrewsLabUCSF/COVID19_heritability); for Mendelian randomization and genetic correlation (https://github.com/marcoralab/MRcovid); and subtype analyses (https://github.com/mjpirinen/covid19-hgi_subtypes) are available at GitHub.Reporting summary:
Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article online at: https://www.nature.com/articles/s41586-023-06355-3#MOESM2 .Supplementary information is available online at: https://www.nature.com/articles/s41586-023-06355-3#Sec4 .Copyright © The Author(s) 2023. Investigating the role of host genetic factors in COVID-19 severity and susceptibility can inform our understanding of the underlying biological mechanisms that influence adverse outcomes and drug development1,2. Here we present a second updated genome-wide association study (GWAS) on COVID-19 severity and infection susceptibility to SARS-CoV-2 from the COVID-19 Host Genetic Initiative (data release 7). We performed a meta-analysis of up to 219,692 cases and over 3 million controls, identifying 51 distinct genome-wide significant loci—adding 28 loci from the previous data release2. The increased number of candidate genes at the identified loci helped to map three major biological pathways that are involved in susceptibility and severity: viral entry, airway defence in mucus and type I interferon
Mining the human phenome using allelic scores that index biological intermediates
J. Kaprio ja M-L. Lokki työryhmien jäseniä.It is common practice in genome-wide association studies (GWAS) to focus on the relationship between disease risk and genetic variants one marker at a time. When relevant genes are identified it is often possible to implicate biological intermediates and pathways likely to be involved in disease aetiology. However, single genetic variants typically explain small amounts of disease risk. Our idea is to construct allelic scores that explain greater proportions of the variance in biological intermediates, and subsequently use these scores to data mine GWAS. To investigate the approach's properties, we indexed three biological intermediates where the results of large GWAS meta-analyses were available: body mass index, C-reactive protein and low density lipoprotein levels. We generated allelic scores in the Avon Longitudinal Study of Parents and Children, and in publicly available data from the first Wellcome Trust Case Control Consortium. We compared the explanatory ability of allelic scores in terms of their capacity to proxy for the intermediate of interest, and the extent to which they associated with disease. We found that allelic scores derived from known variants and allelic scores derived from hundreds of thousands of genetic markers explained significant portions of the variance in biological intermediates of interest, and many of these scores showed expected correlations with disease. Genome-wide allelic scores however tended to lack specificity suggesting that they should be used with caution and perhaps only to proxy biological intermediates for which there are no known individual variants. Power calculations confirm the feasibility of extending our strategy to the analysis of tens of thousands of molecular phenotypes in large genome-wide meta-analyses. We conclude that our method represents a simple way in which potentially tens of thousands of molecular phenotypes could be screened for causal relationships with disease without having to expensively measure these variables in individual disease collections.Peer reviewe
Novel Approach Identifies SNPs in SLC2A10 and KCNK9 with Evidence for Parent-of-Origin Effect on Body Mass Index
Marja-Liisa Lokki työryhmien Generation Scotland Consortium, LifeLines Cohort Study ja GIANT Consortium jäsenPeer reviewe
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