Literature DB >> 3908689

Rigorous pattern-recognition methods for DNA sequences. Analysis of promoter sequences from Escherichia coli.

D J Galas, M Eggert, M S Waterman.   

Abstract

The basic nature of the sequence features that define a promoter sequence for Escherichia coli RNA polymerase have been established by a variety of biochemical and genetic methods. We have developed rigorous analytical methods for finding unknown patterns that occur imperfectly in a set of several sequences, and have used them to examine a set of bacterial promoters. The algorithm easily discovers the "consensus" sequences for the -10 and -35 regions, which are essentially identical to the results of previous analyses, but requires no prior assumptions about the common patterns. By explicitly specifying the nature of the search for consensus sequences, we give a rigorous definition to this concept that should be widely applicable. We also have provided estimates for the statistical significance of common patterns discovered in sets of sequences. In addition to providing a rigorous basis for defining known consensus regions, we have found additional features in these promoters that may have functional significance. These added features were located on either side of the -35 region. The pattern 5', or upstream, from the -35 region was found using the standard alphabet (A, G, C and T), but the pattern between the -10 and the -35 regions was detectable only in a sub-alphabet. Recent results relating DNA sequence to helix conformation suggest that the former (upstream) pattern may have a functional significance. Possible roles in promoter function are discussed in this light, and an observation of altered promoter function involving the upstream region is reported that appears to support the suggestion of function in at least one case.

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Year:  1985        PMID: 3908689     DOI: 10.1016/0022-2836(85)90262-1

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


  64 in total

1.  GeneMarkS: a self-training method for prediction of gene starts in microbial genomes. Implications for finding sequence motifs in regulatory regions.

Authors:  J Besemer; A Lomsadze; M Borodovsky
Journal:  Nucleic Acids Res       Date:  2001-06-15       Impact factor: 16.971

2.  Identification and analysis of 'extended -10' promoters in Escherichia coli.

Authors:  Jennie E Mitchell; Dongling Zheng; Stephen J W Busby; Stephen D Minchin
Journal:  Nucleic Acids Res       Date:  2003-08-15       Impact factor: 16.971

3.  Splicing signals in Drosophila: intron size, information content, and consensus sequences.

Authors:  S M Mount; C Burks; G Hertz; G D Stormo; O White; C Fields
Journal:  Nucleic Acids Res       Date:  1992-08-25       Impact factor: 16.971

4.  Training back-propagation neural networks to define and detect DNA-binding sites.

Authors:  M C O'Neill
Journal:  Nucleic Acids Res       Date:  1991-01-25       Impact factor: 16.971

5.  WORDUP: an efficient algorithm for discovering statistically significant patterns in DNA sequences.

Authors:  G Pesole; N Prunella; S Liuni; M Attimonelli; C Saccone
Journal:  Nucleic Acids Res       Date:  1992-06-11       Impact factor: 16.971

6.  Bubbles and denaturation in DNA.

Authors:  T S van Erp; S Cuesta-López; M Peyrard
Journal:  Eur Phys J E Soft Matter       Date:  2006-09-07       Impact factor: 1.890

7.  Quantitative analysis of the relationship between nucleotide sequence and functional activity.

Authors:  G D Stormo; T D Schneider; L Gold
Journal:  Nucleic Acids Res       Date:  1986-08-26       Impact factor: 16.971

8.  Identification and characterization of multiple A/T-rich cis-acting elements that control expression from Dictyostelium actin promoters: the Dictyostelium actin upstream activating sequence confers growth phase expression and has enhancer-like properties.

Authors:  R Hori; R A Firtel
Journal:  Nucleic Acids Res       Date:  1994-11-25       Impact factor: 16.971

9.  Role of curved DNA in binding of Escherichia coli RNA polymerase to promoters.

Authors:  C A Nickerson; E C Achberger
Journal:  J Bacteriol       Date:  1995-10       Impact factor: 3.490

10.  Multi-alphabet consensus algorithm for identification of low specificity protein-DNA interactions.

Authors:  A V Ulyanov; G D Stormo
Journal:  Nucleic Acids Res       Date:  1995-04-25       Impact factor: 16.971

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