title: Combining phylogenetic footprinting with motif models incorporating intra-motif dependencies.
abstract: BACKGROUND
  Transcriptional gene regulation is a fundamental process in nature, and the experimental and computational investigation of DNA binding motifs and their binding sites is a prerequisite for elucidating this process. Approaches for de-novo motif discovery can be subdivided in phylogenetic footprinting that takes into account phylogenetic dependencies in aligned sequences of more than one species and non-phylogenetic approaches based on sequences from only one species that typically take into account intra-motif dependencies. It has been shown that modeling (i) phylogenetic dependencies as well as (ii) intra-motif dependencies separately improves de-novo motif discovery, but there is no approach capable of modeling both (i) and (ii) simultaneously.
  
  
  RESULTS
  Here, we present an approach for de-novo motif discovery that combines phylogenetic footprinting with motif models capable of taking into account intra-motif dependencies. We study the degree of intra-motif dependencies inferred by this approach from ChIP-seq data of 35 transcription factors. We find that significant intra-motif dependencies of orders 1 and 2 are present in all 35 datasets and that intra-motif dependencies of order 2 are typically stronger than those of order 1. We also find that the presented approach improves the classification performance of phylogenetic footprinting in all 35 datasets and that incorporating intra-motif dependencies of order 2 yields a higher classification performance than incorporating such dependencies of only order 1.
  
  
  CONCLUSIONS
  Combining phylogenetic footprinting with motif models incorporating intra-motif dependencies leads to an improved performance in the classification of transcription factor binding sites. This may advance our understanding of transcriptional gene regulation and its evolution.
authors.affiliation: Institute of Computer Science, Martin Luther University Halle-Wittenberg, Halle, Germany. martin.nettling@informatik.uni-halle.de.
authors.forename: Martin
authors.initials: M
authors.lastname: Nettling
authors.affiliation: Leibniz Institute of Plant Biochemistry, Halle, Germany.
authors.forename: Hendrik
authors.initials: H
authors.lastname: Treutler
authors.affiliation: Institut d'Investigació en Intel ·ligència Artificial, IIIA-CSIC, Campus UAB, Cerdanyola, Spain.
authors.forename: Jesus
authors.initials: J
authors.lastname: Cerquides
authors.affiliation: Institute of Computer Science, Martin Luther University Halle-Wittenberg, Halle, Germany.|German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany.
authors.forename: Ivo
authors.initials: I
authors.lastname: Grosse
mesh_terms: D000465:Algorithms; D020816:Amino Acid Motifs; D001665:Binding Sites / Q000235:genetics; D002843:Chromatin / Q000378:metabolism; D004247:DNA / Q000737:chemistry / Q000378:metabolism; D006801:Humans; D008958:Models, Molecular; D010802:Phylogeny; D011485:Protein Binding; D000072417:Protein Domains; D017422:Sequence Analysis, DNA; D014157:Transcription Factors / Q000145:classification* / Q000235:genetics / Q000378:metabolism
chemical_list: D002843:Chromatin; D014157:Transcription Factors; D004247:DNA
keywords: ChIP-Seq; Evolution; Gene regulation; Phylogenetic footprinting; Transcription factor binding sites