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Making the right connections: biological networks in the light of evolution.

Knight CG, Pinney JW - Bioessays (2009)

Bottom Line: Our understanding of how evolution acts on biological networks remains patchy, as is our knowledge of how that action is best identified, modelled and understood.The approaches highlighted demonstrate a movement away from a focus on network topology towards a more integrated view, placing biological properties centre-stage.We argue that there remains great potential in a closer synergy between evolutionary biology and biological network analysis, although that may require the development of novel approaches and even different analogies for biological networks themselves.

View Article: PubMed Central - PubMed

Affiliation: Faculty of Life Sciences, The University of Manchester, Michael Smith Building, Manchester, UK. chris.knight@manchester.ac.uk

ABSTRACT
Our understanding of how evolution acts on biological networks remains patchy, as is our knowledge of how that action is best identified, modelled and understood. Starting with network structure and the evolution of protein-protein interaction networks, we briefly survey the ways in which network evolution is being addressed in the fields of systems biology, development and ecology. The approaches highlighted demonstrate a movement away from a focus on network topology towards a more integrated view, placing biological properties centre-stage. We argue that there remains great potential in a closer synergy between evolutionary biology and biological network analysis, although that may require the development of novel approaches and even different analogies for biological networks themselves.

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Illustration of some processes of network evolution. These processes range from A: the purely graph-theoretical concept of preferential attachment,13 via increasingly biologically motivated concepts of B: node duplication, C: re-wiring, D: node loss, E: sub-functionalization and F: neo-functionalization, to G: network duplication, analogous to a whole-genome duplication event.
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fig02: Illustration of some processes of network evolution. These processes range from A: the purely graph-theoretical concept of preferential attachment,13 via increasingly biologically motivated concepts of B: node duplication, C: re-wiring, D: node loss, E: sub-functionalization and F: neo-functionalization, to G: network duplication, analogous to a whole-genome duplication event.

Mentions: When researchers started to address the question of how these networks evolved, belief in the primacy of the degree distribution led to a focus on evolutionary mechanisms that would generate power law networks.22 Just as there may be many plausible topological models to fit a particular degree distribution, there are many plausible stochastic models of network evolution that could generate a given topology.23 For example, the preferential attachment model (Fig. 2A)13 is one simple way to generate a power-law network by the progressive addition of nodes, where each new node is attached to an existing node with a probability related to the degree of that node. However, preferential attachment seems a particularly unreasonable mechanism for the evolution of many biological systems. Several biologically motivated schemes incorporating node duplication (Fig. 2B) and subsequent loss and/or gain of interactions (Fig. 2C) have been proposed.24,25


Making the right connections: biological networks in the light of evolution.

Knight CG, Pinney JW - Bioessays (2009)

Illustration of some processes of network evolution. These processes range from A: the purely graph-theoretical concept of preferential attachment,13 via increasingly biologically motivated concepts of B: node duplication, C: re-wiring, D: node loss, E: sub-functionalization and F: neo-functionalization, to G: network duplication, analogous to a whole-genome duplication event.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2962804&req=5

fig02: Illustration of some processes of network evolution. These processes range from A: the purely graph-theoretical concept of preferential attachment,13 via increasingly biologically motivated concepts of B: node duplication, C: re-wiring, D: node loss, E: sub-functionalization and F: neo-functionalization, to G: network duplication, analogous to a whole-genome duplication event.
Mentions: When researchers started to address the question of how these networks evolved, belief in the primacy of the degree distribution led to a focus on evolutionary mechanisms that would generate power law networks.22 Just as there may be many plausible topological models to fit a particular degree distribution, there are many plausible stochastic models of network evolution that could generate a given topology.23 For example, the preferential attachment model (Fig. 2A)13 is one simple way to generate a power-law network by the progressive addition of nodes, where each new node is attached to an existing node with a probability related to the degree of that node. However, preferential attachment seems a particularly unreasonable mechanism for the evolution of many biological systems. Several biologically motivated schemes incorporating node duplication (Fig. 2B) and subsequent loss and/or gain of interactions (Fig. 2C) have been proposed.24,25

Bottom Line: Our understanding of how evolution acts on biological networks remains patchy, as is our knowledge of how that action is best identified, modelled and understood.The approaches highlighted demonstrate a movement away from a focus on network topology towards a more integrated view, placing biological properties centre-stage.We argue that there remains great potential in a closer synergy between evolutionary biology and biological network analysis, although that may require the development of novel approaches and even different analogies for biological networks themselves.

View Article: PubMed Central - PubMed

Affiliation: Faculty of Life Sciences, The University of Manchester, Michael Smith Building, Manchester, UK. chris.knight@manchester.ac.uk

ABSTRACT
Our understanding of how evolution acts on biological networks remains patchy, as is our knowledge of how that action is best identified, modelled and understood. Starting with network structure and the evolution of protein-protein interaction networks, we briefly survey the ways in which network evolution is being addressed in the fields of systems biology, development and ecology. The approaches highlighted demonstrate a movement away from a focus on network topology towards a more integrated view, placing biological properties centre-stage. We argue that there remains great potential in a closer synergy between evolutionary biology and biological network analysis, although that may require the development of novel approaches and even different analogies for biological networks themselves.

Show MeSH