Title |
Detection of Genes with Atypical Nucleotide Sequence in Microbial Genomes
|
---|---|
Published in |
Journal of Molecular Evolution, March 2014
|
DOI | 10.1007/s00239-001-0051-8 |
Pubmed ID | |
Authors |
Sean D. Hooper, Otto G. Berg |
Abstract |
Along the gene, nucleotides in various codon positions tend to exert a slight but observable influence on the nucleotide choice at neighboring positions. Such context biases are different in different organisms and can be used as genomic signatures. In this paper, we will focus specifically on the dinucleotide composed of a third codon position nucleotide and its succeeding first position nucleotide. Using the 16 possible dinucleotide combinations, we calculate how well individual genes conform to the observed mean dinucleotide frequencies of an entire genome, forming a distance measure for each gene. It is found that genes from different genomes can be separated with a high degree of accuracy, according to these distance values. In particular, we address the problem of recent horizontal gene transfer, and how imported genes may be evaluated by their poor assimilation to the host's context biases. By concentrating on the third- and succeeding first position nucleotides, we eliminate most spurious contributions from codon usage and amino-acid requirements, focusing mainly on mutational effects. Since imported genes are expected to converge only gradually to genomic signatures, it is possible to question whether a gene present in only one of two closely related organisms has been imported into one organism or deleted in the other. Striking correlations between the proposed distance measure and poor homology are observed when Escherichia coli genes are compared to Salmonella typhi, indicating that sets of outlier genes in E. coli may contain a high number of genes that have been imported into E. coli, and not deleted in S. typhi. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Netherlands | 1 | 2% |
Brazil | 1 | 2% |
United Kingdom | 1 | 2% |
Mexico | 1 | 2% |
United States | 1 | 2% |
Unknown | 39 | 89% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 9 | 20% |
Student > Ph. D. Student | 9 | 20% |
Professor | 6 | 14% |
Professor > Associate Professor | 5 | 11% |
Student > Master | 4 | 9% |
Other | 8 | 18% |
Unknown | 3 | 7% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 23 | 52% |
Biochemistry, Genetics and Molecular Biology | 8 | 18% |
Computer Science | 3 | 7% |
Immunology and Microbiology | 3 | 7% |
Chemical Engineering | 1 | 2% |
Other | 4 | 9% |
Unknown | 2 | 5% |