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      The novel endosomal membrane protein Ema interacts with the class C Vps–HOPS complex to promote endosomal maturation

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          Abstract

          Defective attenuation of BMP signaling causes synapses to overgrow in Drosophila Ema mutants due to impaired endosomal maturation.

          Abstract

          Endosomal maturation is critical for accurate and efficient cargo transport through endosomal compartments. Here we identify a mutation of the novel Drosophila gene, ema (endosomal maturation defective) in a screen for abnormal synaptic overgrowth and defective protein trafficking. Ema is an endosomal membrane protein required for trafficking of fluid-phase and receptor-mediated endocytic cargos. In the ema mutant, enlarged endosomal compartments accumulate as endosomal maturation fails, with early and late endosomes unable to progress into mature degradative late endosomes and lysosomes. Defective endosomal down-regulation of BMP signaling is responsible for the abnormal synaptic overgrowth. Ema binds to and genetically interacts with Vps16A, a component of the class C Vps–HOPS complex that promotes endosomal maturation. The human orthologue of ema, Clec16A, is a candidate susceptibility locus for autoimmune disorders, and its expression rescues the Drosophila mutant demonstrating conserved function. Characterizing this novel gene family identifies a new component of the endosomal pathway and provides insights into class C Vps–HOPS complex function.

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          Most cited references 48

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          Robust associations of four new chromosome regions from genome-wide analyses of type 1 diabetes.

          The Wellcome Trust Case Control Consortium (WTCCC) primary genome-wide association (GWA) scan on seven diseases, including the multifactorial autoimmune disease type 1 diabetes (T1D), shows associations at P < 5 x 10(-7) between T1D and six chromosome regions: 12q24, 12q13, 16p13, 18p11, 12p13 and 4q27. Here, we attempted to validate these and six other top findings in 4,000 individuals with T1D, 5,000 controls and 2,997 family trios independent of the WTCCC study. We confirmed unequivocally the associations of 12q24, 12q13, 16p13 and 18p11 (P(follow-up)
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            Risk alleles for multiple sclerosis identified by a genomewide study.

            Multiple sclerosis has a clinically significant heritable component. We conducted a genomewide association study to identify alleles associated with the risk of multiple sclerosis. We used DNA microarray technology to identify common DNA sequence variants in 931 family trios (consisting of an affected child and both parents) and tested them for association. For replication, we genotyped another 609 family trios, 2322 case subjects, and 789 control subjects and used genotyping data from two external control data sets. A joint analysis of data from 12,360 subjects was performed to estimate the overall significance and effect size of associations between alleles and the risk of multiple sclerosis. A transmission disequilibrium test of 334,923 single-nucleotide polymorphisms (SNPs) in 931 family trios revealed 49 SNPs having an association with multiple sclerosis (P<1x10(-4)); of these SNPs, 38 were selected for the second-stage analysis. A comparison between the 931 case subjects from the family trios and 2431 control subjects identified an additional nonoverlapping 32 SNPs (P<0.001). An additional 40 SNPs with less stringent P values (<0.01) were also selected, for a total of 110 SNPs for the second-stage analysis. Of these SNPs, two within the interleukin-2 receptor alpha gene (IL2RA) were strongly associated with multiple sclerosis (P=2.96x10(-8)), as were a nonsynonymous SNP in the interleukin-7 receptor alpha gene (IL7RA) (P=2.94x10(-7)) and multiple SNPs in the HLA-DRA locus (P=8.94x10(-81)). Alleles of IL2RA and IL7RA and those in the HLA locus are identified as heritable risk factors for multiple sclerosis. Copyright 2007 Massachusetts Medical Society.
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              CDD: specific functional annotation with the Conserved Domain Database

              NCBI's Conserved Domain Database (CDD) is a collection of multiple sequence alignments and derived database search models, which represent protein domains conserved in molecular evolution. The collection can be accessed at http://www.ncbi.nlm.nih.gov/Structure/cdd/cdd.shtml, and is also part of NCBI's Entrez query and retrieval system, cross-linked to numerous other resources. CDD provides annotation of domain footprints and conserved functional sites on protein sequences. Precalculated domain annotation can be retrieved for protein sequences tracked in NCBI's Entrez system, and CDD's collection of models can be queried with novel protein sequences via the CD-Search service at http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi. Starting with the latest version of CDD, v2.14, information from redundant and homologous domain models is summarized at a superfamily level, and domain annotation on proteins is flagged as either ‘specific’ (identifying molecular function with high confidence) or as ‘non-specific’ (identifying superfamily membership only).
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                Author and article information

                Journal
                J Cell Biol
                J. Cell Biol
                jcb
                The Journal of Cell Biology
                The Rockefeller University Press
                0021-9525
                1540-8140
                8 March 2010
                : 188
                : 5
                : 717-734
                Affiliations
                Department of Developmental Biology, Washington University in St. Louis, St. Louis, MO 63110
                Author notes
                Correspondence to Aaron DiAntonio: diantonio@ 123456wustl.edu

                S. Kim and Y.P. Wairkar contributed equally to this paper.

                R.W. Daniels’ present address is Department of Genetics, University of Wisconsin, Madison, WI 53706.

                Article
                200911126
                10.1083/jcb.200911126
                2835942
                20194640
                © 2010 Kim et al.

                This article is distributed under the terms of an Attribution–Noncommercial–Share Alike–No Mirror Sites license for the first six months after the publication date (see http://www.rupress.org/terms). After six months it is available under a Creative Commons License (Attribution–Noncommercial–Share Alike 3.0 Unported license, as described at http://creativecommons.org/licenses/by-nc-sa/3.0/).

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