Neutral network (evolution)

Not to be confused with Neural network or Network-neutral data center.

A Neutral network is a set of genes all related by point mutations that have equivalent function or fitness. Each node represents a gene sequence and each line represents the mutation connecting two sequences. Neutral networks can be thought of as high, flat plateaus in a fitness landscape. During neutral evolution, genes can randomly move through neutral networks and traverse regions of sequence space which may have consequences for robustness and evolvability.

Genetic and molecular causes

See also: Neutral mutation and Robustness (evolution)

Neutral networks exist in fitness landscapes since proteins are robust to mutations. This leads to extended networks of genes of equivalent function, linked by neutral mutations. Proteins are resistant to mutations because many sequences can fold into highly similar structural folds. A protein adopts a limited ensemble of native conformations because those conformers have lower energy than unfolded and mis-folded states (ΔΔG of folding). This is achieved by a distributed, internal network of cooperative interactions (hydrophobic, polar and covalent). Protein structural robustness results from few single mutations being sufficiently disruptive to compromise function. Proteins have also evolved to avoid aggregation as partially folded proteins can combine to form large, repeating, insoluble protein fibrils and masses. There is evidence that proteins show negative design features to reduce the exposure of aggregation-prone beta-sheet motifs in their structures. Additionally, there is some evidence that the genetic code itself may be optimised such that most point mutations lead to similar amino acids (conservative). Together these factors create a distribution of fitness effects of mutations that contains a high proportion of neutral and nearly-neutral mutations.

Neutral networks and evolution

Neutral networks are a subset of the sequences in sequence space that have equivalent function, and so form a wide, flat plateau in a fitness landscape. Neutral evolution can therefore be visualised as a population diffusing from one set of sequence nodes, through the neutral network, to another cluster of sequence nodes. Since the majority of evolution is thought to be neutral, a large proportion of gene change is the movement though expansive neutral networks.

Neutral networks and robustness

See also: Robustness (evolution)

Each circle represents a functional gene variant and lines represents point mutations between them. Light grid-regions have low fitness, dark regions have high fitness. (a) White circles have few neutral neighbours, black circles have many. Light grid-regions contain no circles because those sequences have low fitness. (b) Within a neutral network, the population is predicted to evolve towards the centre and away from ‘fitness cliffs’ (dark arrows).

The more neutral neighbours a sequence has, the more robust to mutations it is since mutations are more likely to simply neutrally convert it into an equally functional sequence. Indeed, if there are large differences between the number of neutral neighbours of different sequences within a neutral network, the population is predicted to evolve towards these robust sequences. This is sometimes called circum-neutrality and represents the movement of populations away from cliffs in the fitness landscape.

In addition to in silico models, these processes are beginning to be confirmed by experimental evolution of cytochrome P450s and B-lactamase.

Neutral networks and evolvability

See also: Evolvability

Interest in the interplay between genetic drift and selection has been around since the 1930s when the shifting-balance theory proposed that in some situations, genetic drift could facilitate later adaptive evolution. Although the specifics of the theory were largely discredited, it drew attention to the possibility that drift could generate cryptic variation that, though neutral to current function, may affect selection for new functions (evolvability).

By definition, all genes in a neutral network have equivalent function, however some may exhibit promiscuous activities which could serve as starting points for adaptive evolution towards new functions. In terms of sequence space, current theories predict that if the neutral networks for two different activities overlap, a neutrally evolving population may diffuse to regions of the neutral network of the first activity that allow it to access the second. This would only be the case when the distance between activities is smaller than the distance that a neutrally evolving population can cover. The degree of interpenetration of the two networks will determine how common cryptic variation for the promiscuous activity is in sequence space.