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      Evolution and function of CAG/polyglutamine repeats in protein–protein interaction networks

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        1 , 2 ,   1 , *
      Nucleic Acids Research
      Oxford University Press

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          Abstract

          Expanded runs of consecutive trinucleotide CAG repeats encoding polyglutamine (polyQ) stretches are observed in the genes of a large number of patients with different genetic diseases such as Huntington's and several Ataxias. Protein aggregation, which is a key feature of most of these diseases, is thought to be triggered by these expanded polyQ sequences in disease-related proteins. However, polyQ tracts are a normal feature of many human proteins, suggesting that they have an important cellular function. To clarify the potential function of polyQ repeats in biological systems, we systematically analyzed available information stored in sequence and protein interaction databases. By integrating genomic, phylogenetic, protein interaction network and functional information, we obtained evidence that polyQ tracts in proteins stabilize protein interactions. This happens most likely through structural changes whereby the polyQ sequence extends a neighboring coiled-coil region to facilitate its interaction with a coiled-coil region in another protein. Alteration of this important biological function due to polyQ expansion results in gain of abnormal interactions, leading to pathological effects like protein aggregation. Our analyses suggest that research on polyQ proteins should shift focus from expanded polyQ proteins into the characterization of the influence of the wild-type polyQ on protein interactions.

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          Most cited references56

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          The genome of the social amoeba Dictyostelium discoideum.

          The social amoebae are exceptional in their ability to alternate between unicellular and multicellular forms. Here we describe the genome of the best-studied member of this group, Dictyostelium discoideum. The gene-dense chromosomes of this organism encode approximately 12,500 predicted proteins, a high proportion of which have long, repetitive amino acid tracts. There are many genes for polyketide synthases and ABC transporters, suggesting an extensive secondary metabolism for producing and exporting small molecules. The genome is rich in complex repeats, one class of which is clustered and may serve as centromeres. Partial copies of the extrachromosomal ribosomal DNA (rDNA) element are found at the ends of each chromosome, suggesting a novel telomere structure and the use of a common mechanism to maintain both the rDNA and chromosomal termini. A proteome-based phylogeny shows that the amoebozoa diverged from the animal-fungal lineage after the plant-animal split, but Dictyostelium seems to have retained more of the diversity of the ancestral genome than have plants, animals or fungi.
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            GtRNAdb: a database of transfer RNA genes detected in genomic sequence

            Transfer RNAs (tRNAs) represent the single largest, best-understood class of non-protein coding RNA genes found in all living organisms. By far, the major source of new tRNAs is computational identification of genes within newly sequenced genomes. To organize the rapidly growing collection and enable systematic analyses, we created the Genomic tRNA Database (GtRNAdb), currently including over 74 000 tRNA genes predicted from 740 species. The web resource provides overview statistics of tRNA genes within each analyzed genome, including information by isotype and genetic locus, easily downloadable primary sequences, graphical secondary structures and multiple sequence alignments. Direct links for each gene to UCSC eukaryotic and microbial genome browsers provide graphical display of tRNA genes in the context of all other local genetic information. The database can be searched by primary sequence similarity, tRNA characteristics or phylogenetic group. The database is publicly available at http://gtrnadb.ucsc.edu.
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              The BioGRID Interaction Database: 2011 update

              The Biological General Repository for Interaction Datasets (BioGRID) is a public database that archives and disseminates genetic and protein interaction data from model organisms and humans (http://www.thebiogrid.org). BioGRID currently holds 347 966 interactions (170 162 genetic, 177 804 protein) curated from both high-throughput data sets and individual focused studies, as derived from over 23 000 publications in the primary literature. Complete coverage of the entire literature is maintained for budding yeast (Saccharomyces cerevisiae), fission yeast (Schizosaccharomyces pombe) and thale cress (Arabidopsis thaliana), and efforts to expand curation across multiple metazoan species are underway. The BioGRID houses 48 831 human protein interactions that have been curated from 10 247 publications. Current curation drives are focused on particular areas of biology to enable insights into conserved networks and pathways that are relevant to human health. The BioGRID 3.0 web interface contains new search and display features that enable rapid queries across multiple data types and sources. An automated Interaction Management System (IMS) is used to prioritize, coordinate and track curation across international sites and projects. BioGRID provides interaction data to several model organism databases, resources such as Entrez-Gene and other interaction meta-databases. The entire BioGRID 3.0 data collection may be downloaded in multiple file formats, including PSI MI XML. Source code for BioGRID 3.0 is freely available without any restrictions.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                May 2012
                May 2012
                28 January 2012
                28 January 2012
                : 40
                : 10
                : 4273-4287
                Affiliations
                1Computational Biology and Data Mining and 2Neuroproteomics, Max Delbrück Center for Molecular Medicine, Robert-Rössle-Strasse 10, 13125 Berlin, Germany
                Author notes
                *To whom correspondence should be addressed. Tel: +49 30 9406 4250; Fax: +49 30 9406 4240; Email: miguel.andrade@ 123456mdc-berlin.de
                Article
                gks011
                10.1093/nar/gks011
                3378862
                22287626
                566e01f3-1cd7-4686-a888-231c7479df15
                © The Author(s) 2012. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 31 October 2011
                : 15 December 2011
                : 23 December 2011
                Page count
                Pages: 15
                Categories
                Computational Biology

                Genetics
                Genetics

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