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Analysis of the nucleotide content of Escherichia coli promoter sequences related to the alternative sigma factors.

Authors
  • Dall'Alba, Gabriel1
  • Casa, Pedro Lenz1
  • Notari, Daniel Luis2
  • Adami, Andre Gustavo2
  • Echeverrigaray, Sergio1
  • de Avila E Silva, Scheila2
  • 1 Department of Life Sciences, Universidade de Caxias do Sul, Caxias do Sul, Rio Grande do Sul, Brazil. , (Brazil)
  • 2 Department of Exact Sciences, Universidade de Caxias do Sul, Caxias do Sul, Rio Grande do Sul, Brazil. , (Brazil)
Type
Published Article
Journal
Journal of Molecular Recognition
Publisher
Wiley (John Wiley & Sons)
Publication Date
Nov 20, 2018
Identifiers
DOI: 10.1002/jmr.2770
PMID: 30458580
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

Promoters are DNA sequences located upstream of the transcription start site of genes. In bacteria, the RNA polymerase enzyme requires additional subunits, called sigma factors (σ) to begin specific gene transcription in distinct environmental conditions. Currently, promoter prediction still poses many challenges due to the characteristics of these sequences. In this paper, the nucleotide content of Escherichia coli promoter sequences, related to five alternative σ factors, was analyzed by a machine learning technique in order to provide profiles according to the σ factor which recognizes them. For this, the clustering technique was applied since it is a viable method for finding hidden patterns on a data set. As a result, 20 groups of sequences were formed, and, aided by the Weblogo tool, it was possible to determine sequence profiles. These found patterns should be considered for implementing computational prediction tools. In addition, evidence was found of an overlap between the functions of the genes regulated by different σ factors, suggesting that DNA structural properties are also essential parameters for further studies. © 2018 John Wiley & Sons, Ltd.

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