| 1. |
- Kim, Kwangwoo, et al.
(författare)
-
High-density genotyping of immune loci in Koreans and Europeans identifies eight new rheumatoid arthritis risk loci
- 2015
-
Ingår i: Annals of the Rheumatic Diseases. - : BMJ. - 0003-4967 .- 1468-2060. ; 74:3
-
Tidskriftsartikel (refereegranskat)abstract
- Objective A highly polygenic aetiology and high degree of allele-sharing between ancestries have been well elucidated in genetic studies of rheumatoid arthritis. Recently, the high-density genotyping array Immunochip for immune disease loci identified 14 new rheumatoid arthritis risk loci among individuals of European ancestry. Here, we aimed to identify new rheumatoid arthritis risk loci using Korean-specific Immunochip data. Methods We analysed Korean rheumatoid arthritis case-control samples using the Immunochip and genome-wide association studies (GWAS) array to search for new risk alleles of rheumatoid arthritis with anticitrullinated peptide antibodies. To increase power, we performed a meta-analysis of Korean data with previously published European Immunochip and GWAS data for a total sample size of 9299 Korean and 45 790 European case-control samples. Results We identified eight new rheumatoid arthritis susceptibility loci (TNFSF4, LBH, EOMES, ETS1-FLI1, COG6, RAD51B, UBASH3A and SYNGR1) that passed a genome-wide significance threshold (p<5x10(-8)), with evidence for three independent risk alleles at 1q25/TNFSF4. The risk alleles from the seven new loci except for the TNFSF4 locus (monomorphic in Koreans), together with risk alleles from previously established RA risk loci, exhibited a high correlation of effect sizes between ancestries. Further, we refined the number of single nucleotide polymorphisms (SNPs) that represent potentially causal variants through a trans-ethnic comparison of densely genotyped SNPs. Conclusions This study demonstrates the advantage of dense-mapping and trans-ancestral analysis for identification of potentially causal SNPs. In addition, our findings support the importance of T cells in the pathogenesis and the fact of frequent overlap of risk loci among diverse autoimmune diseases.
|
|
| 2. |
- Lee, Hunsang, et al.
(författare)
-
Glycosylatable GFP as a compartment-specific membrane topology reporter
- 2012
-
Ingår i: Biochemical and Biophysical Research Communications - BBRC. - : Elsevier BV. - 0006-291X .- 1090-2104. ; 427:4, s. 780-784
-
Tidskriftsartikel (refereegranskat)abstract
- Determination of the membrane topology is an essential step in structural and functional studies of integral membrane proteins, yet the choices of membrane topology reporters are limited and the experimental analysis can be laborious, especially in eukaryotic cells. Here, we present a robust membrane topology reporter, glycosylatable green fluorescent protein (gGFP). gGFP is fully fluorescent in the yeast cytosol but becomes glycosylated and does not fluoresce in the lumen of the endoplasmic reticulum (ER). Thus, by assaying fluorescence and the glycosylation status of C-terminal fusions of gGFP to target membrane proteins in whole-cell lysates, the localization of the gGFP moiety (and hence the fusion joint) relative to the ER membrane can be unambiguously determined.
|
|
| 3. |
- Qin, Yue, et al.
(författare)
-
A multi-scale map of cell structure fusing protein images and interactions
- 2021
-
Ingår i: Nature. - : Springer Nature. - 0028-0836 .- 1476-4687. ; 600:7889, s. 536-
-
Tidskriftsartikel (refereegranskat)abstract
- The cell is a multi-scale structure with modular organization across at least four orders of magnitude(1). Two central approaches for mapping this structure-protein fluorescent imaging and protein biophysical association-each generate extensive datasets, but of distinct qualities and resolutions that are typically treated separately(2,3). Here we integrate immunofluorescence images in the Human Protein Atlas(4) with affinity purifications in BioPlex(5) to create a unified hierarchical map of human cell architecture. Integration is achieved by configuring each approach as a general measure of protein distance, then calibrating the two measures using machine learning. The map, known as the multi-scale integrated cell (MuSIC 1.0), resolves 69 subcellular systems, of which approximately half are to our knowledge undocumented. Accordingly, we perform 134 additional affinity purifications and validate subunit associations for the majority of systems. The map reveals a pre-ribosomal RNA processing assembly and accessory factors, which we show govern rRNA maturation, and functional roles for SRRM1 and FAM120C in chromatin and RPS3A in splicing. By integration across scales, MuSIC increases the resolution of imaging while giving protein interactions a spatial dimension, paving the way to incorporate diverse types of data in proteome-wide cell maps.
|
|
