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Gene divergence and pathway duplication in the metabolic network of yeast and digital organisms

Philip Gerlee ; Torbjörn Lundh (Institutionen för matematiska vetenskaper, matematik) ; B. Zhang ; A.R.A. Anderson
Journal of the Royal Society Interface (1742-5689). Vol. 6 (2009), p. 1233-1245.
[Artikel, refereegranskad vetenskaplig]

We have studied the metabolic gene–function network in yeast and digital organisms evolved in the artificial life platform Avida. The gene–function network is a bipartite network in which a link exists between a gene and a function (pathway) if that function depends on that gene, and can also be viewed as a decomposition of the more traditional functional gene networks, where two genes are linked if they share any function. We show that the gene–function network exhibits two distinct degree distributions: the gene degree distribution is scale-free while the pathway distribution is exponential. This is true for both yeast and digital organisms, which suggests that this is a general property of evolving systems, and we propose that the scale-free gene degree distribution is due to pathway duplication, i.e. the development of a new pathway where the original function is still retained. Pathway duplication would serve as preferential attachment for the genes, and the experiments with Avida revealed precisely this; genes involved in many pathways are more likely to increase their connectivity. Measuring the overlap between different pathways, in terms of the genes that constitute them, showed that pathway duplication also is a likely mechanism in yeast evolution. This analysis sheds new light on the evolution of genes and functionality, and suggests that function duplication could be an important mechanism in evolution.

Nyckelord: digital evolution, gene–function relationship, metabolic network



Denna post skapades 2009-08-04. Senast ändrad 2015-01-08.
CPL Pubid: 95730

 

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Institutioner (Chalmers)

Institutionen för matematiska vetenskaper, matematik (2005-2016)

Ämnesområden

Annan matematik
Genetik
Funktionsgenomik

Chalmers infrastruktur