Gene regulation network

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A gene regulatory network ( GRN ) is a collection of DNA segments in a cell that interact, directly or indirectly, with one another (through their RNA and protein messengers) or with other substances in the cell, whereby they determine the frequency with which the Genes in the network are transcribed in mRNA , control.

Usually each mRNA molecule produces a specific protein (or set of proteins). On the one hand, the protein can contain structural information and attach to the cell membrane or within the cell in order to give it certain structural properties. On the other hand, the protein can be an enzyme , e.g. B. a micro-machine that acts as a catalyst for a certain reaction, such as the breakdown of nutrients or toxins . Other proteins, in turn, serve exclusively to activate other genes, and it is these transcription factors that play the main role in regulatory networks or chains of effects. By attaching to the promoter regions at the beginning of other genes, they activate them and thus the production of other proteins and so on. Certain transcription factors also serve to prevent it.

In unicellular organisms, the regulatory networks react to the environment in order to maximize the cell's chances of survival in this environment for a certain period of time. For example, a yeast cell that is in a sugar solution will activate genes to convert the sugar into ethanol . This process, which we associate with the production of wine, is the yeast cell's approach to ensure its survival, to produce energy to reproduce which, under normal circumstances, would improve its chances of survival.

In multicellular animals, the same principle is used for the purpose of genetic chains of effects that control body shape. Every time a cell divides, the result is two cells that, while containing the same genome , can differ in which genes are activated and produce proteins. Sometimes a “self-reinforcing cycle” ensures that a cell retains and passes on its genetic identity. Have so far been less understood the mechanisms of epigenetics , in which the modification of the chromatin a cellular memory makes possible by preventing or enabling transcriptions. A common characteristic of multicellular animals is the use of morphogenic gradients , which in turn provide a system for passing on the position to a cell, i.e. ensuring that the cell knows where in the body it is and can develop into a corresponding cell. A gene that has been activated in one cell can leave it and diffuse into neighboring cells and, after entering, activate genes there, provided they have already reached a certain stage in their development. These cells are then given a new purpose and can even produce other morphogens for their part , which transmit a feedback signal to the output cell . Over greater distances, morphogens can use the active process of signal transduction . Such signals control embryogenesis , for example , the realization of the "genetic blueprint" for the construction of a complete organism from the beginning and over a series of sequenced work steps. They also control cell regeneration in the adult body by exchanging two-way feedback between cells, the lack of that feedback due to mutations being responsible for the development of cell overgrowths known as cancer . In addition to creating new organic structures, the genetic chain also activates genes that create structural proteins that give each cell the physical properties it needs. Until now it has been assumed that biomolecular interaction patterns are subject to an intrinsic probability that genetic networks are the result of cellular processes and not their cause (cf. cellular Darwinism). Be that as it may, the latest experimental results suggest the thesis of cell determination.

Gene regulation networks are identified using bioinformatic methods as a result of the gene expression analysis in connection with prior knowledge from molecular biological databases. This data-based network modeling is called network inference or - based on the reconstruction in technical systems - also called reverse engineering .

literature

  • Kristin Missal: Modeling reverse engineering strategies to identify genetic networks from incomplete gene expression data. Thesis. University of Leipzig. 2003. Full text (PDF file; 1.75 MB)
  • Antje Müller: Reverse engineering methods for the reconstruction of gene regulation networks from gene expression data . Diploma thesis Leipzig 2004. Full text (PDF file; 1.40 MB)