Limits...
Latent phenotypes pervade gene regulatory circuits.

Payne JL, Wagner A - BMC Syst Biol (2014)

Bottom Line: Most of this latent repertoire can be easily accessed through a series of small genetic changes that preserve a circuit's main functions.Both circuits and gene expression phenotypes that are robust to genetic change are associated with a greater number of latent phenotypes.Our observations suggest that latent phenotypes are pervasive in regulatory circuits, and may thus be an important source of evolutionary adaptations and innovations involving gene regulation.

View Article: PubMed Central - HTML - PubMed

Affiliation: University of Zurich, Zurich, Switzerland. andreas.wagner@ieu.uzh.ch.

ABSTRACT

Background: Latent phenotypes are non-adaptive byproducts of adaptive phenotypes. They exist in biological systems as different as promiscuous enzymes and genome-scale metabolic reaction networks, and can give rise to evolutionary adaptations and innovations. We know little about their prevalence in the gene expression phenotypes of regulatory circuits, important sources of evolutionary innovations.

Results: Here, we study a space of more than sixteen million three-gene model regulatory circuits, where each circuit is represented by a genotype, and has one or more functions embodied in one or more gene expression phenotypes. We find that the majority of circuits with single functions have latent expression phenotypes. Moreover, the set of circuits with a given spectrum of functions has a repertoire of latent phenotypes that is much larger than that of any one circuit. Most of this latent repertoire can be easily accessed through a series of small genetic changes that preserve a circuit's main functions. Both circuits and gene expression phenotypes that are robust to genetic change are associated with a greater number of latent phenotypes.

Conclusions: Our observations suggest that latent phenotypes are pervasive in regulatory circuits, and may thus be an important source of evolutionary adaptations and innovations involving gene regulation.

Show MeSH
Latent phenotypes vary within the dominant genotype network of ak-function. The data shown is based on 100,000 sampled pairs of genotypes from the dominant genotype network of the bifunction F(1):〈0,0,0〉↦〈0,0,1〉, F(2):〈0,1,0〉↦〈0,1,1〉. Open circles depict the mean fraction δ of latent phenotypes that are unique to one genotype or the other in each pair (see inset and Methods, Eq. 3), shown in relation to the mutational distance between these genotypes. Error bars correspond to one standard deviation. The histogram shows the distribution of sampled mutational distances between circuits in a pair.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
getmorefigures.php?uid=PMC4061115&req=5

Figure 4: Latent phenotypes vary within the dominant genotype network of ak-function. The data shown is based on 100,000 sampled pairs of genotypes from the dominant genotype network of the bifunction F(1):〈0,0,0〉↦〈0,0,1〉, F(2):〈0,1,0〉↦〈0,1,1〉. Open circles depict the mean fraction δ of latent phenotypes that are unique to one genotype or the other in each pair (see inset and Methods, Eq. 3), shown in relation to the mutational distance between these genotypes. Error bars correspond to one standard deviation. The histogram shows the distribution of sampled mutational distances between circuits in a pair.

Mentions: We have shown that the size of a k-function’s latent repertoire depends only on the number of unique expression states that occur in the k-function. However, we have not addressed how these latent phenotypes vary amongst the individual genotypes that have the same k-function. We therefore next asked whether genotypes that are separated by a small number of mutations are likely to have more similar latent phenotypes than those separated by many mutations. To answer this question, we sampled 100,000 pairs of genotypes from the largest connected genotype network (i.e., the dominant genotype network) of every k-function. For each pair of genotypes, we determined (i) their mutational distance from one another, and (ii) the fraction δ of latent phenotypes that is unique to one genotype or the other (Figure 4, inset; Methods). If δ increases with the mutational distance between genotypes, then a circuit’s location on a genotype network determines its latent capacity for exaptation.


Latent phenotypes pervade gene regulatory circuits.

Payne JL, Wagner A - BMC Syst Biol (2014)

Latent phenotypes vary within the dominant genotype network of ak-function. The data shown is based on 100,000 sampled pairs of genotypes from the dominant genotype network of the bifunction F(1):〈0,0,0〉↦〈0,0,1〉, F(2):〈0,1,0〉↦〈0,1,1〉. Open circles depict the mean fraction δ of latent phenotypes that are unique to one genotype or the other in each pair (see inset and Methods, Eq. 3), shown in relation to the mutational distance between these genotypes. Error bars correspond to one standard deviation. The histogram shows the distribution of sampled mutational distances between circuits in a pair.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4061115&req=5

Figure 4: Latent phenotypes vary within the dominant genotype network of ak-function. The data shown is based on 100,000 sampled pairs of genotypes from the dominant genotype network of the bifunction F(1):〈0,0,0〉↦〈0,0,1〉, F(2):〈0,1,0〉↦〈0,1,1〉. Open circles depict the mean fraction δ of latent phenotypes that are unique to one genotype or the other in each pair (see inset and Methods, Eq. 3), shown in relation to the mutational distance between these genotypes. Error bars correspond to one standard deviation. The histogram shows the distribution of sampled mutational distances between circuits in a pair.
Mentions: We have shown that the size of a k-function’s latent repertoire depends only on the number of unique expression states that occur in the k-function. However, we have not addressed how these latent phenotypes vary amongst the individual genotypes that have the same k-function. We therefore next asked whether genotypes that are separated by a small number of mutations are likely to have more similar latent phenotypes than those separated by many mutations. To answer this question, we sampled 100,000 pairs of genotypes from the largest connected genotype network (i.e., the dominant genotype network) of every k-function. For each pair of genotypes, we determined (i) their mutational distance from one another, and (ii) the fraction δ of latent phenotypes that is unique to one genotype or the other (Figure 4, inset; Methods). If δ increases with the mutational distance between genotypes, then a circuit’s location on a genotype network determines its latent capacity for exaptation.

Bottom Line: Most of this latent repertoire can be easily accessed through a series of small genetic changes that preserve a circuit's main functions.Both circuits and gene expression phenotypes that are robust to genetic change are associated with a greater number of latent phenotypes.Our observations suggest that latent phenotypes are pervasive in regulatory circuits, and may thus be an important source of evolutionary adaptations and innovations involving gene regulation.

View Article: PubMed Central - HTML - PubMed

Affiliation: University of Zurich, Zurich, Switzerland. andreas.wagner@ieu.uzh.ch.

ABSTRACT

Background: Latent phenotypes are non-adaptive byproducts of adaptive phenotypes. They exist in biological systems as different as promiscuous enzymes and genome-scale metabolic reaction networks, and can give rise to evolutionary adaptations and innovations. We know little about their prevalence in the gene expression phenotypes of regulatory circuits, important sources of evolutionary innovations.

Results: Here, we study a space of more than sixteen million three-gene model regulatory circuits, where each circuit is represented by a genotype, and has one or more functions embodied in one or more gene expression phenotypes. We find that the majority of circuits with single functions have latent expression phenotypes. Moreover, the set of circuits with a given spectrum of functions has a repertoire of latent phenotypes that is much larger than that of any one circuit. Most of this latent repertoire can be easily accessed through a series of small genetic changes that preserve a circuit's main functions. Both circuits and gene expression phenotypes that are robust to genetic change are associated with a greater number of latent phenotypes.

Conclusions: Our observations suggest that latent phenotypes are pervasive in regulatory circuits, and may thus be an important source of evolutionary adaptations and innovations involving gene regulation.

Show MeSH