Regulatory mechanisms of gene expression: complexity with elements of deterministic chaos

Acta Biochim Pol. 2006;53(1):1-10. Epub 2006 Feb 23.


Linear models based on proportionality between variables have been commonly applied in biology and medicine but in many cases they do not describe correctly the complex relationships of living organisms and now are being replaced by nonlinear theories of deterministic chaos. Recent advances in molecular biology and genome sequencing may lead to a simplistic view that all life processes in a cell, or in the whole organism, are strictly and in a linear fashion controlled by genes. In reality, the existing phenotype arises from a complex interaction of the genome and various environmental factors. Regulation of gene expression in the animal organism occurs at the level of epigenetic DNA modification, RNA transcription, mRNA translation, and many additional alterations of nascent proteins. The process of transcription is highly complicated and includes hundreds of transcription factors, enhancers and silencers, as well as various species of low molecular mass RNAs. In addition, alternative splicing or mRNA editing can generate a family of polypeptides from a single gene. Rearrangement of coding DNA sequences during somatic recombination is the source of great variability in the structure of immunoglobulins and some other proteins. The process of rearrangement of immunoglobulin genes, or such phenomena as parental imprinting of some genes, appear to occur in a random fashion. Therefore, it seems that the mechanism of genetic information flow from DNA to mature proteins does not fit the category of linear relationship based on simple reductionism or hard determinism but would be probably better described by nonlinear models, such as deterministic chaos.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Alleles
  • Alternative Splicing
  • Animals
  • Biochemistry / methods
  • Epigenesis, Genetic
  • Gene Expression Regulation*
  • Genome
  • Humans
  • Models, Genetic
  • Molecular Biology / methods
  • Nonlinear Dynamics*
  • Phenotype
  • RNA Editing
  • Recombination, Genetic