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Dynamic covariation between gene expression and genome characteristics.

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Author

Summary, in English

Gene and protein expression is controlled so that cells can react to changing intra- and extracellular signals by modulating biochemical networks and pathways. We have previously shown that gene expression and the properties of expressed proteins are dynamically correlated. Here we investigated correlations between gene related parameters and gene expression patterns, and found statistically significant correlations in microarray datasets for different cell types, organisms and processes, including human B and T cell stimulation, cell cycle in HeLa cells, infection in intestinal epithelial cells, Drosophila melanogaster life span, and Saccharomyces cerevisiae cell cycle. Our method was applied to time course datasets individually for each time point. We derived from sequence information numerous parameters for nucleotide composition, two-base composition, codon usage, skew parameters, and codon bias. In addition to coding regions, we also investigated correlations for complete genes and introns. Significant dynamic correlations were identified for each of the analyses. Our method also proved useful for detecting dynamic shifts in gene expression profiles, such as in the D. melanogaster dataset. Detection of changes in the properties of expressed genes and proteins might be useful for predicting or following biological processes, responses, growth, differentiation and possibly in related disorders.

Publishing year

2008

Language

English

Pages

53-66

Publication/Series

Gene

Volume

410

Issue

1

Document type

Journal article

Publisher

Elsevier

Topic

  • Medical Genetics

Keywords

  • Drosophila melanogaster: genetics
  • Saccharomyces cerevisiae: cytology
  • Saccharomyces cerevisiae: genetics

Status

Published

ISBN/ISSN/Other

  • ISSN: 1879-0038