Literature DB >> 9245596

A novel method to develop highly specific models for regulatory units detects a new LTR in GenBank which contains a functional promoter.

K Frech1, J Danescu-Mayer, T Werner.   

Abstract

Functional promoters are composed of individual modules (e.g. transcription factor binding sites, secondary structure elements, repeats) arranged in distinct patterns. Recognition of such patterns is essential for identification of promoters in non-coding sequences. However, this is difficult due to the absence of overall sequence similarity in promoters even if they are regulated in a similar way. We implemented simple formal representations of general features of regulatory regions into an algorithm capable of developing complex models reflecting both the element composition and the functional organization of individual elements (ModelGenerator). Though ModelGenerator requires a very simple initial model (e.g. two modules and their relative order) it will generate a much more sophisticated model by analysis of the training set of at least ten sequences. We show ModelGenerator to successfully model different retroviral long terminal repeat (LTR) classes (Lentivirus as well as avian and mammalian C-type) which contain functional promoters. Database searches with the program ModelInspector demonstrated the high specificity of these models and no apparent false negatives were detected. We also verified one match from GenBank to the mammalian C-type LTR model experimentally and showed this sequence to contain an active promoter. Thus, the concept of modular organization of functional regulatory DNA regions (e.g. promoters) could be successfully implemented into a set of computer tools which might be flexible and specific enough to be suitable for prospective analysis of new genomic DNA sequences.

Entities:  

Mesh:

Year:  1997        PMID: 9245596     DOI: 10.1006/jmbi.1997.1140

Source DB:  PubMed          Journal:  J Mol Biol        ISSN: 0022-2836            Impact factor:   5.469


  33 in total

1.  TRANSFAC: an integrated system for gene expression regulation.

Authors:  E Wingender; X Chen; R Hehl; H Karas; I Liebich; V Matys; T Meinhardt; M Prüss; I Reuter; F Schacherer
Journal:  Nucleic Acids Res       Date:  2000-01-01       Impact factor: 16.971

2.  First pass annotation of promoters on human chromosome 22.

Authors:  M Scherf; A Klingenhoff; K Frech; K Quandt; R Schneider; K Grote; M Frisch; V Gailus-Durner; A Seidel; R Brack-Werner; T Werner
Journal:  Genome Res       Date:  2001-03       Impact factor: 9.043

3.  Deciphering genetic regulatory codes: a challenge for functional genomics.

Authors:  Alan M Michelson
Journal:  Proc Natl Acad Sci U S A       Date:  2002-01-22       Impact factor: 11.205

4.  A predictive model for regulatory sequences directing liver-specific transcription.

Authors:  W Krivan; W W Wasserman
Journal:  Genome Res       Date:  2001-09       Impact factor: 9.043

Review 5.  In silico identification of metazoan transcriptional regulatory regions.

Authors:  Wyeth W Wasserman; William Krivan
Journal:  Naturwissenschaften       Date:  2003-03-27

6.  Computation-based discovery of related transcriptional regulatory modules and motifs using an experimentally validated combinatorial model.

Authors:  Marc S Halfon; Yonatan Grad; George M Church; Alan M Michelson
Journal:  Genome Res       Date:  2002-07       Impact factor: 9.043

7.  Statistical significance of clusters of motifs represented by position specific scoring matrices in nucleotide sequences.

Authors:  Martin C Frith; John L Spouge; Ulla Hansen; Zhiping Weng
Journal:  Nucleic Acids Res       Date:  2002-07-15       Impact factor: 16.971

8.  Target Explorer: An automated tool for the identification of new target genes for a specified set of transcription factors.

Authors:  Alona Sosinsky; Christopher P Bonin; Richard S Mann; Barry Honig
Journal:  Nucleic Acids Res       Date:  2003-07-01       Impact factor: 16.971

9.  Cluster-Buster: Finding dense clusters of motifs in DNA sequences.

Authors:  Martin C Frith; Michael C Li; Zhiping Weng
Journal:  Nucleic Acids Res       Date:  2003-07-01       Impact factor: 16.971

10.  Comparative promoter analysis allows de novo identification of specialized cell junction-associated proteins.

Authors:  Clemens D Cohen; Andreas Klingenhoff; Anissa Boucherot; Almut Nitsche; Anna Henger; Bodo Brunner; Holger Schmid; Monika Merkle; Moin A Saleem; Klaus-Peter Koller; Thomas Werner; Hermann-Josef Gröne; Peter J Nelson; Matthias Kretzler
Journal:  Proc Natl Acad Sci U S A       Date:  2006-03-31       Impact factor: 11.205

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