title: Low-complexity regions within protein sequences have position-dependent roles.
abstract: BACKGROUND
  Regions of protein sequences with biased amino acid composition (so-called Low-Complexity Regions (LCRs)) are abundant in the protein universe. A number of studies have revealed that i) these regions show significant divergence across protein families; ii) the genetic mechanisms from which they arise lends them remarkable degrees of compositional plasticity. They have therefore proved difficult to compare using conventional sequence analysis techniques, and functions remain to be elucidated for most of them. Here we undertake a systematic investigation of LCRs in order to explore their possible functional significance, placed in the particular context of Protein-Protein Interaction (PPI) networks and Gene Ontology (GO)-term analysis.
  
  
  RESULTS
  In keeping with previous results, we found that LCR-containing proteins tend to have more binding partners across different PPI networks than proteins that have no LCRs. More specifically, our study suggests i) that LCRs are preferentially positioned towards the protein sequence extremities and, in contrast with centrally-located LCRs, such terminal LCRs show a correlation between their lengths and degrees of connectivity, and ii) that centrally-located LCRs are enriched with transcription-related GO terms, while terminal LCRs are enriched with translation and stress response-related terms.
  
  
  CONCLUSIONS
  Our results suggest not only that LCRs may be involved in flexible binding associated with specific functions, but also that their positions within a sequence may be important in determining both their binding properties and their biological roles.
authors.affiliation: Faculty of Life Sciences, University of Manchester, Manchester M13 9PL, UK. alain.coletta@vub.ac.be
authors.forename: Alain
authors.initials: A
authors.lastname: Coletta
authors.forename: John W
authors.initials: JW
authors.lastname: Pinney
authors.forename: David Y Weiss
authors.initials: DY
authors.lastname: Solís
authors.forename: James
authors.initials: J
authors.lastname: Marsh
authors.forename: Steve R
authors.initials: SR
authors.lastname: Pettifer
authors.forename: Teresa K
authors.initials: TK
authors.lastname: Attwood
mesh_terms: D000465:Algorithms; D000596:Amino Acids / Q000737:chemistry*; D019295:Computational Biology / Q000379:methods*; D005656:Fungal Proteins / Q000737:chemistry*; D015966:Gene Expression Regulation, Fungal; D008954:Models, Biological; D008957:Models, Genetic; D015233:Models, Statistical; D025941:Protein Interaction Mapping; D011506:Proteins / Q000737:chemistry*; D012441:Saccharomyces cerevisiae / Q000235:genetics / Q000378:metabolism; D016415:Sequence Alignment / Q000379:methods; D020539:Sequence Analysis, Protein / Q000379:methods
chemical_list: D000596:Amino Acids; D005656:Fungal Proteins; D011506:Proteins
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